{"group":{"id":1,"name":"Community","lockable":false,"created_at":"2012-01-18T18:02:15.000Z","updated_at":"2025-12-14T01:33:56.000Z","description":"Problems submitted by members of the MATLAB Central community.","is_default":true,"created_by":161519,"badge_id":null,"featured":false,"trending":false,"solution_count_in_trending_period":0,"trending_last_calculated":"2025-12-14T00:00:00.000Z","image_id":null,"published":true,"community_created":false,"status_id":2,"is_default_group_for_player":false,"deleted_by":null,"deleted_at":null,"restored_by":null,"restored_at":null,"description_opc":null,"description_html":null,"published_at":null},"problems":[{"id":384,"title":"Poker Series 08: IsPair","description":"The Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\r\n\r\nA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\r\n\r\nFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\r\n\r\n--------\r\n\r\nA pair is 2 cards of the same rank (column) and the three kickers. The Ace (first column) is highest. The columns represent A, 2, 3, ... K. The next three highest cards are the kickers. If the kickers also form a pair, or three of a kind, it is still considered a pair for the purposes of this function.\r\n\r\nThis hand matrix:\r\n\r\n 0 1 0 0 1 0 0 0 0 0 0 0 0 \r\n 0 0 1 0 0 0 0 1 0 0 0 0 0\r\n 0 1 0 1 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 1 0 0 0 0 0 0 0\r\n\r\nrepresents a pair, so the return value from the function is TRUE.\r\n\r\nThis hand matrix does not:\r\n\r\n 0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 1 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n\r\nso the return value should be FALSE.\r\n\r\nThis hand matrix does represent a pair\r\n\r\n 0 0 0 0 0 0 0 0 0 1 0 0 1 \r\n 0 0 0 0 0 0 0 0 0 0 1 0 0\r\n 0 0 1 0 0 0 0 0 0 1 0 0 0 \r\n 0 0 0 0 0 1 0 0 0 0 0 1 0\r\n\r\nRemember, hand matrices can contain any number of 1's from 0 to 52.\r\n\r\n 0 1 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 1 1 1 0 0 0 1 0 1\r\n 0 0 0 1 0 1 0 0 0 1 0 0 0 \r\n 0 0 1 0 0 0 0 0 0 0 0 1 0 \r\n\r\nWould be TRUE for this function.\r\n\r\nA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand matrix, but it only shows the cards used to make the pair. If more than one pair can be made, return the higher ranking one (the one with the highest rank. Ace being the highest). If different suits are possible for the same pair, return the one higher up in the matrix, same for kickers. If the pair happens to also be a four of a kind or full house, two pair, etc.. it still meets the defintion and should be returned.","description_html":"\u003cp\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/p\u003e\u003cp\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/p\u003e\u003cp\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/p\u003e\u003cp\u003e--------\u003c/p\u003e\u003cp\u003eA pair is 2 cards of the same rank (column) and the three kickers. The Ace (first column) is highest. The columns represent A, 2, 3, ... K. The next three highest cards are the kickers. If the kickers also form a pair, or three of a kind, it is still considered a pair for the purposes of this function.\u003c/p\u003e\u003cp\u003eThis hand matrix:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 0 0 1 0 0 0 0 0 0 0 0 \r\n0 0 1 0 0 0 0 1 0 0 0 0 0\r\n0 1 0 1 0 0 0 0 0 0 0 0 0 \r\n0 0 0 0 0 1 0 0 0 0 0 0 0\r\n\u003c/pre\u003e\u003cp\u003erepresents a pair, so the return value from the function is TRUE.\u003c/p\u003e\u003cp\u003eThis hand matrix does not:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n0 0 0 0 0 0 0 0 0 0 0 0 0\r\n0 0 0 0 0 0 0 0 0 1 0 0 0 \r\n0 0 0 0 0 0 0 0 0 0 0 0 0\r\n\u003c/pre\u003e\u003cp\u003eso the return value should be FALSE.\u003c/p\u003e\u003cp\u003eThis hand matrix does represent a pair\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 0 0 0 0 0 0 0 0 1 0 0 1 \r\n0 0 0 0 0 0 0 0 0 0 1 0 0\r\n0 0 1 0 0 0 0 0 0 1 0 0 0 \r\n0 0 0 0 0 1 0 0 0 0 0 1 0\r\n\u003c/pre\u003e\u003cp\u003eRemember, hand matrices can contain any number of 1's from 0 to 52.\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 0 0 0 0 0 0 0 0 0 0 0 \r\n0 0 0 0 1 1 1 0 0 0 1 0 1\r\n0 0 0 1 0 1 0 0 0 1 0 0 0 \r\n0 0 1 0 0 0 0 0 0 0 0 1 0 \r\n\u003c/pre\u003e\u003cp\u003eWould be TRUE for this function.\u003c/p\u003e\u003cp\u003eA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand matrix, but it only shows the cards used to make the pair. If more than one pair can be made, return the higher ranking one (the one with the highest rank. Ace being the highest). If different suits are possible for the same pair, return the one higher up in the matrix, same for kickers. If the pair happens to also be a four of a kind or full house, two pair, etc.. it still meets the defintion and should be returned.\u003c/p\u003e","function_template":"function out = isPair(hm)\r\n out.flag = false;\r\n out.usedCards = false(4,13);\r\nend","test_suite":"%%\r\nhm = [0 1 0 0 0 0 0 0 1 0 0 0 1 \r\n 0 1 0 0 0 0 0 0 0 0 0 1 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 1 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 1 0 0 0 0 0 0 0 0 0 0 1 \r\n 0 1 0 0 0 0 0 0 0 0 0 1 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 1 0 0])\r\n \r\nassert(isequal(isPair(hm),y_correct))\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 1 0 0 0 1 \r\n 0 1 0 0 0 0 0 1 0 0 0 1 0\r\n 0 0 0 0 0 0 1 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 1 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 1 0 0 0 0 0 0 0 0 0 0 1 \r\n 0 1 0 0 0 0 0 0 0 0 0 1 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 1 0 0])\r\n \r\nassert(isequal(isPair(hm),y_correct))\r\n\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 1 0 0 0 1 \r\n 0 1 0 0 0 0 0 0 0 0 0 1 1\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 1 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 1 0 0 0 1 \r\n 0 0 0 0 0 0 0 0 0 0 0 1 1\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 1 0 0])\r\n \r\nassert(isequal(isPair(hm),y_correct))\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 1 0 0 0 1 \r\n 1 1 0 0 0 0 0 0 0 0 0 1 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 1 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 1 \r\n 1 0 0 0 0 0 0 0 0 0 0 1 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 1 0 0])\r\n \r\nassert(isequal(isPair(hm),y_correct))\r\n\r\n%%\r\nhm = [0 0 0 0 0 0 0 0 1 0 0 0 1 \r\n 0 1 0 0 0 0 0 0 0 0 0 1 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 1 0 0];\r\n\r\ny_correct.flag = false;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isPair(hm),y_correct))\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 1 0 0 0 1 \r\n 1 1 0 0 0 0 0 0 0 0 0 1 1\r\n 0 0 0 0 0 0 0 0 0 0 0 0 1 \r\n 1 0 0 0 0 0 0 0 0 0 1 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 1 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 1\r\n 0 0 0 0 0 0 0 0 0 0 0 0 1 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isPair(hm),y_correct))","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":240,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":55,"test_suite_updated_at":"2012-02-22T19:17:35.000Z","rescore_all_solutions":false,"group_id":15,"created_at":"2012-02-22T19:17:35.000Z","updated_at":"2026-02-15T05:44:51.000Z","published_at":"2012-02-22T19:17:35.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e--------\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA pair is 2 cards of the same rank (column) and the three kickers. The Ace (first column) is highest. The columns represent A, 2, 3, ... K. The next three highest cards are the kickers. If the kickers also form a pair, or three of a kind, it is still considered a pair for the purposes of this function.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 0 0 1 0 0 0 0 0 0 0 0 \\n0 0 1 0 0 0 0 1 0 0 0 0 0\\n0 1 0 1 0 0 0 0 0 0 0 0 0 \\n0 0 0 0 0 1 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003erepresents a pair, so the return value from the function is TRUE.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix does not:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 1 0 1 1 0 0 0 0 0 0 0 \\n0 0 0 0 0 0 0 0 0 0 0 0 0\\n0 0 0 0 0 0 0 0 0 1 0 0 0 \\n0 0 0 0 0 0 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eso the return value should be FALSE.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix does represent a pair\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 0 0 0 0 0 0 0 0 1 0 0 1 \\n0 0 0 0 0 0 0 0 0 0 1 0 0\\n0 0 1 0 0 0 0 0 0 1 0 0 0 \\n0 0 0 0 0 1 0 0 0 0 0 1 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eRemember, hand matrices can contain any number of 1's from 0 to 52.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 0 0 0 0 0 0 0 0 0 0 0 \\n0 0 0 0 1 1 1 0 0 0 1 0 1\\n0 0 0 1 0 1 0 0 0 1 0 0 0 \\n0 0 1 0 0 0 0 0 0 0 0 1 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWould be TRUE for this function.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand matrix, but it only shows the cards used to make the pair. If more than one pair can be made, return the higher ranking one (the one with the highest rank. Ace being the highest). If different suits are possible for the same pair, return the one higher up in the matrix, same for kickers. If the pair happens to also be a four of a kind or full house, two pair, etc.. it still meets the defintion and should be returned.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":385,"title":"Poker Series 09: IsHighCard","description":"The Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\r\n\r\nA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\r\n\r\nFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\r\n\r\n--------\r\n\r\nHigh Card is the five highest cards in your hand. It is basically what you have if you don't have anything else! The Ace (first column) is highest. The columns represent A, 2, 3, ... K. If the kickers also form a pair, it is still considered high card for the purposes of this function.\r\n\r\nThis hand matrix:\r\n\r\n 0 1 0 0 1 0 0 0 0 0 0 0 0 \r\n 0 0 1 0 0 0 0 0 0 0 0 0 0\r\n 0 1 0 1 0 0 0 0 0 0 0 0 0 \r\n 0 1 0 0 0 1 0 0 0 0 0 0 0\r\n\r\nrepresents a high card, so the return value from the function is TRUE.\r\n\r\nThis hand matrix does not (because it is defined as five cards):\r\n\r\n 0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n\r\nso the return value should be FALSE.\r\n\r\nThis hand matrix does represent a high card\r\n\r\n 0 0 0 0 0 0 0 0 0 1 0 0 1 \r\n 0 0 0 0 0 0 0 0 0 0 1 0 0\r\n 0 0 0 0 0 0 0 0 0 1 0 0 0 \r\n 0 0 0 0 0 1 0 0 0 1 0 1 0\r\n\r\nRemember, hand matrices can contain any number of 1's from 0 to 52.\r\n\r\n 0 0 0 0 0 1 0 0 0 0 0 0 0 \r\n 0 0 0 0 1 1 1 0 0 0 0 0 1\r\n 0 0 0 1 0 1 0 0 0 1 0 0 0 \r\n 0 0 1 0 0 0 0 0 0 0 0 1 0 \r\n\r\nWould be TRUE for this function.\r\n\r\nA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand matrix, but it only shows the cards used to make the high card. If more than one hag card can be made, return the higher ranking one (the one with the highest rank. Ace being the highest). If different suits are possible for the same high card, return the one higher up in the matrix, same for kickers. If the high card also happens to also be a four of a kind or full house, it still meets the defintion and should be returned.","description_html":"\u003cp\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/p\u003e\u003cp\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/p\u003e\u003cp\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/p\u003e\u003cp\u003e--------\u003c/p\u003e\u003cp\u003eHigh Card is the five highest cards in your hand. It is basically what you have if you don't have anything else! The Ace (first column) is highest. The columns represent A, 2, 3, ... K. If the kickers also form a pair, it is still considered high card for the purposes of this function.\u003c/p\u003e\u003cp\u003eThis hand matrix:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 0 0 1 0 0 0 0 0 0 0 0 \r\n0 0 1 0 0 0 0 0 0 0 0 0 0\r\n0 1 0 1 0 0 0 0 0 0 0 0 0 \r\n0 1 0 0 0 1 0 0 0 0 0 0 0\r\n\u003c/pre\u003e\u003cp\u003erepresents a high card, so the return value from the function is TRUE.\u003c/p\u003e\u003cp\u003eThis hand matrix does not (because it is defined as five cards):\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n0 0 0 0 0 0 0 0 0 0 0 0 0\r\n0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n0 0 0 0 0 0 0 0 0 0 0 0 0\r\n\u003c/pre\u003e\u003cp\u003eso the return value should be FALSE.\u003c/p\u003e\u003cp\u003eThis hand matrix does represent a high card\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 0 0 0 0 0 0 0 0 1 0 0 1 \r\n0 0 0 0 0 0 0 0 0 0 1 0 0\r\n0 0 0 0 0 0 0 0 0 1 0 0 0 \r\n0 0 0 0 0 1 0 0 0 1 0 1 0\r\n\u003c/pre\u003e\u003cp\u003eRemember, hand matrices can contain any number of 1's from 0 to 52.\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 0 0 0 0 1 0 0 0 0 0 0 0 \r\n0 0 0 0 1 1 1 0 0 0 0 0 1\r\n0 0 0 1 0 1 0 0 0 1 0 0 0 \r\n0 0 1 0 0 0 0 0 0 0 0 1 0 \r\n\u003c/pre\u003e\u003cp\u003eWould be TRUE for this function.\u003c/p\u003e\u003cp\u003eA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand matrix, but it only shows the cards used to make the high card. If more than one hag card can be made, return the higher ranking one (the one with the highest rank. Ace being the highest). If different suits are possible for the same high card, return the one higher up in the matrix, same for kickers. If the high card also happens to also be a four of a kind or full house, it still meets the defintion and should be returned.\u003c/p\u003e","function_template":"function out = isHighCard(hm)\r\n out.flag = false;\r\n out.usedCards = false(4,13);\r\nend","test_suite":"clear\r\nclc\r\n\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 1 1 0 1 1 \r\n 0 1 0 0 0 0 0 0 1 0 0 1 0\r\n 0 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 1 1 0 1 1 \r\n 0 0 0 0 0 0 0 0 0 0 0 1 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isHighCard(hm),y_correct))\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 1 1 0 1 1 \r\n 1 1 0 0 0 0 0 0 1 0 0 1 0\r\n 0 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 1 0 1 1 \r\n 1 0 0 0 0 0 0 0 0 0 0 1 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isHighCard(hm),y_correct))\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 1 1 0 1 1 \r\n 1 1 0 0 0 0 0 0 1 0 0 1 0\r\n 0 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 1 1 \r\n 1 0 0 0 0 0 0 0 0 0 0 1 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isHighCard(hm),y_correct))\r\n%%\r\nhm = [0 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 0 1 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = false;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isHighCard(hm),y_correct))","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":240,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":55,"test_suite_updated_at":"2012-02-22T19:38:00.000Z","rescore_all_solutions":false,"group_id":15,"created_at":"2012-02-22T19:38:00.000Z","updated_at":"2026-02-15T05:43:12.000Z","published_at":"2012-02-22T19:48:08.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e--------\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eHigh Card is the five highest cards in your hand. It is basically what you have if you don't have anything else! The Ace (first column) is highest. The columns represent A, 2, 3, ... K. If the kickers also form a pair, it is still considered high card for the purposes of this function.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 0 0 1 0 0 0 0 0 0 0 0 \\n0 0 1 0 0 0 0 0 0 0 0 0 0\\n0 1 0 1 0 0 0 0 0 0 0 0 0 \\n0 1 0 0 0 1 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003erepresents a high card, so the return value from the function is TRUE.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix does not (because it is defined as five cards):\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 1 0 1 1 0 0 0 0 0 0 0 \\n0 0 0 0 0 0 0 0 0 0 0 0 0\\n0 0 0 0 0 0 0 0 0 0 0 0 0 \\n0 0 0 0 0 0 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eso the return value should be FALSE.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix does represent a high card\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 0 0 0 0 0 0 0 0 1 0 0 1 \\n0 0 0 0 0 0 0 0 0 0 1 0 0\\n0 0 0 0 0 0 0 0 0 1 0 0 0 \\n0 0 0 0 0 1 0 0 0 1 0 1 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eRemember, hand matrices can contain any number of 1's from 0 to 52.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 0 0 0 0 1 0 0 0 0 0 0 0 \\n0 0 0 0 1 1 1 0 0 0 0 0 1\\n0 0 0 1 0 1 0 0 0 1 0 0 0 \\n0 0 1 0 0 0 0 0 0 0 0 1 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWould be TRUE for this function.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand matrix, but it only shows the cards used to make the high card. If more than one hag card can be made, return the higher ranking one (the one with the highest rank. Ace being the highest). If different suits are possible for the same high card, return the one higher up in the matrix, same for kickers. If the high card also happens to also be a four of a kind or full house, it still meets the defintion and should be returned.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1512,"title":"Clock Solitaire","description":"Many card players will be familiar with the game of \u003chttp://en.wikipedia.org/wiki/Clock_patience Clock Solitaire\u003e. Briefly, the player sets up by creating thirteen piles of four face-down cards at random, each associated with one of the ranks ace through king. Beginning with the top card in the king's pile, the player places the drawn card face up beneath its home pile, and draws a new card from the top of that same pile. Play continues until the fourth king is drawn. If all cards are face up in their home piles at this time, the game is a winner.\r\n\r\nSince clock solitaire is a purely deterministic game, a computer can easily be programmed to play. For this problem, you will write a function that takes a deck and reports whether or not it is a winning configuration. More specifically, the input will be some permutation of the integers 1:52, where 1:13 represent the ace through king of clubs, 14:26 the ace through king of diamonds, 27:39 the hearts, and 40:52 the spades. Assume that the cards are formed into 13 piles by taking the first four cards as the ace pile, next four as the deuce pile, etc. Output is a single scalar boolean indicating whether the game will be won using this deck.\r\n\r\nArmed with this function, one can determine empirically what the win rate is for randomly shuffled decks. See if you can find out!","description_html":"\u003cp\u003eMany card players will be familiar with the game of \u003ca href = \"http://en.wikipedia.org/wiki/Clock_patience\"\u003eClock Solitaire\u003c/a\u003e. Briefly, the player sets up by creating thirteen piles of four face-down cards at random, each associated with one of the ranks ace through king. Beginning with the top card in the king's pile, the player places the drawn card face up beneath its home pile, and draws a new card from the top of that same pile. Play continues until the fourth king is drawn. If all cards are face up in their home piles at this time, the game is a winner.\u003c/p\u003e\u003cp\u003eSince clock solitaire is a purely deterministic game, a computer can easily be programmed to play. For this problem, you will write a function that takes a deck and reports whether or not it is a winning configuration. More specifically, the input will be some permutation of the integers 1:52, where 1:13 represent the ace through king of clubs, 14:26 the ace through king of diamonds, 27:39 the hearts, and 40:52 the spades. Assume that the cards are formed into 13 piles by taking the first four cards as the ace pile, next four as the deuce pile, etc. Output is a single scalar boolean indicating whether the game will be won using this deck.\u003c/p\u003e\u003cp\u003eArmed with this function, one can determine empirically what the win rate is for randomly shuffled decks. See if you can find out!\u003c/p\u003e","function_template":"function isWinner = clockSolitaire(deck)\r\n isWinner = true;\r\nend","test_suite":"%%\r\ndeck = [1:52];\r\nassert(isequal(clockSolitaire(deck),false))\r\n\r\n%%\r\ndeck = [8 1 5 2 30 23 46 21 3 51 6 27 42 48 37 33 12 25 45 36 31 34 29 35 15 17 43 13 39 40 18 50 26 9 4 28 38 16 11 22 49 24 14 7 32 20 47 44 19 10 41 52];\r\nassert(isequal(clockSolitaire(deck),true))\r\n%%\r\ndeck = [52:-1:1];\r\nassert(isequal(clockSolitaire(deck),false))\r\n\r\n%%\r\ndeck = [40 29 25 37 23 41 13 50 33 2 42 20 49 48 27 46 36 45 28 1 7 11 14 5 9 26 15 21 12 8 19 35 10 38 34 52 32 51 31 16 18 22 6 3 47 44 43 4 24 17 30 39];\r\nassert(isequal(clockSolitaire(deck),true))\r\n\r\n%%\r\ndeck = [40 29 25 37 23 41 13 50 33 2 42 20 52 48 27 46 36 45 28 1 7 11 14 5 9 26 15 21 12 8 19 35 10 38 34 49 32 51 31 16 18 22 6 3 47 44 43 4 24 17 30 39];\r\nassert(isequal(clockSolitaire(deck),false))\r\n\r\n%%\r\ndeck = [8 1 5 2 30 23 46 21 3 51 6 27 13 48 37 33 12 25 45 36 31 34 29 35 15 17 43 42 39 40 18 50 26 9 4 28 38 16 11 22 49 24 14 7 32 20 47 44 19 10 41 52];\r\nassert(isequal(clockSolitaire(deck),false))","published":true,"deleted":false,"likes_count":2,"comments_count":1,"created_by":3117,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":39,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":15,"created_at":"2013-05-16T01:27:06.000Z","updated_at":"2026-02-15T04:05:23.000Z","published_at":"2013-05-16T01:27:05.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eMany card players will be familiar with the game of \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://en.wikipedia.org/wiki/Clock_patience\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eClock Solitaire\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e. Briefly, the player sets up by creating thirteen piles of four face-down cards at random, each associated with one of the ranks ace through king. Beginning with the top card in the king's pile, the player places the drawn card face up beneath its home pile, and draws a new card from the top of that same pile. Play continues until the fourth king is drawn. If all cards are face up in their home piles at this time, the game is a winner.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eSince clock solitaire is a purely deterministic game, a computer can easily be programmed to play. For this problem, you will write a function that takes a deck and reports whether or not it is a winning configuration. More specifically, the input will be some permutation of the integers 1:52, where 1:13 represent the ace through king of clubs, 14:26 the ace through king of diamonds, 27:39 the hearts, and 40:52 the spades. Assume that the cards are formed into 13 piles by taking the first four cards as the ace pile, next four as the deuce pile, etc. Output is a single scalar boolean indicating whether the game will be won using this deck.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eArmed with this function, one can determine empirically what the win rate is for randomly shuffled decks. See if you can find out!\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":376,"title":"Poker Series 05: isStraight","description":"The Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\r\n\r\nA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\r\n\r\nFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\r\n\r\n--------\r\n\r\nA straight is 5 cards of the adjacent ranks (columns) regardless of suits (rows). The Ace (first column) is both lowest and highest. The columns represent A, 2, 3, ... K. This means A, K, Q, J, Ten is a straight also.\r\n\r\nThis hand matrix:\r\n\r\n 0 1 0 0 1 0 0 0 0 0 0 0 0 \r\n 0 0 1 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 1 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 1 0 0 0 0 0 0 0\r\n\r\nrepresents a straight, so the return value from the function is TRUE.\r\n\r\nThis hand matrix does not:\r\n\r\n 0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 1 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n\r\nso the return value should be FALSE.\r\n\r\nThis hand matrix does represent a straight\r\n\r\n 0 0 0 0 0 0 0 0 0 1 0 0 1 \r\n 0 0 0 0 0 0 0 0 0 0 1 0 0\r\n 0 0 1 0 0 0 0 0 0 0 0 0 0 \r\n 1 0 0 0 0 1 0 0 0 0 0 1 0\r\n\r\nRemember, hand matrices can contain any number of 1's from 0 to 52.\r\n\r\n 0 0 0 0 0 1 0 0 0 0 0 0 0 \r\n 0 0 0 0 1 0 1 0 0 0 0 0 0\r\n 0 0 0 1 0 0 0 0 0 0 0 0 0 \r\n 0 0 1 0 0 0 0 0 0 0 0 0 0 \r\n\r\nWould be TRUE for this function.\r\n\r\nA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand matrix, but it only shows the cards used to make the straight. If more than one straight can be made, return the higher ranking one (the one with the highest top card. Ace being the highest). If different suits are possible for the same straight cards, return the one higher up in the matrix. If the straight happens to also be a straight flush, it still meets the defintion and should be returned. The highest straight should be returned, even if a straight flush can also be made.","description_html":"\u003cp\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/p\u003e\u003cp\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/p\u003e\u003cp\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/p\u003e\u003cp\u003e--------\u003c/p\u003e\u003cp\u003eA straight is 5 cards of the adjacent ranks (columns) regardless of suits (rows). The Ace (first column) is both lowest and highest. The columns represent A, 2, 3, ... K. This means A, K, Q, J, Ten is a straight also.\u003c/p\u003e\u003cp\u003eThis hand matrix:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 0 0 1 0 0 0 0 0 0 0 0 \r\n0 0 1 0 0 0 0 0 0 0 0 0 0\r\n0 0 0 1 0 0 0 0 0 0 0 0 0 \r\n0 0 0 0 0 1 0 0 0 0 0 0 0\r\n\u003c/pre\u003e\u003cp\u003erepresents a straight, so the return value from the function is TRUE.\u003c/p\u003e\u003cp\u003eThis hand matrix does not:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n0 0 0 0 0 0 0 0 0 0 0 0 0\r\n0 0 0 0 0 0 0 0 0 1 0 0 0 \r\n0 0 0 0 0 0 0 0 0 0 0 0 0\r\n\u003c/pre\u003e\u003cp\u003eso the return value should be FALSE.\u003c/p\u003e\u003cp\u003eThis hand matrix does represent a straight\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 0 0 0 0 0 0 0 0 1 0 0 1 \r\n0 0 0 0 0 0 0 0 0 0 1 0 0\r\n0 0 1 0 0 0 0 0 0 0 0 0 0 \r\n1 0 0 0 0 1 0 0 0 0 0 1 0\r\n\u003c/pre\u003e\u003cp\u003eRemember, hand matrices can contain any number of 1's from 0 to 52.\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 0 0 0 0 1 0 0 0 0 0 0 0 \r\n0 0 0 0 1 0 1 0 0 0 0 0 0\r\n0 0 0 1 0 0 0 0 0 0 0 0 0 \r\n0 0 1 0 0 0 0 0 0 0 0 0 0 \r\n\u003c/pre\u003e\u003cp\u003eWould be TRUE for this function.\u003c/p\u003e\u003cp\u003eA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand matrix, but it only shows the cards used to make the straight. If more than one straight can be made, return the higher ranking one (the one with the highest top card. Ace being the highest). If different suits are possible for the same straight cards, return the one higher up in the matrix. If the straight happens to also be a straight flush, it still meets the defintion and should be returned. The highest straight should be returned, even if a straight flush can also be made.\u003c/p\u003e","function_template":"function out = isStraight(hm)\r\n out.flag = false;\r\n out.usedCards = false(4,13);\r\nend","test_suite":"%%\r\nhm = [0 1 0 0 0 0 0 0 1 1 0 1 1 \r\n 0 1 0 0 0 0 0 0 1 0 0 1 0\r\n 0 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = false;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isStraight(hm),y_correct))\r\n\r\n%%\r\nhm = [0 1 1 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 1 0 0 0 0 0 0 0\r\n 0 0 0 1 0 0 0 0 0 1 0 1 0 \r\n 0 0 0 0 1 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 1 1 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 1 0 0 0 0 0 0 0\r\n 0 0 0 1 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 1 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isStraight(hm),y_correct))\r\n\r\n%%\r\nhm = [0 1 1 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 1 0 0 0 0 0 0 0\r\n 0 1 0 1 0 0 0 0 0 1 0 1 0 \r\n 0 0 0 0 1 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 1 1 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 1 0 0 0 0 0 0 0\r\n 0 0 0 1 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 1 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isStraight(hm),y_correct))\r\n\r\n%%\r\nhm = [0 1 1 0 0 0 0 0 0 0 0 0 0 \r\n 1 0 0 0 0 1 0 0 0 0 0 0 0\r\n 0 1 0 1 0 0 0 0 0 1 0 1 0 \r\n 0 0 0 0 1 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 1 1 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 1 0 0 0 0 0 0 0\r\n 0 0 0 1 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 1 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isStraight(hm),y_correct))\r\n\r\n%%\r\nhm = [0 1 1 0 0 0 0 0 0 0 1 0 0 \r\n 0 0 0 0 0 1 0 0 0 0 0 0 1\r\n 0 1 0 1 0 0 0 0 0 1 0 1 0 \r\n 1 0 0 0 1 0 0 0 0 0 0 0 1];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 1 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 1\r\n 0 0 0 0 0 0 0 0 0 1 0 1 0 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isStraight(hm),y_correct))","published":true,"deleted":false,"likes_count":1,"comments_count":3,"created_by":240,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":62,"test_suite_updated_at":"2012-02-21T19:24:51.000Z","rescore_all_solutions":false,"group_id":15,"created_at":"2012-02-21T19:24:51.000Z","updated_at":"2026-02-15T05:51:00.000Z","published_at":"2012-02-21T19:50:10.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e--------\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA straight is 5 cards of the adjacent ranks (columns) regardless of suits (rows). The Ace (first column) is both lowest and highest. The columns represent A, 2, 3, ... K. This means A, K, Q, J, Ten is a straight also.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 0 0 1 0 0 0 0 0 0 0 0 \\n0 0 1 0 0 0 0 0 0 0 0 0 0\\n0 0 0 1 0 0 0 0 0 0 0 0 0 \\n0 0 0 0 0 1 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003erepresents a straight, so the return value from the function is TRUE.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix does not:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 1 0 1 1 0 0 0 0 0 0 0 \\n0 0 0 0 0 0 0 0 0 0 0 0 0\\n0 0 0 0 0 0 0 0 0 1 0 0 0 \\n0 0 0 0 0 0 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eso the return value should be FALSE.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix does represent a straight\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 0 0 0 0 0 0 0 0 1 0 0 1 \\n0 0 0 0 0 0 0 0 0 0 1 0 0\\n0 0 1 0 0 0 0 0 0 0 0 0 0 \\n1 0 0 0 0 1 0 0 0 0 0 1 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eRemember, hand matrices can contain any number of 1's from 0 to 52.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 0 0 0 0 1 0 0 0 0 0 0 0 \\n0 0 0 0 1 0 1 0 0 0 0 0 0\\n0 0 0 1 0 0 0 0 0 0 0 0 0 \\n0 0 1 0 0 0 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWould be TRUE for this function.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand matrix, but it only shows the cards used to make the straight. If more than one straight can be made, return the higher ranking one (the one with the highest top card. Ace being the highest). If different suits are possible for the same straight cards, return the one higher up in the matrix. If the straight happens to also be a straight flush, it still meets the defintion and should be returned. The highest straight should be returned, even if a straight flush can also be made.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":335,"title":"Poker Series 04: isFlush","description":"The Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\r\n\r\nA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\r\n\r\nFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\r\n\r\n--------\r\n\r\nA flush is 5 cards of the same suit (row). If there are more than five cards in a suit to choose from, the highest five count. The Ace (first column) is the highest. The columns represent A, 2, 3, ... K.\r\n\r\nThis hand matrix:\r\n\r\n 0 1 1 0 1 1 0 0 0 0 0 1 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n\r\nrepresents a flush, so the return value from the function is TRUE.\r\n\r\nThis hand matrix does not:\r\n\r\n 0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n 0 0 0 1 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n\r\nso the return value should be FALSE.\r\n\r\nThis hand matrix does represent a flush\r\n\r\n 1 0 0 0 0 0 0 0 0 1 1 1 1 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 1 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 1 0 0 0 0 0 0 0\r\n\r\nRemember, hand matrices can contain any number of 1's from 0 to 52.\r\n\r\n 0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n 0 0 0 0 1 0 1 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 1 0 0 0 0 0 0 0 0 0 0 \r\n\r\nWould be FALSE for this function.\r\n\r\nA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand matrix, but it only shows the cards used to make the flush. If more than one flush can be made, return the higher ranking one (the one with the highest top card. Ace being the highest- ties broken by the second, third, fourth, and then fifth card). If different suits are possible for the same flush, return the one higher up in the matrix. If the flush happens to also be a straight flush, it still meets the defintion and should be returned. The highest flush should be returned, even if a straight flush can also be made.","description_html":"\u003cp\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/p\u003e\u003cp\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/p\u003e\u003cp\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/p\u003e\u003cp\u003e--------\u003c/p\u003e\u003cp\u003eA flush is 5 cards of the same suit (row). If there are more than five cards in a suit to choose from, the highest five count. The Ace (first column) is the highest. The columns represent A, 2, 3, ... K.\u003c/p\u003e\u003cp\u003eThis hand matrix:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 1 0 1 1 0 0 0 0 0 1 0 \r\n0 0 0 0 0 0 0 0 0 0 0 0 0\r\n0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n0 0 0 0 0 0 0 0 0 0 0 0 0\r\n\u003c/pre\u003e\u003cp\u003erepresents a flush, so the return value from the function is TRUE.\u003c/p\u003e\u003cp\u003eThis hand matrix does not:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n0 0 0 1 0 0 0 0 0 0 0 0 0\r\n0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n0 0 0 0 0 0 0 0 0 0 0 0 0\r\n\u003c/pre\u003e\u003cp\u003eso the return value should be FALSE.\u003c/p\u003e\u003cp\u003eThis hand matrix does represent a flush\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e1 0 0 0 0 0 0 0 0 1 1 1 1 \r\n0 0 0 0 0 0 0 0 0 0 0 0 0\r\n0 0 1 0 0 0 0 0 0 0 0 0 0 \r\n0 0 0 0 0 1 0 0 0 0 0 0 0\r\n\u003c/pre\u003e\u003cp\u003eRemember, hand matrices can contain any number of 1's from 0 to 52.\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n0 0 0 0 1 0 1 0 0 0 0 0 0\r\n0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n0 0 1 0 0 0 0 0 0 0 0 0 0 \r\n\u003c/pre\u003e\u003cp\u003eWould be FALSE for this function.\u003c/p\u003e\u003cp\u003eA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand matrix, but it only shows the cards used to make the flush. If more than one flush can be made, return the higher ranking one (the one with the highest top card. Ace being the highest- ties broken by the second, third, fourth, and then fifth card). If different suits are possible for the same flush, return the one higher up in the matrix. If the flush happens to also be a straight flush, it still meets the defintion and should be returned. The highest flush should be returned, even if a straight flush can also be made.\u003c/p\u003e","function_template":"function out = isFlush(hm)\r\n out.flag = false;\r\n out.usedCards = false(4,13);\r\nend","test_suite":"%%\r\nhm = [0 1 0 0 0 0 0 0 1 1 0 1 1 \r\n 0 1 0 0 0 0 0 0 1 0 0 1 0\r\n 0 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 1 0 0 0 0 0 0 1 1 0 1 1 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isFlush(hm),y_correct))\r\n\r\n%%\r\nhm = [1 1 0 0 0 0 0 0 1 1 0 1 1 \r\n 0 1 0 0 0 0 0 0 1 0 0 1 0\r\n 0 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([1 0 0 0 0 0 0 0 1 1 0 1 1 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isFlush(hm),y_correct))\r\n\r\n%%\r\nhm = [1 1 0 0 0 0 0 0 1 1 0 1 0 \r\n 0 1 0 0 0 0 0 0 1 0 0 1 0\r\n 1 1 0 1 0 0 0 0 1 1 1 1 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 1 0 0 0 0 0 0 0 1 1 1 1 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isFlush(hm),y_correct))\r\n\r\n%%\r\nhm = [1 1 0 0 0 0 0 0 1 1 0 1 0 \r\n 0 1 0 0 0 0 0 0 1 0 0 1 0\r\n 1 1 0 1 0 0 0 0 1 1 1 1 0 \r\n 1 0 0 0 0 0 0 0 1 1 1 1 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 1 0 0 0 0 0 0 0 1 1 1 1 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isFlush(hm),y_correct))\r\n\r\n%%\r\nhm = [1 1 0 0 0 0 0 0 0 0 0 1 0 \r\n 0 1 0 0 0 0 0 0 1 0 0 1 0\r\n 0 0 0 0 0 0 0 0 1 0 1 1 0 \r\n 1 0 0 0 0 0 0 0 1 1 0 1 0];\r\n\r\ny_correct.flag = false;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isFlush(hm),y_correct))","published":true,"deleted":false,"likes_count":1,"comments_count":3,"created_by":240,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":69,"test_suite_updated_at":"2012-02-21T19:24:06.000Z","rescore_all_solutions":false,"group_id":15,"created_at":"2012-02-17T21:55:47.000Z","updated_at":"2026-04-02T20:50:40.000Z","published_at":"2012-02-21T19:24:06.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e--------\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA flush is 5 cards of the same suit (row). If there are more than five cards in a suit to choose from, the highest five count. The Ace (first column) is the highest. The columns represent A, 2, 3, ... K.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 1 0 1 1 0 0 0 0 0 1 0 \\n0 0 0 0 0 0 0 0 0 0 0 0 0\\n0 0 0 0 0 0 0 0 0 0 0 0 0 \\n0 0 0 0 0 0 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003erepresents a flush, so the return value from the function is TRUE.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix does not:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 1 0 1 1 0 0 0 0 0 0 0 \\n0 0 0 1 0 0 0 0 0 0 0 0 0\\n0 0 0 0 0 0 0 0 0 0 0 0 0 \\n0 0 0 0 0 0 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eso the return value should be FALSE.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix does represent a flush\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[1 0 0 0 0 0 0 0 0 1 1 1 1 \\n0 0 0 0 0 0 0 0 0 0 0 0 0\\n0 0 1 0 0 0 0 0 0 0 0 0 0 \\n0 0 0 0 0 1 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eRemember, hand matrices can contain any number of 1's from 0 to 52.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 1 0 1 1 0 0 0 0 0 0 0 \\n0 0 0 0 1 0 1 0 0 0 0 0 0\\n0 0 0 0 0 0 0 0 0 0 0 0 0 \\n0 0 1 0 0 0 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWould be FALSE for this function.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand matrix, but it only shows the cards used to make the flush. If more than one flush can be made, return the higher ranking one (the one with the highest top card. Ace being the highest- ties broken by the second, third, fourth, and then fifth card). If different suits are possible for the same flush, return the one higher up in the matrix. If the flush happens to also be a straight flush, it still meets the defintion and should be returned. The highest flush should be returned, even if a straight flush can also be made.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":329,"title":"Poker Series 01: isStraightFlush","description":"The Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\r\nA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\r\nFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\r\n--------\r\nA straight flush is 5 cards of the same suit (row) and five continuous ranks (columns). The Ace (first column) can also make a straight flush when combined with the last four columns. The columns represent A, 2, 3, ... K.\r\nThis hand matrix:\r\n0 1 1 1 1 1 0 0 0 0 0 0 0 \r\n0 0 0 0 0 0 0 0 0 0 0 0 0\r\n0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n0 0 0 0 0 0 0 0 0 0 0 0 0\r\nrepresents a straight flush, so the return value from the function is TRUE.\r\nThis hand matrix does not:\r\n0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n0 0 0 1 0 0 0 0 0 0 0 0 0\r\n0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n0 0 0 0 0 0 0 0 0 0 0 0 0\r\nso the return value should be FALSE.