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Using logicals in arrayfun

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Hi,
I have two arrays:
tempA, size(10, 18)
tempB, size(1, 10) (is a column vector),
For each row in tempA, I want to extract the number of columns specified for that row by tempB. However, there are certain rows in tempB that are 'nan'.
u = arrayfun(@(x,y) x{1}(1:y), tempA, tempB, 'UniformOutput', false);
Can I use logical in the arrayfun so that it automatically excludes cases that are 'nan'?
Thank you

Accepted Answer

Walter Roberson
Walter Roberson on 6 Jul 2024
Edited: Walter Roberson on 6 Jul 2024
u = arrayfun(@(x,y) x{1}(1:max(0,y)), tempA, tempB, 'UniformOutput', false);
The secret here is that max(0,VALUE) is 0 if VALUE is nan. 1:0 is then empty, and indexing by empty is well-defined as being empty.
  3 Comments
Paul
Paul on 6 Jul 2024
Missing a parenthesis after (0,y), but, that aside, u will contain cell elements that are empty arrays, if that's o.k. I thought those cases are to be excluded from the result.
Walter Roberson
Walter Roberson on 6 Jul 2024
Fixed the missing ) thanks!

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More Answers (1)

Paul
Paul on 6 Jul 2024
rng(100)
tempA = rand(10,18);
tempB = 1:10;
u = arrayfun(@(x,y) x{1}(1:y), num2cell(tempA,2), tempB.', 'UniformOutput', false)
u = 10x1 cell array
{[ 0.5434]} {[ 0.2784 0.2092]} {[ 0.4245 0.1853 0.8176]} {[ 0.8448 0.1084 0.3361 0.3819]} {[ 0.0047 0.2197 0.1754 0.0365 0.2100]} {[ 0.1216 0.9786 0.3728 0.8904 0.5447 0.3402]} {[ 0.6707 0.8117 0.0057 0.9809 0.7691 0.1781 0.6023]} {[ 0.8259 0.1719 0.2524 0.0599 0.2507 0.2377 0.3878 0.3404]} {[ 0.1367 0.8162 0.7957 0.8905 0.2859 0.0449 0.3632 0.0921 0.3131]} {[0.5751 0.2741 0.0153 0.5769 0.8524 0.5054 0.2043 0.4635 0.6340 0.6576]}
If all the odd numbered indices of tempB are nan:
tempB(1:2:end) = NaN;
u = arrayfun(@(x,y) x{1}(1:y), num2cell(tempA(~isnan(tempB),:),2), tempB(~isnan(tempB)).', 'UniformOutput', false)
u = 5x1 cell array
{[ 0.2784 0.2092]} {[ 0.8448 0.1084 0.3361 0.3819]} {[ 0.1216 0.9786 0.3728 0.8904 0.5447 0.3402]} {[ 0.8259 0.1719 0.2524 0.0599 0.2507 0.2377 0.3878 0.3404]} {[0.5751 0.2741 0.0153 0.5769 0.8524 0.5054 0.2043 0.4635 0.6340 0.6576]}
  1 Comment
Rashi Monga
Rashi Monga on 6 Jul 2024
thank you for your response! this was helpful. :)

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