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Exciting news for students! 🚀Simulink Student Challenge 2023 is live! Unleash your engineering skills and compete for exciting rewards. Submission deadline is December 12th, 2023!
Over the weekend I came across a pi approximation using durations of years and weeks (image below, Wolfram, eq. 89), accurate to 6 digits using the average Gregorian year (365.2425 days).
Here it is in MATLAB. I divided by 1 week at the end rather than multiplying by its reciprocal because you can’t divide a numeric by a duration in MATLAB (1/week).
weeks = @(n)n*days(7);
piApprox = ((years(13)-weeks(6))/years(13) + weeks(3)) / weeks(1)
% piApprox = 3.141593493469302
Here’s a breakdown
- The first argument becomes 12.885 yrs / 13 yrs or 0.99115
- Add three weeks: 0.99115 + 3 weeks = 21.991 days
- The reduced fraction becomes 21.991 days / 7 days
Now it looks a lot closer to the more familiar approximation for pi 22/7 but with greater precision!
I'm curious how the community uses the hold command when creating charts and graphics in MATLAB. In short, hold on sets up the axes to add new objects to the axes while hold off sets up the axes to reset when new objects are added.
When you use hold on do you always follow up with hold off? What's your reasoning on this decision?
Can't wait to discuss this here! I'd love to hear from newbies and experts alike!
Calling all students! New to MATLAB or need helpful resources? Check out our MATLAB GitHub for Students repository! Find MATLAB examples, videos, cheat sheets, and more!
Visit the repository here: MATLAB GitHub for Students
Imagine x is a large vector and you want the smallest 10 elements. How might you do it?
The way we've solved ODEs in MATLAB has been relatively unchanged at the user-level for decades. Indeed, I consider ode45 to be as iconic as backslash! There have been a few new solvers in recent years -- ode78 and ode89 for example -- and various things have gotten much faster but if you learned how to solve ODEs in MATLAB in 1997 then your knowledge is still applicable today.
In R2023b, there's a completely new framework for solving ODEs and I love it! You might argue that I'm contractually obliged to love it since I'm a MathWorker but I can assure you this is the real thing!
I wrote it up in a tutorial style on The MATLAB Blog https://blogs.mathworks.com/matlab/2023/10/03/the-new-solution-framework-for-ordinary-differential-equations-odes-in-matlab-r2023b/
The new interface makes a lot of things a much easier to do. Its also setting us up for a future where we'll be able to do some very cool algorithmic stuff behind the scenes.
Let me know what you think of the new functionality and what you think MathWorks should be doing next in the area of ODEs.
The MATLAB Answers community is an invaluable resource for all MATLAB users, providing selfless assistance and support. However, with the emergence of AI-based chatbots, like chatGPT, there may be concerns about the future relevance and utility of the MATLAB Answer community. What are your thoughts?
I've now seen linear programming questions pop up on Answers recently, with some common failure modes for linprog that people seem not to understand.
One basic failure mode is an infeasible problem. What does this mean, and can it be resolved?
The most common failure mode seems to be a unbounded problem. What does this mean? How can it be avoided/solved/fixed? Is there some direction I can move where the objective obviously grows without bounds towards +/- inf?
Finally, I also see questions where someone wants the tool to produce all possible solutions.
A truly good exposition about linear programming would probably result in a complete course on the subject, and Aswers is limited in how much I can write (plus I'll only have a finite amount of energy to keep writing.) I'll try to answer each sub-question as separate answers, but if someone else would like to offer their own take, feel free to do so as an answer, since it has been many years for me since I learned linear programming.
Introduction
Comma-separated lists are really very simple. You use them all the time. Here is one:
a,b,c,d
That is a comma-separated list containing four variables, the variables a, b, c, and d. Every time you write a list separated by commas then you are writing a comma-separated list. Most commonly you would write a comma-separated list as inputs when calling a function:
fun(a,b,c,d)
or as arguments to the concatenation operator or cell construction operator:
[a,b,c,d]
{a,b,c,d}
or as function outputs:
[a,b,c,d] = fun();
It is very important to understand that in general a comma-separated list is NOT one variable (but it could be). However, sometimes it is useful to create a comma-separated list from one variable (or define one variable from a comma-separated list), and MATLAB has several ways of doing this from various container array types:
struct_array.field % all elements
struct_array(idx).field % selected elements
cell_array{:} % all elements
cell_array{idx} % selected elements
string_array{:} % all elements
string_array{idx} % selected elements
Note that in all cases, the comma-separated list consists of the content of the container array, not subsets (or "slices") of the container array itself (use parentheses to "slice" any array). In other words, they will be equivalent to writing this comma-separated list of the container array content:
content1, content2, content3, .. , contentN
and will return as many content arrays as the original container array has elements (or that you select using indexing, in the requested order). A comma-separated list of one element is just one array, but in general there can be any number of separate arrays in the comma-separated list (zero, one, two, three, four, or more). Here is an example showing that a comma-separated list generated from the content of a cell array is the same as a comma-separated list written explicitly:
>> C = {1,0,Inf};
>> C{:}
ans =
1
ans =
0
ans =
Inf
>> 1,0,Inf
ans =
1
ans =
0
ans =
Inf
How to Use Comma-Separated Lists
Function Inputs: Remember that every time you call a function with multiple input arguments you are using a comma-separated list:
fun(a,b,c,d)
and this is exactly why they are useful: because you can specify the arguments for a function or operator without knowing anything about the arguments (even how many there are). Using the example cell array from above:
>> vertcat(C{:})
ans =
1
0
Inf
which, as we should know by now, is exactly equivalent to writing the same comma-separated list directly into the function call:
>> vertcat(1,0,Inf)
ans =
1
0
Inf
How can we use this? Commonly these are used to generate vectors of values from a structure or cell array, e.g. to concatenate the filenames which are in the output structure of dir:
S = dir(..);
F = {S.name}
which is simply equivalent to
F = {S(1).name, S(2).name, S(3).name, .. , S(end).name}
Or, consider a function with multiple optional input arguments:
opt = {'HeaderLines',2, 'Delimiter',',', 'CollectOutputs',true);
fid = fopen(..);
C = textscan(fid,'%f%f',opt{:});
fclose(fid);
Note how we can pass the optional arguments as a comma-separated list. Remember how a comma-separated list is equivalent to writing var1,var2,var3,..., then the above example is really just this:
C = textscan(fid,'%f%f', 'HeaderLines',2, 'Delimiter',',', 'CollectOutputs',true)
with the added advantage that we can specify all of the optional arguments elsewhere and handle them as one cell array (e.g. as a function input, or at the top of the file). Or we could select which options we want simply by using indexing on that cell array. Note that varargin and varargout can also be useful here.