\r\nThis hand matrix does represent a straight flush\r\n1 0 0 0 0 0 0 0 0 1 1 1 1 \r\n0 0 0 0 0 0 0 0 0 0 0 0 0\r\n0 0 1 0 0 0 0 0 0 0 0 0 0 \r\n0 0 0 0 0 1 0 0 0 0 0 0 0\r\nRemember, hand matrices can contain any number of 1's from 0 to 52.\r\n0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n0 0 0 0 1 0 1 0 0 0 0 0 0\r\n0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n0 0 1 0 0 0 0 0 0 0 0 0 0\r\nWould be FALSE for this function.\r\nA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand Matrix, but it only shows the cards used to make the Straight Flush. If more than one straight flush can be made, return the higher ranking one (the one with the highest top card. Ace being the highest). If different suits are possible for the same straight flush, return the one higher up in the matrix.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 940.933px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 470.467px; transform-origin: 407px 470.467px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 373px 8px; transform-origin: 373px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 31.5px; text-align: left; transform-origin: 384px 31.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 373px 8px; transform-origin: 373px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 31.5px; text-align: left; transform-origin: 384px 31.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 384px 8px; transform-origin: 384px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 20px 8px; transform-origin: 20px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e--------\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 369.5px 8px; transform-origin: 369.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eA straight flush is 5 cards of the same suit (row) and five continuous ranks (columns). The Ace (first column) can also make a straight flush when combined with the last four columns. The columns represent A, 2, 3, ... K.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 54px 8px; transform-origin: 54px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThis hand matrix:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 81.7333px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-end-end-radius: 4px; border-end-start-radius: 4px; border-start-end-radius: 4px; border-start-start-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 404px 40.8667px; transform-origin: 404px 40.8667px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 104px 8.5px; tab-size: 4; transform-origin: 104px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e0 1 1 1 1 1 0 0 0 0 0 0 0 \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 100px 8.5px; tab-size: 4; transform-origin: 100px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e0 0 0 0 0 0 0 0 0 0 0 0 0\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 104px 8.5px; tab-size: 4; transform-origin: 104px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e0 0 0 0 0 0 0 0 0 0 0 0 0 \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 100px 8.5px; tab-size: 4; transform-origin: 100px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e0 0 0 0 0 0 0 0 0 0 0 0 0\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 10px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 10px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 10px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 230.5px 8px; transform-origin: 230.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003erepresents a straight flush, so the return value from the function is TRUE.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 83.5px 8px; transform-origin: 83.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThis hand matrix does not:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 81.7333px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-end-end-radius: 4px; border-end-start-radius: 4px; border-start-end-radius: 4px; border-start-start-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 404px 40.8667px; transform-origin: 404px 40.8667px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 104px 8.5px; tab-size: 4; transform-origin: 104px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e0 1 1 0 1 1 0 0 0 0 0 0 0 \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 100px 8.5px; tab-size: 4; transform-origin: 100px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e0 0 0 1 0 0 0 0 0 0 0 0 0\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 104px 8.5px; tab-size: 4; transform-origin: 104px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e0 0 0 0 0 0 0 0 0 0 0 0 0 \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 100px 8.5px; tab-size: 4; transform-origin: 100px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e0 0 0 0 0 0 0 0 0 0 0 0 0\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 10px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 10px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 10px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 118px 8px; transform-origin: 118px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eso the return value should be FALSE.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 150.5px 8px; transform-origin: 150.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThis hand matrix does represent a straight flush\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 81.7333px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-end-end-radius: 4px; border-end-start-radius: 4px; border-start-end-radius: 4px; border-start-start-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 404px 40.8667px; transform-origin: 404px 40.8667px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 104px 8.5px; tab-size: 4; transform-origin: 104px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e1 0 0 0 0 0 0 0 0 1 1 1 1 \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 100px 8.5px; tab-size: 4; transform-origin: 100px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e0 0 0 0 0 0 0 0 0 0 0 0 0\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 104px 8.5px; tab-size: 4; transform-origin: 104px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e0 0 1 0 0 0 0 0 0 0 0 0 0 \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 100px 8.5px; tab-size: 4; transform-origin: 100px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e0 0 0 0 0 1 0 0 0 0 0 0 0\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 10px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 10px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 10px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 221.5px 8px; transform-origin: 221.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eRemember, hand matrices can contain any number of 1's from 0 to 52.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 81.7333px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-end-end-radius: 4px; border-end-start-radius: 4px; border-start-end-radius: 4px; border-start-start-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 404px 40.8667px; transform-origin: 404px 40.8667px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 104px 8.5px; tab-size: 4; transform-origin: 104px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e0 1 1 0 1 1 0 0 0 0 0 0 0 \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 100px 8.5px; tab-size: 4; transform-origin: 100px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e0 0 0 0 1 0 1 0 0 0 0 0 0\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 104px 8.5px; tab-size: 4; transform-origin: 104px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e0 0 0 0 0 0 0 0 0 0 0 0 0 \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 100px 8.5px; tab-size: 4; transform-origin: 100px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e0 0 1 0 0 0 0 0 0 0 0 0 0\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 10px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 10px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 10px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 106px 8px; transform-origin: 106px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eWould be FALSE for this function.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 84px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 42px; text-align: left; transform-origin: 384px 42px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 370px 8px; transform-origin: 370px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand Matrix, but it only shows the cards used to make the Straight Flush. If more than one straight flush can be made, return the higher ranking one (the one with the highest top card. Ace being the highest). If different suits are possible for the same straight flush, return the one higher up in the matrix.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function out = isStraightFlush(hm)\r\n out.flag = false;\r\n out.usedCards = false(4,13);\r\nend","test_suite":"%%\r\nhm = [0 0 0 0 0 0 0 0 1 1 1 1 1 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 1 1 1 1 1 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\nassert(isequal(isStraightFlush(hm),y_correct))\r\n\r\n%%\r\nhm = [0 0 0 0 0 0 0 0 1 1 0 1 1 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 1 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = false;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\nassert(isequal(isStraightFlush(hm),y_correct))\r\n\r\n%%\r\nhm = [0 0 0 0 0 0 0 0 1 1 0 1 1 \r\n 1 0 0 0 0 0 0 0 0 1 1 1 1\r\n 0 1 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 1 1 1 1\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\nassert(isequal(isStraightFlush(hm),y_correct))\r\n\r\n%%\r\nhm = [0 0 0 0 0 0 0 0 1 1 0 1 1 \r\n 1 0 0 0 0 0 0 0 0 1 1 1 1\r\n 1 1 0 0 0 0 0 0 0 1 1 1 1 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 1 1 1 1\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\nassert(isequal(isStraightFlush(hm),y_correct))","published":true,"deleted":false,"likes_count":3,"comments_count":8,"created_by":240,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":124,"test_suite_updated_at":"2021-09-27T06:47:34.000Z","rescore_all_solutions":false,"group_id":15,"created_at":"2012-02-16T20:30:55.000Z","updated_at":"2026-04-02T20:19:31.000Z","published_at":"2012-02-17T18:24:19.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e--------\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA straight flush is 5 cards of the same suit (row) and five continuous ranks (columns). The Ace (first column) can also make a straight flush when combined with the last four columns. The columns represent A, 2, 3, ... K.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 1 1 1 1 0 0 0 0 0 0 0 \\n0 0 0 0 0 0 0 0 0 0 0 0 0\\n0 0 0 0 0 0 0 0 0 0 0 0 0 \\n0 0 0 0 0 0 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003erepresents a straight flush, so the return value from the function is TRUE.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix does not:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 1 0 1 1 0 0 0 0 0 0 0 \\n0 0 0 1 0 0 0 0 0 0 0 0 0\\n0 0 0 0 0 0 0 0 0 0 0 0 0 \\n0 0 0 0 0 0 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eso the return value should be FALSE.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix does represent a straight flush\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[1 0 0 0 0 0 0 0 0 1 1 1 1 \\n0 0 0 0 0 0 0 0 0 0 0 0 0\\n0 0 1 0 0 0 0 0 0 0 0 0 0 \\n0 0 0 0 0 1 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eRemember, hand matrices can contain any number of 1's from 0 to 52.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 1 0 1 1 0 0 0 0 0 0 0 \\n0 0 0 0 1 0 1 0 0 0 0 0 0\\n0 0 0 0 0 0 0 0 0 0 0 0 0 \\n0 0 1 0 0 0 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWould be FALSE for this function.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand Matrix, but it only shows the cards used to make the Straight Flush. If more than one straight flush can be made, return the higher ranking one (the one with the highest top card. Ace being the highest). If different suits are possible for the same straight flush, return the one higher up in the matrix.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":377,"title":"Poker Series 06: isThreeKind","description":"The Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\r\n\r\nA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\r\n\r\nFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\r\n\r\n--------\r\n\r\nA three of a kind is 3 cards of the same rank (column). The Ace (first column) is highest. The columns represent A, 2, 3, ... K. The next two highest cards are the kickers. If the kickers also form a pair, it is still considered three of a kind for the purposes of this function.\r\n\r\nThis hand matrix:\r\n\r\n 0 1 0 0 1 0 0 0 0 0 0 0 0 \r\n 0 0 1 0 0 0 0 0 0 0 0 0 0\r\n 0 1 0 1 0 0 0 0 0 0 0 0 0 \r\n 0 1 0 0 0 1 0 0 0 0 0 0 0\r\n\r\nrepresents a three of a kind, so the return value from the function is TRUE.\r\n\r\nThis hand matrix does not:\r\n\r\n 0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 1 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n\r\nso the return value should be FALSE.\r\n\r\nThis hand matrix does represent a three of a kind\r\n\r\n 0 0 0 0 0 0 0 0 0 1 0 0 1 \r\n 0 0 0 0 0 0 0 0 0 0 1 0 0\r\n 0 0 0 0 0 0 0 0 0 1 0 0 0 \r\n 0 0 0 0 0 1 0 0 0 1 0 1 0\r\n\r\nRemember, hand matrices can contain any number of 1's from 0 to 52.\r\n\r\n 0 0 0 0 0 1 0 0 0 0 0 0 0 \r\n 0 0 0 0 1 1 1 0 0 0 0 0 1\r\n 0 0 0 1 0 1 0 0 0 1 0 0 0 \r\n 0 0 1 0 0 0 0 0 0 0 0 1 0 \r\n\r\nWould be TRUE for this function.\r\n\r\nA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand matrix, but it only shows the cards used to make the three of a kind. If more than one three of a kind can be made, return the higher ranking one (the one with the highest rank. Ace being the highest). If different suits are possible for the same three of a kind cards, return the one higher up in the matrix, same for kickers. If the three of a kind happens to also be a four of a kind or full house, it still meets the defintion and should be returned.","description_html":"\u003cp\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/p\u003e\u003cp\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/p\u003e\u003cp\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/p\u003e\u003cp\u003e--------\u003c/p\u003e\u003cp\u003eA three of a kind is 3 cards of the same rank (column). The Ace (first column) is highest. The columns represent A, 2, 3, ... K. The next two highest cards are the kickers. If the kickers also form a pair, it is still considered three of a kind for the purposes of this function.\u003c/p\u003e\u003cp\u003eThis hand matrix:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 0 0 1 0 0 0 0 0 0 0 0 \r\n0 0 1 0 0 0 0 0 0 0 0 0 0\r\n0 1 0 1 0 0 0 0 0 0 0 0 0 \r\n0 1 0 0 0 1 0 0 0 0 0 0 0\r\n\u003c/pre\u003e\u003cp\u003erepresents a three of a kind, so the return value from the function is TRUE.\u003c/p\u003e\u003cp\u003eThis hand matrix does not:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n0 0 0 0 0 0 0 0 0 0 0 0 0\r\n0 0 0 0 0 0 0 0 0 1 0 0 0 \r\n0 0 0 0 0 0 0 0 0 0 0 0 0\r\n\u003c/pre\u003e\u003cp\u003eso the return value should be FALSE.\u003c/p\u003e\u003cp\u003eThis hand matrix does represent a three of a kind\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 0 0 0 0 0 0 0 0 1 0 0 1 \r\n0 0 0 0 0 0 0 0 0 0 1 0 0\r\n0 0 0 0 0 0 0 0 0 1 0 0 0 \r\n0 0 0 0 0 1 0 0 0 1 0 1 0\r\n\u003c/pre\u003e\u003cp\u003eRemember, hand matrices can contain any number of 1's from 0 to 52.\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 0 0 0 0 1 0 0 0 0 0 0 0 \r\n0 0 0 0 1 1 1 0 0 0 0 0 1\r\n0 0 0 1 0 1 0 0 0 1 0 0 0 \r\n0 0 1 0 0 0 0 0 0 0 0 1 0 \r\n\u003c/pre\u003e\u003cp\u003eWould be TRUE for this function.\u003c/p\u003e\u003cp\u003eA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand matrix, but it only shows the cards used to make the three of a kind. If more than one three of a kind can be made, return the higher ranking one (the one with the highest rank. Ace being the highest). If different suits are possible for the same three of a kind cards, return the one higher up in the matrix, same for kickers. If the three of a kind happens to also be a four of a kind or full house, it still meets the defintion and should be returned.\u003c/p\u003e","function_template":"function out = isThreeKind(hm)\r\n out.flag = false;\r\n out.usedCards = false(4,13);\r\nend","test_suite":"%%\r\nhm = [0 1 0 0 0 0 0 0 1 1 0 1 1 \r\n 0 1 0 0 0 0 0 0 1 0 0 1 0\r\n 0 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 1 0 0 1 1 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0\r\n 0 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isThreeKind(hm),y_correct))\r\n\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 1 1 0 1 1 \r\n 0 1 0 0 0 0 0 0 1 0 0 0 0\r\n 1 0 0 1 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 1 0 0 0 1 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0\r\n 1 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0])\r\n \r\nassert(isequal(isThreeKind(hm),y_correct))\r\n\r\n%%\r\nhm = [1 1 0 0 0 0 0 0 1 1 0 0 1 \r\n 0 1 0 0 0 0 0 0 1 0 0 1 0\r\n 1 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([1 0 0 0 0 0 0 0 0 0 0 0 1 \r\n 0 0 0 0 0 0 0 0 0 0 0 1 0\r\n 1 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isThreeKind(hm),y_correct))\r\n\r\n%%\r\nhm = [1 1 0 0 0 0 0 0 1 1 0 0 1 \r\n 0 1 0 0 0 0 0 0 1 0 0 1 0\r\n 1 0 0 1 0 0 0 0 1 0 0 0 1 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 1];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([1 0 0 0 0 0 0 0 0 0 0 0 1 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 1 0 0 0 0 0 0 0 0 0 0 0 1 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isThreeKind(hm),y_correct))\r\n\r\n%%\r\nhm = [1 1 0 0 0 0 0 0 1 1 0 0 1 \r\n 0 1 0 0 0 0 0 0 0 0 0 1 0\r\n 1 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = false;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isThreeKind(hm),y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":240,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":56,"test_suite_updated_at":"2012-02-21T21:50:59.000Z","rescore_all_solutions":false,"group_id":15,"created_at":"2012-02-21T21:17:05.000Z","updated_at":"2026-02-15T05:49:06.000Z","published_at":"2012-02-22T17:26:53.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e--------\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA three of a kind is 3 cards of the same rank (column). The Ace (first column) is highest. The columns represent A, 2, 3, ... K. The next two highest cards are the kickers. If the kickers also form a pair, it is still considered three of a kind for the purposes of this function.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 0 0 1 0 0 0 0 0 0 0 0 \\n0 0 1 0 0 0 0 0 0 0 0 0 0\\n0 1 0 1 0 0 0 0 0 0 0 0 0 \\n0 1 0 0 0 1 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003erepresents a three of a kind, so the return value from the function is TRUE.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix does not:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 1 0 1 1 0 0 0 0 0 0 0 \\n0 0 0 0 0 0 0 0 0 0 0 0 0\\n0 0 0 0 0 0 0 0 0 1 0 0 0 \\n0 0 0 0 0 0 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eso the return value should be FALSE.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix does represent a three of a kind\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 0 0 0 0 0 0 0 0 1 0 0 1 \\n0 0 0 0 0 0 0 0 0 0 1 0 0\\n0 0 0 0 0 0 0 0 0 1 0 0 0 \\n0 0 0 0 0 1 0 0 0 1 0 1 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eRemember, hand matrices can contain any number of 1's from 0 to 52.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 0 0 0 0 1 0 0 0 0 0 0 0 \\n0 0 0 0 1 1 1 0 0 0 0 0 1\\n0 0 0 1 0 1 0 0 0 1 0 0 0 \\n0 0 1 0 0 0 0 0 0 0 0 1 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWould be TRUE for this function.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand matrix, but it only shows the cards used to make the three of a kind. If more than one three of a kind can be made, return the higher ranking one (the one with the highest rank. Ace being the highest). If different suits are possible for the same three of a kind cards, return the one higher up in the matrix, same for kickers. If the three of a kind happens to also be a four of a kind or full house, it still meets the defintion and should be returned.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":334,"title":"Poker Series 03: isFullHouse","description":"The Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\r\n\r\nA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\r\n\r\nFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\r\n\r\n--------\r\n\r\nA full house is three cards of one rank (column) and two cards of a different rank. The Ace (first column) is the highest rank. The columns represent A, 2, 3, ... K. When there is a choice between two possible three of a kind, choose the higher. Once a three of a kind is choosen, choose the highest possible pair.\r\n\r\nThis hand matrix:\r\n\r\n 0 1 0 0 0 0 0 1 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 1 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 1 0 0 0 0 0 1 0 0 0 0 0\r\n\r\nrepresents a full house, so the return value from the function is TRUE.\r\n\r\nThis hand matrix does not:\r\n\r\n 0 1 1 0 1 0 0 0 0 0 0 0 0 \r\n 0 0 0 1 0 0 0 0 0 0 0 0 0\r\n 0 0 0 1 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 1 0 0 0 0 0 0 0 0 0\r\n\r\nso the return value should be FALSE.\r\n\r\nThis hand matrix does represent a full house\r\n\r\n 1 0 1 0 0 0 0 0 0 0 1 0 1 \r\n 0 0 1 0 0 1 0 0 0 0 0 0 0\r\n 0 0 1 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 1 0 0 0 0 0 0 0\r\n\r\nRemember, hand matrices can contain any number of 1's from 0 to 52.\r\n\r\n 0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n 0 0 0 0 1 0 1 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 1 0 0 0 0 0 0 0 0 0 0 \r\n\r\nWould be FALSE for this function.\r\n\r\nA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand Matrix, but it only shows the cards used to make the full house. If more than one full house can be made, return the higher ranking one (the one with the highest ranking three of a kind. Ace being the highest. Ties are broken with the highest ranking pair). If different suits are possible for the same full house, return the ones higher up in the matrix.","description_html":"\u003cp\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/p\u003e\u003cp\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/p\u003e\u003cp\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/p\u003e\u003cp\u003e--------\u003c/p\u003e\u003cp\u003eA full house is three cards of one rank (column) and two cards of a different rank. The Ace (first column) is the highest rank. The columns represent A, 2, 3, ... K. When there is a choice between two possible three of a kind, choose the higher. Once a three of a kind is choosen, choose the highest possible pair.\u003c/p\u003e\u003cp\u003eThis hand matrix:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 0 0 0 0 0 1 0 0 0 0 0 \r\n0 0 0 0 0 0 0 0 0 0 0 0 0\r\n0 1 0 0 0 0 0 0 0 0 0 0 0 \r\n0 1 0 0 0 0 0 1 0 0 0 0 0\r\n\u003c/pre\u003e\u003cp\u003erepresents a full house, so the return value from the function is TRUE.\u003c/p\u003e\u003cp\u003eThis hand matrix does not:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 1 0 1 0 0 0 0 0 0 0 0 \r\n0 0 0 1 0 0 0 0 0 0 0 0 0\r\n0 0 0 1 0 0 0 0 0 0 0 0 0 \r\n0 0 0 1 0 0 0 0 0 0 0 0 0\r\n\u003c/pre\u003e\u003cp\u003eso the return value should be FALSE.\u003c/p\u003e\u003cp\u003eThis hand matrix does represent a full house\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e1 0 1 0 0 0 0 0 0 0 1 0 1 \r\n0 0 1 0 0 1 0 0 0 0 0 0 0\r\n0 0 1 0 0 0 0 0 0 0 0 0 0 \r\n0 0 0 0 0 1 0 0 0 0 0 0 0\r\n\u003c/pre\u003e\u003cp\u003eRemember, hand matrices can contain any number of 1's from 0 to 52.\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n0 0 0 0 1 0 1 0 0 0 0 0 0\r\n0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n0 0 1 0 0 0 0 0 0 0 0 0 0 \r\n\u003c/pre\u003e\u003cp\u003eWould be FALSE for this function.\u003c/p\u003e\u003cp\u003eA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand Matrix, but it only shows the cards used to make the full house. If more than one full house can be made, return the higher ranking one (the one with the highest ranking three of a kind. Ace being the highest. Ties are broken with the highest ranking pair). If different suits are possible for the same full house, return the ones higher up in the matrix.\u003c/p\u003e","function_template":"function out = isFullHouse(hm)\r\n out.flag = false;\r\n out.usedCards = false(4,13);\r\nend","test_suite":"%%\r\nhm = [0 0 0 0 0 0 0 0 1 1 0 1 1 \r\n 0 1 0 0 0 0 0 0 1 0 0 1 0\r\n 0 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 1 0 0 1 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 1 0\r\n 0 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\nassert(isequal(isFullHouse(hm),y_correct))\r\n%%\r\nhm = [0 0 0 0 0 0 0 0 1 1 0 1 1 \r\n 0 1 0 0 0 0 0 0 1 0 0 1 0\r\n 0 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 1 0 0 1 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 1 0\r\n 0 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\nassert(isequal(isFullHouse(hm),y_correct))\r\n\r\n%%\r\nhm = [0 0 0 0 1 0 0 0 1 1 0 1 1 \r\n 0 1 0 0 1 0 0 0 0 0 0 1 0\r\n 0 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 1 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 1 0 0 0 0 0 0 1 0 \r\n 0 0 0 0 1 0 0 0 0 0 0 1 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 1 0 0 0 0 0 0 0 0])\r\nassert(isequal(isFullHouse(hm),y_correct))\r\n\r\n%%\r\nhm = [0 0 0 0 1 0 0 0 1 1 0 1 1 \r\n 1 1 0 0 1 0 0 0 0 0 0 0 0\r\n 1 0 0 1 1 0 0 0 0 0 0 0 0 \r\n 1 1 0 0 1 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 1 0 0 0 0 0 0 0 0 \r\n 1 0 0 0 1 0 0 0 0 0 0 0 0\r\n 1 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 0])\r\nassert(isequal(isFullHouse(hm),y_correct))\r\n%%\r\nhm = [0 0 0 0 0 0 0 0 1 1 0 1 1 \r\n 0 1 0 0 0 0 0 0 1 0 0 0 0\r\n 0 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0];\r\n\r\ny_correct.flag = false;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\nassert(isequal(isFullHouse(hm),y_correct))\r\n\r\n%%\r\nhm = [0 0 0 0 0 0 0 0 1 1 0 1 1 \r\n 1 1 0 0 0 1 0 0 0 0 0 1 0\r\n 0 0 0 1 0 1 0 0 1 0 0 0 0 \r\n 1 0 0 0 0 1 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 1 0 0 0 0 1 0 0 0 0 0 0 0\r\n 0 0 0 0 0 1 0 0 0 0 0 0 0 \r\n 1 0 0 0 0 1 0 0 0 0 0 0 0])\r\nassert(isequal(isFullHouse(hm),y_correct))","published":true,"deleted":false,"likes_count":1,"comments_count":1,"created_by":240,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":71,"test_suite_updated_at":"2012-02-17T21:20:39.000Z","rescore_all_solutions":false,"group_id":15,"created_at":"2012-02-17T21:20:39.000Z","updated_at":"2026-04-02T20:43:08.000Z","published_at":"2012-02-17T21:54:57.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e--------\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA full house is three cards of one rank (column) and two cards of a different rank. The Ace (first column) is the highest rank. The columns represent A, 2, 3, ... K. When there is a choice between two possible three of a kind, choose the higher. Once a three of a kind is choosen, choose the highest possible pair.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 0 0 0 0 0 1 0 0 0 0 0 \\n0 0 0 0 0 0 0 0 0 0 0 0 0\\n0 1 0 0 0 0 0 0 0 0 0 0 0 \\n0 1 0 0 0 0 0 1 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003erepresents a full house, so the return value from the function is TRUE.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix does not:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 1 0 1 0 0 0 0 0 0 0 0 \\n0 0 0 1 0 0 0 0 0 0 0 0 0\\n0 0 0 1 0 0 0 0 0 0 0 0 0 \\n0 0 0 1 0 0 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eso the return value should be FALSE.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix does represent a full house\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[1 0 1 0 0 0 0 0 0 0 1 0 1 \\n0 0 1 0 0 1 0 0 0 0 0 0 0\\n0 0 1 0 0 0 0 0 0 0 0 0 0 \\n0 0 0 0 0 1 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eRemember, hand matrices can contain any number of 1's from 0 to 52.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 1 0 1 1 0 0 0 0 0 0 0 \\n0 0 0 0 1 0 1 0 0 0 0 0 0\\n0 0 0 0 0 0 0 0 0 0 0 0 0 \\n0 0 1 0 0 0 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWould be FALSE for this function.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand Matrix, but it only shows the cards used to make the full house. If more than one full house can be made, return the higher ranking one (the one with the highest ranking three of a kind. Ace being the highest. Ties are broken with the highest ranking pair). If different suits are possible for the same full house, return the ones higher up in the matrix.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":333,"title":"Poker Series 02: isQuads","description":"The Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\r\n\r\nA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\r\n\r\nFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\r\n\r\n--------\r\n\r\nFour of a kind is four cards of the same rank (column) and the highest other card as a 'kicker'. The columns represent A, 2, 3, ... K in the input. Aces are high.\r\n\r\nThis hand matrix:\r\n\r\n 0 1 0 0 0 1 0 0 0 0 0 0 0 \r\n 0 1 0 0 0 0 0 0 0 0 0 0 0\r\n 0 1 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 1 0 0 0 0 0 0 0 0 0 0 0\r\nrepresents quads, so the return value from the function is TRUE.\r\n\r\nThis hand matrix does not:\r\n\r\n 0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n 0 0 0 1 0 0 0 0 0 0 0 0 0\r\n 0 0 0 1 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 1 0 0 0 0 0 0 0 0 0\r\nso the return value should be FALSE.\r\n\r\nThis hand matrix does represent quads\r\n\r\n 1 0 0 0 0 0 0 0 0 0 0 0 1 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 0\r\n 1 0 1 0 0 0 0 0 0 1 0 0 0 \r\n 1 0 0 0 0 1 0 0 0 0 0 0 0\r\nRemember, hand matrices can contain any number of 1's from 0 to 52.\r\n\r\n 0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n 0 0 0 0 1 0 1 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 1 0 0 0 0 0 0 0 0 0 0 \r\nWould be FALSE for this function.\r\n\r\nA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand Matrix, but it only shows the cards used to make the Quads plus kicker. If more than one Quads can be made, return the higher ranking one (Ace being the highest). If different suits are possible for the kicker, return the one higher up in the matrix.\r\n\r\n","description_html":"\u003cp\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/p\u003e\u003cp\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/p\u003e\u003cp\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/p\u003e\u003cp\u003e--------\u003c/p\u003e\u003cp\u003eFour of a kind is four cards of the same rank (column) and the highest other card as a 'kicker'. The columns represent A, 2, 3, ... K in the input. Aces are high.\u003c/p\u003e\u003cp\u003eThis hand matrix:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 0 0 0 1 0 0 0 0 0 0 0 \r\n0 1 0 0 0 0 0 0 0 0 0 0 0\r\n0 1 0 0 0 0 0 0 0 0 0 0 0 \r\n0 1 0 0 0 0 0 0 0 0 0 0 0\r\nrepresents quads, so the return value from the function is TRUE.\r\n\u003c/pre\u003e\u003cp\u003eThis hand matrix does not:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n0 0 0 1 0 0 0 0 0 0 0 0 0\r\n0 0 0 1 0 0 0 0 0 0 0 0 0 \r\n0 0 0 1 0 0 0 0 0 0 0 0 0\r\nso the return value should be FALSE.\r\n\u003c/pre\u003e\u003cp\u003eThis hand matrix does represent quads\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e1 0 0 0 0 0 0 0 0 0 0 0 1 \r\n1 0 0 0 0 0 0 0 0 0 0 0 0\r\n1 0 1 0 0 0 0 0 0 1 0 0 0 \r\n1 0 0 0 0 1 0 0 0 0 0 0 0\r\nRemember, hand matrices can contain any number of 1's from 0 to 52.\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003e0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n0 0 0 0 1 0 1 0 0 0 0 0 0\r\n0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n0 0 1 0 0 0 0 0 0 0 0 0 0 \r\nWould be FALSE for this function.\r\n\u003c/pre\u003e\u003cp\u003eA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand Matrix, but it only shows the cards used to make the Quads plus kicker. If more than one Quads can be made, return the higher ranking one (Ace being the highest). If different suits are possible for the kicker, return the one higher up in the matrix.\u003c/p\u003e","function_template":"function out = isQuads(hm)\r\n out.flag = false;\r\n out.usedCards = false(4,13)\r\nend","test_suite":"%%\r\nhm = [0 0 0 0 0 0 0 0 1 1 0 1 1 \r\n 0 1 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = false;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\nassert(isequal(isQuads(hm),y_correct))\r\n\r\n%%\r\nhm = [0 0 0 0 0 0 0 0 1 0 0 0 1 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0\r\n 0 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 1 0 0 0 1 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0\r\n 0 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0])\r\nassert(isequal(isQuads(hm),y_correct))\r\n\r\n%%\r\nhm = [0 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0\r\n 0 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0];\r\n\r\ny_correct.flag = false;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\nassert(isequal(isQuads(hm),y_correct))\r\n\r\n%%\r\nhm = [1 0 0 0 0 0 0 0 1 0 0 0 1 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0\r\n 0 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([1 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0\r\n 0 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0])\r\nassert(isequal(isQuads(hm),y_correct))\r\n\r\n%%\r\nhm = [0 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 0 1 0 0 0 0 0 0 1 0 0 0 0\r\n 0 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 0 1 0 0 0 0 0 0 1 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 0 1 0 0 0 0 0 0 1 0 0 0 0\r\n 0 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0])\r\nassert(isequal(isQuads(hm),y_correct))\r\n\r\n%%\r\nhm = [1 0 0 1 0 0 0 0 1 0 0 0 1 \r\n 0 0 0 1 0 0 0 0 1 0 0 0 0\r\n 0 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 1 0 0 0 0 1 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([1 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0\r\n 0 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0])\r\nassert(isequal(isQuads(hm),y_correct))\r\n\r\n%%\r\n hm = [1 0 0 0 0 0 0 1 0 0 0 0 0\r\n 1 0 0 0 0 0 0 1 0 0 0 0 1\r\n 1 0 0 0 0 0 0 1 0 0 0 0 0\r\n 1 0 0 0 0 0 0 1 0 0 0 0 0];\r\n \r\ny_correct.flag = true; \r\ny_correct.usedCards = logical(...\r\n [1 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 1 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 0]);\r\n \r\nassert(isequal(isQuads(hm),y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":3,"created_by":240,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":90,"test_suite_updated_at":"2016-12-13T18:48:26.000Z","rescore_all_solutions":false,"group_id":15,"created_at":"2012-02-17T18:21:26.000Z","updated_at":"2026-04-02T20:32:11.000Z","published_at":"2012-02-17T21:02:57.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e--------\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFour of a kind is four cards of the same rank (column) and the highest other card as a 'kicker'. The columns represent A, 2, 3, ... K in the input. Aces are high.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 0 0 0 1 0 0 0 0 0 0 0 \\n0 1 0 0 0 0 0 0 0 0 0 0 0\\n0 1 0 0 0 0 0 0 0 0 0 0 0 \\n0 1 0 0 0 0 0 0 0 0 0 0 0\\nrepresents quads, so the return value from the function is TRUE.]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix does not:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 1 0 1 1 0 0 0 0 0 0 0 \\n0 0 0 1 0 0 0 0 0 0 0 0 0\\n0 0 0 1 0 0 0 0 0 0 0 0 0 \\n0 0 0 1 0 0 0 0 0 0 0 0 0\\nso the return value should be FALSE.]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix does represent quads\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[1 0 0 0 0 0 0 0 0 0 0 0 1 \\n1 0 0 0 0 0 0 0 0 0 0 0 0\\n1 0 1 0 0 0 0 0 0 1 0 0 0 \\n1 0 0 0 0 1 0 0 0 0 0 0 0\\nRemember, hand matrices can contain any number of 1's from 0 to 52.\\n\\n0 1 1 0 1 1 0 0 0 0 0 0 0 \\n0 0 0 0 1 0 1 0 0 0 0 0 0\\n0 0 0 0 0 0 0 0 0 0 0 0 0 \\n0 0 1 0 0 0 0 0 0 0 0 0 0 \\nWould be FALSE for this function.]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand Matrix, but it only shows the cards used to make the Quads plus kicker. If more than one Quads can be made, return the higher ranking one (Ace being the highest). If different suits are possible for the kicker, return the one higher up in the matrix.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":386,"title":"Poker Series 10: bestHand","description":"The Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\r\n\r\nA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\r\n\r\nFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\r\n\r\n--------\r\n\r\nFind the best hand using the definitions from earlier in this series.\r\n\r\nout.code is:\r\n\r\n# Straight Flush\r\n# Quads\r\n# Full House\r\n# Flush\r\n# Straight\r\n# Three of a kind\r\n# Two pair\r\n# Pair\r\n# High Card\r\n# No valid Hand\r\n\r\nout.cardsUsed is the same as is returned from the functions defined earlier for each type of hand.\r\n\r\nThis hand matrix:\r\n\r\n 0 1 0 0 1 0 0 0 0 0 0 0 0 \r\n 0 0 1 0 0 0 0 0 0 0 0 0 0\r\n 0 1 0 1 0 0 0 0 0 0 0 0 0 \r\n 0 1 0 0 0 1 0 0 0 0 0 0 0\r\n\r\nrepresents a three of a kind, so the return code is 6.","description_html":"\u003cp\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/p\u003e\u003cp\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/p\u003e\u003cp\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/p\u003e\u003cp\u003e--------\u003c/p\u003e\u003cp\u003eFind the best hand using the definitions from earlier in this series.\u003c/p\u003e\u003cp\u003eout.code is:\u003c/p\u003e\u003col\u003e\u003cli\u003eStraight Flush\u003c/li\u003e\u003cli\u003eQuads\u003c/li\u003e\u003cli\u003eFull House\u003c/li\u003e\u003cli\u003eFlush\u003c/li\u003e\u003cli\u003eStraight\u003c/li\u003e\u003cli\u003eThree of a kind\u003c/li\u003e\u003cli\u003eTwo pair\u003c/li\u003e\u003cli\u003ePair\u003c/li\u003e\u003cli\u003eHigh Card\u003c/li\u003e\u003cli\u003eNo valid Hand\u003c/li\u003e\u003c/ol\u003e\u003cp\u003eout.cardsUsed is the same as is returned from the functions defined earlier for each type of hand.\u003c/p\u003e\u003cp\u003eThis hand matrix:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 0 0 1 0 0 0 0 0 0 0 0 \r\n0 0 1 0 0 0 0 0 0 0 0 0 0\r\n0 1 0 1 0 0 0 0 0 0 0 0 0 \r\n0 1 0 0 0 1 0 0 0 0 0 0 0\r\n\u003c/pre\u003e\u003cp\u003erepresents a three of a kind, so the return code is 6.\u003c/p\u003e","function_template":"function out = bestPokerHand(hm)\r\n\r\nout.code = 10;\r\nout.usedCards = false(4,13); ","test_suite":"%%\r\nhm = [0 1 0 0 0 0 0 0 0 0 0 0 1 \r\n 0 1 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 1 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.code = 10;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(bestPokerHand(hm),y_correct))\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 0 0 0 0 1 \r\n 0 0 0 0 1 0 0 0 0 0 0 1 0\r\n 0 0 0 1 0 0 1 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 1 0 0 0];\r\n\r\ny_correct.code = 9;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 1 \r\n 0 0 0 0 1 0 0 0 0 0 0 1 0\r\n 0 0 0 0 0 0 1 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 1 0 0 0])\r\n \r\nassert(isequal(bestPokerHand(hm),y_correct))\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 0 0 0 0 1 \r\n 0 1 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 1 0 0];\r\n\r\ny_correct.code = 8;\r\ny_correct.usedCards = logical([0 1 0 0 0 0 0 0 0 0 0 0 1 \r\n 0 1 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 1 0 0])\r\n \r\nassert(isequal(bestPokerHand(hm),y_correct))\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 0 0 0 0 1 \r\n 0 1 0 0 0 0 0 0 1 0 0 0 0\r\n 0 0 0 1 0 0 0 0 0 0 0 0 0 \r\n 1 0 0 1 0 0 0 0 0 0 1 0 0];\r\n\r\ny_correct.code = 7;\r\ny_correct.usedCards = logical([0 1 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 1 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 1 0 0 0 0 0 0 0 0 0 \r\n 1 0 0 1 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(bestPokerHand(hm),y_correct))\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 0 0 0 0 1 \r\n 0 0 0 0 0 0 1 0 0 0 0 0 0\r\n 0 0 0 1 0 0 1 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 1 0 0 0 0 1 0];\r\n\r\ny_correct.code = 6;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 1 \r\n 0 0 0 0 0 0 1 0 0 0 0 0 0\r\n 0 0 0 0 0 0 1 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 1 0 0 0 0 1 0])\r\n \r\nassert(isequal(bestPokerHand(hm),y_correct))\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 0 0 0 0 1 \r\n 1 1 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 1 1 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 1 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.code = 5;\r\ny_correct.usedCards = logical([0 1 0 0 0 0 0 0 0 0 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 1 1 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 1 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(bestPokerHand(hm),y_correct))\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 1 1 0 1 1 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0\r\n 0 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.code = 4;\r\ny_correct.usedCards = logical([0 1 0 0 0 0 0 0 1 1 0 1 1 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(bestPokerHand(hm),y_correct))\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 1 1 0 1 0 \r\n 0 1 0 0 0 0 0 0 0 0 0 1 0\r\n 0 1 0 1 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0];\r\n\r\ny_correct.code = 3;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 1 0 0 1 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 1 0\r\n 0 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0])\r\n \r\nassert(isequal(bestPokerHand(hm),y_correct))\r\n\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 1 0 1 1 1 \r\n 0 1 0 0 0 0 0 0 1 0 0 1 0\r\n 0 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0];\r\n\r\ny_correct.code = 2;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 1 0 0 0 1 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0\r\n 0 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0])\r\n \r\nassert(isequal(bestPokerHand(hm),y_correct))\r\n%%\r\nhm = [0 1 0 0 0 0 0 1 1 1 1 1 1 \r\n 0 1 0 0 0 0 0 0 0 0 0 1 0\r\n 0 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0];\r\n\r\ny_correct.code = 1;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 1 1 1 1 1 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(bestPokerHand(hm),y_correct))","published":true,"deleted":false,"likes_count":2,"comments_count":18,"created_by":240,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":44,"test_suite_updated_at":"2016-12-13T18:56:05.000Z","rescore_all_solutions":false,"group_id":15,"created_at":"2012-02-22T20:58:19.000Z","updated_at":"2026-02-15T04:18:26.000Z","published_at":"2012-02-22T20:58:26.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e--------\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFind the best hand using the definitions from earlier in this series.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eout.code is:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eStraight Flush\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eQuads\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFull House\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFlush\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eStraight\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThree of a kind\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eTwo pair\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ePair\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eHigh Card\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eNo valid Hand\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eout.cardsUsed is the same as is returned from the functions defined earlier for each type of hand.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 0 0 1 0 0 0 0 0 0 0 0 \\n0 0 1 0 0 0 0 0 0 0 0 0 0\\n0 1 0 1 0 0 0 0 0 0 0 0 0 \\n0 1 0 0 0 1 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003erepresents a three of a kind, so the return code is 6.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray 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Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\r\n\r\nA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\r\n\r\nFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\r\n\r\n--------\r\n\r\nA two pair is two pairs of cards of the same rank (column). The Ace (first column) is highest. The columns represent A, 2, 3, ... K. The next highest card is the kicker. If the kicker also form three of a kind with a pair, it is still considered two pair for the purposes of this function. Four of a kind is still two pair also. (I got two pair, a pair of Aces and another Pair of Aces!)\r\n\r\nThis hand matrix:\r\n\r\n 0 1 0 0 1 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 1 0 0 0\r\n 0 1 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 1 1 0 0 1 0 0 0 0\r\n\r\nrepresents a two pair, so the return value from the function is TRUE.\r\n\r\nThis hand matrix does not:\r\n\r\n 0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 1 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n\r\nso the return value should be FALSE.\r\n\r\nThis hand matrix does represent a two pair\r\n\r\n 0 0 0 0 0 0 0 0 0 1 0 0 1 \r\n 0 0 1 0 0 0 0 0 0 0 1 0 1\r\n 0 0 0 0 0 0 0 0 0 1 0 0 0 \r\n 0 0 0 0 0 1 0 0 0 0 0 0 0\r\n\r\nRemember, hand matrices can contain any number of 1's from 0 to 52.\r\n\r\n 0 0 0 0 0 1 0 0 0 0 0 0 0 \r\n 0 1 0 0 1 1 1 0 0 0 0 1 0\r\n 0 1 0 1 0 0 0 0 0 1 0 0 0 \r\n 0 0 1 0 0 0 0 0 0 0 0 1 0 \r\n\r\nWould be TRUE for this function.\r\n\r\nA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand matrix, but it only shows the cards used to make the three of a kind. If more than one two pair can be made, return the higher ranking one (the one with the highest rank. Ace being the highest). If different suits are possible for the same pair, return the ones higher up in the matrix, same for kickers. If the two pair happens to also be a four of a kind or full house, it still meets the defintion and should be returned.","description_html":"\u003cp\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/p\u003e\u003cp\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/p\u003e\u003cp\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/p\u003e\u003cp\u003e--------\u003c/p\u003e\u003cp\u003eA two pair is two pairs of cards of the same rank (column). The Ace (first column) is highest. The columns represent A, 2, 3, ... K. The next highest card is the kicker. If the kicker also form three of a kind with a pair, it is still considered two pair for the purposes of this function. Four of a kind is still two pair also. (I got two pair, a pair of Aces and another Pair of Aces!)\u003c/p\u003e\u003cp\u003eThis hand matrix:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 0 0 1 0 0 0 0 0 0 0 0 \r\n0 0 0 0 0 0 0 0 0 1 0 0 0\r\n0 1 0 0 0 0 0 0 0 0 0 0 0 \r\n0 0 0 0 1 1 0 0 1 0 0 0 0\r\n\u003c/pre\u003e\u003cp\u003erepresents a two pair, so the return value from the function is TRUE.\u003c/p\u003e\u003cp\u003eThis hand matrix does not:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n0 0 0 0 0 0 0 0 0 0 0 0 0\r\n0 0 0 0 0 0 0 0 0 1 0 0 0 \r\n0 0 0 0 0 0 0 0 0 0 0 0 0\r\n\u003c/pre\u003e\u003cp\u003eso the return value should be FALSE.\u003c/p\u003e\u003cp\u003eThis hand matrix does represent a two pair\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 0 0 0 0 0 0 0 0 1 0 0 1 \r\n0 0 1 0 0 0 0 0 0 0 1 0 1\r\n0 0 0 0 0 0 0 0 0 1 0 0 0 \r\n0 0 0 0 0 1 0 0 0 0 0 0 0\r\n\u003c/pre\u003e\u003cp\u003eRemember, hand matrices can contain any number of 1's from 0 to 52.\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 0 0 0 0 1 0 0 0 0 0 0 0 \r\n0 1 0 0 1 1 1 0 0 0 0 1 0\r\n0 1 0 1 0 0 0 0 0 1 0 0 0 \r\n0 0 1 0 0 0 0 0 0 0 0 1 0 \r\n\u003c/pre\u003e\u003cp\u003eWould be TRUE for this function.\u003c/p\u003e\u003cp\u003eA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand matrix, but it only shows the cards used to make the three of a kind. If more than one two pair can be made, return the higher ranking one (the one with the highest rank. Ace being the highest). If different suits are possible for the same pair, return the ones higher up in the matrix, same for kickers. If the two pair happens to also be a four of a kind or full house, it still meets the defintion and should be returned.\u003c/p\u003e","function_template":"function out = isTwoPair(hm)\r\n out.flag = false;\r\n out.usedCards = false(4,13);\r\nend","test_suite":"%%\r\nhm = [0 1 0 0 0 0 0 0 1 1 0 1 1 \r\n 0 1 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 1 0 0 0 0 0 0 1 0 0 0 1 \r\n 0 1 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isTwoPair(hm),y_correct))\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 1 1 0 0 0 \r\n 0 1 0 0 0 0 0 0 0 0 0 0 0\r\n 1 0 0 1 0 0 0 0 1 1 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 1 1 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 1 0 0 0 0 0 0 0 0 1 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isTwoPair(hm),y_correct))\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 0 1 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 1 0 0 0 0 1 1 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = false;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isTwoPair(hm),y_correct))\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 1 1 0 0 0 \r\n 0 1 0 0 0 0 0 0 0 1 0 0 0\r\n 1 0 0 1 0 0 0 0 1 1 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 1 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 1 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 1 0 0 0\r\n 1 0 0 0 0 0 0 0 0 1 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isTwoPair(hm),y_correct))\r\n\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 1 1 0 0 0 \r\n 0 1 0 0 0 0 0 0 0 1 0 0 0\r\n 1 0 0 1 0 0 0 0 1 1 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 1 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 1 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 1 0 0 0\r\n 1 0 0 0 0 0 0 0 0 1 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 1 0 0 0])\r\n \r\nassert(isequal(isTwoPair(hm),y_correct))\r\n\r\n%%\r\nhm = [0 0 0 0 0 0 0 0 0 1 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 0\r\n 1 0 0 0 0 0 0 0 0 1 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = false;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isTwoPair(hm),y_correct))","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":240,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":53,"test_suite_updated_at":"2012-02-22T17:28:05.000Z","rescore_all_solutions":false,"group_id":15,"created_at":"2012-02-22T17:28:05.000Z","updated_at":"2026-02-15T05:47:26.000Z","published_at":"2012-02-22T17:28:08.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e--------\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA two pair is two pairs of cards of the same rank (column). The Ace (first column) is highest. The columns represent A, 2, 3, ... K. The next highest card is the kicker. If the kicker also form three of a kind with a pair, it is still considered two pair for the purposes of this function. Four of a kind is still two pair also. (I got two pair, a pair of Aces and another Pair of Aces!)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 0 0 1 0 0 0 0 0 0 0 0 \\n0 0 0 0 0 0 0 0 0 1 0 0 0\\n0 1 0 0 0 0 0 0 0 0 0 0 0 \\n0 0 0 0 1 1 0 0 1 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003erepresents a two pair, so the return value from the function is TRUE.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix does not:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 1 0 1 1 0 0 0 0 0 0 0 \\n0 0 0 0 0 0 0 0 0 0 0 0 0\\n0 0 0 0 0 0 0 0 0 1 0 0 0 \\n0 0 0 0 0 0 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eso the return value should be FALSE.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix does represent a two pair\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 0 0 0 0 0 0 0 0 1 0 0 1 \\n0 0 1 0 0 0 0 0 0 0 1 0 1\\n0 0 0 0 0 0 0 0 0 1 0 0 0 \\n0 0 0 0 0 1 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eRemember, hand matrices can contain any number of 1's from 0 to 52.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 0 0 0 0 1 0 0 0 0 0 0 0 \\n0 1 0 0 1 1 1 0 0 0 0 1 0\\n0 1 0 1 0 0 0 0 0 1 0 0 0 \\n0 0 1 0 0 0 0 0 0 0 0 1 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWould be TRUE for this function.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand matrix, but it only shows the cards used to make the three of a kind. If more than one two pair can be made, return the higher ranking one (the one with the highest rank. Ace being the highest). If different suits are possible for the same pair, return the ones higher up in the matrix, same for kickers. If the two pair happens to also be a four of a kind or full house, it still meets the defintion and should be returned.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":61069,"title":"Clueless - Lord Ned in the Game Room with the Technical Computing Language","description":"[Warning: this is a nontrivial programming problem]\r\n\r\nWorried about the decline in reasoning skills in the clueless populace of Nedland, Lord Ned had the finest minds at the University of Nedsburg develop a fun game to sharpen logical inference skills.\r\nThe game consists of a deck of 3n cards, with n cards in each of three categories.\r\n\r\n\r\nOne card from each category is randomly selected and these three cards are placed, unseen, in an envelope. The goal of the game is for the players to figure out which cards are in the envelope.\r\n\r\n\r\nThe remaining 3(n-1) cards are shuffled together and then dealt to the players. Every player receives the same number of cards; any leftover cards are placed face-up so that all players can see them. Because all the cards are shuffled together, the players will not all have an equal distribution of cards from the three categories.\r\n\r\n\r\nPlayers take it in turns to ask any other player about three cards, one from each category. If the player asked has any of the cards asked for, they must show one of those cards to the player who asked. (If they have more than one of the specified cards, they can choose which card to show.) The other players do not get to see which card has been shown, but they do know which three cards were asked for and that the player asked had one of them. If the player asked has none of the cards asked for, they simply state this and do not have to show any of their cards.\r\nOnce a player believes they have deduced the identity of the three cards in the envelope, they can, on their turn, announce their guess, then check the cards in the envelope. If the player is correct, they can reveal the cards as proof and they win the game. If not, they are eliminated. They must return the cards to the envelope, and the game continues without them.\r\nWrite a function that takes information about a game as inputs and returns the solution (that is, the deduced identity of the cards in the envelope) as output.\r\nThe inputs to the function are:\r\nm, the number of players\r\nn, the number of cards in each category\r\npnum, which player you are (from 1 to m). Players take turns in order (1 to m, and back to 1). If a card is revealed and it is your turn, you know the exact identity of that card. If it is not your turn, you know only that one of the cards asked for was revealed.\r\nyourcards, a 3-element cell array representing the cards dealt to you. Each cell contains the cards for one category. The cards from that category are given as a vector of values from 1 to n. If there are no cards for that category, the cell will contain an empty vector. In the example image, if you are the player in the bottom left (player 4), yourcards = {[1 3],[],[]}. If instead you are the player in the bottom right (player 3), yourcards = {[],[4],[2]}.\r\ncommoncards, a 3-element cell array representing the extra cards visible to everyone. The format is the same as for yourcards. In the example image, commoncards = {[],[3],[]}.\r\nturns, an nt-by-5 matrix representing nt turns of the game. Each row of turns records one player's turn as a 5-element vector. The first value is the number of the player asked. The next three values are the cards asked for, one for each category in order. The final value is the result: -1 represents the asked player responding that they do not have any of the requested cards; 0 represents the asked player showing a card (but you do not know which specific card); a value of 1-3 represents the asked player showing you a specific card, where the value is the index (or, equivalently, category) of the three cards asked for. For example, a row of turns that was the vector [5 4 3 2 1] would represent player 5 being asked for card 4 in category 1, card 3 in category 2, and card 2 in category 3, and showing you card 4 of category 1.\r\nThe output should be a single 3-element vector of the cards in the envelope, in order. For the example image, the output would be [4 2 1].\r\n\r\nAssumptions\r\nThe game is still new to Nedland, so don't expect the players to make the best requests on their turn, but the solution can be inferred from the inputs given. It may be possible to determine the solution from less information than is given, but the information given will always be sufficient.\r\nAlthough it shouldn't matter for your implementation, the official rules have 4-8 players (m) and card decks with up to 8 cards in each category (n), using at least enough cards to ensure that each player gets at least two cards in their hand.\r\n\r\nExample\r\nFor the example images, m = 4, n = 4. Suppose pnum = 4, in which case yourcards = {[1 3],[],[]} and commoncards = {[],[3],[]}.\r\nmoves = 12×5\r\n3 1 4 3 0\r\n1 3 4 4 0\r\n2 3 1 3 0\r\n1 4 2 2 -1\r\n4 3 1 1 0\r\n3 2 2 2 0\r\n2 1 1 4 0\r\n2 4 2 3 3\r\n3 3 2 1 -1\r\n1 4 4 2 -1\r\n2 4 2 1 -1\r\n1 2 2 4 1\r\nIn the first turn, player 1 asks player 3 for cards [1 4 3] (that is, card 1 from category 1, card 4 from category 2, and card 3 from category 3). Player 3 shows them a card but you, player 4, don't know which. You have the first card in your hand, so it must have been one of the other two, but so far no further information can be extracted.\r\nSimilarly, player 2 then asks player 1 for cards [3 4 4] and is shown one. Again, you hold the first card, so player 1 must have either card 4 from category 2 or card 4 from category 3, but you don't yet know which.\r\nOn the fourth turn, you ask player 1 for cards [4 2 2], but player 1 has none of these.\r\nMore turns occur where you cannot determine any concrete information yet.\r\nOn the eight turn, things suddenly get interesting. You ask player 2 for [4 2 3] and are shown the third of these. That is, you know that player 2 holds card 3 from category 3.\r\nMoreover, this makes some of the earlier turns more useful. Revisiting the first turn where player 3 was asked for [1 4 3], you now know that you held the first card and player 2 held the third card. The card that player 3 showed player 1 must therefore be the second card, so now you know that player 3 has card 4 from category 2.\r\nAnd similarly, now you can deduce from turn 2 that player 1 has card 4 from category 3 (because you hold the first card and player 3 holds the second card). And again from turn 7, you can now deduce that player 2 has card 1 from category 2, using the same logic.\r\nAt this point, you now know both cards that player 2 holds, so you can eliminate all other cards from possibly being held by them.\r\nYou also now know the locations of three of the four cards in category 2: player 2 has card 1, the common card is card 3, and player 3 has card 4. That means the remaining card (2) is in the envelope.\r\nTurn 9 tells you that player 3 does not have card 1 from category 3. The next two turns provide no new information.\r\nFinally, turn 12 reveals that player 1 has card 2 from category 1. This means you now know both cards player 1 holds (2 from category 1 and 4 from category 3). Consequently, you know that no player has card 1 from category 3 (you know both cards held by players 1 and 2, you know player 3 doesn't have it, you don't have it, and it's not the common card), so it must be in the envelope.\r\nThis just leaves category 1 but you now know the location of three of the four cards (you have cards 1 \u0026 3, player 1 has card 2). And so you have the solution: [4 2 1].\r\nsoln = infercards(m,n,pnum,yourcards,commoncards,moves)\r\nsoln =\r\n4 2 1\r\n\r\nImplementation Suggestions/Tips\r\nOne way to find the solution is to keep an array of all cards and all players, with values indicating your state of knowledge about whether that player has that card: unknown, yes, or no. Start with everything unknown, and fill in information as you go. For this tracking, you can treat the common cards as player m+1. Each category has one card that nobody has, which is the card in the envelope. Once you have identified that card for each category, you have your solution.\r\nYou start with complete knowledge of which cards you and the common \"player\" do and do not have.\r\nGo through the turns and use the provided information to update your state of knowledge. Also use the following observations to extend the logic to find new information:\r\nIf you know a player has a card, you know all other players do not.\r\nYou know how many cards each player has: the same number that you have. Equivalently, you can calculate it: ncards = floor(3*(n-1)/m). If you know the identities of ncards cards for a player, you know they have no other cards. (The common cards are an exception, but this doesn't matter because you already know exactly what cards are and are not in the common set.)\r\nOnce you know the locations of (n-1) cards in a category, the remaining card must be in the envelope.\r\nEach player holds ncards cards. If you can identify 3n-ncards cards that a player definitely does not hold, then they must hold the remaining ncards cards. That is, if the no, yes, and maybe/unknown cards for a player are distributed such that there are ncards yes or maybe (and 3n-ncards no), then all the remaining maybes are yeses.\r\nRemember that, as in the example, new information disclosed in a turn may make previous turns more relevant.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 4023.25px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 408px 2011.62px; transform-origin: 408px 2011.62px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003e[Warning: this is a nontrivial programming problem]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 21px; text-align: left; transform-origin: 385px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eWorried about the decline in reasoning skills in the clueless populace of Nedland, Lord Ned had the finest minds at the University of \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eNedsburg\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e develop a fun game to sharpen logical inference skills.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe game consists of a deck of 3\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003en\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e cards, with \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003en\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e cards in each of three categories.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 445px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; 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\" data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 21px; text-align: left; transform-origin: 385px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eOne card from each category is randomly selected and these three cards are placed, unseen, in an envelope. The goal of the game is for the players to figure out which cards are in the envelope.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 312px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 156px; text-align: left; transform-origin: 385px 156px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cimg class=\"imageNode\" width=\"700\" height=\"306\" style=\"vertical-align: baseline;width: 700px;height: 306px\" 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data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 31.5px; text-align: left; transform-origin: 385px 31.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe remaining 3(\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003en\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e-1) cards are shuffled together and then dealt to the players. Every player receives the same number of cards; any leftover cards are placed face-up so that all players can see them. Because all the cards are shuffled together, the players will not all have an equal distribution of cards from the three categories.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan 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data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 105px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 52.5px; text-align: left; transform-origin: 385px 52.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003ePlayers take it in turns to ask any other player about three cards, one from each category. If the player asked has any of the cards asked for, they must show one of those cards to the player who asked. (If they have more than one of the specified cards, they can choose which card to show.) The other players do not get to see which card has been shown, but they do know which three cards were asked for and that the player asked had one of them. If the player asked has none of the cards asked for, they simply state this and do not have to show any of their cards.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 31.5px; text-align: left; transform-origin: 385px 31.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eOnce a player believes they have deduced the identity of the three cards in the envelope, they can, on their turn, announce their guess, then check the cards in the envelope. If the player is correct, they can reveal the cards as proof and they win the game. If not, they are eliminated. They must return the cards to the envelope, and the game continues without them.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 21px; text-align: left; transform-origin: 385px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eWrite a function that takes information about a game as inputs and returns the solution (that is, the deduced identity of the cards in the envelope) as output.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe inputs to the function are:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cul style=\"block-size: 396.312px; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; perspective-origin: 392px 198.156px; transform-origin: 392px 198.156px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"block-size: 20.4375px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 364px 10.2188px; text-align: left; transform-origin: 364px 10.2188px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003em\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, the number of players\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4375px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 364px 10.2188px; text-align: left; transform-origin: 364px 10.2188px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003en\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, the number of cards in each category\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 62.3125px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 364px 31.1562px; text-align: left; transform-origin: 364px 31.1562px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003epnum\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, which player you are (from 1 to \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003em\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e). Players take turns in order (1 to \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003em\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, and back to 1). If a card is revealed and it is your turn, you know the exact identity of that card. If it is not your turn, you know only that one of the cards asked for was revealed.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 84.75px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 364px 42.375px; text-align: left; transform-origin: 364px 42.375px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eyourcards\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, a 3-element cell array representing the cards dealt to you. Each cell contains the cards for one category. The cards from that category are given as a vector of values from 1 to \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003en\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e. If there are no cards for that category, the cell will contain an empty vector. In the example image, if you are the player in the bottom left (player 4), \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eyourcards = {[1 3],[],[]}\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e. If instead you are the player in the bottom right (player 3), \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eyourcards = {[],[4],[2]}\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 42.875px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 364px 21.4375px; text-align: left; transform-origin: 364px 21.4375px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ecommoncards\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, a 3-element cell array representing the extra cards visible to everyone. The format is the same as for \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eyourcards\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e. In the example image, \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ecommoncards = {[],[3],[]}\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 165.5px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 364px 82.75px; text-align: left; transform-origin: 364px 82.75px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eturns\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, an \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003ent\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e-by-5 matrix representing \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003ent\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e turns of the game. Each row of \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eturns\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e records one player's turn as a 5-element vector. The first value is the number of the player asked. The next three values are the cards asked for, one for each category in order. The final value is the result: -1 represents the asked player responding that they do not have any of the requested cards; 0 represents the asked player showing a card (but you do not know which specific card); a value of 1-3 represents the asked player showing you a specific card, where the value is the index (or, equivalently, category) of the three cards asked for. For example, a row of \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eturns\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e that was the vector \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[5 4 3 2 1]\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e would represent player 5 being asked for card 4 in category 1, card 3 in category 2, and card 2 in category 3, and showing you card 4 of category 1.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 21px; text-align: left; transform-origin: 385px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe output should be a single 3-element vector of the cards in the envelope, in order. For the example image, the output would be \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[4 2 1]\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eAssumptions\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 31.5px; text-align: left; transform-origin: 385px 31.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe game is still new to \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eNedland\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, so don't expect the players to make the best requests on their turn, but the solution can be inferred from the inputs given. It may be possible to determine the solution from less information than is given, but the information given will always be sufficient.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 21px; text-align: left; transform-origin: 385px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eAlthough it shouldn't matter for your implementation, the official rules have 4-8 players (\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003em\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e) and card decks with up to 8 cards in each category (\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003en\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e), using at least enough cards to ensure that each player gets at least two cards in their hand.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eExample\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 21px; text-align: left; transform-origin: 385px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eFor the example images, \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003em\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e = 4, \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003en\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e = 4. Suppose \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003epnum\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e = 4, in which case \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eyourcards = {[1 3],[],[]}\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e and \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ecommoncards = {[],[3],[]}\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 265.688px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-end-end-radius: 4px; border-end-start-radius: 4px; border-start-end-radius: 4px; border-start-start-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 405px 132.844px; transform-origin: 405px 132.844px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 405px 10.2188px; text-wrap-mode: nowrap; transform-origin: 405px 10.2188px; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; unicode-bidi: normal; white-space-collapse: preserve; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003emoves = 12\u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(255, 0, 0); border-block-start-color: rgb(255, 0, 0); border-bottom-color: rgb(255, 0, 0); border-inline-end-color: rgb(255, 0, 0); border-inline-start-color: rgb(255, 0, 0); border-left-color: rgb(255, 0, 0); border-right-color: rgb(255, 0, 0); border-top-color: rgb(255, 0, 0); caret-color: rgb(255, 0, 0); color: rgb(255, 0, 0); column-rule-color: rgb(255, 0, 0); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(255, 0, 0); text-decoration-color: rgb(255, 0, 0); text-emphasis-color: rgb(255, 0, 0); \"\u003e×\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e5\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 405px 10.2188px; text-wrap-mode: nowrap; transform-origin: 405px 10.2188px; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; unicode-bidi: normal; white-space-collapse: preserve; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e3 1 4 3 0\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 405px 10.2188px; text-wrap-mode: nowrap; transform-origin: 405px 10.2188px; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; unicode-bidi: normal; white-space-collapse: preserve; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e1 3 4 4 0\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 405px 10.2188px; text-wrap-mode: nowrap; transform-origin: 405px 10.2188px; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; unicode-bidi: normal; white-space-collapse: preserve; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e2 3 1 3 0\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 405px 10.2188px; text-wrap-mode: nowrap; transform-origin: 405px 10.2188px; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; unicode-bidi: normal; white-space-collapse: preserve; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e1 4 2 2 -1\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 405px 10.2188px; text-wrap-mode: nowrap; transform-origin: 405px 10.2188px; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; unicode-bidi: normal; white-space-collapse: preserve; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e4 3 1 1 0\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 405px 10.2188px; text-wrap-mode: nowrap; transform-origin: 405px 10.2188px; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; unicode-bidi: normal; white-space-collapse: preserve; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e3 2 2 2 0\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 405px 10.2188px; text-wrap-mode: nowrap; transform-origin: 405px 10.2188px; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; unicode-bidi: normal; white-space-collapse: preserve; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e2 1 1 4 0\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 405px 10.2188px; text-wrap-mode: nowrap; transform-origin: 405px 10.2188px; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; unicode-bidi: normal; white-space-collapse: preserve; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e2 4 2 3 3\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 405px 10.2188px; text-wrap-mode: nowrap; transform-origin: 405px 10.2188px; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; unicode-bidi: normal; white-space-collapse: preserve; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e3 3 2 1 -1\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 405px 10.2188px; text-wrap-mode: nowrap; transform-origin: 405px 10.2188px; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; unicode-bidi: normal; white-space-collapse: preserve; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e1 4 4 2 -1\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 405px 10.2188px; text-wrap-mode: nowrap; transform-origin: 405px 10.2188px; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; unicode-bidi: normal; white-space-collapse: preserve; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e2 4 2 1 -1\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 405px 10.2188px; text-wrap-mode: nowrap; transform-origin: 405px 10.2188px; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; unicode-bidi: normal; white-space-collapse: preserve; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e1 2 2 4 1\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 10px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 10px; perspective-origin: 385px 31.5px; text-align: left; transform-origin: 385px 31.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 10px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eIn the first turn, player 1 asks player 3 for cards \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[1 4 3]\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e (that is, card 1 from category 1, card 4 from category 2, and card 3 from category 3). Player 3 shows them a card but you, player 4, don't know which. You have the first card in your hand, so it must have been one of the other two, but so far no further information can be extracted.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 21px; text-align: left; transform-origin: 385px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eSimilarly, player 2 then asks player 1 for cards \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[3 4 4]\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e and is shown one. Again, you hold the first card, so player 1 must have either card 4 from category 2 or card 4 from category 3, but you don't yet know which.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eOn the fourth turn, you ask player 1 for cards \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[4 2 2]\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, but player 1 has none of these.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eMore turns occur where you cannot determine any concrete information yet.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 21px; text-align: left; transform-origin: 385px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eOn the eight turn, things suddenly get interesting. You ask player 2 for \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[4 2 3]\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e and are shown the third of these. That is, you know that player 2 holds card 3 from category 3.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 31.5px; text-align: left; transform-origin: 385px 31.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eMoreover, this makes some of the earlier turns more useful. Revisiting the first turn where player 3 was asked for \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[1 4 3]\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, you now know that you held the first card and player 2 held the third card. The card that player 3 showed player 1 must therefore be the second card, so now you know that player 3 has card 4 from category 2.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 31.5px; text-align: left; transform-origin: 385px 31.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eAnd similarly, now you can deduce from turn 2 that player 1 has card 4 from category 3 (because you hold the first card and player 3 holds the second card). And again from turn 7, you can now deduce that player 2 has card 1 from category 2, using the same logic.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 21px; text-align: left; transform-origin: 385px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eAt this point, you now know both cards that player 2 holds, so you can eliminate all other cards from possibly being held by them.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 21px; text-align: left; transform-origin: 385px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eYou also now know the locations of three of the four cards in category 2: player 2 has card 1, the common card is card 3, and player 3 has card 4. That means the remaining card (2) is in the envelope.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eTurn 9 tells you that player 3 does not have card 1 from category 3. The next two turns provide no new information.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 84px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 42px; text-align: left; transform-origin: 385px 42px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eFinally, turn 12 reveals that player 1 has card 2 from category 1. This means you now know both cards player 1 holds (2 from category 1 and 4 from category 3). Consequently, you know that no player has card 1 from category 3 (you know both cards held by players 1 and 2, you know player 3 doesn't have it, you don't have it, and it's not the common card), so it must be in the envelope.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 21px; text-align: left; transform-origin: 385px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThis just leaves category 1 but you now know the location of three of the four cards (you have cards 1 \u0026amp; 3, player 1 has card 2). And so you have the solution: \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[4 2 1]\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 61.3125px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-end-end-radius: 4px; border-end-start-radius: 4px; border-start-end-radius: 4px; border-start-start-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 405px 30.6562px; transform-origin: 405px 30.6562px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 405px 10.2188px; text-wrap-mode: nowrap; transform-origin: 405px 10.2188px; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; unicode-bidi: normal; white-space-collapse: preserve; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003esoln = infercards(m,n,pnum,yourcards,commoncards,moves)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 405px 10.2188px; text-wrap-mode: nowrap; transform-origin: 405px 10.2188px; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; unicode-bidi: normal; white-space-collapse: preserve; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003esoln =\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 405px 10.2188px; text-wrap-mode: nowrap; transform-origin: 405px 10.2188px; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; unicode-bidi: normal; white-space-collapse: preserve; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e4 2 1\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 10px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 10px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 10px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eImplementation Suggestions/Tips\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 84px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 42px; text-align: left; transform-origin: 385px 42px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eOne way to find the solution is to keep an array of all cards and all players, with values indicating your state of knowledge about whether that player has that card: unknown, yes, or no. Start with everything unknown, and fill in information as you go. For this tracking, you can treat the common cards as player \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003em\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e+1. Each category has one card that nobody has, which is the card in the envelope. Once you have identified that card for each category, you have your solution.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eYou start with complete knowledge of which cards you and the common \"player\" do and do not have.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 21px; text-align: left; transform-origin: 385px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGo through the turns and use the provided information to update your state of knowledge. Also use the following observations to extend the logic to find new information:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cul style=\"block-size: 187.938px; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; perspective-origin: 392px 93.9688px; transform-origin: 392px 93.9688px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"block-size: 20.4375px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 364px 10.2188px; text-align: left; transform-origin: 364px 10.2188px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eIf you know a player has a card, you know all other players do not.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 82.75px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 364px 41.375px; text-align: left; transform-origin: 364px 41.375px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eYou know how many cards each player has: the same number that you have. Equivalently, you can calculate it: \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003encards = floor(3*(n-1)/m)\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e. If you know the identities of \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003encards\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e cards for a player, you know they have no other cards. (The common cards are an exception, but this doesn't matter because you already know exactly what cards are and are not in the common set.)\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4375px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 364px 10.2188px; text-align: left; transform-origin: 364px 10.2188px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eOnce you know the locations of (\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003en\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e-1) cards in a category, the remaining card must be in the envelope.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 64.3125px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 364px 32.1562px; text-align: left; transform-origin: 364px 32.1562px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eEach player holds \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003encards\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e cards. If you can identify 3\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003en\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e-\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003encards\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e cards that a player definitely does \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"text-decoration: underline; text-decoration-line: underline; \"\u003enot\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e hold, then they must hold the remaining \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003encards\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e cards. That is, if the no, yes, and maybe/unknown cards for a player are distributed such that there are \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003encards\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e yes or maybe (and 3\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003en\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e-\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003encards\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e no), then all the remaining maybes are yeses.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eRemember that, as in the example, new information disclosed in a turn may make previous turns more relevant.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function sol = infercards(m,n,pnum,yourcards,commoncards,turns)\r\nsol = randi(n,1,3);\r\nend","test_suite":"%% Test case #1: 4 players, 7 cards (per category)\r\nyourcards = {4,[1 3],5};\r\ncommoncards = {1,[],7};\r\nmoves = [4 6 1 1 0;3 4 7 1 0;2 6 7 5 0;2 7 7 1 1;4 6 3 6 0;3 4 7 4 -1;2 4 3 5 -1;2 2 6 2 -1;2 4 4 1 0;3 3 3 4 -1;4 7 2 5 0;3 3 5 6 3;3 3 1 6 0;3 3 2 6 0;2 3 5 5 -1;1 2 2 1 2;4 3 1 6 0;4 4 2 1 0;1 6 7 5 0;3 7 5 3 -1;2 3 4 5 0;1 3 3 5 -1;1 6 5 4 0;1 2 2 6 2;4 3 6 2 -1;4 2 2 1 -1;2 6 4 4 0;2 3 6 3 -1;2 4 3 5 -1;4 3 5 6 -1;4 5 5 3 -1;1 3 4 4 3;3 2 3 5 0;1 3 2 6 0;2 6 4 3 0;2 6 5 1 1;4 7 4 3 -1;1 2 1 4 0;1 3 4 5 -1;3 7 7 4 -1;3 6 3 6 0;3 3 7 1 0;1 3 1 5 -1;3 5 2 1 3;3 6 4 6 0;3 2 7 6 0;1 4 4 4 0;1 7 5 3 2];\r\nsol = infercards(4,7,4,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[3 6 3]))\r\n\r\n%% Test case #2: 6 players, 6 cards (per category)\r\nyourcards = {4,6,[]};\r\ncommoncards = {1,5,3};\r\nmoves = [5 5 2 1 -1;6 2 3 5 0;1 6 2 2 3;2 4 2 5 -1;6 4 2 6 -1;4 4 4 4 0;6 3 1 6 0;5 4 2 5 -1;4 2 4 4 2;3 6 6 4 0;2 4 2 2 -1;4 2 4 6 0;5 6 3 6 0;6 2 1 4 -1;6 2 1 5 -1;6 4 2 6 -1;6 5 6 5 -1;4 5 6 1 0;3 2 3 1 -1;6 4 6 5 -1;4 6 1 2 -1;2 4 3 2 -1;1 2 6 6 -1;4 5 2 4 0;2 2 2 4 -1;3 2 1 5 -1;6 5 3 5 2;3 2 1 4 -1;4 5 6 5 0;4 6 1 5 -1;4 2 4 6 0;5 5 2 4 -1;6 2 1 5 -1;6 3 2 4 0;4 5 4 4 0;3 4 4 6 0;5 3 4 6 -1;5 4 1 4 0;1 6 1 6 -1;6 6 2 1 -1;2 3 4 6 0;4 4 2 1 -1;2 6 3 1 0;3 3 6 5 0;2 5 3 4 -1;1 3 2 6 -1;2 5 4 4 -1;3 5 6 4 0;5 2 3 4 -1;3 4 6 2 0;5 6 3 1 1;6 6 2 5 -1;3 4 6 4 0;3 4 6 4 0;5 2 6 4 -1;5 3 4 2 -1;1 6 4 6 -1;1 6 3 5 0];\r\nsol = infercards(6,6,3,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[2 2 4]))\r\n\r\n%% Test case #3: 5 players, 7 cards (per category)\r\nyourcards = {2,[3 5],[]};\r\ncommoncards = {5,2,3};\r\nmoves = [4 1 7 5 -1;5 3 3 7 0;2 3 6 7 0;1 7 6 6 -1;2 1 3 2 -1;3 4 1 7 -1;5 4 4 1 -1;5 6 3 1 0;3 7 6 2 -1;2 4 5 1 -1;4 7 5 1 0;5 2 3 7 0;5 3 3 4 -1;3 7 1 1 -1;1 4 5 4 0;2 4 1 7 0;4 3 7 4 -1;5 6 1 2 0;2 6 1 7 2;3 7 3 1 -1;5 4 6 6 0;3 1 5 2 0;4 6 3 7 0;2 6 1 6 2;1 1 3 1 -1;5 6 3 6 0;1 2 5 2 0;1 2 6 6 -1;3 3 7 7 -1;1 1 7 4 0;3 4 4 5 0;5 4 7 7 0;4 7 1 4 -1;1 4 4 7 -1;3 4 7 1 -1;5 1 7 5 -1;1 1 7 6 -1;2 3 3 7 -1];\r\nsol = infercards(5,7,4,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[4 7 1]))\r\n\r\n%% Test case #4: 6 players, 5 cards (per category)\r\nyourcards = {1,[],1};\r\ncommoncards = {[],[],[]};\r\nmoves = [5 5 1 5 -1;5 2 2 2 -1;6 5 5 4 0;5 5 3 2 -1;1 4 3 5 -1;5 2 1 1 0;4 5 3 2 -1;3 2 4 2 -1;4 1 2 4 -1;6 1 2 4 -1;4 5 3 5 -1;5 3 2 5 -1;6 1 1 2 0;5 2 5 5 -1;6 5 4 4 0;2 5 3 2 0;6 3 3 3 -1;3 4 5 4 -1;4 5 5 1 0;3 4 5 2 -1;2 3 5 4 -1;3 5 2 2 -1;1 3 5 5 1;2 4 3 4 0;5 4 3 2 -1;3 5 4 4 -1;4 4 5 4 0;2 2 4 5 -1;3 3 1 5 3;4 2 2 5 -1;4 2 5 1 0;1 5 4 1 0;2 5 3 2 0;2 1 2 5 -1;2 2 4 4 -1;5 4 2 5 -1;3 2 5 2 -1;5 5 2 1 0;4 5 3 2 -1;2 5 3 3 0;4 5 4 4 -1;4 4 5 5 0;3 5 3 1 -1;5 4 2 3 -1;6 5 2 1 0;3 5 1 4 -1;2 5 3 3 2;2 2 3 1 0;2 2 2 2 -1;5 1 2 2 0;6 5 1 4 0;2 3 1 1 0];\r\nsol = infercards(6,5,5,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[2 2 4]))\r\n\r\n%% Test case #5: 8 players, 7 cards (per category)\r\nyourcards = {7,[],3};\r\ncommoncards = {5,[],2};\r\nmoves = [7 6 2 1 0;6 7 6 6 0;7 3 5 4 -1;8 7 1 1 -1;3 2 5 4 -1;7 2 5 3 -1;2 3 6 5 0;4 6 2 3 0;8 3 6 3 -1;1 7 1 6 0;1 3 5 3 -1;1 4 1 5 0;8 1 6 5 -1;3 4 2 3 -1;2 3 6 4 0;2 1 1 3 -1;8 7 4 3 0;4 1 1 1 -1;1 6 5 7 -1;2 2 1 1 0;6 6 4 1 -1;3 7 5 6 -1;1 4 7 3 0;6 7 3 6 0;2 2 1 7 0;7 1 3 4 -1;2 3 4 3 0;1 4 3 3 0;7 4 2 5 -1;8 1 5 7 -1;3 1 7 4 0;2 6 6 5 -1;8 2 6 1 -1;8 7 2 4 0;6 2 2 1 -1;8 1 6 4 0;3 1 1 7 1;8 7 5 4 0;1 1 1 5 -1;7 1 7 1 0;7 7 4 4 -1;5 4 3 5 -1;1 7 4 7 -1;2 7 6 7 -1;2 4 7 5 -1;5 6 7 4 -1;6 3 5 5 -1;2 4 2 5 -1;7 2 1 5 -1;6 7 4 4 -1;8 3 6 7 -1;7 7 3 6 -1;3 2 7 4 2];\r\nsol = infercards(8,7,5,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[6 1 5]))\r\n\r\n%% Test case #6: 5 players, 7 cards (per category)\r\nyourcards = {5,3,2};\r\ncommoncards = {[1 7],[],7};\r\nmoves = [4 3 3 2 0;1 3 7 6 -1;5 6 7 2 0;2 3 7 6 -1;2 2 1 4 -1;3 4 3 5 -1;3 5 7 4 -1;2 3 3 1 -1;1 2 2 5 -1;4 4 5 4 -1;3 5 3 2 -1;4 2 2 1 -1;5 3 7 2 0;1 6 6 3 -1;3 5 5 4 -1;5 4 7 2 0;1 2 4 6 0;2 4 4 5 0;5 3 2 4 -1;2 2 6 4 0;5 5 7 5 0;3 5 5 1 -1;4 5 5 5 0;3 4 6 4 -1;1 6 4 1 0;3 6 2 4 0;1 3 5 4 -1;5 3 7 5 0;5 6 2 3 -1;1 3 2 4 -1;3 2 7 4 0;1 3 1 3 0;4 5 4 4 0;3 3 4 6 -1;3 5 1 2 -1;4 2 3 2 0;3 3 4 2 -1;2 3 5 1 -1;1 3 7 5 -1;2 4 4 4 0;4 6 2 4 -1;3 3 1 2 -1;4 5 3 5 0;1 3 6 5 -1;3 6 3 2 -1];\r\nsol = infercards(5,7,4,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[3 5 4]))\r\n\r\n%% Test case #7: 5 players, 7 cards (per category)\r\nyourcards = {[],[2 6],6};\r\ncommoncards = {4,[3 5],[]};\r\nmoves = [3 3 6 3 -1;3 3 4 5 -1;2 2 2 1 -1;5 2 1 1 3;3 6 6 2 0;3 2 2 1 -1;1 5 1 2 0;5 2 1 3 -1;5 6 1 7 -1;3 2 6 5 -1;3 7 6 6 -1;1 3 2 1 -1;4 3 4 5 -1;1 7 7 2 -1;1 6 7 6 0;3 7 4 5 -1;5 1 1 7 -1;2 3 7 4 0;1 3 1 2 2;2 5 4 5 -1;3 5 6 1 0;3 6 2 4 -1;5 1 6 3 -1;2 7 4 2 1;4 7 7 6 0;3 3 6 6 -1;4 3 1 1 -1;4 6 1 3 -1;5 1 1 7 -1;4 6 6 7 0;4 5 6 1 0;5 5 6 6 -1;1 3 6 4 -1;1 1 7 5 1;4 2 2 2 0;3 2 7 1 -1;3 5 4 7 0;4 3 6 1 0;2 7 4 7 1;2 1 7 3 0;3 5 4 7 0;5 6 1 5 -1;1 3 7 1 -1;5 3 7 7 1;4 7 4 7 -1;5 7 7 1 0;5 5 4 7 -1;2 7 4 3 0;3 1 4 4 -1;4 5 1 7 -1;4 2 2 4 0;1 1 1 6 0;5 6 2 6 -1;5 5 7 5 -1];\r\nsol = infercards(5,7,4,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[2 4 5]))\r\n\r\n%% Test case #8: 5 players, 5 cards (per category)\r\nyourcards = {4,[],4};\r\ncommoncards = {2,[],3};\r\nmoves = [2 5 1 2 -1;4 1 5 2 1;1 5 4 4 -1;1 4 4 1 0;4 1 5 4 0;2 4 4 2 0;1 5 1 5 -1;2 3 1 4 0;1 3 4 4 -1;2 3 3 4 0;3 5 1 2 -1;1 1 4 1 3;5 1 1 4 0;5 4 1 1 0;2 1 4 2 -1;5 4 2 5 0;5 3 2 5 2;2 4 5 4 0;3 3 1 2 -1;3 4 5 4 -1;3 4 4 5 0;1 1 1 5 -1;2 1 4 2 -1;2 3 2 5 -1;4 3 3 1 -1;3 3 1 5 0;1 5 5 1 2;2 5 1 4 0;5 4 1 5 0;1 4 4 2 -1;2 1 1 5 -1;1 1 2 2 -1;1 4 5 1 0;5 4 1 1 0;2 4 4 2 0;3 1 4 2 -1];\r\nsol = infercards(5,5,2,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[3 4 2]))\r\n\r\n%% Test case #9: 5 players, 5 cards (per category)\r\nyourcards = {3,[],4};\r\ncommoncards = {5,4,[]};\r\nmoves = [2 4 5 2 2;3 2 3 1 0;2 2 2 4 -1;5 3 3 5 0;4 1 5 1 0;3 4 1 5 -1;5 2 2 2 -1;1 3 5 5 0;2 2 2 1 -1;2 3 5 4 0;2 1 3 5 -1;4 4 1 5 0;4 4 2 5 0;5 3 3 4 -1;1 3 5 1 0;3 2 5 5 -1;5 1 1 1 0;2 2 1 5 -1;1 3 1 4 0;4 2 5 4 -1;5 1 1 1 2;4 4 3 5 0;4 1 1 4 0;5 3 1 1 0;2 2 2 4 -1;3 4 3 5 2;3 1 1 2 0];\r\nsol = infercards(5,5,1,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[2 2 1]))\r\n\r\n%% Test case #10: 5 players, 7 cards (per category)\r\nyourcards = {[],[2 4 7],[]};\r\ncommoncards = {4,[],[3 6]};\r\nmoves = [2 7 7 7 0;4 2 4 2 -1;2 6 3 4 3;1 2 5 1 0;3 3 5 5 -1;3 7 2 4 0;3 2 4 1 0;1 5 5 1 3;1 2 7 1 0;1 1 6 7 -1;3 3 7 7 0;1 3 4 7 -1;1 3 1 2 -1;5 6 1 4 0;4 1 4 5 -1;5 7 2 7 -1;4 3 1 7 0;5 7 3 1 2;3 2 5 2 -1;2 3 5 4 0;3 7 4 5 0;3 6 4 7 0;5 1 3 2 3;1 1 4 5 -1;4 2 7 4 -1;2 3 2 7 -1;3 1 3 2 -1;2 2 6 7 -1;3 1 4 2 0;4 3 5 4 0;4 1 1 4 -1;5 1 5 7 -1;1 5 5 4 -1;1 7 3 7 -1;4 5 2 5 0;4 7 3 7 -1;4 3 3 2 0;4 6 5 4 -1];\r\nsol = infercards(5,7,3,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[1 5 7]))\r\n\r\n%% Test case #11: 8 players, 7 cards (per category)\r\nyourcards = {2,4,[]};\r\ncommoncards = {[],5,6};\r\nmoves = [2 2 6 4 -1;4 7 6 1 -1;6 6 6 2 2;5 3 6 5 -1;4 1 3 2 0;7 7 3 5 -1;4 4 6 4 -1;1 2 4 2 0;8 3 6 5 -1;7 3 2 2 0;8 7 1 2 -1;3 7 4 5 0;4 2 7 2 -1;1 4 7 4 -1;4 2 3 4 0;3 5 3 4 -1;3 6 3 1 -1;6 7 6 2 0;4 5 1 7 2;1 1 7 5 -1;1 3 4 2 0;2 4 1 2 -1;1 4 6 4 -1;7 4 3 3 -1;8 4 7 7 -1;6 6 4 4 -1;7 5 2 7 3;1 5 7 5 -1;7 4 1 7 0;4 5 3 1 0;2 5 2 2 -1;2 5 3 7 -1;7 7 4 5 -1;7 6 6 1 -1;6 6 7 4 -1;8 1 7 4 -1;2 6 1 5 0;8 6 7 1 0;6 1 6 2 0;1 5 4 3 0;4 5 4 4 -1;8 7 3 1 0;2 7 2 4 -1;6 6 2 3 0;3 6 7 5 -1;7 6 4 4 -1;1 1 2 4 -1;7 1 4 7 0;2 4 7 5 0;4 2 7 7 -1;4 6 2 4 -1;6 4 7 4 -1;6 1 2 3 0;4 4 7 2 -1;4 6 7 3 -1;1 7 1 3 0;5 4 1 7 -1];\r\nsol = infercards(8,7,3,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[4 7 4]))\r\n\r\n%% Test case #12: 5 players, 6 cards (per category)\r\nyourcards = {[],[3 4 6],[]};\r\ncommoncards = {[],[],[]};\r\nmoves = [2 1 5 6 -1;4 4 6 2 0;4 3 1 5 -1;2 4 2 5 0;1 4 2 6 1;5 6 4 3 0;4 2 4 1 0;4 4 6 5 -1;5 4 1 6 -1;4 3 1 4 -1;2 6 5 4 -1;5 1 6 3 0;2 6 5 1 -1;5 6 6 6 0;3 5 5 5 -1;5 2 2 3 -1;1 2 3 3 -1;4 1 4 5 0;3 4 2 5 0;2 2 2 6 -1;5 6 3 6 0;5 4 2 4 -1;2 4 3 4 -1;5 6 2 5 -1;4 3 2 2 3;5 3 4 3 0;3 1 4 3 0;2 2 1 4 -1;1 4 1 1 0;3 2 2 3 3;3 3 2 4 0;1 6 4 4 -1;2 3 6 2 0;5 3 2 1 -1;4 5 1 3 -1;2 5 5 6 0;4 1 1 3 0;2 5 5 1 0;3 5 6 4 -1;4 6 2 5 -1;3 1 6 5 -1;1 6 5 2 -1;1 4 4 2 0;2 5 4 4 0;2 3 2 2 1;5 3 2 4 -1;3 1 2 2 0;1 2 3 2 -1;3 3 1 6 0;2 4 5 6 -1;4 5 6 5 -1;4 1 5 1 0;4 5 6 5 -1;5 3 5 6 -1;3 3 1 3 3;5 2 6 2 0;3 4 1 1 -1];\r\nsol = infercards(5,6,5,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[6 5 4]))\r\n\r\n%% Test case #13: 4 players, 6 cards (per category)\r\nyourcards = {5,4,4};\r\ncommoncards = {[1 4],[],1};\r\nmoves = [3 2 5 4 -1;4 6 6 3 2;1 2 6 5 0;1 6 2 3 0;3 5 6 3 -1;1 2 2 6 2;4 5 2 5 -1;1 3 2 4 0;2 5 4 4 0;3 2 5 3 -1;2 2 1 6 -1;2 6 5 2 -1;4 2 6 4 0;4 2 6 3 2;2 5 1 5 0;1 5 3 5 0;4 2 1 4 0;1 6 2 5 3;1 5 1 2 0;1 5 3 5 0;3 3 1 3 0;1 2 5 5 3;4 2 2 6 0;1 3 5 4 -1;2 6 5 3 -1;1 3 2 2 3;2 5 2 2 0;3 2 4 2 -1;2 6 4 4 0;4 6 5 2 -1;1 2 5 6 -1;2 3 2 2 -1;2 6 5 4 0;1 3 2 3 2;2 2 6 5 -1;1 3 4 3 -1;2 3 6 4 0;3 2 2 5 -1;2 5 4 4 0;1 2 4 2 0;3 6 1 3 0;1 2 5 6 -1;1 5 5 6 -1;3 3 3 2 0;2 3 1 4 0;4 2 2 5 -1];\r\nsol = infercards(4,6,2,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[2 5 3]))\r\n\r\n%% Test case #14: 4 players, 5 cards (per category)\r\nyourcards = {[2 5],[],5};\r\ncommoncards = {[],[],[]};\r\nmoves = [2 2 4 3 0;4 1 1 3 2;1 5 1 5 -1;2 4 4 1 -1;2 1 4 1 -1;4 1 1 3 3;1 2 1 3 -1;2 4 5 1 -1;3 4 1 1 0;4 3 4 4 -1;2 3 2 2 -1;3 5 4 4 -1;2 1 3 5 0;1 3 2 4 1;2 2 4 3 0;3 4 2 2 0;3 4 5 3 0;1 3 2 3 2;2 3 2 2 -1;1 2 2 2 0;4 4 3 4 0;3 3 1 2 -1;4 2 2 3 0;3 4 5 4 0;4 2 3 3 0;1 1 4 2 3];\r\nsol = infercards(4,5,2,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[1 4 4]))\r\n\r\n%% Test case #15: 4 players, 4 cards (per category)\r\nyourcards = {[],[2 4],[]};\r\ncommoncards = {1,[],[]};\r\nmoves = [3 3 1 3 1;3 3 1 4 0;1 2 4 4 0;2 4 4 1 -1;4 2 1 1 -1;1 3 4 2 0;2 2 2 4 0;3 4 3 1 -1;4 3 3 1 -1;1 4 4 1 0;2 4 3 2 0;1 2 1 3 -1;2 4 1 1 -1;1 4 1 2 -1;1 4 2 4 0;3 4 4 1 -1;2 4 1 4 -1;3 3 2 3 0;2 4 4 4 -1;1 4 1 1 -1;4 4 1 1 -1;4 3 2 4 0;1 2 2 1 0;2 3 2 3 -1;2 4 1 4 -1;4 4 4 2 0];\r\nsol = infercards(4,4,1,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[4 1 1]))\r\n\r\n%% Test case #16: 5 players, 7 cards (per category)\r\nyourcards = {[3 5],[],1};\r\ncommoncards = {[6 7],[],7};\r\nmoves = [3 4 5 3 0;1 3 1 4 -1;1 5 5 2 0;2 2 4 6 -1;2 1 6 5 3;4 3 5 6 -1;4 3 2 2 -1;4 2 6 4 0;5 5 4 5 0;2 4 2 2 1;4 3 6 3 0;4 2 6 1 0;4 1 6 4 0;1 4 2 1 -1;3 2 3 6 2;5 5 3 3 0;3 5 2 3 0;4 5 5 1 -1;5 1 3 1 0;3 4 2 5 -1;5 4 4 4 -1;4 2 4 3 -1;5 2 1 6 -1;2 5 7 3 -1;1 1 1 6 -1;2 1 4 6 -1;3 1 1 4 -1;4 3 7 6 -1;1 4 3 5 -1;1 2 6 4 1;3 1 6 6 -1;5 1 3 3 -1;4 5 2 4 0;1 4 3 1 -1;3 2 1 6 -1;3 5 4 4 0;4 1 6 2 0;5 2 7 4 -1;5 2 7 6 -1;3 1 1 6 -1;5 4 1 4 -1;3 5 2 4 -1;4 1 5 6 -1;3 1 3 1 0;1 4 3 2 3;2 5 1 6 -1;3 3 2 2 -1;5 4 5 5 -1;1 1 3 6 -1;4 4 6 2 2;3 1 5 5 -1;1 1 1 1 -1;5 2 6 2 -1;2 3 4 3 -1;4 2 1 3 2;3 5 5 5 -1;3 5 6 1 -1;2 3 1 2 -1;2 3 5 3 0];\r\nsol = infercards(5,7,5,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[1 2 6]))\r\n\r\n%% Test case #17: 5 players, 6 cards (per category)\r\nyourcards = {[],[],[2 3 6]};\r\ncommoncards = {[],[],[]};\r\nmoves = [2 2 4 6 0;4 2 2 4 1;5 2 4 5 0;1 4 1 4 -1;1 5 2 2 0;2 2 6 1 -1;4 5 1 5 1;2 3 4 6 0;1 6 5 4 0;3 1 6 2 0;4 4 5 2 -1;3 5 1 4 2;2 5 6 5 -1;1 3 4 2 -1;4 6 6 6 -1;2 2 6 3 0;1 6 2 5 1;4 2 4 3 0;5 6 2 6 -1;2 6 3 3 0;3 1 3 4 0;1 3 5 1 -1;4 5 4 4 0;1 3 2 1 0;4 5 6 1 0;3 5 6 3 -1;4 3 1 4 -1;2 5 2 2 0;3 3 2 4 -1;2 1 2 3 0;2 3 5 4 -1;1 1 4 1 -1;2 3 6 4 -1;3 4 2 2 -1;4 5 2 1 0;2 3 5 6 0;3 3 2 1 3;2 4 5 3 0;2 3 5 3 0;1 4 2 4 0;5 1 3 4 -1;1 2 4 1 -1;4 4 2 3 -1;3 4 6 1 0;1 5 6 4 -1;5 5 1 3 -1;4 5 5 4 1;5 4 6 4 -1];\r\nsol = infercards(5,6,2,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[4 6 4]))\r\n\r\n%% Test case #18: 7 players, 7 cards (per category)\r\nyourcards = {[],3,2};\r\ncommoncards = {[],5,[1 3 4]};\r\nmoves = [2 3 6 2 -1;1 7 3 2 -1;5 4 7 6 0;6 2 7 5 1;2 4 4 7 0;4 7 1 2 0;3 2 2 5 -1;6 3 1 5 -1;4 2 3 5 0;2 6 7 6 0;1 4 1 7 -1;7 3 2 6 0;2 3 7 7 0;4 7 6 2 0;2 7 3 6 0;4 5 6 2 0;7 6 4 6 0;1 3 7 7 -1;7 3 1 2 0;7 3 3 6 0;3 7 7 7 0;3 4 1 6 0;1 5 4 2 -1;7 6 7 7 -1;2 4 4 5 -1;1 4 3 6 -1;4 4 6 7 -1;4 7 1 2 0;7 5 2 7 -1;5 7 3 5 -1;2 4 4 5 -1;2 6 2 6 3;6 7 2 2 -1;1 6 1 7 0;2 2 7 5 -1;6 5 2 7 0;7 5 6 2 -1;2 1 3 7 0;7 3 2 7 1;7 6 2 6 -1;5 6 1 6 -1;4 2 1 6 -1;5 5 7 5 0;5 5 2 2 -1;5 1 7 5 0;3 5 4 6 -1;4 1 2 2 0;1 1 7 2 0];\r\nsol = infercards(7,7,4,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[4 2 5]))\r\n\r\n%% Test case #19: 5 players, 6 cards (per category)\r\nyourcards = {4,4,6};\r\ncommoncards = {[],[],[]};\r\nmoves = [2 3 5 1 0;4 5 3 1 -1;1 2 2 2 0;3 3 2 4 -1;4 6 4 4 0;2 6 2 1 -1;1 4 2 3 -1;4 5 6 6 0;3 3 6 3 -1;2 3 2 6 0;5 5 6 5 0;1 2 6 2 0;4 1 1 2 -1;1 2 3 1 -1;1 1 3 2 0;5 6 6 5 0;4 4 3 3 0;5 1 6 5 0;3 1 1 4 -1;2 4 4 4 0;5 2 2 6 -1;4 5 1 1 -1;1 4 2 2 0;1 6 1 4 2;3 1 3 2 0;2 4 4 3 -1;1 1 2 1 0;5 1 2 5 -1;2 2 5 3 -1;3 4 5 5 0;3 2 6 4 -1;4 5 4 3 0;4 4 2 5 0;2 5 6 5 3;4 2 5 6 0;4 2 2 6 0;5 1 3 3 -1];\r\nsol = infercards(5,6,4,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[2 2 3]))\r\n\r\n%% Test case #20: 6 players, 8 cards (per category)\r\nyourcards = {[3 4 6],[],[]};\r\ncommoncards = {[],[1 3 5],[]};\r\nmoves = [5 6 8 1 -1;4 5 6 1 0;4 8 6 8 0;6 8 7 2 -1;3 3 6 8 -1;1 7 8 5 -1;3 6 2 5 0;1 3 2 7 0;2 4 7 3 -1;3 2 4 2 0;3 1 8 4 0;2 1 6 8 -1;2 8 8 2 0;5 6 4 5 0;1 6 7 5 -1;2 7 7 7 0;1 7 2 7 0;5 1 4 5 2;5 8 8 6 0;5 8 6 1 -1;4 5 7 3 0;1 1 4 4 -1;6 6 7 7 0;2 8 8 4 2;5 2 8 6 0;5 6 7 7 -1;4 4 7 6 -1;3 7 7 8 -1;1 4 6 4 -1;4 1 7 4 -1;3 1 2 4 0;6 1 2 2 -1;2 3 8 4 0;2 4 7 2 -1;1 5 2 5 -1;5 1 6 1 -1;4 4 8 5 -1;4 1 2 3 -1;2 8 6 8 -1;3 8 8 5 -1;2 5 8 8 0;5 8 6 5 -1;4 1 4 4 -1;3 3 7 6 -1;1 8 8 1 -1;3 6 2 7 0;3 2 6 3 0;4 5 6 2 2;4 4 2 4 -1;5 6 4 2 0;1 4 8 8 0;5 6 7 5 -1;3 2 2 1 0;5 1 8 2 3;6 5 7 5 -1;4 8 6 8 0;5 4 6 1 -1;1 6 4 7 0;2 6 2 4 0];\r\nsol = infercards(6,8,6,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[8 7 5]))","published":true,"deleted":false,"likes_count":12,"comments_count":5,"created_by":287,"edited_by":287,"edited_at":"2025-11-14T17:50:41.000Z","deleted_by":null,"deleted_at":null,"solvers_count":56,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2025-11-04T20:44:39.000Z","updated_at":"2026-02-24T14:43:50.000Z","published_at":"2025-11-10T02:24:19.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[Warning: this is a nontrivial programming problem]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWorried about the decline in reasoning skills in the clueless populace of Nedland, Lord Ned had the finest minds at the University of \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003eNedsburg\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e develop a fun game to sharpen logical inference skills.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe game consists of a deck of 3\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e cards, with \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e cards in each of three categories.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"439\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"600\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOne card from each category is randomly selected and these three cards are placed, unseen, in an envelope. The goal of the game is for the players to figure out which cards are in the envelope.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"306\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"700\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId2\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe remaining 3(\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e-1) cards are shuffled together and then dealt to the players. Every player receives the same number of cards; any leftover cards are placed face-up so that all players can see them. Because all the cards are shuffled together, the players will not all have an equal distribution of cards from the three categories.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"383\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"700\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId3\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ePlayers take it in turns to ask any other player about three cards, one from each category. If the player asked has any of the cards asked for, they must show one of those cards to the player who asked. (If they have more than one of the specified cards, they can choose which card to show.) The other players do not get to see which card has been shown, but they do know which three cards were asked for and that the player asked had one of them. If the player asked has none of the cards asked for, they simply state this and do not have to show any of their cards.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOnce a player believes they have deduced the identity of the three cards in the envelope, they can, on their turn, announce their guess, then check the cards in the envelope. If the player is correct, they can reveal the cards as proof and they win the game. If not, they are eliminated. They must return the cards to the envelope, and the game continues without them.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWrite a function that takes information about a game as inputs and returns the solution (that is, the deduced identity of the cards in the envelope) as output.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe inputs to the function are:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003em\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, the number of players\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, the number of cards in each category\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003epnum\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, which player you are (from 1 to \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003em\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e). Players take turns in order (1 to \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003em\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, and back to 1). If a card is revealed and it is your turn, you know the exact identity of that card. If it is not your turn, you know only that one of the cards asked for was revealed.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eyourcards\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, a 3-element cell array representing the cards dealt to you. Each cell contains the cards for one category. The cards from that category are given as a vector of values from 1 to \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e. If there are no cards for that category, the cell will contain an empty vector. In the example image, if you are the player in the bottom left (player 4), \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eyourcards = {[1 3],[],[]}\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e. If instead you are the player in the bottom right (player 3), \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eyourcards = {[],[4],[2]}\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ecommoncards\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, a 3-element cell array representing the extra cards visible to everyone. The format is the same as for \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eyourcards\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e. In the example image, \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ecommoncards = {[],[3],[]}\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eturns\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, an \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ent\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e-by-5 matrix representing \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ent\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e turns of the game. Each row of \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eturns\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e records one player's turn as a 5-element vector. The first value is the number of the player asked. The next three values are the cards asked for, one for each category in order. The final value is the result: -1 represents the asked player responding that they do not have any of the requested cards; 0 represents the asked player showing a card (but you do not know which specific card); a value of 1-3 represents the asked player showing you a specific card, where the value is the index (or, equivalently, category) of the three cards asked for. For example, a row of \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eturns\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e that was the vector \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[5 4 3 2 1]\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e would represent player 5 being asked for card 4 in category 1, card 3 in category 2, and card 2 in category 3, and showing you card 4 of category 1.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe output should be a single 3-element vector of the cards in the envelope, in order. For the example image, the output would be \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[4 2 1]\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eAssumptions\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe game is still new to \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003eNedland\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, so don't expect the players to make the best requests on their turn, but the solution can be inferred from the inputs given. It may be possible to determine the solution from less information than is given, but the information given will always be sufficient.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAlthough it shouldn't matter for your implementation, the official rules have 4-8 players (\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003em\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e) and card decks with up to 8 cards in each category (\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e), using at least enough cards to ensure that each player gets at least two cards in their hand.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eExample\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor the example images, \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003em\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e = 4, \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e = 4. Suppose \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003epnum\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e = 4, in which case \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eyourcards = {[1 3],[],[]}\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e and \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ecommoncards = {[],[3],[]}\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[moves = 12×5\\n3 1 4 3 0\\n1 3 4 4 0\\n2 3 1 3 0\\n1 4 2 2 -1\\n4 3 1 1 0\\n3 2 2 2 0\\n2 1 1 4 0\\n2 4 2 3 3\\n3 3 2 1 -1\\n1 4 4 2 -1\\n2 4 2 1 -1\\n1 2 2 4 1]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIn the first turn, player 1 asks player 3 for cards \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[1 4 3]\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e (that is, card 1 from category 1, card 4 from category 2, and card 3 from category 3). Player 3 shows them a card but you, player 4, don't know which. You have the first card in your hand, so it must have been one of the other two, but so far no further information can be extracted.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eSimilarly, player 2 then asks player 1 for cards \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[3 4 4]\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e and is shown one. Again, you hold the first card, so player 1 must have either card 4 from category 2 or card 4 from category 3, but you don't yet know which.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOn the fourth turn, you ask player 1 for cards \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[4 2 2]\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, but player 1 has none of these.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eMore turns occur where you cannot determine any concrete information yet.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOn the eight turn, things suddenly get interesting. You ask player 2 for \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[4 2 3]\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e and are shown the third of these. That is, you know that player 2 holds card 3 from category 3.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eMoreover, this makes some of the earlier turns more useful. Revisiting the first turn where player 3 was asked for \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[1 4 3]\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, you now know that you held the first card and player 2 held the third card. The card that player 3 showed player 1 must therefore be the second card, so now you know that player 3 has card 4 from category 2.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAnd similarly, now you can deduce from turn 2 that player 1 has card 4 from category 3 (because you hold the first card and player 3 holds the second card). And again from turn 7, you can now deduce that player 2 has card 1 from category 2, using the same logic.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAt this point, you now know both cards that player 2 holds, so you can eliminate all other cards from possibly being held by them.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eYou also now know the locations of three of the four cards in category 2: player 2 has card 1, the common card is card 3, and player 3 has card 4. That means the remaining card (2) is in the envelope.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eTurn 9 tells you that player 3 does not have card 1 from category 3. The next two turns provide no new information.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFinally, turn 12 reveals that player 1 has card 2 from category 1. This means you now know both cards player 1 holds (2 from category 1 and 4 from category 3). Consequently, you know that no player has card 1 from category 3 (you know both cards held by players 1 and 2, you know player 3 doesn't have it, you don't have it, and it's not the common card), so it must be in the envelope.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis just leaves category 1 but you now know the location of three of the four cards (you have cards 1 \u0026amp; 3, player 1 has card 2). And so you have the solution: \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[4 2 1]\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[soln = infercards(m,n,pnum,yourcards,commoncards,moves)\\nsoln =\\n4 2 1]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eImplementation Suggestions/Tips\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOne way to find the solution is to keep an array of all cards and all players, with values indicating your state of knowledge about whether that player has that card: unknown, yes, or no. Start with everything unknown, and fill in information as you go. For this tracking, you can treat the common cards as player \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003em\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e+1. Each category has one card that nobody has, which is the card in the envelope. Once you have identified that card for each category, you have your solution.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eYou start with complete knowledge of which cards you and the common \\\"player\\\" do and do not have.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGo through the turns and use the provided information to update your state of knowledge. Also use the following observations to extend the logic to find new information:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIf you know a player has a card, you know all other players do not.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eYou know how many cards each player has: the same number that you have. Equivalently, you can calculate it: \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003encards = floor(3*(n-1)/m)\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e. If you know the identities of \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003encards\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e cards for a player, you know they have no other cards. (The common cards are an exception, but this doesn't matter because you already know exactly what cards are and are not in the common set.)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOnce you know the locations of (\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e-1) cards in a category, the remaining card must be in the envelope.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eEach player holds \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003encards\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e cards. If you can identify 3\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e-\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003encards\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e cards that a player definitely does \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:u/\u003e\u003c/w:rPr\u003e\u003cw:t\u003enot\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e hold, then they must hold the remaining \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003encards\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e cards. That is, if the no, yes, and maybe/unknown cards for a player are distributed such that there are \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003encards\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e yes or maybe (and 3\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e-\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003encards\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e no), then all the remaining maybes are yeses.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eRemember that, as in the example, new information disclosed in a turn may make previous turns more 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Series 08: IsPair","description":"The Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\r\n\r\nA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\r\n\r\nFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\r\n\r\n--------\r\n\r\nA pair is 2 cards of the same rank (column) and the three kickers. The Ace (first column) is highest. The columns represent A, 2, 3, ... K. The next three highest cards are the kickers. If the kickers also form a pair, or three of a kind, it is still considered a pair for the purposes of this function.\r\n\r\nThis hand matrix:\r\n\r\n 0 1 0 0 1 0 0 0 0 0 0 0 0 \r\n 0 0 1 0 0 0 0 1 0 0 0 0 0\r\n 0 1 0 1 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 1 0 0 0 0 0 0 0\r\n\r\nrepresents a pair, so the return value from the function is TRUE.\r\n\r\nThis hand matrix does not:\r\n\r\n 0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 1 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n\r\nso the return value should be FALSE.\r\n\r\nThis hand matrix does represent a pair\r\n\r\n 0 0 0 0 0 0 0 0 0 1 0 0 1 \r\n 0 0 0 0 0 0 0 0 0 0 1 0 0\r\n 0 0 1 0 0 0 0 0 0 1 0 0 0 \r\n 0 0 0 0 0 1 0 0 0 0 0 1 0\r\n\r\nRemember, hand matrices can contain any number of 1's from 0 to 52.\r\n\r\n 0 1 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 1 1 1 0 0 0 1 0 1\r\n 0 0 0 1 0 1 0 0 0 1 0 0 0 \r\n 0 0 1 0 0 0 0 0 0 0 0 1 0 \r\n\r\nWould be TRUE for this function.\r\n\r\nA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand matrix, but it only shows the cards used to make the pair. If more than one pair can be made, return the higher ranking one (the one with the highest rank. Ace being the highest). If different suits are possible for the same pair, return the one higher up in the matrix, same for kickers. If the pair happens to also be a four of a kind or full house, two pair, etc.. it still meets the defintion and should be returned.","description_html":"\u003cp\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/p\u003e\u003cp\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/p\u003e\u003cp\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/p\u003e\u003cp\u003e--------\u003c/p\u003e\u003cp\u003eA pair is 2 cards of the same rank (column) and the three kickers. The Ace (first column) is highest. The columns represent A, 2, 3, ... K. The next three highest cards are the kickers. If the kickers also form a pair, or three of a kind, it is still considered a pair for the purposes of this function.\u003c/p\u003e\u003cp\u003eThis hand matrix:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 0 0 1 0 0 0 0 0 0 0 0 \r\n0 0 1 0 0 0 0 1 0 0 0 0 0\r\n0 1 0 1 0 0 0 0 0 0 0 0 0 \r\n0 0 0 0 0 1 0 0 0 0 0 0 0\r\n\u003c/pre\u003e\u003cp\u003erepresents a pair, so the return value from the function is TRUE.\u003c/p\u003e\u003cp\u003eThis hand matrix does not:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n0 0 0 0 0 0 0 0 0 0 0 0 0\r\n0 0 0 0 0 0 0 0 0 1 0 0 0 \r\n0 0 0 0 0 0 0 0 0 0 0 0 0\r\n\u003c/pre\u003e\u003cp\u003eso the return value should be FALSE.\u003c/p\u003e\u003cp\u003eThis hand matrix does represent a pair\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 0 0 0 0 0 0 0 0 1 0 0 1 \r\n0 0 0 0 0 0 0 0 0 0 1 0 0\r\n0 0 1 0 0 0 0 0 0 1 0 0 0 \r\n0 0 0 0 0 1 0 0 0 0 0 1 0\r\n\u003c/pre\u003e\u003cp\u003eRemember, hand matrices can contain any number of 1's from 0 to 52.\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 0 0 0 0 0 0 0 0 0 0 0 \r\n0 0 0 0 1 1 1 0 0 0 1 0 1\r\n0 0 0 1 0 1 0 0 0 1 0 0 0 \r\n0 0 1 0 0 0 0 0 0 0 0 1 0 \r\n\u003c/pre\u003e\u003cp\u003eWould be TRUE for this function.\u003c/p\u003e\u003cp\u003eA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand matrix, but it only shows the cards used to make the pair. If more than one pair can be made, return the higher ranking one (the one with the highest rank. Ace being the highest). If different suits are possible for the same pair, return the one higher up in the matrix, same for kickers. If the pair happens to also be a four of a kind or full house, two pair, etc.. it still meets the defintion and should be returned.\u003c/p\u003e","function_template":"function out = isPair(hm)\r\n out.flag = false;\r\n out.usedCards = false(4,13);\r\nend","test_suite":"%%\r\nhm = [0 1 0 0 0 0 0 0 1 0 0 0 1 \r\n 0 1 0 0 0 0 0 0 0 0 0 1 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 1 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 1 0 0 0 0 0 0 0 0 0 0 1 \r\n 0 1 0 0 0 0 0 0 0 0 0 1 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 1 0 0])\r\n \r\nassert(isequal(isPair(hm),y_correct))\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 1 0 0 0 1 \r\n 0 1 0 0 0 0 0 1 0 0 0 1 0\r\n 0 0 0 0 0 0 1 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 1 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 1 0 0 0 0 0 0 0 0 0 0 1 \r\n 0 1 0 0 0 0 0 0 0 0 0 1 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 1 0 0])\r\n \r\nassert(isequal(isPair(hm),y_correct))\r\n\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 1 0 0 0 1 \r\n 0 1 0 0 0 0 0 0 0 0 0 1 1\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 1 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 1 0 0 0 1 \r\n 0 0 0 0 0 0 0 0 0 0 0 1 1\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 1 0 0])\r\n \r\nassert(isequal(isPair(hm),y_correct))\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 1 0 0 0 1 \r\n 1 1 0 0 0 0 0 0 0 0 0 1 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 1 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 1 \r\n 1 0 0 0 0 0 0 0 0 0 0 1 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 1 0 0])\r\n \r\nassert(isequal(isPair(hm),y_correct))\r\n\r\n%%\r\nhm = [0 0 0 0 0 0 0 0 1 0 0 0 1 \r\n 0 1 0 0 0 0 0 0 0 0 0 1 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 1 0 0];\r\n\r\ny_correct.flag = false;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isPair(hm),y_correct))\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 1 0 0 0 1 \r\n 1 1 0 0 0 0 0 0 0 0 0 1 1\r\n 0 0 0 0 0 0 0 0 0 0 0 0 1 \r\n 1 0 0 0 0 0 0 0 0 0 1 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 1 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 1\r\n 0 0 0 0 0 0 0 0 0 0 0 0 1 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isPair(hm),y_correct))","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":240,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":55,"test_suite_updated_at":"2012-02-22T19:17:35.000Z","rescore_all_solutions":false,"group_id":15,"created_at":"2012-02-22T19:17:35.000Z","updated_at":"2026-02-15T05:44:51.000Z","published_at":"2012-02-22T19:17:35.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e--------\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA pair is 2 cards of the same rank (column) and the three kickers. The Ace (first column) is highest. The columns represent A, 2, 3, ... K. The next three highest cards are the kickers. If the kickers also form a pair, or three of a kind, it is still considered a pair for the purposes of this function.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 0 0 1 0 0 0 0 0 0 0 0 \\n0 0 1 0 0 0 0 1 0 0 0 0 0\\n0 1 0 1 0 0 0 0 0 0 0 0 0 \\n0 0 0 0 0 1 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003erepresents a pair, so the return value from the function is TRUE.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix does not:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 1 0 1 1 0 0 0 0 0 0 0 \\n0 0 0 0 0 0 0 0 0 0 0 0 0\\n0 0 0 0 0 0 0 0 0 1 0 0 0 \\n0 0 0 0 0 0 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eso the return value should be FALSE.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix does represent a pair\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 0 0 0 0 0 0 0 0 1 0 0 1 \\n0 0 0 0 0 0 0 0 0 0 1 0 0\\n0 0 1 0 0 0 0 0 0 1 0 0 0 \\n0 0 0 0 0 1 0 0 0 0 0 1 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eRemember, hand matrices can contain any number of 1's from 0 to 52.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 0 0 0 0 0 0 0 0 0 0 0 \\n0 0 0 0 1 1 1 0 0 0 1 0 1\\n0 0 0 1 0 1 0 0 0 1 0 0 0 \\n0 0 1 0 0 0 0 0 0 0 0 1 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWould be TRUE for this function.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand matrix, but it only shows the cards used to make the pair. If more than one pair can be made, return the higher ranking one (the one with the highest rank. Ace being the highest). If different suits are possible for the same pair, return the one higher up in the matrix, same for kickers. If the pair happens to also be a four of a kind or full house, two pair, etc.. it still meets the defintion and should be returned.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":385,"title":"Poker Series 09: IsHighCard","description":"The Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\r\n\r\nA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\r\n\r\nFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\r\n\r\n--------\r\n\r\nHigh Card is the five highest cards in your hand. It is basically what you have if you don't have anything else! The Ace (first column) is highest. The columns represent A, 2, 3, ... K. If the kickers also form a pair, it is still considered high card for the purposes of this function.\r\n\r\nThis hand matrix:\r\n\r\n 0 1 0 0 1 0 0 0 0 0 0 0 0 \r\n 0 0 1 0 0 0 0 0 0 0 0 0 0\r\n 0 1 0 1 0 0 0 0 0 0 0 0 0 \r\n 0 1 0 0 0 1 0 0 0 0 0 0 0\r\n\r\nrepresents a high card, so the return value from the function is TRUE.\r\n\r\nThis hand matrix does not (because it is defined as five cards):\r\n\r\n 0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n\r\nso the return value should be FALSE.\r\n\r\nThis hand matrix does represent a high card\r\n\r\n 0 0 0 0 0 0 0 0 0 1 0 0 1 \r\n 0 0 0 0 0 0 0 0 0 0 1 0 0\r\n 0 0 0 0 0 0 0 0 0 1 0 0 0 \r\n 0 0 0 0 0 1 0 0 0 1 0 1 0\r\n\r\nRemember, hand matrices can contain any number of 1's from 0 to 52.\r\n\r\n 0 0 0 0 0 1 0 0 0 0 0 0 0 \r\n 0 0 0 0 1 1 1 0 0 0 0 0 1\r\n 0 0 0 1 0 1 0 0 0 1 0 0 0 \r\n 0 0 1 0 0 0 0 0 0 0 0 1 0 \r\n\r\nWould be TRUE for this function.\r\n\r\nA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand matrix, but it only shows the cards used to make the high card. If more than one hag card can be made, return the higher ranking one (the one with the highest rank. Ace being the highest). If different suits are possible for the same high card, return the one higher up in the matrix, same for kickers. If the high card also happens to also be a four of a kind or full house, it still meets the defintion and should be returned.","description_html":"\u003cp\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/p\u003e\u003cp\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/p\u003e\u003cp\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/p\u003e\u003cp\u003e--------\u003c/p\u003e\u003cp\u003eHigh Card is the five highest cards in your hand. It is basically what you have if you don't have anything else! The Ace (first column) is highest. The columns represent A, 2, 3, ... K. If the kickers also form a pair, it is still considered high card for the purposes of this function.\u003c/p\u003e\u003cp\u003eThis hand matrix:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 0 0 1 0 0 0 0 0 0 0 0 \r\n0 0 1 0 0 0 0 0 0 0 0 0 0\r\n0 1 0 1 0 0 0 0 0 0 0 0 0 \r\n0 1 0 0 0 1 0 0 0 0 0 0 0\r\n\u003c/pre\u003e\u003cp\u003erepresents a high card, so the return value from the function is TRUE.\u003c/p\u003e\u003cp\u003eThis hand matrix does not (because it is defined as five cards):\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n0 0 0 0 0 0 0 0 0 0 0 0 0\r\n0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n0 0 0 0 0 0 0 0 0 0 0 0 0\r\n\u003c/pre\u003e\u003cp\u003eso the return value should be FALSE.\u003c/p\u003e\u003cp\u003eThis hand matrix does represent a high card\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 0 0 0 0 0 0 0 0 1 0 0 1 \r\n0 0 0 0 0 0 0 0 0 0 1 0 0\r\n0 0 0 0 0 0 0 0 0 1 0 0 0 \r\n0 0 0 0 0 1 0 0 0 1 0 1 0\r\n\u003c/pre\u003e\u003cp\u003eRemember, hand matrices can contain any number of 1's from 0 to 52.\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 0 0 0 0 1 0 0 0 0 0 0 0 \r\n0 0 0 0 1 1 1 0 0 0 0 0 1\r\n0 0 0 1 0 1 0 0 0 1 0 0 0 \r\n0 0 1 0 0 0 0 0 0 0 0 1 0 \r\n\u003c/pre\u003e\u003cp\u003eWould be TRUE for this function.\u003c/p\u003e\u003cp\u003eA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand matrix, but it only shows the cards used to make the high card. If more than one hag card can be made, return the higher ranking one (the one with the highest rank. Ace being the highest). If different suits are possible for the same high card, return the one higher up in the matrix, same for kickers. If the high card also happens to also be a four of a kind or full house, it still meets the defintion and should be returned.\u003c/p\u003e","function_template":"function out = isHighCard(hm)\r\n out.flag = false;\r\n out.usedCards = false(4,13);\r\nend","test_suite":"clear\r\nclc\r\n\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 1 1 0 1 1 \r\n 0 1 0 0 0 0 0 0 1 0 0 1 0\r\n 0 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 1 1 0 1 1 \r\n 0 0 0 0 0 0 0 0 0 0 0 1 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isHighCard(hm),y_correct))\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 1 1 0 1 1 \r\n 1 1 0 0 0 0 0 0 1 0 0 1 0\r\n 0 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 1 0 1 1 \r\n 1 0 0 0 0 0 0 0 0 0 0 1 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isHighCard(hm),y_correct))\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 1 1 0 1 1 \r\n 1 1 0 0 0 0 0 0 1 0 0 1 0\r\n 0 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 1 1 \r\n 1 0 0 0 0 0 0 0 0 0 0 1 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isHighCard(hm),y_correct))\r\n%%\r\nhm = [0 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 0 1 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = false;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isHighCard(hm),y_correct))","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":240,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":55,"test_suite_updated_at":"2012-02-22T19:38:00.000Z","rescore_all_solutions":false,"group_id":15,"created_at":"2012-02-22T19:38:00.000Z","updated_at":"2026-02-15T05:43:12.000Z","published_at":"2012-02-22T19:48:08.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e--------\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eHigh Card is the five highest cards in your hand. It is basically what you have if you don't have anything else! The Ace (first column) is highest. The columns represent A, 2, 3, ... K. If the kickers also form a pair, it is still considered high card for the purposes of this function.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 0 0 1 0 0 0 0 0 0 0 0 \\n0 0 1 0 0 0 0 0 0 0 0 0 0\\n0 1 0 1 0 0 0 0 0 0 0 0 0 \\n0 1 0 0 0 1 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003erepresents a high card, so the return value from the function is TRUE.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix does not (because it is defined as five cards):\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 1 0 1 1 0 0 0 0 0 0 0 \\n0 0 0 0 0 0 0 0 0 0 0 0 0\\n0 0 0 0 0 0 0 0 0 0 0 0 0 \\n0 0 0 0 0 0 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eso the return value should be FALSE.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix does represent a high card\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 0 0 0 0 0 0 0 0 1 0 0 1 \\n0 0 0 0 0 0 0 0 0 0 1 0 0\\n0 0 0 0 0 0 0 0 0 1 0 0 0 \\n0 0 0 0 0 1 0 0 0 1 0 1 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eRemember, hand matrices can contain any number of 1's from 0 to 52.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 0 0 0 0 1 0 0 0 0 0 0 0 \\n0 0 0 0 1 1 1 0 0 0 0 0 1\\n0 0 0 1 0 1 0 0 0 1 0 0 0 \\n0 0 1 0 0 0 0 0 0 0 0 1 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWould be TRUE for this function.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand matrix, but it only shows the cards used to make the high card. If more than one hag card can be made, return the higher ranking one (the one with the highest rank. Ace being the highest). If different suits are possible for the same high card, return the one higher up in the matrix, same for kickers. If the high card also happens to also be a four of a kind or full house, it still meets the defintion and should be returned.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1512,"title":"Clock Solitaire","description":"Many card players will be familiar with the game of \u003chttp://en.wikipedia.org/wiki/Clock_patience Clock Solitaire\u003e. Briefly, the player sets up by creating thirteen piles of four face-down cards at random, each associated with one of the ranks ace through king. Beginning with the top card in the king's pile, the player places the drawn card face up beneath its home pile, and draws a new card from the top of that same pile. Play continues until the fourth king is drawn. If all cards are face up in their home piles at this time, the game is a winner.\r\n\r\nSince clock solitaire is a purely deterministic game, a computer can easily be programmed to play. For this problem, you will write a function that takes a deck and reports whether or not it is a winning configuration. More specifically, the input will be some permutation of the integers 1:52, where 1:13 represent the ace through king of clubs, 14:26 the ace through king of diamonds, 27:39 the hearts, and 40:52 the spades. Assume that the cards are formed into 13 piles by taking the first four cards as the ace pile, next four as the deuce pile, etc. Output is a single scalar boolean indicating whether the game will be won using this deck.\r\n\r\nArmed with this function, one can determine empirically what the win rate is for randomly shuffled decks. See if you can find out!","description_html":"\u003cp\u003eMany card players will be familiar with the game of \u003ca href = \"http://en.wikipedia.org/wiki/Clock_patience\"\u003eClock Solitaire\u003c/a\u003e. Briefly, the player sets up by creating thirteen piles of four face-down cards at random, each associated with one of the ranks ace through king. Beginning with the top card in the king's pile, the player places the drawn card face up beneath its home pile, and draws a new card from the top of that same pile. Play continues until the fourth king is drawn. If all cards are face up in their home piles at this time, the game is a winner.\u003c/p\u003e\u003cp\u003eSince clock solitaire is a purely deterministic game, a computer can easily be programmed to play. For this problem, you will write a function that takes a deck and reports whether or not it is a winning configuration. More specifically, the input will be some permutation of the integers 1:52, where 1:13 represent the ace through king of clubs, 14:26 the ace through king of diamonds, 27:39 the hearts, and 40:52 the spades. Assume that the cards are formed into 13 piles by taking the first four cards as the ace pile, next four as the deuce pile, etc. Output is a single scalar boolean indicating whether the game will be won using this deck.\u003c/p\u003e\u003cp\u003eArmed with this function, one can determine empirically what the win rate is for randomly shuffled decks. See if you can find out!\u003c/p\u003e","function_template":"function isWinner = clockSolitaire(deck)\r\n isWinner = true;\r\nend","test_suite":"%%\r\ndeck = [1:52];\r\nassert(isequal(clockSolitaire(deck),false))\r\n\r\n%%\r\ndeck = [8 1 5 2 30 23 46 21 3 51 6 27 42 48 37 33 12 25 45 36 31 34 29 35 15 17 43 13 39 40 18 50 26 9 4 28 38 16 11 22 49 24 14 7 32 20 47 44 19 10 41 52];\r\nassert(isequal(clockSolitaire(deck),true))\r\n%%\r\ndeck = [52:-1:1];\r\nassert(isequal(clockSolitaire(deck),false))\r\n\r\n%%\r\ndeck = [40 29 25 37 23 41 13 50 33 2 42 20 49 48 27 46 36 45 28 1 7 11 14 5 9 26 15 21 12 8 19 35 10 38 34 52 32 51 31 16 18 22 6 3 47 44 43 4 24 17 30 39];\r\nassert(isequal(clockSolitaire(deck),true))\r\n\r\n%%\r\ndeck = [40 29 25 37 23 41 13 50 33 2 42 20 52 48 27 46 36 45 28 1 7 11 14 5 9 26 15 21 12 8 19 35 10 38 34 49 32 51 31 16 18 22 6 3 47 44 43 4 24 17 30 39];\r\nassert(isequal(clockSolitaire(deck),false))\r\n\r\n%%\r\ndeck = [8 1 5 2 30 23 46 21 3 51 6 27 13 48 37 33 12 25 45 36 31 34 29 35 15 17 43 42 39 40 18 50 26 9 4 28 38 16 11 22 49 24 14 7 32 20 47 44 19 10 41 52];\r\nassert(isequal(clockSolitaire(deck),false))","published":true,"deleted":false,"likes_count":2,"comments_count":1,"created_by":3117,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":39,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":15,"created_at":"2013-05-16T01:27:06.000Z","updated_at":"2026-02-15T04:05:23.000Z","published_at":"2013-05-16T01:27:05.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eMany card players will be familiar with the game of \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://en.wikipedia.org/wiki/Clock_patience\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eClock Solitaire\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e. Briefly, the player sets up by creating thirteen piles of four face-down cards at random, each associated with one of the ranks ace through king. Beginning with the top card in the king's pile, the player places the drawn card face up beneath its home pile, and draws a new card from the top of that same pile. Play continues until the fourth king is drawn. If all cards are face up in their home piles at this time, the game is a winner.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eSince clock solitaire is a purely deterministic game, a computer can easily be programmed to play. For this problem, you will write a function that takes a deck and reports whether or not it is a winning configuration. More specifically, the input will be some permutation of the integers 1:52, where 1:13 represent the ace through king of clubs, 14:26 the ace through king of diamonds, 27:39 the hearts, and 40:52 the spades. Assume that the cards are formed into 13 piles by taking the first four cards as the ace pile, next four as the deuce pile, etc. Output is a single scalar boolean indicating whether the game will be won using this deck.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eArmed with this function, one can determine empirically what the win rate is for randomly shuffled decks. See if you can find out!\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":376,"title":"Poker Series 05: isStraight","description":"The Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\r\n\r\nA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\r\n\r\nFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\r\n\r\n--------\r\n\r\nA straight is 5 cards of the adjacent ranks (columns) regardless of suits (rows). The Ace (first column) is both lowest and highest. The columns represent A, 2, 3, ... K. This means A, K, Q, J, Ten is a straight also.\r\n\r\nThis hand matrix:\r\n\r\n 0 1 0 0 1 0 0 0 0 0 0 0 0 \r\n 0 0 1 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 1 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 1 0 0 0 0 0 0 0\r\n\r\nrepresents a straight, so the return value from the function is TRUE.\r\n\r\nThis hand matrix does not:\r\n\r\n 0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 1 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n\r\nso the return value should be FALSE.\r\n\r\nThis hand matrix does represent a straight\r\n\r\n 0 0 0 0 0 0 0 0 0 1 0 0 1 \r\n 0 0 0 0 0 0 0 0 0 0 1 0 0\r\n 0 0 1 0 0 0 0 0 0 0 0 0 0 \r\n 1 0 0 0 0 1 0 0 0 0 0 1 0\r\n\r\nRemember, hand matrices can contain any number of 1's from 0 to 52.\r\n\r\n 0 0 0 0 0 1 0 0 0 0 0 0 0 \r\n 0 0 0 0 1 0 1 0 0 0 0 0 0\r\n 0 0 0 1 0 0 0 0 0 0 0 0 0 \r\n 0 0 1 0 0 0 0 0 0 0 0 0 0 \r\n\r\nWould be TRUE for this function.\r\n\r\nA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand matrix, but it only shows the cards used to make the straight. If more than one straight can be made, return the higher ranking one (the one with the highest top card. Ace being the highest). If different suits are possible for the same straight cards, return the one higher up in the matrix. If the straight happens to also be a straight flush, it still meets the defintion and should be returned. The highest straight should be returned, even if a straight flush can also be made.","description_html":"\u003cp\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/p\u003e\u003cp\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/p\u003e\u003cp\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/p\u003e\u003cp\u003e--------\u003c/p\u003e\u003cp\u003eA straight is 5 cards of the adjacent ranks (columns) regardless of suits (rows). The Ace (first column) is both lowest and highest. The columns represent A, 2, 3, ... K. This means A, K, Q, J, Ten is a straight also.\u003c/p\u003e\u003cp\u003eThis hand matrix:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 0 0 1 0 0 0 0 0 0 0 0 \r\n0 0 1 0 0 0 0 0 0 0 0 0 0\r\n0 0 0 1 0 0 0 0 0 0 0 0 0 \r\n0 0 0 0 0 1 0 0 0 0 0 0 0\r\n\u003c/pre\u003e\u003cp\u003erepresents a straight, so the return value from the function is TRUE.\u003c/p\u003e\u003cp\u003eThis hand matrix does not:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n0 0 0 0 0 0 0 0 0 0 0 0 0\r\n0 0 0 0 0 0 0 0 0 1 0 0 0 \r\n0 0 0 0 0 0 0 0 0 0 0 0 0\r\n\u003c/pre\u003e\u003cp\u003eso the return value should be FALSE.\u003c/p\u003e\u003cp\u003eThis hand matrix does represent a straight\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 0 0 0 0 0 0 0 0 1 0 0 1 \r\n0 0 0 0 0 0 0 0 0 0 1 0 0\r\n0 0 1 0 0 0 0 0 0 0 0 0 0 \r\n1 0 0 0 0 1 0 0 0 0 0 1 0\r\n\u003c/pre\u003e\u003cp\u003eRemember, hand matrices can contain any number of 1's from 0 to 52.\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 0 0 0 0 1 0 0 0 0 0 0 0 \r\n0 0 0 0 1 0 1 0 0 0 0 0 0\r\n0 0 0 1 0 0 0 0 0 0 0 0 0 \r\n0 0 1 0 0 0 0 0 0 0 0 0 0 \r\n\u003c/pre\u003e\u003cp\u003eWould be TRUE for this function.\u003c/p\u003e\u003cp\u003eA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand matrix, but it only shows the cards used to make the straight. If more than one straight can be made, return the higher ranking one (the one with the highest top card. Ace being the highest). If different suits are possible for the same straight cards, return the one higher up in the matrix. If the straight happens to also be a straight flush, it still meets the defintion and should be returned. The highest straight should be returned, even if a straight flush can also be made.\u003c/p\u003e","function_template":"function out = isStraight(hm)\r\n out.flag = false;\r\n out.usedCards = false(4,13);\r\nend","test_suite":"%%\r\nhm = [0 1 0 0 0 0 0 0 1 1 0 1 1 \r\n 0 1 0 0 0 0 0 0 1 0 0 1 0\r\n 0 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = false;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isStraight(hm),y_correct))\r\n\r\n%%\r\nhm = [0 1 1 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 1 0 0 0 0 0 0 0\r\n 0 0 0 1 0 0 0 0 0 1 0 1 0 \r\n 0 0 0 0 1 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 1 1 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 1 0 0 0 0 0 0 0\r\n 0 0 0 1 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 1 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isStraight(hm),y_correct))\r\n\r\n%%\r\nhm = [0 1 1 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 1 0 0 0 0 0 0 0\r\n 0 1 0 1 0 0 0 0 0 1 0 1 0 \r\n 0 0 0 0 1 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 1 1 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 1 0 0 0 0 0 0 0\r\n 0 0 0 1 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 1 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isStraight(hm),y_correct))\r\n\r\n%%\r\nhm = [0 1 1 0 0 0 0 0 0 0 0 0 0 \r\n 1 0 0 0 0 1 0 0 0 0 0 0 0\r\n 0 1 0 1 0 0 0 0 0 1 0 1 0 \r\n 0 0 0 0 1 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 1 1 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 1 0 0 0 0 0 0 0\r\n 0 0 0 1 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 1 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isStraight(hm),y_correct))\r\n\r\n%%\r\nhm = [0 1 1 0 0 0 0 0 0 0 1 0 0 \r\n 0 0 0 0 0 1 0 0 0 0 0 0 1\r\n 0 1 0 1 0 0 0 0 0 1 0 1 0 \r\n 1 0 0 0 1 0 0 0 0 0 0 0 1];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 1 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 1\r\n 0 0 0 0 0 0 0 0 0 1 0 1 0 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isStraight(hm),y_correct))","published":true,"deleted":false,"likes_count":1,"comments_count":3,"created_by":240,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":62,"test_suite_updated_at":"2012-02-21T19:24:51.000Z","rescore_all_solutions":false,"group_id":15,"created_at":"2012-02-21T19:24:51.000Z","updated_at":"2026-02-15T05:51:00.000Z","published_at":"2012-02-21T19:50:10.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e--------\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA straight is 5 cards of the adjacent ranks (columns) regardless of suits (rows). The Ace (first column) is both lowest and highest. The columns represent A, 2, 3, ... K. This means A, K, Q, J, Ten is a straight also.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 0 0 1 0 0 0 0 0 0 0 0 \\n0 0 1 0 0 0 0 0 0 0 0 0 0\\n0 0 0 1 0 0 0 0 0 0 0 0 0 \\n0 0 0 0 0 1 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003erepresents a straight, so the return value from the function is TRUE.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix does not:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 1 0 1 1 0 0 0 0 0 0 0 \\n0 0 0 0 0 0 0 0 0 0 0 0 0\\n0 0 0 0 0 0 0 0 0 1 0 0 0 \\n0 0 0 0 0 0 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eso the return value should be FALSE.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix does represent a straight\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 0 0 0 0 0 0 0 0 1 0 0 1 \\n0 0 0 0 0 0 0 0 0 0 1 0 0\\n0 0 1 0 0 0 0 0 0 0 0 0 0 \\n1 0 0 0 0 1 0 0 0 0 0 1 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eRemember, hand matrices can contain any number of 1's from 0 to 52.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 0 0 0 0 1 0 0 0 0 0 0 0 \\n0 0 0 0 1 0 1 0 0 0 0 0 0\\n0 0 0 1 0 0 0 0 0 0 0 0 0 \\n0 0 1 0 0 0 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWould be TRUE for this function.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand matrix, but it only shows the cards used to make the straight. If more than one straight can be made, return the higher ranking one (the one with the highest top card. Ace being the highest). If different suits are possible for the same straight cards, return the one higher up in the matrix. If the straight happens to also be a straight flush, it still meets the defintion and should be returned. The highest straight should be returned, even if a straight flush can also be made.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":335,"title":"Poker Series 04: isFlush","description":"The Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\r\n\r\nA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\r\n\r\nFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\r\n\r\n--------\r\n\r\nA flush is 5 cards of the same suit (row). If there are more than five cards in a suit to choose from, the highest five count. The Ace (first column) is the highest. The columns represent A, 2, 3, ... K.\r\n\r\nThis hand matrix:\r\n\r\n 0 1 1 0 1 1 0 0 0 0 0 1 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n\r\nrepresents a flush, so the return value from the function is TRUE.\r\n\r\nThis hand matrix does not:\r\n\r\n 0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n 0 0 0 1 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n\r\nso the return value should be FALSE.\r\n\r\nThis hand matrix does represent a flush\r\n\r\n 1 0 0 0 0 0 0 0 0 1 1 1 1 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 1 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 1 0 0 0 0 0 0 0\r\n\r\nRemember, hand matrices can contain any number of 1's from 0 to 52.\r\n\r\n 0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n 0 0 0 0 1 0 1 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 1 0 0 0 0 0 0 0 0 0 0 \r\n\r\nWould be FALSE for this function.\r\n\r\nA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand matrix, but it only shows the cards used to make the flush. If more than one flush can be made, return the higher ranking one (the one with the highest top card. Ace being the highest- ties broken by the second, third, fourth, and then fifth card). If different suits are possible for the same flush, return the one higher up in the matrix. If the flush happens to also be a straight flush, it still meets the defintion and should be returned. The highest flush should be returned, even if a straight flush can also be made.","description_html":"\u003cp\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/p\u003e\u003cp\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/p\u003e\u003cp\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/p\u003e\u003cp\u003e--------\u003c/p\u003e\u003cp\u003eA flush is 5 cards of the same suit (row). If there are more than five cards in a suit to choose from, the highest five count. The Ace (first column) is the highest. The columns represent A, 2, 3, ... K.\u003c/p\u003e\u003cp\u003eThis hand matrix:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 1 0 1 1 0 0 0 0 0 1 0 \r\n0 0 0 0 0 0 0 0 0 0 0 0 0\r\n0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n0 0 0 0 0 0 0 0 0 0 0 0 0\r\n\u003c/pre\u003e\u003cp\u003erepresents a flush, so the return value from the function is TRUE.\u003c/p\u003e\u003cp\u003eThis hand matrix does not:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n0 0 0 1 0 0 0 0 0 0 0 0 0\r\n0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n0 0 0 0 0 0 0 0 0 0 0 0 0\r\n\u003c/pre\u003e\u003cp\u003eso the return value should be FALSE.\u003c/p\u003e\u003cp\u003eThis hand matrix does represent a flush\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e1 0 0 0 0 0 0 0 0 1 1 1 1 \r\n0 0 0 0 0 0 0 0 0 0 0 0 0\r\n0 0 1 0 0 0 0 0 0 0 0 0 0 \r\n0 0 0 0 0 1 0 0 0 0 0 0 0\r\n\u003c/pre\u003e\u003cp\u003eRemember, hand matrices can contain any number of 1's from 0 to 52.\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n0 0 0 0 1 0 1 0 0 0 0 0 0\r\n0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n0 0 1 0 0 0 0 0 0 0 0 0 0 \r\n\u003c/pre\u003e\u003cp\u003eWould be FALSE for this function.\u003c/p\u003e\u003cp\u003eA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand matrix, but it only shows the cards used to make the flush. If more than one flush can be made, return the higher ranking one (the one with the highest top card. Ace being the highest- ties broken by the second, third, fourth, and then fifth card). If different suits are possible for the same flush, return the one higher up in the matrix. If the flush happens to also be a straight flush, it still meets the defintion and should be returned. The highest flush should be returned, even if a straight flush can also be made.\u003c/p\u003e","function_template":"function out = isFlush(hm)\r\n out.flag = false;\r\n out.usedCards = false(4,13);\r\nend","test_suite":"%%\r\nhm = [0 1 0 0 0 0 0 0 1 1 0 1 1 \r\n 0 1 0 0 0 0 0 0 1 0 0 1 0\r\n 0 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 1 0 0 0 0 0 0 1 1 0 1 1 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isFlush(hm),y_correct))\r\n\r\n%%\r\nhm = [1 1 0 0 0 0 0 0 1 1 0 1 1 \r\n 0 1 0 0 0 0 0 0 1 0 0 1 0\r\n 0 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([1 0 0 0 0 0 0 0 1 1 0 1 1 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isFlush(hm),y_correct))\r\n\r\n%%\r\nhm = [1 1 0 0 0 0 0 0 1 1 0 1 0 \r\n 0 1 0 0 0 0 0 0 1 0 0 1 0\r\n 1 1 0 1 0 0 0 0 1 1 1 1 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 1 0 0 0 0 0 0 0 1 1 1 1 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isFlush(hm),y_correct))\r\n\r\n%%\r\nhm = [1 1 0 0 0 0 0 0 1 1 0 1 0 \r\n 0 1 0 0 0 0 0 0 1 0 0 1 0\r\n 1 1 0 1 0 0 0 0 1 1 1 1 0 \r\n 1 0 0 0 0 0 0 0 1 1 1 1 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 1 0 0 0 0 0 0 0 1 1 1 1 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isFlush(hm),y_correct))\r\n\r\n%%\r\nhm = [1 1 0 0 0 0 0 0 0 0 0 1 0 \r\n 0 1 0 0 0 0 0 0 1 0 0 1 0\r\n 0 0 0 0 0 0 0 0 1 0 1 1 0 \r\n 1 0 0 0 0 0 0 0 1 1 0 1 0];\r\n\r\ny_correct.flag = false;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isFlush(hm),y_correct))","published":true,"deleted":false,"likes_count":1,"comments_count":3,"created_by":240,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":69,"test_suite_updated_at":"2012-02-21T19:24:06.000Z","rescore_all_solutions":false,"group_id":15,"created_at":"2012-02-17T21:55:47.000Z","updated_at":"2026-04-02T20:50:40.000Z","published_at":"2012-02-21T19:24:06.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e--------\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA flush is 5 cards of the same suit (row). If there are more than five cards in a suit to choose from, the highest five count. The Ace (first column) is the highest. The columns represent A, 2, 3, ... K.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 1 0 1 1 0 0 0 0 0 1 0 \\n0 0 0 0 0 0 0 0 0 0 0 0 0\\n0 0 0 0 0 0 0 0 0 0 0 0 0 \\n0 0 0 0 0 0 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003erepresents a flush, so the return value from the function is TRUE.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix does not:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 1 0 1 1 0 0 0 0 0 0 0 \\n0 0 0 1 0 0 0 0 0 0 0 0 0\\n0 0 0 0 0 0 0 0 0 0 0 0 0 \\n0 0 0 0 0 0 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eso the return value should be FALSE.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix does represent a flush\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[1 0 0 0 0 0 0 0 0 1 1 1 1 \\n0 0 0 0 0 0 0 0 0 0 0 0 0\\n0 0 1 0 0 0 0 0 0 0 0 0 0 \\n0 0 0 0 0 1 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eRemember, hand matrices can contain any number of 1's from 0 to 52.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 1 0 1 1 0 0 0 0 0 0 0 \\n0 0 0 0 1 0 1 0 0 0 0 0 0\\n0 0 0 0 0 0 0 0 0 0 0 0 0 \\n0 0 1 0 0 0 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWould be FALSE for this function.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand matrix, but it only shows the cards used to make the flush. If more than one flush can be made, return the higher ranking one (the one with the highest top card. Ace being the highest- ties broken by the second, third, fourth, and then fifth card). If different suits are possible for the same flush, return the one higher up in the matrix. If the flush happens to also be a straight flush, it still meets the defintion and should be returned. The highest flush should be returned, even if a straight flush can also be made.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":329,"title":"Poker Series 01: isStraightFlush","description":"The Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\r\nA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\r\nFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\r\n--------\r\nA straight flush is 5 cards of the same suit (row) and five continuous ranks (columns). The Ace (first column) can also make a straight flush when combined with the last four columns. The columns represent A, 2, 3, ... K.\r\nThis hand matrix:\r\n0 1 1 1 1 1 0 0 0 0 0 0 0 \r\n0 0 0 0 0 0 0 0 0 0 0 0 0\r\n0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n0 0 0 0 0 0 0 0 0 0 0 0 0\r\nrepresents a straight flush, so the return value from the function is TRUE.\r\nThis hand matrix does not:\r\n0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n0 0 0 1 0 0 0 0 0 0 0 0 0\r\n0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n0 0 0 0 0 0 0 0 0 0 0 0 0\r\nso the return value should be FALSE.\r\nThis hand matrix does represent a straight flush\r\n1 0 0 0 0 0 0 0 0 1 1 1 1 \r\n0 0 0 0 0 0 0 0 0 0 0 0 0\r\n0 0 1 0 0 0 0 0 0 0 0 0 0 \r\n0 0 0 0 0 1 0 0 0 0 0 0 0\r\nRemember, hand matrices can contain any number of 1's from 0 to 52.\r\n0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n0 0 0 0 1 0 1 0 0 0 0 0 0\r\n0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n0 0 1 0 0 0 0 0 0 0 0 0 0\r\nWould be FALSE for this function.\r\nA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand Matrix, but it only shows the cards used to make the Straight Flush. If more than one straight flush can be made, return the higher ranking one (the one with the highest top card. Ace being the highest). If different suits are possible for the same straight flush, return the one higher up in the matrix.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 940.933px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 470.467px; transform-origin: 407px 470.467px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 373px 8px; transform-origin: 373px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 31.5px; text-align: left; transform-origin: 384px 31.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 373px 8px; transform-origin: 373px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 31.5px; text-align: left; transform-origin: 384px 31.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 384px 8px; transform-origin: 384px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 20px 8px; transform-origin: 20px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e--------\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 369.5px 8px; transform-origin: 369.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eA straight flush is 5 cards of the same suit (row) and five continuous ranks (columns). The Ace (first column) can also make a straight flush when combined with the last four columns. The columns represent A, 2, 3, ... K.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 54px 8px; transform-origin: 54px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThis hand matrix:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 81.7333px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-end-end-radius: 4px; border-end-start-radius: 4px; border-start-end-radius: 4px; border-start-start-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 404px 40.8667px; transform-origin: 404px 40.8667px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 104px 8.5px; tab-size: 4; transform-origin: 104px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e0 1 1 1 1 1 0 0 0 0 0 0 0 \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 100px 8.5px; tab-size: 4; transform-origin: 100px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e0 0 0 0 0 0 0 0 0 0 0 0 0\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 104px 8.5px; tab-size: 4; transform-origin: 104px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e0 0 0 0 0 0 0 0 0 0 0 0 0 \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 100px 8.5px; tab-size: 4; transform-origin: 100px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e0 0 0 0 0 0 0 0 0 0 0 0 0\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 10px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 10px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 10px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 230.5px 8px; transform-origin: 230.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003erepresents a straight flush, so the return value from the function is TRUE.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 83.5px 8px; transform-origin: 83.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThis hand matrix does not:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 81.7333px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-end-end-radius: 4px; border-end-start-radius: 4px; border-start-end-radius: 4px; border-start-start-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 404px 40.8667px; transform-origin: 404px 40.8667px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 104px 8.5px; tab-size: 4; transform-origin: 104px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e0 1 1 0 1 1 0 0 0 0 0 0 0 \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 100px 8.5px; tab-size: 4; transform-origin: 100px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e0 0 0 1 0 0 0 0 0 0 0 0 0\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 104px 8.5px; tab-size: 4; transform-origin: 104px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e0 0 0 0 0 0 0 0 0 0 0 0 0 \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 100px 8.5px; tab-size: 4; transform-origin: 100px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e0 0 0 0 0 0 0 0 0 0 0 0 0\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 10px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 10px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 10px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 118px 8px; transform-origin: 118px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eso the return value should be FALSE.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 150.5px 8px; transform-origin: 150.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThis hand matrix does represent a straight flush\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 81.7333px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-end-end-radius: 4px; border-end-start-radius: 4px; border-start-end-radius: 4px; border-start-start-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 404px 40.8667px; transform-origin: 404px 40.8667px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 104px 8.5px; tab-size: 4; transform-origin: 104px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e1 0 0 0 0 0 0 0 0 1 1 1 1 \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 100px 8.5px; tab-size: 4; transform-origin: 100px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e0 0 0 0 0 0 0 0 0 0 0 0 0\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 104px 8.5px; tab-size: 4; transform-origin: 104px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e0 0 1 0 0 0 0 0 0 0 0 0 0 \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 100px 8.5px; tab-size: 4; transform-origin: 100px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e0 0 0 0 0 1 0 0 0 0 0 0 0\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 10px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 10px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 10px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 221.5px 8px; transform-origin: 221.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eRemember, hand matrices can contain any number of 1's from 0 to 52.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 81.7333px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-end-end-radius: 4px; border-end-start-radius: 4px; border-start-end-radius: 4px; border-start-start-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 404px 40.8667px; transform-origin: 404px 40.8667px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 104px 8.5px; tab-size: 4; transform-origin: 104px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e0 1 1 0 1 1 0 0 0 0 0 0 0 \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 100px 8.5px; tab-size: 4; transform-origin: 100px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e0 0 0 0 1 0 1 0 0 0 0 0 0\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 104px 8.5px; tab-size: 4; transform-origin: 104px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e0 0 0 0 0 0 0 0 0 0 0 0 0 \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 100px 8.5px; tab-size: 4; transform-origin: 100px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e0 0 1 0 0 0 0 0 0 0 0 0 0\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 10px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 10px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 10px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 106px 8px; transform-origin: 106px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eWould be FALSE for this function.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 84px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 42px; text-align: left; transform-origin: 384px 42px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 370px 8px; transform-origin: 370px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand Matrix, but it only shows the cards used to make the Straight Flush. If more than one straight flush can be made, return the higher ranking one (the one with the highest top card. Ace being the highest). If different suits are possible for the same straight flush, return the one higher up in the matrix.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function out = isStraightFlush(hm)\r\n out.flag = false;\r\n out.usedCards = false(4,13);\r\nend","test_suite":"%%\r\nhm = [0 0 0 0 0 0 0 0 1 1 1 1 1 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 1 1 1 1 1 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\nassert(isequal(isStraightFlush(hm),y_correct))\r\n\r\n%%\r\nhm = [0 0 0 0 0 0 0 0 1 1 0 1 1 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 1 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = false;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\nassert(isequal(isStraightFlush(hm),y_correct))\r\n\r\n%%\r\nhm = [0 0 0 0 0 0 0 0 1 1 0 1 1 \r\n 1 0 0 0 0 0 0 0 0 1 1 1 1\r\n 0 1 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 1 1 1 1\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\nassert(isequal(isStraightFlush(hm),y_correct))\r\n\r\n%%\r\nhm = [0 0 0 0 0 0 0 0 1 1 0 1 1 \r\n 1 0 0 0 0 0 0 0 0 1 1 1 1\r\n 1 1 0 0 0 0 0 0 0 1 1 1 1 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 1 1 1 1\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\nassert(isequal(isStraightFlush(hm),y_correct))","published":true,"deleted":false,"likes_count":3,"comments_count":8,"created_by":240,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":124,"test_suite_updated_at":"2021-09-27T06:47:34.000Z","rescore_all_solutions":false,"group_id":15,"created_at":"2012-02-16T20:30:55.000Z","updated_at":"2026-04-02T20:19:31.000Z","published_at":"2012-02-17T18:24:19.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e--------\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA straight flush is 5 cards of the same suit (row) and five continuous ranks (columns). The Ace (first column) can also make a straight flush when combined with the last four columns. The columns represent A, 2, 3, ... K.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 1 1 1 1 0 0 0 0 0 0 0 \\n0 0 0 0 0 0 0 0 0 0 0 0 0\\n0 0 0 0 0 0 0 0 0 0 0 0 0 \\n0 0 0 0 0 0 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003erepresents a straight flush, so the return value from the function is TRUE.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix does not:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 1 0 1 1 0 0 0 0 0 0 0 \\n0 0 0 1 0 0 0 0 0 0 0 0 0\\n0 0 0 0 0 0 0 0 0 0 0 0 0 \\n0 0 0 0 0 0 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eso the return value should be FALSE.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix does represent a straight flush\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[1 0 0 0 0 0 0 0 0 1 1 1 1 \\n0 0 0 0 0 0 0 0 0 0 0 0 0\\n0 0 1 0 0 0 0 0 0 0 0 0 0 \\n0 0 0 0 0 1 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eRemember, hand matrices can contain any number of 1's from 0 to 52.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 1 0 1 1 0 0 0 0 0 0 0 \\n0 0 0 0 1 0 1 0 0 0 0 0 0\\n0 0 0 0 0 0 0 0 0 0 0 0 0 \\n0 0 1 0 0 0 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWould be FALSE for this function.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand Matrix, but it only shows the cards used to make the Straight Flush. If more than one straight flush can be made, return the higher ranking one (the one with the highest top card. Ace being the highest). If different suits are possible for the same straight flush, return the one higher up in the matrix.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":377,"title":"Poker Series 06: isThreeKind","description":"The Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\r\n\r\nA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\r\n\r\nFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\r\n\r\n--------\r\n\r\nA three of a kind is 3 cards of the same rank (column). The Ace (first column) is highest. The columns represent A, 2, 3, ... K. The next two highest cards are the kickers. If the kickers also form a pair, it is still considered three of a kind for the purposes of this function.\r\n\r\nThis hand matrix:\r\n\r\n 0 1 0 0 1 0 0 0 0 0 0 0 0 \r\n 0 0 1 0 0 0 0 0 0 0 0 0 0\r\n 0 1 0 1 0 0 0 0 0 0 0 0 0 \r\n 0 1 0 0 0 1 0 0 0 0 0 0 0\r\n\r\nrepresents a three of a kind, so the return value from the function is TRUE.\r\n\r\nThis hand matrix does not:\r\n\r\n 0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 1 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n\r\nso the return value should be FALSE.\r\n\r\nThis hand matrix does represent a three of a kind\r\n\r\n 0 0 0 0 0 0 0 0 0 1 0 0 1 \r\n 0 0 0 0 0 0 0 0 0 0 1 0 0\r\n 0 0 0 0 0 0 0 0 0 1 0 0 0 \r\n 0 0 0 0 0 1 0 0 0 1 0 1 0\r\n\r\nRemember, hand matrices can contain any number of 1's from 0 to 52.\r\n\r\n 0 0 0 0 0 1 0 0 0 0 0 0 0 \r\n 0 0 0 0 1 1 1 0 0 0 0 0 1\r\n 0 0 0 1 0 1 0 0 0 1 0 0 0 \r\n 0 0 1 0 0 0 0 0 0 0 0 1 0 \r\n\r\nWould be TRUE for this function.\r\n\r\nA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand matrix, but it only shows the cards used to make the three of a kind. If more than one three of a kind can be made, return the higher ranking one (the one with the highest rank. Ace being the highest). If different suits are possible for the same three of a kind cards, return the one higher up in the matrix, same for kickers. If the three of a kind happens to also be a four of a kind or full house, it still meets the defintion and should be returned.","description_html":"\u003cp\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/p\u003e\u003cp\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/p\u003e\u003cp\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/p\u003e\u003cp\u003e--------\u003c/p\u003e\u003cp\u003eA three of a kind is 3 cards of the same rank (column). The Ace (first column) is highest. The columns represent A, 2, 3, ... K. The next two highest cards are the kickers. If the kickers also form a pair, it is still considered three of a kind for the purposes of this function.\u003c/p\u003e\u003cp\u003eThis hand matrix:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 0 0 1 0 0 0 0 0 0 0 0 \r\n0 0 1 0 0 0 0 0 0 0 0 0 0\r\n0 1 0 1 0 0 0 0 0 0 0 0 0 \r\n0 1 0 0 0 1 0 0 0 0 0 0 0\r\n\u003c/pre\u003e\u003cp\u003erepresents a three of a kind, so the return value from the function is TRUE.\u003c/p\u003e\u003cp\u003eThis hand matrix does not:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n0 0 0 0 0 0 0 0 0 0 0 0 0\r\n0 0 0 0 0 0 0 0 0 1 0 0 0 \r\n0 0 0 0 0 0 0 0 0 0 0 0 0\r\n\u003c/pre\u003e\u003cp\u003eso the return value should be FALSE.\u003c/p\u003e\u003cp\u003eThis hand matrix does represent a three of a kind\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 0 0 0 0 0 0 0 0 1 0 0 1 \r\n0 0 0 0 0 0 0 0 0 0 1 0 0\r\n0 0 0 0 0 0 0 0 0 1 0 0 0 \r\n0 0 0 0 0 1 0 0 0 1 0 1 0\r\n\u003c/pre\u003e\u003cp\u003eRemember, hand matrices can contain any number of 1's from 0 to 52.\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 0 0 0 0 1 0 0 0 0 0 0 0 \r\n0 0 0 0 1 1 1 0 0 0 0 0 1\r\n0 0 0 1 0 1 0 0 0 1 0 0 0 \r\n0 0 1 0 0 0 0 0 0 0 0 1 0 \r\n\u003c/pre\u003e\u003cp\u003eWould be TRUE for this function.\u003c/p\u003e\u003cp\u003eA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand matrix, but it only shows the cards used to make the three of a kind. If more than one three of a kind can be made, return the higher ranking one (the one with the highest rank. Ace being the highest). If different suits are possible for the same three of a kind cards, return the one higher up in the matrix, same for kickers. If the three of a kind happens to also be a four of a kind or full house, it still meets the defintion and should be returned.\u003c/p\u003e","function_template":"function out = isThreeKind(hm)\r\n out.flag = false;\r\n out.usedCards = false(4,13);\r\nend","test_suite":"%%\r\nhm = [0 1 0 0 0 0 0 0 1 1 0 1 1 \r\n 0 1 0 0 0 0 0 0 1 0 0 1 0\r\n 0 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 1 0 0 1 1 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0\r\n 0 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isThreeKind(hm),y_correct))\r\n\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 1 1 0 1 1 \r\n 0 1 0 0 0 0 0 0 1 0 0 0 0\r\n 1 0 0 1 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 1 0 0 0 1 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0\r\n 1 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0])\r\n \r\nassert(isequal(isThreeKind(hm),y_correct))\r\n\r\n%%\r\nhm = [1 1 0 0 0 0 0 0 1 1 0 0 1 \r\n 0 1 0 0 0 0 0 0 1 0 0 1 0\r\n 1 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([1 0 0 0 0 0 0 0 0 0 0 0 1 \r\n 0 0 0 0 0 0 0 0 0 0 0 1 0\r\n 1 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isThreeKind(hm),y_correct))\r\n\r\n%%\r\nhm = [1 1 0 0 0 0 0 0 1 1 0 0 1 \r\n 0 1 0 0 0 0 0 0 1 0 0 1 0\r\n 1 0 0 1 0 0 0 0 1 0 0 0 1 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 1];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([1 0 0 0 0 0 0 0 0 0 0 0 1 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 1 0 0 0 0 0 0 0 0 0 0 0 1 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isThreeKind(hm),y_correct))\r\n\r\n%%\r\nhm = [1 1 0 0 0 0 0 0 1 1 0 0 1 \r\n 0 1 0 0 0 0 0 0 0 0 0 1 0\r\n 1 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = false;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isThreeKind(hm),y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":240,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":56,"test_suite_updated_at":"2012-02-21T21:50:59.000Z","rescore_all_solutions":false,"group_id":15,"created_at":"2012-02-21T21:17:05.000Z","updated_at":"2026-02-15T05:49:06.000Z","published_at":"2012-02-22T17:26:53.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e--------\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA three of a kind is 3 cards of the same rank (column). The Ace (first column) is highest. The columns represent A, 2, 3, ... K. The next two highest cards are the kickers. If the kickers also form a pair, it is still considered three of a kind for the purposes of this function.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 0 0 1 0 0 0 0 0 0 0 0 \\n0 0 1 0 0 0 0 0 0 0 0 0 0\\n0 1 0 1 0 0 0 0 0 0 0 0 0 \\n0 1 0 0 0 1 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003erepresents a three of a kind, so the return value from the function is TRUE.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix does not:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 1 0 1 1 0 0 0 0 0 0 0 \\n0 0 0 0 0 0 0 0 0 0 0 0 0\\n0 0 0 0 0 0 0 0 0 1 0 0 0 \\n0 0 0 0 0 0 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eso the return value should be FALSE.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix does represent a three of a kind\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 0 0 0 0 0 0 0 0 1 0 0 1 \\n0 0 0 0 0 0 0 0 0 0 1 0 0\\n0 0 0 0 0 0 0 0 0 1 0 0 0 \\n0 0 0 0 0 1 0 0 0 1 0 1 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eRemember, hand matrices can contain any number of 1's from 0 to 52.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 0 0 0 0 1 0 0 0 0 0 0 0 \\n0 0 0 0 1 1 1 0 0 0 0 0 1\\n0 0 0 1 0 1 0 0 0 1 0 0 0 \\n0 0 1 0 0 0 0 0 0 0 0 1 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWould be TRUE for this function.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand matrix, but it only shows the cards used to make the three of a kind. If more than one three of a kind can be made, return the higher ranking one (the one with the highest rank. Ace being the highest). If different suits are possible for the same three of a kind cards, return the one higher up in the matrix, same for kickers. If the three of a kind happens to also be a four of a kind or full house, it still meets the defintion and should be returned.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":334,"title":"Poker Series 03: isFullHouse","description":"The Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\r\n\r\nA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\r\n\r\nFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\r\n\r\n--------\r\n\r\nA full house is three cards of one rank (column) and two cards of a different rank. The Ace (first column) is the highest rank. The columns represent A, 2, 3, ... K. When there is a choice between two possible three of a kind, choose the higher. Once a three of a kind is choosen, choose the highest possible pair.\r\n\r\nThis hand matrix:\r\n\r\n 0 1 0 0 0 0 0 1 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 1 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 1 0 0 0 0 0 1 0 0 0 0 0\r\n\r\nrepresents a full house, so the return value from the function is TRUE.\r\n\r\nThis hand matrix does not:\r\n\r\n 0 1 1 0 1 0 0 0 0 0 0 0 0 \r\n 0 0 0 1 0 0 0 0 0 0 0 0 0\r\n 0 0 0 1 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 1 0 0 0 0 0 0 0 0 0\r\n\r\nso the return value should be FALSE.\r\n\r\nThis hand matrix does represent a full house\r\n\r\n 1 0 1 0 0 0 0 0 0 0 1 0 1 \r\n 0 0 1 0 0 1 0 0 0 0 0 0 0\r\n 0 0 1 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 1 0 0 0 0 0 0 0\r\n\r\nRemember, hand matrices can contain any number of 1's from 0 to 52.\r\n\r\n 0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n 0 0 0 0 1 0 1 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 1 0 0 0 0 0 0 0 0 0 0 \r\n\r\nWould be FALSE for this function.\r\n\r\nA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand Matrix, but it only shows the cards used to make the full house. If more than one full house can be made, return the higher ranking one (the one with the highest ranking three of a kind. Ace being the highest. Ties are broken with the highest ranking pair). If different suits are possible for the same full house, return the ones higher up in the matrix.","description_html":"\u003cp\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/p\u003e\u003cp\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/p\u003e\u003cp\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/p\u003e\u003cp\u003e--------\u003c/p\u003e\u003cp\u003eA full house is three cards of one rank (column) and two cards of a different rank. The Ace (first column) is the highest rank. The columns represent A, 2, 3, ... K. When there is a choice between two possible three of a kind, choose the higher. Once a three of a kind is choosen, choose the highest possible pair.\u003c/p\u003e\u003cp\u003eThis hand matrix:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 0 0 0 0 0 1 0 0 0 0 0 \r\n0 0 0 0 0 0 0 0 0 0 0 0 0\r\n0 1 0 0 0 0 0 0 0 0 0 0 0 \r\n0 1 0 0 0 0 0 1 0 0 0 0 0\r\n\u003c/pre\u003e\u003cp\u003erepresents a full house, so the return value from the function is TRUE.\u003c/p\u003e\u003cp\u003eThis hand matrix does not:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 1 0 1 0 0 0 0 0 0 0 0 \r\n0 0 0 1 0 0 0 0 0 0 0 0 0\r\n0 0 0 1 0 0 0 0 0 0 0 0 0 \r\n0 0 0 1 0 0 0 0 0 0 0 0 0\r\n\u003c/pre\u003e\u003cp\u003eso the return value should be FALSE.\u003c/p\u003e\u003cp\u003eThis hand matrix does represent a full house\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e1 0 1 0 0 0 0 0 0 0 1 0 1 \r\n0 0 1 0 0 1 0 0 0 0 0 0 0\r\n0 0 1 0 0 0 0 0 0 0 0 0 0 \r\n0 0 0 0 0 1 0 0 0 0 0 0 0\r\n\u003c/pre\u003e\u003cp\u003eRemember, hand matrices can contain any number of 1's from 0 to 52.\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n0 0 0 0 1 0 1 0 0 0 0 0 0\r\n0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n0 0 1 0 0 0 0 0 0 0 0 0 0 \r\n\u003c/pre\u003e\u003cp\u003eWould be FALSE for this function.\u003c/p\u003e\u003cp\u003eA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand Matrix, but it only shows the cards used to make the full house. If more than one full house can be made, return the higher ranking one (the one with the highest ranking three of a kind. Ace being the highest. Ties are broken with the highest ranking pair). If different suits are possible for the same full house, return the ones higher up in the matrix.\u003c/p\u003e","function_template":"function out = isFullHouse(hm)\r\n out.flag = false;\r\n out.usedCards = false(4,13);\r\nend","test_suite":"%%\r\nhm = [0 0 0 0 0 0 0 0 1 1 0 1 1 \r\n 0 1 0 0 0 0 0 0 1 0 0 1 0\r\n 0 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 1 0 0 1 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 1 0\r\n 0 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\nassert(isequal(isFullHouse(hm),y_correct))\r\n%%\r\nhm = [0 0 0 0 0 0 0 0 1 1 0 1 1 \r\n 0 1 0 0 0 0 0 0 1 0 0 1 0\r\n 0 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 1 0 0 1 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 1 0\r\n 0 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\nassert(isequal(isFullHouse(hm),y_correct))\r\n\r\n%%\r\nhm = [0 0 0 0 1 0 0 0 1 1 0 1 1 \r\n 0 1 0 0 1 0 0 0 0 0 0 1 0\r\n 0 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 1 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 1 0 0 0 0 0 0 1 0 \r\n 0 0 0 0 1 0 0 0 0 0 0 1 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 1 0 0 0 0 0 0 0 0])\r\nassert(isequal(isFullHouse(hm),y_correct))\r\n\r\n%%\r\nhm = [0 0 0 0 1 0 0 0 1 1 0 1 1 \r\n 1 1 0 0 1 0 0 0 0 0 0 0 0\r\n 1 0 0 1 1 0 0 0 0 0 0 0 0 \r\n 1 1 0 0 1 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 1 0 0 0 0 0 0 0 0 \r\n 1 0 0 0 1 0 0 0 0 0 0 0 0\r\n 1 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 0])\r\nassert(isequal(isFullHouse(hm),y_correct))\r\n%%\r\nhm = [0 0 0 0 0 0 0 0 1 1 0 1 1 \r\n 0 1 0 0 0 0 0 0 1 0 0 0 0\r\n 0 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0];\r\n\r\ny_correct.flag = false;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\nassert(isequal(isFullHouse(hm),y_correct))\r\n\r\n%%\r\nhm = [0 0 0 0 0 0 0 0 1 1 0 1 1 \r\n 1 1 0 0 0 1 0 0 0 0 0 1 0\r\n 0 0 0 1 0 1 0 0 1 0 0 0 0 \r\n 1 0 0 0 0 1 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 1 0 0 0 0 1 0 0 0 0 0 0 0\r\n 0 0 0 0 0 1 0 0 0 0 0 0 0 \r\n 1 0 0 0 0 1 0 0 0 0 0 0 0])\r\nassert(isequal(isFullHouse(hm),y_correct))","published":true,"deleted":false,"likes_count":1,"comments_count":1,"created_by":240,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":71,"test_suite_updated_at":"2012-02-17T21:20:39.000Z","rescore_all_solutions":false,"group_id":15,"created_at":"2012-02-17T21:20:39.000Z","updated_at":"2026-04-02T20:43:08.000Z","published_at":"2012-02-17T21:54:57.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e--------\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA full house is three cards of one rank (column) and two cards of a different rank. The Ace (first column) is the highest rank. The columns represent A, 2, 3, ... K. When there is a choice between two possible three of a kind, choose the higher. Once a three of a kind is choosen, choose the highest possible pair.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 0 0 0 0 0 1 0 0 0 0 0 \\n0 0 0 0 0 0 0 0 0 0 0 0 0\\n0 1 0 0 0 0 0 0 0 0 0 0 0 \\n0 1 0 0 0 0 0 1 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003erepresents a full house, so the return value from the function is TRUE.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix does not:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 1 0 1 0 0 0 0 0 0 0 0 \\n0 0 0 1 0 0 0 0 0 0 0 0 0\\n0 0 0 1 0 0 0 0 0 0 0 0 0 \\n0 0 0 1 0 0 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eso the return value should be FALSE.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix does represent a full house\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[1 0 1 0 0 0 0 0 0 0 1 0 1 \\n0 0 1 0 0 1 0 0 0 0 0 0 0\\n0 0 1 0 0 0 0 0 0 0 0 0 0 \\n0 0 0 0 0 1 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eRemember, hand matrices can contain any number of 1's from 0 to 52.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 1 0 1 1 0 0 0 0 0 0 0 \\n0 0 0 0 1 0 1 0 0 0 0 0 0\\n0 0 0 0 0 0 0 0 0 0 0 0 0 \\n0 0 1 0 0 0 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWould be FALSE for this function.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand Matrix, but it only shows the cards used to make the full house. If more than one full house can be made, return the higher ranking one (the one with the highest ranking three of a kind. Ace being the highest. Ties are broken with the highest ranking pair). If different suits are possible for the same full house, return the ones higher up in the matrix.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":333,"title":"Poker Series 02: isQuads","description":"The Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\r\n\r\nA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\r\n\r\nFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\r\n\r\n--------\r\n\r\nFour of a kind is four cards of the same rank (column) and the highest other card as a 'kicker'. The columns represent A, 2, 3, ... K in the input. Aces are high.\r\n\r\nThis hand matrix:\r\n\r\n 0 1 0 0 0 1 0 0 0 0 0 0 0 \r\n 0 1 0 0 0 0 0 0 0 0 0 0 0\r\n 0 1 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 1 0 0 0 0 0 0 0 0 0 0 0\r\nrepresents quads, so the return value from the function is TRUE.\r\n\r\nThis hand matrix does not:\r\n\r\n 0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n 0 0 0 1 0 0 0 0 0 0 0 0 0\r\n 0 0 0 1 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 1 0 0 0 0 0 0 0 0 0\r\nso the return value should be FALSE.\r\n\r\nThis hand matrix does represent quads\r\n\r\n 1 0 0 0 0 0 0 0 0 0 0 0 1 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 0\r\n 1 0 1 0 0 0 0 0 0 1 0 0 0 \r\n 1 0 0 0 0 1 0 0 0 0 0 0 0\r\nRemember, hand matrices can contain any number of 1's from 0 to 52.\r\n\r\n 0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n 0 0 0 0 1 0 1 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 1 0 0 0 0 0 0 0 0 0 0 \r\nWould be FALSE for this function.\r\n\r\nA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand Matrix, but it only shows the cards used to make the Quads plus kicker. If more than one Quads can be made, return the higher ranking one (Ace being the highest). If different suits are possible for the kicker, return the one higher up in the matrix.\r\n\r\n","description_html":"\u003cp\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/p\u003e\u003cp\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/p\u003e\u003cp\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/p\u003e\u003cp\u003e--------\u003c/p\u003e\u003cp\u003eFour of a kind is four cards of the same rank (column) and the highest other card as a 'kicker'. The columns represent A, 2, 3, ... K in the input. Aces are high.\u003c/p\u003e\u003cp\u003eThis hand matrix:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 0 0 0 1 0 0 0 0 0 0 0 \r\n0 1 0 0 0 0 0 0 0 0 0 0 0\r\n0 1 0 0 0 0 0 0 0 0 0 0 0 \r\n0 1 0 0 0 0 0 0 0 0 0 0 0\r\nrepresents quads, so the return value from the function is TRUE.\r\n\u003c/pre\u003e\u003cp\u003eThis hand matrix does not:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n0 0 0 1 0 0 0 0 0 0 0 0 0\r\n0 0 0 1 0 0 0 0 0 0 0 0 0 \r\n0 0 0 1 0 0 0 0 0 0 0 0 0\r\nso the return value should be FALSE.\r\n\u003c/pre\u003e\u003cp\u003eThis hand matrix does represent quads\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e1 0 0 0 0 0 0 0 0 0 0 0 1 \r\n1 0 0 0 0 0 0 0 0 0 0 0 0\r\n1 0 1 0 0 0 0 0 0 1 0 0 0 \r\n1 0 0 0 0 1 0 0 0 0 0 0 0\r\nRemember, hand matrices can contain any number of 1's from 0 to 52.\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003e0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n0 0 0 0 1 0 1 0 0 0 0 0 0\r\n0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n0 0 1 0 0 0 0 0 0 0 0 0 0 \r\nWould be FALSE for this function.\r\n\u003c/pre\u003e\u003cp\u003eA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand Matrix, but it only shows the cards used to make the Quads plus kicker. If more than one Quads can be made, return the higher ranking one (Ace being the highest). If different suits are possible for the kicker, return the one higher up in the matrix.\u003c/p\u003e","function_template":"function out = isQuads(hm)\r\n out.flag = false;\r\n out.usedCards = false(4,13)\r\nend","test_suite":"%%\r\nhm = [0 0 0 0 0 0 0 0 1 1 0 1 1 \r\n 0 1 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = false;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\nassert(isequal(isQuads(hm),y_correct))\r\n\r\n%%\r\nhm = [0 0 0 0 0 0 0 0 1 0 0 0 1 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0\r\n 0 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 1 0 0 0 1 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0\r\n 0 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0])\r\nassert(isequal(isQuads(hm),y_correct))\r\n\r\n%%\r\nhm = [0 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0\r\n 0 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0];\r\n\r\ny_correct.flag = false;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\nassert(isequal(isQuads(hm),y_correct))\r\n\r\n%%\r\nhm = [1 0 0 0 0 0 0 0 1 0 0 0 1 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0\r\n 0 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([1 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0\r\n 0 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0])\r\nassert(isequal(isQuads(hm),y_correct))\r\n\r\n%%\r\nhm = [0 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 0 1 0 0 0 0 0 0 1 0 0 0 0\r\n 0 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 0 1 0 0 0 0 0 0 1 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 0 1 0 0 0 0 0 0 1 0 0 0 0\r\n 0 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0])\r\nassert(isequal(isQuads(hm),y_correct))\r\n\r\n%%\r\nhm = [1 0 0 1 0 0 0 0 1 0 0 0 1 \r\n 0 0 0 1 0 0 0 0 1 0 0 0 0\r\n 0 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 1 0 0 0 0 1 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([1 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0\r\n 0 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0])\r\nassert(isequal(isQuads(hm),y_correct))\r\n\r\n%%\r\n hm = [1 0 0 0 0 0 0 1 0 0 0 0 0\r\n 1 0 0 0 0 0 0 1 0 0 0 0 1\r\n 1 0 0 0 0 0 0 1 0 0 0 0 0\r\n 1 0 0 0 0 0 0 1 0 0 0 0 0];\r\n \r\ny_correct.flag = true; \r\ny_correct.usedCards = logical(...\r\n [1 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 1 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 0]);\r\n \r\nassert(isequal(isQuads(hm),y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":3,"created_by":240,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":90,"test_suite_updated_at":"2016-12-13T18:48:26.000Z","rescore_all_solutions":false,"group_id":15,"created_at":"2012-02-17T18:21:26.000Z","updated_at":"2026-04-02T20:32:11.000Z","published_at":"2012-02-17T21:02:57.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e--------\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFour of a kind is four cards of the same rank (column) and the highest other card as a 'kicker'. The columns represent A, 2, 3, ... K in the input. Aces are high.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 0 0 0 1 0 0 0 0 0 0 0 \\n0 1 0 0 0 0 0 0 0 0 0 0 0\\n0 1 0 0 0 0 0 0 0 0 0 0 0 \\n0 1 0 0 0 0 0 0 0 0 0 0 0\\nrepresents quads, so the return value from the function is TRUE.]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix does not:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 1 0 1 1 0 0 0 0 0 0 0 \\n0 0 0 1 0 0 0 0 0 0 0 0 0\\n0 0 0 1 0 0 0 0 0 0 0 0 0 \\n0 0 0 1 0 0 0 0 0 0 0 0 0\\nso the return value should be FALSE.]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix does represent quads\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[1 0 0 0 0 0 0 0 0 0 0 0 1 \\n1 0 0 0 0 0 0 0 0 0 0 0 0\\n1 0 1 0 0 0 0 0 0 1 0 0 0 \\n1 0 0 0 0 1 0 0 0 0 0 0 0\\nRemember, hand matrices can contain any number of 1's from 0 to 52.\\n\\n0 1 1 0 1 1 0 0 0 0 0 0 0 \\n0 0 0 0 1 0 1 0 0 0 0 0 0\\n0 0 0 0 0 0 0 0 0 0 0 0 0 \\n0 0 1 0 0 0 0 0 0 0 0 0 0 \\nWould be FALSE for this function.]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand Matrix, but it only shows the cards used to make the Quads plus kicker. If more than one Quads can be made, return the higher ranking one (Ace being the highest). If different suits are possible for the kicker, return the one higher up in the matrix.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":386,"title":"Poker Series 10: bestHand","description":"The Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\r\n\r\nA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\r\n\r\nFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\r\n\r\n--------\r\n\r\nFind the best hand using the definitions from earlier in this series.\r\n\r\nout.code is:\r\n\r\n# Straight Flush\r\n# Quads\r\n# Full House\r\n# Flush\r\n# Straight\r\n# Three of a kind\r\n# Two pair\r\n# Pair\r\n# High Card\r\n# No valid Hand\r\n\r\nout.cardsUsed is the same as is returned from the functions defined earlier for each type of hand.\r\n\r\nThis hand matrix:\r\n\r\n 0 1 0 0 1 0 0 0 0 0 0 0 0 \r\n 0 0 1 0 0 0 0 0 0 0 0 0 0\r\n 0 1 0 1 0 0 0 0 0 0 0 0 0 \r\n 0 1 0 0 0 1 0 0 0 0 0 0 0\r\n\r\nrepresents a three of a kind, so the return code is 6.","description_html":"\u003cp\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/p\u003e\u003cp\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/p\u003e\u003cp\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/p\u003e\u003cp\u003e--------\u003c/p\u003e\u003cp\u003eFind the best hand using the definitions from earlier in this series.\u003c/p\u003e\u003cp\u003eout.code is:\u003c/p\u003e\u003col\u003e\u003cli\u003eStraight Flush\u003c/li\u003e\u003cli\u003eQuads\u003c/li\u003e\u003cli\u003eFull House\u003c/li\u003e\u003cli\u003eFlush\u003c/li\u003e\u003cli\u003eStraight\u003c/li\u003e\u003cli\u003eThree of a kind\u003c/li\u003e\u003cli\u003eTwo pair\u003c/li\u003e\u003cli\u003ePair\u003c/li\u003e\u003cli\u003eHigh Card\u003c/li\u003e\u003cli\u003eNo valid Hand\u003c/li\u003e\u003c/ol\u003e\u003cp\u003eout.cardsUsed is the same as is returned from the functions defined earlier for each type of hand.\u003c/p\u003e\u003cp\u003eThis hand matrix:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 0 0 1 0 0 0 0 0 0 0 0 \r\n0 0 1 0 0 0 0 0 0 0 0 0 0\r\n0 1 0 1 0 0 0 0 0 0 0 0 0 \r\n0 1 0 0 0 1 0 0 0 0 0 0 0\r\n\u003c/pre\u003e\u003cp\u003erepresents a three of a kind, so the return code is 6.\u003c/p\u003e","function_template":"function out = bestPokerHand(hm)\r\n\r\nout.code = 10;\r\nout.usedCards = false(4,13); ","test_suite":"%%\r\nhm = [0 1 0 0 0 0 0 0 0 0 0 0 1 \r\n 0 1 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 1 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.code = 10;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(bestPokerHand(hm),y_correct))\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 0 0 0 0 1 \r\n 0 0 0 0 1 0 0 0 0 0 0 1 0\r\n 0 0 0 1 0 0 1 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 1 0 0 0];\r\n\r\ny_correct.code = 9;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 1 \r\n 0 0 0 0 1 0 0 0 0 0 0 1 0\r\n 0 0 0 0 0 0 1 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 1 0 0 0])\r\n \r\nassert(isequal(bestPokerHand(hm),y_correct))\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 0 0 0 0 1 \r\n 0 1 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 1 0 0];\r\n\r\ny_correct.code = 8;\r\ny_correct.usedCards = logical([0 1 0 0 0 0 0 0 0 0 0 0 1 \r\n 0 1 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 1 0 0])\r\n \r\nassert(isequal(bestPokerHand(hm),y_correct))\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 0 0 0 0 1 \r\n 0 1 0 0 0 0 0 0 1 0 0 0 0\r\n 0 0 0 1 0 0 0 0 0 0 0 0 0 \r\n 1 0 0 1 0 0 0 0 0 0 1 0 0];\r\n\r\ny_correct.code = 7;\r\ny_correct.usedCards = logical([0 1 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 1 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 1 0 0 0 0 0 0 0 0 0 \r\n 1 0 0 1 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(bestPokerHand(hm),y_correct))\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 0 0 0 0 1 \r\n 0 0 0 0 0 0 1 0 0 0 0 0 0\r\n 0 0 0 1 0 0 1 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 1 0 0 0 0 1 0];\r\n\r\ny_correct.code = 6;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 1 \r\n 0 0 0 0 0 0 1 0 0 0 0 0 0\r\n 0 0 0 0 0 0 1 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 1 0 0 0 0 1 0])\r\n \r\nassert(isequal(bestPokerHand(hm),y_correct))\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 0 0 0 0 1 \r\n 1 1 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 1 1 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 1 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.code = 5;\r\ny_correct.usedCards = logical([0 1 0 0 0 0 0 0 0 0 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 1 1 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 1 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(bestPokerHand(hm),y_correct))\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 1 1 0 1 1 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0\r\n 0 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.code = 4;\r\ny_correct.usedCards = logical([0 1 0 0 0 0 0 0 1 1 0 1 1 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(bestPokerHand(hm),y_correct))\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 1 1 0 1 0 \r\n 0 1 0 0 0 0 0 0 0 0 0 1 0\r\n 0 1 0 1 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0];\r\n\r\ny_correct.code = 3;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 1 0 0 1 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 1 0\r\n 0 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0])\r\n \r\nassert(isequal(bestPokerHand(hm),y_correct))\r\n\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 1 0 1 1 1 \r\n 0 1 0 0 0 0 0 0 1 0 0 1 0\r\n 0 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0];\r\n\r\ny_correct.code = 2;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 1 0 0 0 1 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0\r\n 0 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0])\r\n \r\nassert(isequal(bestPokerHand(hm),y_correct))\r\n%%\r\nhm = [0 1 0 0 0 0 0 1 1 1 1 1 1 \r\n 0 1 0 0 0 0 0 0 0 0 0 1 0\r\n 0 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 1 0 0 0 0];\r\n\r\ny_correct.code = 1;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 1 1 1 1 1 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(bestPokerHand(hm),y_correct))","published":true,"deleted":false,"likes_count":2,"comments_count":18,"created_by":240,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":44,"test_suite_updated_at":"2016-12-13T18:56:05.000Z","rescore_all_solutions":false,"group_id":15,"created_at":"2012-02-22T20:58:19.000Z","updated_at":"2026-02-15T04:18:26.000Z","published_at":"2012-02-22T20:58:26.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e--------\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFind the best hand using the definitions from earlier in this series.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eout.code is:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eStraight Flush\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eQuads\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFull House\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFlush\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eStraight\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThree of a kind\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eTwo pair\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ePair\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eHigh Card\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eNo valid Hand\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eout.cardsUsed is the same as is returned from the functions defined earlier for each type of hand.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 0 0 1 0 0 0 0 0 0 0 0 \\n0 0 1 0 0 0 0 0 0 0 0 0 0\\n0 1 0 1 0 0 0 0 0 0 0 0 0 \\n0 1 0 0 0 1 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003erepresents a three of a kind, so the return code is 6.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray 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Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\r\n\r\nA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\r\n\r\nFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\r\n\r\n--------\r\n\r\nA two pair is two pairs of cards of the same rank (column). The Ace (first column) is highest. The columns represent A, 2, 3, ... K. The next highest card is the kicker. If the kicker also form three of a kind with a pair, it is still considered two pair for the purposes of this function. Four of a kind is still two pair also. (I got two pair, a pair of Aces and another Pair of Aces!)\r\n\r\nThis hand matrix:\r\n\r\n 0 1 0 0 1 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 1 0 0 0\r\n 0 1 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 1 1 0 0 1 0 0 0 0\r\n\r\nrepresents a two pair, so the return value from the function is TRUE.\r\n\r\nThis hand matrix does not:\r\n\r\n 0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 1 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n\r\nso the return value should be FALSE.\r\n\r\nThis hand matrix does represent a two pair\r\n\r\n 0 0 0 0 0 0 0 0 0 1 0 0 1 \r\n 0 0 1 0 0 0 0 0 0 0 1 0 1\r\n 0 0 0 0 0 0 0 0 0 1 0 0 0 \r\n 0 0 0 0 0 1 0 0 0 0 0 0 0\r\n\r\nRemember, hand matrices can contain any number of 1's from 0 to 52.\r\n\r\n 0 0 0 0 0 1 0 0 0 0 0 0 0 \r\n 0 1 0 0 1 1 1 0 0 0 0 1 0\r\n 0 1 0 1 0 0 0 0 0 1 0 0 0 \r\n 0 0 1 0 0 0 0 0 0 0 0 1 0 \r\n\r\nWould be TRUE for this function.\r\n\r\nA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand matrix, but it only shows the cards used to make the three of a kind. If more than one two pair can be made, return the higher ranking one (the one with the highest rank. Ace being the highest). If different suits are possible for the same pair, return the ones higher up in the matrix, same for kickers. If the two pair happens to also be a four of a kind or full house, it still meets the defintion and should be returned.","description_html":"\u003cp\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/p\u003e\u003cp\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/p\u003e\u003cp\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/p\u003e\u003cp\u003e--------\u003c/p\u003e\u003cp\u003eA two pair is two pairs of cards of the same rank (column). The Ace (first column) is highest. The columns represent A, 2, 3, ... K. The next highest card is the kicker. If the kicker also form three of a kind with a pair, it is still considered two pair for the purposes of this function. Four of a kind is still two pair also. (I got two pair, a pair of Aces and another Pair of Aces!)\u003c/p\u003e\u003cp\u003eThis hand matrix:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 0 0 1 0 0 0 0 0 0 0 0 \r\n0 0 0 0 0 0 0 0 0 1 0 0 0\r\n0 1 0 0 0 0 0 0 0 0 0 0 0 \r\n0 0 0 0 1 1 0 0 1 0 0 0 0\r\n\u003c/pre\u003e\u003cp\u003erepresents a two pair, so the return value from the function is TRUE.\u003c/p\u003e\u003cp\u003eThis hand matrix does not:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 1 1 0 1 1 0 0 0 0 0 0 0 \r\n0 0 0 0 0 0 0 0 0 0 0 0 0\r\n0 0 0 0 0 0 0 0 0 1 0 0 0 \r\n0 0 0 0 0 0 0 0 0 0 0 0 0\r\n\u003c/pre\u003e\u003cp\u003eso the return value should be FALSE.\u003c/p\u003e\u003cp\u003eThis hand matrix does represent a two pair\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 0 0 0 0 0 0 0 0 1 0 0 1 \r\n0 0 1 0 0 0 0 0 0 0 1 0 1\r\n0 0 0 0 0 0 0 0 0 1 0 0 0 \r\n0 0 0 0 0 1 0 0 0 0 0 0 0\r\n\u003c/pre\u003e\u003cp\u003eRemember, hand matrices can contain any number of 1's from 0 to 52.\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e0 0 0 0 0 1 0 0 0 0 0 0 0 \r\n0 1 0 0 1 1 1 0 0 0 0 1 0\r\n0 1 0 1 0 0 0 0 0 1 0 0 0 \r\n0 0 1 0 0 0 0 0 0 0 0 1 0 \r\n\u003c/pre\u003e\u003cp\u003eWould be TRUE for this function.\u003c/p\u003e\u003cp\u003eA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand matrix, but it only shows the cards used to make the three of a kind. If more than one two pair can be made, return the higher ranking one (the one with the highest rank. Ace being the highest). If different suits are possible for the same pair, return the ones higher up in the matrix, same for kickers. If the two pair happens to also be a four of a kind or full house, it still meets the defintion and should be returned.\u003c/p\u003e","function_template":"function out = isTwoPair(hm)\r\n out.flag = false;\r\n out.usedCards = false(4,13);\r\nend","test_suite":"%%\r\nhm = [0 1 0 0 0 0 0 0 1 1 0 1 1 \r\n 0 1 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 1 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 1 0 0 0 0 0 0 1 0 0 0 1 \r\n 0 1 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 1 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isTwoPair(hm),y_correct))\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 1 1 0 0 0 \r\n 0 1 0 0 0 0 0 0 0 0 0 0 0\r\n 1 0 0 1 0 0 0 0 1 1 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 1 1 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 1 0 0 0 0 0 0 0 0 1 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isTwoPair(hm),y_correct))\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 0 1 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 1 0 0 0 0 1 1 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = false;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isTwoPair(hm),y_correct))\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 1 1 0 0 0 \r\n 0 1 0 0 0 0 0 0 0 1 0 0 0\r\n 1 0 0 1 0 0 0 0 1 1 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 1 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 1 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 1 0 0 0\r\n 1 0 0 0 0 0 0 0 0 1 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isTwoPair(hm),y_correct))\r\n\r\n%%\r\nhm = [0 1 0 0 0 0 0 0 1 1 0 0 0 \r\n 0 1 0 0 0 0 0 0 0 1 0 0 0\r\n 1 0 0 1 0 0 0 0 1 1 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 1 0 0 0];\r\n\r\ny_correct.flag = true;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 1 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 1 0 0 0\r\n 1 0 0 0 0 0 0 0 0 1 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 1 0 0 0])\r\n \r\nassert(isequal(isTwoPair(hm),y_correct))\r\n\r\n%%\r\nhm = [0 0 0 0 0 0 0 0 0 1 0 0 0 \r\n 1 0 0 0 0 0 0 0 0 0 0 0 0\r\n 1 0 0 0 0 0 0 0 0 1 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0];\r\n\r\ny_correct.flag = false;\r\ny_correct.usedCards = logical([0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0\r\n 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n 0 0 0 0 0 0 0 0 0 0 0 0 0])\r\n \r\nassert(isequal(isTwoPair(hm),y_correct))","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":240,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":53,"test_suite_updated_at":"2012-02-22T17:28:05.000Z","rescore_all_solutions":false,"group_id":15,"created_at":"2012-02-22T17:28:05.000Z","updated_at":"2026-02-15T05:47:26.000Z","published_at":"2012-02-22T17:28:08.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe Poker Series consists of many short, well defined functions that when combined will lead to complex behavior. Our goal is to create a function that will take two hand matrices (defined below) and return the winning hand.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA hand matrix is 4x13 binary matrix showing the cards that are available for a poker player to use. This program will be expandable to use 5 card hands through 52 card hands! Suits of the cards are all equally ranked, so they only matter for determination of flushes (and straight flushes).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor each challenge, you should feel free to reuse your solutions from prior challenges in the series. To break this problem into smaller pieces, I am likely making architectural choices that are sub-optimal for speed. This is being done as an exercise in coding. The larger goal of this project can likely be done in a much faster, but more obscure way.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e--------\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA two pair is two pairs of cards of the same rank (column). The Ace (first column) is highest. The columns represent A, 2, 3, ... K. The next highest card is the kicker. If the kicker also form three of a kind with a pair, it is still considered two pair for the purposes of this function. Four of a kind is still two pair also. (I got two pair, a pair of Aces and another Pair of Aces!)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 0 0 1 0 0 0 0 0 0 0 0 \\n0 0 0 0 0 0 0 0 0 1 0 0 0\\n0 1 0 0 0 0 0 0 0 0 0 0 0 \\n0 0 0 0 1 1 0 0 1 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003erepresents a two pair, so the return value from the function is TRUE.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix does not:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 1 1 0 1 1 0 0 0 0 0 0 0 \\n0 0 0 0 0 0 0 0 0 0 0 0 0\\n0 0 0 0 0 0 0 0 0 1 0 0 0 \\n0 0 0 0 0 0 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eso the return value should be FALSE.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis hand matrix does represent a two pair\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 0 0 0 0 0 0 0 0 1 0 0 1 \\n0 0 1 0 0 0 0 0 0 0 1 0 1\\n0 0 0 0 0 0 0 0 0 1 0 0 0 \\n0 0 0 0 0 1 0 0 0 0 0 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eRemember, hand matrices can contain any number of 1's from 0 to 52.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[0 0 0 0 0 1 0 0 0 0 0 0 0 \\n0 1 0 0 1 1 1 0 0 0 0 1 0\\n0 1 0 1 0 0 0 0 0 1 0 0 0 \\n0 0 1 0 0 0 0 0 0 0 0 1 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWould be TRUE for this function.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA second output argument should come from this function. It is a usedCards Matrix. It is of the same form as the hand matrix, but it only shows the cards used to make the three of a kind. If more than one two pair can be made, return the higher ranking one (the one with the highest rank. Ace being the highest). If different suits are possible for the same pair, return the ones higher up in the matrix, same for kickers. If the two pair happens to also be a four of a kind or full house, it still meets the defintion and should be returned.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":61069,"title":"Clueless - Lord Ned in the Game Room with the Technical Computing Language","description":"[Warning: this is a nontrivial programming problem]\r\n\r\nWorried about the decline in reasoning skills in the clueless populace of Nedland, Lord Ned had the finest minds at the University of Nedsburg develop a fun game to sharpen logical inference skills.\r\nThe game consists of a deck of 3n cards, with n cards in each of three categories.\r\n\r\n\r\nOne card from each category is randomly selected and these three cards are placed, unseen, in an envelope. The goal of the game is for the players to figure out which cards are in the envelope.\r\n\r\n\r\nThe remaining 3(n-1) cards are shuffled together and then dealt to the players. Every player receives the same number of cards; any leftover cards are placed face-up so that all players can see them. Because all the cards are shuffled together, the players will not all have an equal distribution of cards from the three categories.\r\n\r\n\r\nPlayers take it in turns to ask any other player about three cards, one from each category. If the player asked has any of the cards asked for, they must show one of those cards to the player who asked. (If they have more than one of the specified cards, they can choose which card to show.) The other players do not get to see which card has been shown, but they do know which three cards were asked for and that the player asked had one of them. If the player asked has none of the cards asked for, they simply state this and do not have to show any of their cards.\r\nOnce a player believes they have deduced the identity of the three cards in the envelope, they can, on their turn, announce their guess, then check the cards in the envelope. If the player is correct, they can reveal the cards as proof and they win the game. If not, they are eliminated. They must return the cards to the envelope, and the game continues without them.\r\nWrite a function that takes information about a game as inputs and returns the solution (that is, the deduced identity of the cards in the envelope) as output.\r\nThe inputs to the function are:\r\nm, the number of players\r\nn, the number of cards in each category\r\npnum, which player you are (from 1 to m). Players take turns in order (1 to m, and back to 1). If a card is revealed and it is your turn, you know the exact identity of that card. If it is not your turn, you know only that one of the cards asked for was revealed.\r\nyourcards, a 3-element cell array representing the cards dealt to you. Each cell contains the cards for one category. The cards from that category are given as a vector of values from 1 to n. If there are no cards for that category, the cell will contain an empty vector. In the example image, if you are the player in the bottom left (player 4), yourcards = {[1 3],[],[]}. If instead you are the player in the bottom right (player 3), yourcards = {[],[4],[2]}.\r\ncommoncards, a 3-element cell array representing the extra cards visible to everyone. The format is the same as for yourcards. In the example image, commoncards = {[],[3],[]}.\r\nturns, an nt-by-5 matrix representing nt turns of the game. Each row of turns records one player's turn as a 5-element vector. The first value is the number of the player asked. The next three values are the cards asked for, one for each category in order. The final value is the result: -1 represents the asked player responding that they do not have any of the requested cards; 0 represents the asked player showing a card (but you do not know which specific card); a value of 1-3 represents the asked player showing you a specific card, where the value is the index (or, equivalently, category) of the three cards asked for. For example, a row of turns that was the vector [5 4 3 2 1] would represent player 5 being asked for card 4 in category 1, card 3 in category 2, and card 2 in category 3, and showing you card 4 of category 1.\r\nThe output should be a single 3-element vector of the cards in the envelope, in order. For the example image, the output would be [4 2 1].\r\n\r\nAssumptions\r\nThe game is still new to Nedland, so don't expect the players to make the best requests on their turn, but the solution can be inferred from the inputs given. It may be possible to determine the solution from less information than is given, but the information given will always be sufficient.\r\nAlthough it shouldn't matter for your implementation, the official rules have 4-8 players (m) and card decks with up to 8 cards in each category (n), using at least enough cards to ensure that each player gets at least two cards in their hand.\r\n\r\nExample\r\nFor the example images, m = 4, n = 4. Suppose pnum = 4, in which case yourcards = {[1 3],[],[]} and commoncards = {[],[3],[]}.\r\nmoves = 12×5\r\n3 1 4 3 0\r\n1 3 4 4 0\r\n2 3 1 3 0\r\n1 4 2 2 -1\r\n4 3 1 1 0\r\n3 2 2 2 0\r\n2 1 1 4 0\r\n2 4 2 3 3\r\n3 3 2 1 -1\r\n1 4 4 2 -1\r\n2 4 2 1 -1\r\n1 2 2 4 1\r\nIn the first turn, player 1 asks player 3 for cards [1 4 3] (that is, card 1 from category 1, card 4 from category 2, and card 3 from category 3). Player 3 shows them a card but you, player 4, don't know which. You have the first card in your hand, so it must have been one of the other two, but so far no further information can be extracted.\r\nSimilarly, player 2 then asks player 1 for cards [3 4 4] and is shown one. Again, you hold the first card, so player 1 must have either card 4 from category 2 or card 4 from category 3, but you don't yet know which.\r\nOn the fourth turn, you ask player 1 for cards [4 2 2], but player 1 has none of these.\r\nMore turns occur where you cannot determine any concrete information yet.\r\nOn the eight turn, things suddenly get interesting. You ask player 2 for [4 2 3] and are shown the third of these. That is, you know that player 2 holds card 3 from category 3.\r\nMoreover, this makes some of the earlier turns more useful. Revisiting the first turn where player 3 was asked for [1 4 3], you now know that you held the first card and player 2 held the third card. The card that player 3 showed player 1 must therefore be the second card, so now you know that player 3 has card 4 from category 2.\r\nAnd similarly, now you can deduce from turn 2 that player 1 has card 4 from category 3 (because you hold the first card and player 3 holds the second card). And again from turn 7, you can now deduce that player 2 has card 1 from category 2, using the same logic.\r\nAt this point, you now know both cards that player 2 holds, so you can eliminate all other cards from possibly being held by them.\r\nYou also now know the locations of three of the four cards in category 2: player 2 has card 1, the common card is card 3, and player 3 has card 4. That means the remaining card (2) is in the envelope.\r\nTurn 9 tells you that player 3 does not have card 1 from category 3. The next two turns provide no new information.\r\nFinally, turn 12 reveals that player 1 has card 2 from category 1. This means you now know both cards player 1 holds (2 from category 1 and 4 from category 3). Consequently, you know that no player has card 1 from category 3 (you know both cards held by players 1 and 2, you know player 3 doesn't have it, you don't have it, and it's not the common card), so it must be in the envelope.\r\nThis just leaves category 1 but you now know the location of three of the four cards (you have cards 1 \u0026 3, player 1 has card 2). And so you have the solution: [4 2 1].\r\nsoln = infercards(m,n,pnum,yourcards,commoncards,moves)\r\nsoln =\r\n4 2 1\r\n\r\nImplementation Suggestions/Tips\r\nOne way to find the solution is to keep an array of all cards and all players, with values indicating your state of knowledge about whether that player has that card: unknown, yes, or no. Start with everything unknown, and fill in information as you go. For this tracking, you can treat the common cards as player m+1. Each category has one card that nobody has, which is the card in the envelope. Once you have identified that card for each category, you have your solution.\r\nYou start with complete knowledge of which cards you and the common \"player\" do and do not have.\r\nGo through the turns and use the provided information to update your state of knowledge. Also use the following observations to extend the logic to find new information:\r\nIf you know a player has a card, you know all other players do not.\r\nYou know how many cards each player has: the same number that you have. Equivalently, you can calculate it: ncards = floor(3*(n-1)/m). If you know the identities of ncards cards for a player, you know they have no other cards. (The common cards are an exception, but this doesn't matter because you already know exactly what cards are and are not in the common set.)\r\nOnce you know the locations of (n-1) cards in a category, the remaining card must be in the envelope.\r\nEach player holds ncards cards. If you can identify 3n-ncards cards that a player definitely does not hold, then they must hold the remaining ncards cards. That is, if the no, yes, and maybe/unknown cards for a player are distributed such that there are ncards yes or maybe (and 3n-ncards no), then all the remaining maybes are yeses.\r\nRemember that, as in the example, new information disclosed in a turn may make previous turns more relevant.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 4023.25px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 408px 2011.62px; transform-origin: 408px 2011.62px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003e[Warning: this is a nontrivial programming problem]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 21px; text-align: left; transform-origin: 385px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eWorried about the decline in reasoning skills in the clueless populace of Nedland, Lord Ned had the finest minds at the University of \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eNedsburg\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e develop a fun game to sharpen logical inference skills.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe game consists of a deck of 3\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003en\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e cards, with \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003en\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e cards in each of three categories.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 445px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; 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\" data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 21px; text-align: left; transform-origin: 385px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eOne card from each category is randomly selected and these three cards are placed, unseen, in an envelope. The goal of the game is for the players to figure out which cards are in the envelope.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 312px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 156px; text-align: left; transform-origin: 385px 156px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cimg class=\"imageNode\" width=\"700\" height=\"306\" style=\"vertical-align: baseline;width: 700px;height: 306px\" 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data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 31.5px; text-align: left; transform-origin: 385px 31.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe remaining 3(\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003en\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e-1) cards are shuffled together and then dealt to the players. Every player receives the same number of cards; any leftover cards are placed face-up so that all players can see them. Because all the cards are shuffled together, the players will not all have an equal distribution of cards from the three categories.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan 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data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 105px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 52.5px; text-align: left; transform-origin: 385px 52.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003ePlayers take it in turns to ask any other player about three cards, one from each category. If the player asked has any of the cards asked for, they must show one of those cards to the player who asked. (If they have more than one of the specified cards, they can choose which card to show.) The other players do not get to see which card has been shown, but they do know which three cards were asked for and that the player asked had one of them. If the player asked has none of the cards asked for, they simply state this and do not have to show any of their cards.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 31.5px; text-align: left; transform-origin: 385px 31.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eOnce a player believes they have deduced the identity of the three cards in the envelope, they can, on their turn, announce their guess, then check the cards in the envelope. If the player is correct, they can reveal the cards as proof and they win the game. If not, they are eliminated. They must return the cards to the envelope, and the game continues without them.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 21px; text-align: left; transform-origin: 385px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eWrite a function that takes information about a game as inputs and returns the solution (that is, the deduced identity of the cards in the envelope) as output.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe inputs to the function are:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cul style=\"block-size: 396.312px; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; perspective-origin: 392px 198.156px; transform-origin: 392px 198.156px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"block-size: 20.4375px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 364px 10.2188px; text-align: left; transform-origin: 364px 10.2188px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003em\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, the number of players\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4375px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 364px 10.2188px; text-align: left; transform-origin: 364px 10.2188px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003en\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, the number of cards in each category\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 62.3125px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 364px 31.1562px; text-align: left; transform-origin: 364px 31.1562px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003epnum\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, which player you are (from 1 to \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003em\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e). Players take turns in order (1 to \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003em\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, and back to 1). If a card is revealed and it is your turn, you know the exact identity of that card. If it is not your turn, you know only that one of the cards asked for was revealed.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 84.75px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 364px 42.375px; text-align: left; transform-origin: 364px 42.375px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eyourcards\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, a 3-element cell array representing the cards dealt to you. Each cell contains the cards for one category. The cards from that category are given as a vector of values from 1 to \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003en\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e. If there are no cards for that category, the cell will contain an empty vector. In the example image, if you are the player in the bottom left (player 4), \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eyourcards = {[1 3],[],[]}\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e. If instead you are the player in the bottom right (player 3), \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eyourcards = {[],[4],[2]}\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 42.875px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 364px 21.4375px; text-align: left; transform-origin: 364px 21.4375px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ecommoncards\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, a 3-element cell array representing the extra cards visible to everyone. The format is the same as for \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eyourcards\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e. In the example image, \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ecommoncards = {[],[3],[]}\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 165.5px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 364px 82.75px; text-align: left; transform-origin: 364px 82.75px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eturns\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, an \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003ent\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e-by-5 matrix representing \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003ent\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e turns of the game. Each row of \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eturns\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e records one player's turn as a 5-element vector. The first value is the number of the player asked. The next three values are the cards asked for, one for each category in order. The final value is the result: -1 represents the asked player responding that they do not have any of the requested cards; 0 represents the asked player showing a card (but you do not know which specific card); a value of 1-3 represents the asked player showing you a specific card, where the value is the index (or, equivalently, category) of the three cards asked for. For example, a row of \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eturns\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e that was the vector \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[5 4 3 2 1]\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e would represent player 5 being asked for card 4 in category 1, card 3 in category 2, and card 2 in category 3, and showing you card 4 of category 1.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 21px; text-align: left; transform-origin: 385px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe output should be a single 3-element vector of the cards in the envelope, in order. For the example image, the output would be \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[4 2 1]\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eAssumptions\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 31.5px; text-align: left; transform-origin: 385px 31.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe game is still new to \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eNedland\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, so don't expect the players to make the best requests on their turn, but the solution can be inferred from the inputs given. It may be possible to determine the solution from less information than is given, but the information given will always be sufficient.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 21px; text-align: left; transform-origin: 385px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eAlthough it shouldn't matter for your implementation, the official rules have 4-8 players (\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003em\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e) and card decks with up to 8 cards in each category (\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003en\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e), using at least enough cards to ensure that each player gets at least two cards in their hand.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eExample\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 21px; text-align: left; transform-origin: 385px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eFor the example images, \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003em\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e = 4, \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003en\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e = 4. Suppose \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003epnum\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e = 4, in which case \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eyourcards = {[1 3],[],[]}\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e and \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ecommoncards = {[],[3],[]}\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 265.688px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-end-end-radius: 4px; border-end-start-radius: 4px; border-start-end-radius: 4px; border-start-start-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 405px 132.844px; transform-origin: 405px 132.844px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 405px 10.2188px; text-wrap-mode: nowrap; transform-origin: 405px 10.2188px; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; unicode-bidi: normal; white-space-collapse: preserve; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003emoves = 12\u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(255, 0, 0); border-block-start-color: rgb(255, 0, 0); border-bottom-color: rgb(255, 0, 0); border-inline-end-color: rgb(255, 0, 0); border-inline-start-color: rgb(255, 0, 0); border-left-color: rgb(255, 0, 0); border-right-color: rgb(255, 0, 0); border-top-color: rgb(255, 0, 0); caret-color: rgb(255, 0, 0); color: rgb(255, 0, 0); column-rule-color: rgb(255, 0, 0); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(255, 0, 0); text-decoration-color: rgb(255, 0, 0); text-emphasis-color: rgb(255, 0, 0); \"\u003e×\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e5\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 405px 10.2188px; text-wrap-mode: nowrap; transform-origin: 405px 10.2188px; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; unicode-bidi: normal; white-space-collapse: preserve; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e3 1 4 3 0\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 405px 10.2188px; text-wrap-mode: nowrap; transform-origin: 405px 10.2188px; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; unicode-bidi: normal; white-space-collapse: preserve; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e1 3 4 4 0\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 405px 10.2188px; text-wrap-mode: nowrap; transform-origin: 405px 10.2188px; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; unicode-bidi: normal; white-space-collapse: preserve; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e2 3 1 3 0\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 405px 10.2188px; text-wrap-mode: nowrap; transform-origin: 405px 10.2188px; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; unicode-bidi: normal; white-space-collapse: preserve; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e1 4 2 2 -1\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 405px 10.2188px; text-wrap-mode: nowrap; transform-origin: 405px 10.2188px; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; unicode-bidi: normal; white-space-collapse: preserve; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e4 3 1 1 0\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 405px 10.2188px; text-wrap-mode: nowrap; transform-origin: 405px 10.2188px; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; unicode-bidi: normal; white-space-collapse: preserve; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e3 2 2 2 0\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 405px 10.2188px; text-wrap-mode: nowrap; transform-origin: 405px 10.2188px; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; unicode-bidi: normal; white-space-collapse: preserve; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e2 1 1 4 0\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 405px 10.2188px; text-wrap-mode: nowrap; transform-origin: 405px 10.2188px; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; unicode-bidi: normal; white-space-collapse: preserve; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e2 4 2 3 3\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 405px 10.2188px; text-wrap-mode: nowrap; transform-origin: 405px 10.2188px; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; unicode-bidi: normal; white-space-collapse: preserve; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e3 3 2 1 -1\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 405px 10.2188px; text-wrap-mode: nowrap; transform-origin: 405px 10.2188px; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; unicode-bidi: normal; white-space-collapse: preserve; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e1 4 4 2 -1\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 405px 10.2188px; text-wrap-mode: nowrap; transform-origin: 405px 10.2188px; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; unicode-bidi: normal; white-space-collapse: preserve; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e2 4 2 1 -1\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 405px 10.2188px; text-wrap-mode: nowrap; transform-origin: 405px 10.2188px; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; unicode-bidi: normal; white-space-collapse: preserve; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e1 2 2 4 1\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 10px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 10px; perspective-origin: 385px 31.5px; text-align: left; transform-origin: 385px 31.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 10px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eIn the first turn, player 1 asks player 3 for cards \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[1 4 3]\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e (that is, card 1 from category 1, card 4 from category 2, and card 3 from category 3). Player 3 shows them a card but you, player 4, don't know which. You have the first card in your hand, so it must have been one of the other two, but so far no further information can be extracted.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 21px; text-align: left; transform-origin: 385px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eSimilarly, player 2 then asks player 1 for cards \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[3 4 4]\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e and is shown one. Again, you hold the first card, so player 1 must have either card 4 from category 2 or card 4 from category 3, but you don't yet know which.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eOn the fourth turn, you ask player 1 for cards \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[4 2 2]\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, but player 1 has none of these.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eMore turns occur where you cannot determine any concrete information yet.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 21px; text-align: left; transform-origin: 385px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eOn the eight turn, things suddenly get interesting. You ask player 2 for \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[4 2 3]\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e and are shown the third of these. That is, you know that player 2 holds card 3 from category 3.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 31.5px; text-align: left; transform-origin: 385px 31.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eMoreover, this makes some of the earlier turns more useful. Revisiting the first turn where player 3 was asked for \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[1 4 3]\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, you now know that you held the first card and player 2 held the third card. The card that player 3 showed player 1 must therefore be the second card, so now you know that player 3 has card 4 from category 2.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 31.5px; text-align: left; transform-origin: 385px 31.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eAnd similarly, now you can deduce from turn 2 that player 1 has card 4 from category 3 (because you hold the first card and player 3 holds the second card). And again from turn 7, you can now deduce that player 2 has card 1 from category 2, using the same logic.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 21px; text-align: left; transform-origin: 385px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eAt this point, you now know both cards that player 2 holds, so you can eliminate all other cards from possibly being held by them.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 21px; text-align: left; transform-origin: 385px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eYou also now know the locations of three of the four cards in category 2: player 2 has card 1, the common card is card 3, and player 3 has card 4. That means the remaining card (2) is in the envelope.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eTurn 9 tells you that player 3 does not have card 1 from category 3. The next two turns provide no new information.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 84px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 42px; text-align: left; transform-origin: 385px 42px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eFinally, turn 12 reveals that player 1 has card 2 from category 1. This means you now know both cards player 1 holds (2 from category 1 and 4 from category 3). Consequently, you know that no player has card 1 from category 3 (you know both cards held by players 1 and 2, you know player 3 doesn't have it, you don't have it, and it's not the common card), so it must be in the envelope.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 21px; text-align: left; transform-origin: 385px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThis just leaves category 1 but you now know the location of three of the four cards (you have cards 1 \u0026amp; 3, player 1 has card 2). And so you have the solution: \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[4 2 1]\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 61.3125px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-end-end-radius: 4px; border-end-start-radius: 4px; border-start-end-radius: 4px; border-start-start-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 405px 30.6562px; transform-origin: 405px 30.6562px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 405px 10.2188px; text-wrap-mode: nowrap; transform-origin: 405px 10.2188px; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; unicode-bidi: normal; white-space-collapse: preserve; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003esoln = infercards(m,n,pnum,yourcards,commoncards,moves)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 405px 10.2188px; text-wrap-mode: nowrap; transform-origin: 405px 10.2188px; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; unicode-bidi: normal; white-space-collapse: preserve; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003esoln =\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 405px 10.2188px; text-wrap-mode: nowrap; transform-origin: 405px 10.2188px; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; unicode-bidi: normal; white-space-collapse: preserve; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e4 2 1\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 10px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 10px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 10px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eImplementation Suggestions/Tips\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 84px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 42px; text-align: left; transform-origin: 385px 42px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eOne way to find the solution is to keep an array of all cards and all players, with values indicating your state of knowledge about whether that player has that card: unknown, yes, or no. Start with everything unknown, and fill in information as you go. For this tracking, you can treat the common cards as player \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003em\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e+1. Each category has one card that nobody has, which is the card in the envelope. Once you have identified that card for each category, you have your solution.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eYou start with complete knowledge of which cards you and the common \"player\" do and do not have.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 21px; text-align: left; transform-origin: 385px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGo through the turns and use the provided information to update your state of knowledge. Also use the following observations to extend the logic to find new information:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cul style=\"block-size: 187.938px; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; perspective-origin: 392px 93.9688px; transform-origin: 392px 93.9688px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"block-size: 20.4375px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 364px 10.2188px; text-align: left; transform-origin: 364px 10.2188px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eIf you know a player has a card, you know all other players do not.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 82.75px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 364px 41.375px; text-align: left; transform-origin: 364px 41.375px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eYou know how many cards each player has: the same number that you have. Equivalently, you can calculate it: \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003encards = floor(3*(n-1)/m)\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e. If you know the identities of \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003encards\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e cards for a player, you know they have no other cards. (The common cards are an exception, but this doesn't matter because you already know exactly what cards are and are not in the common set.)\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4375px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 364px 10.2188px; text-align: left; transform-origin: 364px 10.2188px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eOnce you know the locations of (\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003en\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e-1) cards in a category, the remaining card must be in the envelope.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 64.3125px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 364px 32.1562px; text-align: left; transform-origin: 364px 32.1562px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eEach player holds \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003encards\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e cards. If you can identify 3\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003en\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e-\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003encards\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e cards that a player definitely does \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"text-decoration: underline; text-decoration-line: underline; \"\u003enot\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e hold, then they must hold the remaining \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003encards\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e cards. That is, if the no, yes, and maybe/unknown cards for a player are distributed such that there are \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003encards\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e yes or maybe (and 3\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003en\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e-\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003encards\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e no), then all the remaining maybes are yeses.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 385px 10.5px; text-align: left; transform-origin: 385px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eRemember that, as in the example, new information disclosed in a turn may make previous turns more relevant.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function sol = infercards(m,n,pnum,yourcards,commoncards,turns)\r\nsol = randi(n,1,3);\r\nend","test_suite":"%% Test case #1: 4 players, 7 cards (per category)\r\nyourcards = {4,[1 3],5};\r\ncommoncards = {1,[],7};\r\nmoves = [4 6 1 1 0;3 4 7 1 0;2 6 7 5 0;2 7 7 1 1;4 6 3 6 0;3 4 7 4 -1;2 4 3 5 -1;2 2 6 2 -1;2 4 4 1 0;3 3 3 4 -1;4 7 2 5 0;3 3 5 6 3;3 3 1 6 0;3 3 2 6 0;2 3 5 5 -1;1 2 2 1 2;4 3 1 6 0;4 4 2 1 0;1 6 7 5 0;3 7 5 3 -1;2 3 4 5 0;1 3 3 5 -1;1 6 5 4 0;1 2 2 6 2;4 3 6 2 -1;4 2 2 1 -1;2 6 4 4 0;2 3 6 3 -1;2 4 3 5 -1;4 3 5 6 -1;4 5 5 3 -1;1 3 4 4 3;3 2 3 5 0;1 3 2 6 0;2 6 4 3 0;2 6 5 1 1;4 7 4 3 -1;1 2 1 4 0;1 3 4 5 -1;3 7 7 4 -1;3 6 3 6 0;3 3 7 1 0;1 3 1 5 -1;3 5 2 1 3;3 6 4 6 0;3 2 7 6 0;1 4 4 4 0;1 7 5 3 2];\r\nsol = infercards(4,7,4,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[3 6 3]))\r\n\r\n%% Test case #2: 6 players, 6 cards (per category)\r\nyourcards = {4,6,[]};\r\ncommoncards = {1,5,3};\r\nmoves = [5 5 2 1 -1;6 2 3 5 0;1 6 2 2 3;2 4 2 5 -1;6 4 2 6 -1;4 4 4 4 0;6 3 1 6 0;5 4 2 5 -1;4 2 4 4 2;3 6 6 4 0;2 4 2 2 -1;4 2 4 6 0;5 6 3 6 0;6 2 1 4 -1;6 2 1 5 -1;6 4 2 6 -1;6 5 6 5 -1;4 5 6 1 0;3 2 3 1 -1;6 4 6 5 -1;4 6 1 2 -1;2 4 3 2 -1;1 2 6 6 -1;4 5 2 4 0;2 2 2 4 -1;3 2 1 5 -1;6 5 3 5 2;3 2 1 4 -1;4 5 6 5 0;4 6 1 5 -1;4 2 4 6 0;5 5 2 4 -1;6 2 1 5 -1;6 3 2 4 0;4 5 4 4 0;3 4 4 6 0;5 3 4 6 -1;5 4 1 4 0;1 6 1 6 -1;6 6 2 1 -1;2 3 4 6 0;4 4 2 1 -1;2 6 3 1 0;3 3 6 5 0;2 5 3 4 -1;1 3 2 6 -1;2 5 4 4 -1;3 5 6 4 0;5 2 3 4 -1;3 4 6 2 0;5 6 3 1 1;6 6 2 5 -1;3 4 6 4 0;3 4 6 4 0;5 2 6 4 -1;5 3 4 2 -1;1 6 4 6 -1;1 6 3 5 0];\r\nsol = infercards(6,6,3,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[2 2 4]))\r\n\r\n%% Test case #3: 5 players, 7 cards (per category)\r\nyourcards = {2,[3 5],[]};\r\ncommoncards = {5,2,3};\r\nmoves = [4 1 7 5 -1;5 3 3 7 0;2 3 6 7 0;1 7 6 6 -1;2 1 3 2 -1;3 4 1 7 -1;5 4 4 1 -1;5 6 3 1 0;3 7 6 2 -1;2 4 5 1 -1;4 7 5 1 0;5 2 3 7 0;5 3 3 4 -1;3 7 1 1 -1;1 4 5 4 0;2 4 1 7 0;4 3 7 4 -1;5 6 1 2 0;2 6 1 7 2;3 7 3 1 -1;5 4 6 6 0;3 1 5 2 0;4 6 3 7 0;2 6 1 6 2;1 1 3 1 -1;5 6 3 6 0;1 2 5 2 0;1 2 6 6 -1;3 3 7 7 -1;1 1 7 4 0;3 4 4 5 0;5 4 7 7 0;4 7 1 4 -1;1 4 4 7 -1;3 4 7 1 -1;5 1 7 5 -1;1 1 7 6 -1;2 3 3 7 -1];\r\nsol = infercards(5,7,4,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[4 7 1]))\r\n\r\n%% Test case #4: 6 players, 5 cards (per category)\r\nyourcards = {1,[],1};\r\ncommoncards = {[],[],[]};\r\nmoves = [5 5 1 5 -1;5 2 2 2 -1;6 5 5 4 0;5 5 3 2 -1;1 4 3 5 -1;5 2 1 1 0;4 5 3 2 -1;3 2 4 2 -1;4 1 2 4 -1;6 1 2 4 -1;4 5 3 5 -1;5 3 2 5 -1;6 1 1 2 0;5 2 5 5 -1;6 5 4 4 0;2 5 3 2 0;6 3 3 3 -1;3 4 5 4 -1;4 5 5 1 0;3 4 5 2 -1;2 3 5 4 -1;3 5 2 2 -1;1 3 5 5 1;2 4 3 4 0;5 4 3 2 -1;3 5 4 4 -1;4 4 5 4 0;2 2 4 5 -1;3 3 1 5 3;4 2 2 5 -1;4 2 5 1 0;1 5 4 1 0;2 5 3 2 0;2 1 2 5 -1;2 2 4 4 -1;5 4 2 5 -1;3 2 5 2 -1;5 5 2 1 0;4 5 3 2 -1;2 5 3 3 0;4 5 4 4 -1;4 4 5 5 0;3 5 3 1 -1;5 4 2 3 -1;6 5 2 1 0;3 5 1 4 -1;2 5 3 3 2;2 2 3 1 0;2 2 2 2 -1;5 1 2 2 0;6 5 1 4 0;2 3 1 1 0];\r\nsol = infercards(6,5,5,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[2 2 4]))\r\n\r\n%% Test case #5: 8 players, 7 cards (per category)\r\nyourcards = {7,[],3};\r\ncommoncards = {5,[],2};\r\nmoves = [7 6 2 1 0;6 7 6 6 0;7 3 5 4 -1;8 7 1 1 -1;3 2 5 4 -1;7 2 5 3 -1;2 3 6 5 0;4 6 2 3 0;8 3 6 3 -1;1 7 1 6 0;1 3 5 3 -1;1 4 1 5 0;8 1 6 5 -1;3 4 2 3 -1;2 3 6 4 0;2 1 1 3 -1;8 7 4 3 0;4 1 1 1 -1;1 6 5 7 -1;2 2 1 1 0;6 6 4 1 -1;3 7 5 6 -1;1 4 7 3 0;6 7 3 6 0;2 2 1 7 0;7 1 3 4 -1;2 3 4 3 0;1 4 3 3 0;7 4 2 5 -1;8 1 5 7 -1;3 1 7 4 0;2 6 6 5 -1;8 2 6 1 -1;8 7 2 4 0;6 2 2 1 -1;8 1 6 4 0;3 1 1 7 1;8 7 5 4 0;1 1 1 5 -1;7 1 7 1 0;7 7 4 4 -1;5 4 3 5 -1;1 7 4 7 -1;2 7 6 7 -1;2 4 7 5 -1;5 6 7 4 -1;6 3 5 5 -1;2 4 2 5 -1;7 2 1 5 -1;6 7 4 4 -1;8 3 6 7 -1;7 7 3 6 -1;3 2 7 4 2];\r\nsol = infercards(8,7,5,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[6 1 5]))\r\n\r\n%% Test case #6: 5 players, 7 cards (per category)\r\nyourcards = {5,3,2};\r\ncommoncards = {[1 7],[],7};\r\nmoves = [4 3 3 2 0;1 3 7 6 -1;5 6 7 2 0;2 3 7 6 -1;2 2 1 4 -1;3 4 3 5 -1;3 5 7 4 -1;2 3 3 1 -1;1 2 2 5 -1;4 4 5 4 -1;3 5 3 2 -1;4 2 2 1 -1;5 3 7 2 0;1 6 6 3 -1;3 5 5 4 -1;5 4 7 2 0;1 2 4 6 0;2 4 4 5 0;5 3 2 4 -1;2 2 6 4 0;5 5 7 5 0;3 5 5 1 -1;4 5 5 5 0;3 4 6 4 -1;1 6 4 1 0;3 6 2 4 0;1 3 5 4 -1;5 3 7 5 0;5 6 2 3 -1;1 3 2 4 -1;3 2 7 4 0;1 3 1 3 0;4 5 4 4 0;3 3 4 6 -1;3 5 1 2 -1;4 2 3 2 0;3 3 4 2 -1;2 3 5 1 -1;1 3 7 5 -1;2 4 4 4 0;4 6 2 4 -1;3 3 1 2 -1;4 5 3 5 0;1 3 6 5 -1;3 6 3 2 -1];\r\nsol = infercards(5,7,4,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[3 5 4]))\r\n\r\n%% Test case #7: 5 players, 7 cards (per category)\r\nyourcards = {[],[2 6],6};\r\ncommoncards = {4,[3 5],[]};\r\nmoves = [3 3 6 3 -1;3 3 4 5 -1;2 2 2 1 -1;5 2 1 1 3;3 6 6 2 0;3 2 2 1 -1;1 5 1 2 0;5 2 1 3 -1;5 6 1 7 -1;3 2 6 5 -1;3 7 6 6 -1;1 3 2 1 -1;4 3 4 5 -1;1 7 7 2 -1;1 6 7 6 0;3 7 4 5 -1;5 1 1 7 -1;2 3 7 4 0;1 3 1 2 2;2 5 4 5 -1;3 5 6 1 0;3 6 2 4 -1;5 1 6 3 -1;2 7 4 2 1;4 7 7 6 0;3 3 6 6 -1;4 3 1 1 -1;4 6 1 3 -1;5 1 1 7 -1;4 6 6 7 0;4 5 6 1 0;5 5 6 6 -1;1 3 6 4 -1;1 1 7 5 1;4 2 2 2 0;3 2 7 1 -1;3 5 4 7 0;4 3 6 1 0;2 7 4 7 1;2 1 7 3 0;3 5 4 7 0;5 6 1 5 -1;1 3 7 1 -1;5 3 7 7 1;4 7 4 7 -1;5 7 7 1 0;5 5 4 7 -1;2 7 4 3 0;3 1 4 4 -1;4 5 1 7 -1;4 2 2 4 0;1 1 1 6 0;5 6 2 6 -1;5 5 7 5 -1];\r\nsol = infercards(5,7,4,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[2 4 5]))\r\n\r\n%% Test case #8: 5 players, 5 cards (per category)\r\nyourcards = {4,[],4};\r\ncommoncards = {2,[],3};\r\nmoves = [2 5 1 2 -1;4 1 5 2 1;1 5 4 4 -1;1 4 4 1 0;4 1 5 4 0;2 4 4 2 0;1 5 1 5 -1;2 3 1 4 0;1 3 4 4 -1;2 3 3 4 0;3 5 1 2 -1;1 1 4 1 3;5 1 1 4 0;5 4 1 1 0;2 1 4 2 -1;5 4 2 5 0;5 3 2 5 2;2 4 5 4 0;3 3 1 2 -1;3 4 5 4 -1;3 4 4 5 0;1 1 1 5 -1;2 1 4 2 -1;2 3 2 5 -1;4 3 3 1 -1;3 3 1 5 0;1 5 5 1 2;2 5 1 4 0;5 4 1 5 0;1 4 4 2 -1;2 1 1 5 -1;1 1 2 2 -1;1 4 5 1 0;5 4 1 1 0;2 4 4 2 0;3 1 4 2 -1];\r\nsol = infercards(5,5,2,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[3 4 2]))\r\n\r\n%% Test case #9: 5 players, 5 cards (per category)\r\nyourcards = {3,[],4};\r\ncommoncards = {5,4,[]};\r\nmoves = [2 4 5 2 2;3 2 3 1 0;2 2 2 4 -1;5 3 3 5 0;4 1 5 1 0;3 4 1 5 -1;5 2 2 2 -1;1 3 5 5 0;2 2 2 1 -1;2 3 5 4 0;2 1 3 5 -1;4 4 1 5 0;4 4 2 5 0;5 3 3 4 -1;1 3 5 1 0;3 2 5 5 -1;5 1 1 1 0;2 2 1 5 -1;1 3 1 4 0;4 2 5 4 -1;5 1 1 1 2;4 4 3 5 0;4 1 1 4 0;5 3 1 1 0;2 2 2 4 -1;3 4 3 5 2;3 1 1 2 0];\r\nsol = infercards(5,5,1,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[2 2 1]))\r\n\r\n%% Test case #10: 5 players, 7 cards (per category)\r\nyourcards = {[],[2 4 7],[]};\r\ncommoncards = {4,[],[3 6]};\r\nmoves = [2 7 7 7 0;4 2 4 2 -1;2 6 3 4 3;1 2 5 1 0;3 3 5 5 -1;3 7 2 4 0;3 2 4 1 0;1 5 5 1 3;1 2 7 1 0;1 1 6 7 -1;3 3 7 7 0;1 3 4 7 -1;1 3 1 2 -1;5 6 1 4 0;4 1 4 5 -1;5 7 2 7 -1;4 3 1 7 0;5 7 3 1 2;3 2 5 2 -1;2 3 5 4 0;3 7 4 5 0;3 6 4 7 0;5 1 3 2 3;1 1 4 5 -1;4 2 7 4 -1;2 3 2 7 -1;3 1 3 2 -1;2 2 6 7 -1;3 1 4 2 0;4 3 5 4 0;4 1 1 4 -1;5 1 5 7 -1;1 5 5 4 -1;1 7 3 7 -1;4 5 2 5 0;4 7 3 7 -1;4 3 3 2 0;4 6 5 4 -1];\r\nsol = infercards(5,7,3,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[1 5 7]))\r\n\r\n%% Test case #11: 8 players, 7 cards (per category)\r\nyourcards = {2,4,[]};\r\ncommoncards = {[],5,6};\r\nmoves = [2 2 6 4 -1;4 7 6 1 -1;6 6 6 2 2;5 3 6 5 -1;4 1 3 2 0;7 7 3 5 -1;4 4 6 4 -1;1 2 4 2 0;8 3 6 5 -1;7 3 2 2 0;8 7 1 2 -1;3 7 4 5 0;4 2 7 2 -1;1 4 7 4 -1;4 2 3 4 0;3 5 3 4 -1;3 6 3 1 -1;6 7 6 2 0;4 5 1 7 2;1 1 7 5 -1;1 3 4 2 0;2 4 1 2 -1;1 4 6 4 -1;7 4 3 3 -1;8 4 7 7 -1;6 6 4 4 -1;7 5 2 7 3;1 5 7 5 -1;7 4 1 7 0;4 5 3 1 0;2 5 2 2 -1;2 5 3 7 -1;7 7 4 5 -1;7 6 6 1 -1;6 6 7 4 -1;8 1 7 4 -1;2 6 1 5 0;8 6 7 1 0;6 1 6 2 0;1 5 4 3 0;4 5 4 4 -1;8 7 3 1 0;2 7 2 4 -1;6 6 2 3 0;3 6 7 5 -1;7 6 4 4 -1;1 1 2 4 -1;7 1 4 7 0;2 4 7 5 0;4 2 7 7 -1;4 6 2 4 -1;6 4 7 4 -1;6 1 2 3 0;4 4 7 2 -1;4 6 7 3 -1;1 7 1 3 0;5 4 1 7 -1];\r\nsol = infercards(8,7,3,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[4 7 4]))\r\n\r\n%% Test case #12: 5 players, 6 cards (per category)\r\nyourcards = {[],[3 4 6],[]};\r\ncommoncards = {[],[],[]};\r\nmoves = [2 1 5 6 -1;4 4 6 2 0;4 3 1 5 -1;2 4 2 5 0;1 4 2 6 1;5 6 4 3 0;4 2 4 1 0;4 4 6 5 -1;5 4 1 6 -1;4 3 1 4 -1;2 6 5 4 -1;5 1 6 3 0;2 6 5 1 -1;5 6 6 6 0;3 5 5 5 -1;5 2 2 3 -1;1 2 3 3 -1;4 1 4 5 0;3 4 2 5 0;2 2 2 6 -1;5 6 3 6 0;5 4 2 4 -1;2 4 3 4 -1;5 6 2 5 -1;4 3 2 2 3;5 3 4 3 0;3 1 4 3 0;2 2 1 4 -1;1 4 1 1 0;3 2 2 3 3;3 3 2 4 0;1 6 4 4 -1;2 3 6 2 0;5 3 2 1 -1;4 5 1 3 -1;2 5 5 6 0;4 1 1 3 0;2 5 5 1 0;3 5 6 4 -1;4 6 2 5 -1;3 1 6 5 -1;1 6 5 2 -1;1 4 4 2 0;2 5 4 4 0;2 3 2 2 1;5 3 2 4 -1;3 1 2 2 0;1 2 3 2 -1;3 3 1 6 0;2 4 5 6 -1;4 5 6 5 -1;4 1 5 1 0;4 5 6 5 -1;5 3 5 6 -1;3 3 1 3 3;5 2 6 2 0;3 4 1 1 -1];\r\nsol = infercards(5,6,5,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[6 5 4]))\r\n\r\n%% Test case #13: 4 players, 6 cards (per category)\r\nyourcards = {5,4,4};\r\ncommoncards = {[1 4],[],1};\r\nmoves = [3 2 5 4 -1;4 6 6 3 2;1 2 6 5 0;1 6 2 3 0;3 5 6 3 -1;1 2 2 6 2;4 5 2 5 -1;1 3 2 4 0;2 5 4 4 0;3 2 5 3 -1;2 2 1 6 -1;2 6 5 2 -1;4 2 6 4 0;4 2 6 3 2;2 5 1 5 0;1 5 3 5 0;4 2 1 4 0;1 6 2 5 3;1 5 1 2 0;1 5 3 5 0;3 3 1 3 0;1 2 5 5 3;4 2 2 6 0;1 3 5 4 -1;2 6 5 3 -1;1 3 2 2 3;2 5 2 2 0;3 2 4 2 -1;2 6 4 4 0;4 6 5 2 -1;1 2 5 6 -1;2 3 2 2 -1;2 6 5 4 0;1 3 2 3 2;2 2 6 5 -1;1 3 4 3 -1;2 3 6 4 0;3 2 2 5 -1;2 5 4 4 0;1 2 4 2 0;3 6 1 3 0;1 2 5 6 -1;1 5 5 6 -1;3 3 3 2 0;2 3 1 4 0;4 2 2 5 -1];\r\nsol = infercards(4,6,2,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[2 5 3]))\r\n\r\n%% Test case #14: 4 players, 5 cards (per category)\r\nyourcards = {[2 5],[],5};\r\ncommoncards = {[],[],[]};\r\nmoves = [2 2 4 3 0;4 1 1 3 2;1 5 1 5 -1;2 4 4 1 -1;2 1 4 1 -1;4 1 1 3 3;1 2 1 3 -1;2 4 5 1 -1;3 4 1 1 0;4 3 4 4 -1;2 3 2 2 -1;3 5 4 4 -1;2 1 3 5 0;1 3 2 4 1;2 2 4 3 0;3 4 2 2 0;3 4 5 3 0;1 3 2 3 2;2 3 2 2 -1;1 2 2 2 0;4 4 3 4 0;3 3 1 2 -1;4 2 2 3 0;3 4 5 4 0;4 2 3 3 0;1 1 4 2 3];\r\nsol = infercards(4,5,2,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[1 4 4]))\r\n\r\n%% Test case #15: 4 players, 4 cards (per category)\r\nyourcards = {[],[2 4],[]};\r\ncommoncards = {1,[],[]};\r\nmoves = [3 3 1 3 1;3 3 1 4 0;1 2 4 4 0;2 4 4 1 -1;4 2 1 1 -1;1 3 4 2 0;2 2 2 4 0;3 4 3 1 -1;4 3 3 1 -1;1 4 4 1 0;2 4 3 2 0;1 2 1 3 -1;2 4 1 1 -1;1 4 1 2 -1;1 4 2 4 0;3 4 4 1 -1;2 4 1 4 -1;3 3 2 3 0;2 4 4 4 -1;1 4 1 1 -1;4 4 1 1 -1;4 3 2 4 0;1 2 2 1 0;2 3 2 3 -1;2 4 1 4 -1;4 4 4 2 0];\r\nsol = infercards(4,4,1,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[4 1 1]))\r\n\r\n%% Test case #16: 5 players, 7 cards (per category)\r\nyourcards = {[3 5],[],1};\r\ncommoncards = {[6 7],[],7};\r\nmoves = [3 4 5 3 0;1 3 1 4 -1;1 5 5 2 0;2 2 4 6 -1;2 1 6 5 3;4 3 5 6 -1;4 3 2 2 -1;4 2 6 4 0;5 5 4 5 0;2 4 2 2 1;4 3 6 3 0;4 2 6 1 0;4 1 6 4 0;1 4 2 1 -1;3 2 3 6 2;5 5 3 3 0;3 5 2 3 0;4 5 5 1 -1;5 1 3 1 0;3 4 2 5 -1;5 4 4 4 -1;4 2 4 3 -1;5 2 1 6 -1;2 5 7 3 -1;1 1 1 6 -1;2 1 4 6 -1;3 1 1 4 -1;4 3 7 6 -1;1 4 3 5 -1;1 2 6 4 1;3 1 6 6 -1;5 1 3 3 -1;4 5 2 4 0;1 4 3 1 -1;3 2 1 6 -1;3 5 4 4 0;4 1 6 2 0;5 2 7 4 -1;5 2 7 6 -1;3 1 1 6 -1;5 4 1 4 -1;3 5 2 4 -1;4 1 5 6 -1;3 1 3 1 0;1 4 3 2 3;2 5 1 6 -1;3 3 2 2 -1;5 4 5 5 -1;1 1 3 6 -1;4 4 6 2 2;3 1 5 5 -1;1 1 1 1 -1;5 2 6 2 -1;2 3 4 3 -1;4 2 1 3 2;3 5 5 5 -1;3 5 6 1 -1;2 3 1 2 -1;2 3 5 3 0];\r\nsol = infercards(5,7,5,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[1 2 6]))\r\n\r\n%% Test case #17: 5 players, 6 cards (per category)\r\nyourcards = {[],[],[2 3 6]};\r\ncommoncards = {[],[],[]};\r\nmoves = [2 2 4 6 0;4 2 2 4 1;5 2 4 5 0;1 4 1 4 -1;1 5 2 2 0;2 2 6 1 -1;4 5 1 5 1;2 3 4 6 0;1 6 5 4 0;3 1 6 2 0;4 4 5 2 -1;3 5 1 4 2;2 5 6 5 -1;1 3 4 2 -1;4 6 6 6 -1;2 2 6 3 0;1 6 2 5 1;4 2 4 3 0;5 6 2 6 -1;2 6 3 3 0;3 1 3 4 0;1 3 5 1 -1;4 5 4 4 0;1 3 2 1 0;4 5 6 1 0;3 5 6 3 -1;4 3 1 4 -1;2 5 2 2 0;3 3 2 4 -1;2 1 2 3 0;2 3 5 4 -1;1 1 4 1 -1;2 3 6 4 -1;3 4 2 2 -1;4 5 2 1 0;2 3 5 6 0;3 3 2 1 3;2 4 5 3 0;2 3 5 3 0;1 4 2 4 0;5 1 3 4 -1;1 2 4 1 -1;4 4 2 3 -1;3 4 6 1 0;1 5 6 4 -1;5 5 1 3 -1;4 5 5 4 1;5 4 6 4 -1];\r\nsol = infercards(5,6,2,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[4 6 4]))\r\n\r\n%% Test case #18: 7 players, 7 cards (per category)\r\nyourcards = {[],3,2};\r\ncommoncards = {[],5,[1 3 4]};\r\nmoves = [2 3 6 2 -1;1 7 3 2 -1;5 4 7 6 0;6 2 7 5 1;2 4 4 7 0;4 7 1 2 0;3 2 2 5 -1;6 3 1 5 -1;4 2 3 5 0;2 6 7 6 0;1 4 1 7 -1;7 3 2 6 0;2 3 7 7 0;4 7 6 2 0;2 7 3 6 0;4 5 6 2 0;7 6 4 6 0;1 3 7 7 -1;7 3 1 2 0;7 3 3 6 0;3 7 7 7 0;3 4 1 6 0;1 5 4 2 -1;7 6 7 7 -1;2 4 4 5 -1;1 4 3 6 -1;4 4 6 7 -1;4 7 1 2 0;7 5 2 7 -1;5 7 3 5 -1;2 4 4 5 -1;2 6 2 6 3;6 7 2 2 -1;1 6 1 7 0;2 2 7 5 -1;6 5 2 7 0;7 5 6 2 -1;2 1 3 7 0;7 3 2 7 1;7 6 2 6 -1;5 6 1 6 -1;4 2 1 6 -1;5 5 7 5 0;5 5 2 2 -1;5 1 7 5 0;3 5 4 6 -1;4 1 2 2 0;1 1 7 2 0];\r\nsol = infercards(7,7,4,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[4 2 5]))\r\n\r\n%% Test case #19: 5 players, 6 cards (per category)\r\nyourcards = {4,4,6};\r\ncommoncards = {[],[],[]};\r\nmoves = [2 3 5 1 0;4 5 3 1 -1;1 2 2 2 0;3 3 2 4 -1;4 6 4 4 0;2 6 2 1 -1;1 4 2 3 -1;4 5 6 6 0;3 3 6 3 -1;2 3 2 6 0;5 5 6 5 0;1 2 6 2 0;4 1 1 2 -1;1 2 3 1 -1;1 1 3 2 0;5 6 6 5 0;4 4 3 3 0;5 1 6 5 0;3 1 1 4 -1;2 4 4 4 0;5 2 2 6 -1;4 5 1 1 -1;1 4 2 2 0;1 6 1 4 2;3 1 3 2 0;2 4 4 3 -1;1 1 2 1 0;5 1 2 5 -1;2 2 5 3 -1;3 4 5 5 0;3 2 6 4 -1;4 5 4 3 0;4 4 2 5 0;2 5 6 5 3;4 2 5 6 0;4 2 2 6 0;5 1 3 3 -1];\r\nsol = infercards(5,6,4,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[2 2 3]))\r\n\r\n%% Test case #20: 6 players, 8 cards (per category)\r\nyourcards = {[3 4 6],[],[]};\r\ncommoncards = {[],[1 3 5],[]};\r\nmoves = [5 6 8 1 -1;4 5 6 1 0;4 8 6 8 0;6 8 7 2 -1;3 3 6 8 -1;1 7 8 5 -1;3 6 2 5 0;1 3 2 7 0;2 4 7 3 -1;3 2 4 2 0;3 1 8 4 0;2 1 6 8 -1;2 8 8 2 0;5 6 4 5 0;1 6 7 5 -1;2 7 7 7 0;1 7 2 7 0;5 1 4 5 2;5 8 8 6 0;5 8 6 1 -1;4 5 7 3 0;1 1 4 4 -1;6 6 7 7 0;2 8 8 4 2;5 2 8 6 0;5 6 7 7 -1;4 4 7 6 -1;3 7 7 8 -1;1 4 6 4 -1;4 1 7 4 -1;3 1 2 4 0;6 1 2 2 -1;2 3 8 4 0;2 4 7 2 -1;1 5 2 5 -1;5 1 6 1 -1;4 4 8 5 -1;4 1 2 3 -1;2 8 6 8 -1;3 8 8 5 -1;2 5 8 8 0;5 8 6 5 -1;4 1 4 4 -1;3 3 7 6 -1;1 8 8 1 -1;3 6 2 7 0;3 2 6 3 0;4 5 6 2 2;4 4 2 4 -1;5 6 4 2 0;1 4 8 8 0;5 6 7 5 -1;3 2 2 1 0;5 1 8 2 3;6 5 7 5 -1;4 8 6 8 0;5 4 6 1 -1;1 6 4 7 0;2 6 2 4 0];\r\nsol = infercards(6,8,6,yourcards,commoncards,moves);\r\nassert(isequal(sol(:)',[8 7 5]))","published":true,"deleted":false,"likes_count":12,"comments_count":5,"created_by":287,"edited_by":287,"edited_at":"2025-11-14T17:50:41.000Z","deleted_by":null,"deleted_at":null,"solvers_count":56,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2025-11-04T20:44:39.000Z","updated_at":"2026-02-24T14:43:50.000Z","published_at":"2025-11-10T02:24:19.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[Warning: this is a nontrivial programming problem]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWorried about the decline in reasoning skills in the clueless populace of Nedland, Lord Ned had the finest minds at the University of \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003eNedsburg\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e develop a fun game to sharpen logical inference skills.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe game consists of a deck of 3\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e cards, with \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e cards in each of three categories.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"439\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"600\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOne card from each category is randomly selected and these three cards are placed, unseen, in an envelope. The goal of the game is for the players to figure out which cards are in the envelope.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"306\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"700\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId2\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe remaining 3(\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e-1) cards are shuffled together and then dealt to the players. Every player receives the same number of cards; any leftover cards are placed face-up so that all players can see them. Because all the cards are shuffled together, the players will not all have an equal distribution of cards from the three categories.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"383\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"700\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId3\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ePlayers take it in turns to ask any other player about three cards, one from each category. If the player asked has any of the cards asked for, they must show one of those cards to the player who asked. (If they have more than one of the specified cards, they can choose which card to show.) The other players do not get to see which card has been shown, but they do know which three cards were asked for and that the player asked had one of them. If the player asked has none of the cards asked for, they simply state this and do not have to show any of their cards.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOnce a player believes they have deduced the identity of the three cards in the envelope, they can, on their turn, announce their guess, then check the cards in the envelope. If the player is correct, they can reveal the cards as proof and they win the game. If not, they are eliminated. They must return the cards to the envelope, and the game continues without them.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWrite a function that takes information about a game as inputs and returns the solution (that is, the deduced identity of the cards in the envelope) as output.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe inputs to the function are:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003em\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, the number of players\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, the number of cards in each category\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003epnum\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, which player you are (from 1 to \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003em\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e). Players take turns in order (1 to \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003em\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, and back to 1). If a card is revealed and it is your turn, you know the exact identity of that card. If it is not your turn, you know only that one of the cards asked for was revealed.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eyourcards\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, a 3-element cell array representing the cards dealt to you. Each cell contains the cards for one category. The cards from that category are given as a vector of values from 1 to \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e. If there are no cards for that category, the cell will contain an empty vector. In the example image, if you are the player in the bottom left (player 4), \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eyourcards = {[1 3],[],[]}\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e. If instead you are the player in the bottom right (player 3), \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eyourcards = {[],[4],[2]}\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ecommoncards\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, a 3-element cell array representing the extra cards visible to everyone. The format is the same as for \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eyourcards\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e. In the example image, \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ecommoncards = {[],[3],[]}\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eturns\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, an \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ent\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e-by-5 matrix representing \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ent\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e turns of the game. Each row of \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eturns\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e records one player's turn as a 5-element vector. The first value is the number of the player asked. The next three values are the cards asked for, one for each category in order. The final value is the result: -1 represents the asked player responding that they do not have any of the requested cards; 0 represents the asked player showing a card (but you do not know which specific card); a value of 1-3 represents the asked player showing you a specific card, where the value is the index (or, equivalently, category) of the three cards asked for. For example, a row of \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eturns\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e that was the vector \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[5 4 3 2 1]\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e would represent player 5 being asked for card 4 in category 1, card 3 in category 2, and card 2 in category 3, and showing you card 4 of category 1.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe output should be a single 3-element vector of the cards in the envelope, in order. For the example image, the output would be \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[4 2 1]\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eAssumptions\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe game is still new to \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003eNedland\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, so don't expect the players to make the best requests on their turn, but the solution can be inferred from the inputs given. It may be possible to determine the solution from less information than is given, but the information given will always be sufficient.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAlthough it shouldn't matter for your implementation, the official rules have 4-8 players (\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003em\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e) and card decks with up to 8 cards in each category (\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e), using at least enough cards to ensure that each player gets at least two cards in their hand.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eExample\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor the example images, \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003em\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e = 4, \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e = 4. Suppose \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003epnum\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e = 4, in which case \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eyourcards = {[1 3],[],[]}\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e and \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ecommoncards = {[],[3],[]}\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[moves = 12×5\\n3 1 4 3 0\\n1 3 4 4 0\\n2 3 1 3 0\\n1 4 2 2 -1\\n4 3 1 1 0\\n3 2 2 2 0\\n2 1 1 4 0\\n2 4 2 3 3\\n3 3 2 1 -1\\n1 4 4 2 -1\\n2 4 2 1 -1\\n1 2 2 4 1]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIn the first turn, player 1 asks player 3 for cards \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[1 4 3]\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e (that is, card 1 from category 1, card 4 from category 2, and card 3 from category 3). Player 3 shows them a card but you, player 4, don't know which. You have the first card in your hand, so it must have been one of the other two, but so far no further information can be extracted.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eSimilarly, player 2 then asks player 1 for cards \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[3 4 4]\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e and is shown one. Again, you hold the first card, so player 1 must have either card 4 from category 2 or card 4 from category 3, but you don't yet know which.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOn the fourth turn, you ask player 1 for cards \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[4 2 2]\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, but player 1 has none of these.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eMore turns occur where you cannot determine any concrete information yet.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOn the eight turn, things suddenly get interesting. You ask player 2 for \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[4 2 3]\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e and are shown the third of these. That is, you know that player 2 holds card 3 from category 3.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eMoreover, this makes some of the earlier turns more useful. Revisiting the first turn where player 3 was asked for \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[1 4 3]\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, you now know that you held the first card and player 2 held the third card. The card that player 3 showed player 1 must therefore be the second card, so now you know that player 3 has card 4 from category 2.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAnd similarly, now you can deduce from turn 2 that player 1 has card 4 from category 3 (because you hold the first card and player 3 holds the second card). And again from turn 7, you can now deduce that player 2 has card 1 from category 2, using the same logic.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAt this point, you now know both cards that player 2 holds, so you can eliminate all other cards from possibly being held by them.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eYou also now know the locations of three of the four cards in category 2: player 2 has card 1, the common card is card 3, and player 3 has card 4. That means the remaining card (2) is in the envelope.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eTurn 9 tells you that player 3 does not have card 1 from category 3. The next two turns provide no new information.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFinally, turn 12 reveals that player 1 has card 2 from category 1. This means you now know both cards player 1 holds (2 from category 1 and 4 from category 3). Consequently, you know that no player has card 1 from category 3 (you know both cards held by players 1 and 2, you know player 3 doesn't have it, you don't have it, and it's not the common card), so it must be in the envelope.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis just leaves category 1 but you now know the location of three of the four cards (you have cards 1 \u0026amp; 3, player 1 has card 2). And so you have the solution: \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[4 2 1]\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[soln = infercards(m,n,pnum,yourcards,commoncards,moves)\\nsoln =\\n4 2 1]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eImplementation Suggestions/Tips\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOne way to find the solution is to keep an array of all cards and all players, with values indicating your state of knowledge about whether that player has that card: unknown, yes, or no. Start with everything unknown, and fill in information as you go. For this tracking, you can treat the common cards as player \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003em\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e+1. Each category has one card that nobody has, which is the card in the envelope. Once you have identified that card for each category, you have your solution.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eYou start with complete knowledge of which cards you and the common \\\"player\\\" do and do not have.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGo through the turns and use the provided information to update your state of knowledge. Also use the following observations to extend the logic to find new information:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIf you know a player has a card, you know all other players do not.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eYou know how many cards each player has: the same number that you have. Equivalently, you can calculate it: \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003encards = floor(3*(n-1)/m)\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e. If you know the identities of \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003encards\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e cards for a player, you know they have no other cards. (The common cards are an exception, but this doesn't matter because you already know exactly what cards are and are not in the common set.)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOnce you know the locations of (\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e-1) cards in a category, the remaining card must be in the envelope.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eEach player holds \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003encards\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e cards. If you can identify 3\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e-\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003encards\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e cards that a player definitely does \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:u/\u003e\u003c/w:rPr\u003e\u003cw:t\u003enot\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e hold, then they must hold the remaining \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003encards\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e cards. That is, if the no, yes, and maybe/unknown cards for a player are distributed such that there are \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003encards\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e yes or maybe (and 3\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e-\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003encards\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e no), then all the remaining maybes are yeses.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eRemember that, as in the example, new information disclosed in a turn may make previous turns more 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