Function Outputs: In much the same way that the input arguments can be specified, so can an arbitrary number of output arguments. This is commonly used for functions which return a variable number of output arguments, specifically ind2sub and gradient and ndgrid. For example we can easily get all outputs of ndgrid, for any number of inputs (in this example three inputs and three outputs, determined by the number of elements in the cell array):
C = {1:3,4:7,8:9};
[C{:}] = ndgrid(C{:});
which is thus equivalent to:
[C{1},C{2},C{3}] = ndgrid(C{1},C{2},C{3});
Further Topics:
MATLAB documentation:
Click on these links to jump to relevant comments below:
Dynamic Indexing (indexing into arrays with arbitrary numbers of dimensions)
Summary
Just remember that in general a comma-separated list is not one variable (although they can be), and that they are exactly what they say: a list (of arrays) separated with commas. You use them all the time without even realizing it, every time you write this:
fun(a,b,c,d)
Similar to what has happened with the wishlist threads (#1 #2 #3 #4 #5), the "what frustrates you about MATLAB" thread has become very large. This makes navigation difficult and increases page load times.
So here is the follow-up page.
What should you post where?
Next Gen threads (#1): features that would break compatibility with previous versions, but would be nice to have
@anyone posting a new thread when the last one gets too large (about 50 answers seems a reasonable limit per thread), please update this list in all last threads. (if you don't have editing privileges, just post a comment asking someone to do the edit)
After reading Rik's comment I looked for a list of Matlab releases and their corresponding features. Wiki: Matlab contains an exhaustive list, but what about having a lean version directly in the forum?
If this is useful, feel free to expand the list and to insert additions. Thank you.
There are multiple ways to create a graphical user interface (GUI) in Matlab. Which method is the best depends on multiple factors: the complexity of the project, to what extent it should be a long-term solution, on what releases your GUI should work, your available time, your skill level, and probably other factors I'm forgetting.
To keep the thread clear I'll attempt to provide a short outline a few ways in this question, and leave the details for the answers. (@anyone with editing privileges: feel free to update the section below if I missed something important and am slow in editing this question)
---------------------------------------------------------------------------------------------------
GUIDE
GUIDE is probably the first tool new users will encounter. It is very useful for quickly putting something together, but it is otherwise fairly limited. It requires maintaining (and distributing) both a .m and a .fig file. Note that the GUIDE environment will be removed in a future release. After GUIDE is removed, existing GUIDE apps will continue to run in Matlab but they will not be editable in GUIDE. If you're starting a new GUI, don't use GUIDE. If you're updating an existing GUIDE GUI, migrate it to AppDesigner. In R2021a the first step for this removal was taken: all templates except the blank template have been removed.
GUILT
Although I haven't had a detailed look myself, it seems a list like this is not complete without at least mentioning the GUI Layout Toolbox, which is available on the file exchange and offers a lot of customization options.
Programmatic GUIs
You can bypass GUIDE and use the normal figures and functions like uicontrol to build GUIs from code. This makes the design less visual, but more flexible for future additions.
App Designer
The official successor to GUIDE, AppDesigner is not based on functions, but works similar to a class. It uses uifigure and mostly uses graphical elements that are incompatible with 'normal' GUIs that are created with a figure (or .fig).
Dear MATLAB community,
How can I help my close friend who's bad at math and programming learn MATLAB?
He's a final year chemical engineering student who struggles even to plot two functions on the same graph in his computational fluid dynamics class (there was no prereq for matlab skills).
In his first year, I saw him get dragged through the introductory engineering classes which was his first encounter with MATLAB. Students were taught a few rudimentary programming skills and then were expected to make a code for a 'simple' tic-tac-toe game. It took him hours of blank looks and tutoring to even understand the simplest of boolean operators. He was never able to write a working function without the supervision of a friend or tutor. Needless to say, he was permanently scarred by the experience and swore to avoid using it forever.
After 3 years of avoiding MATLAB, he realised how not knowing it hurt him during his final year project. He had to solve a system of pdes to model the performance of a reactor and practically speaking, MATLAB was the most suitable software at hand. He ended up having to get a friend to help him code the equations in while also having to oversimplify his model.
The weird thing is that: most students from his chemical engineering faculty were not expected or encouraged to use MATLAB, almost all of their prior assignments required no use of MATLAB except that infamous first year course, and most of his peers also avoided using MATLAB and resorted to Excel. It is my understanding that Excel cannot match MATLAB's efficiency and clarity when solving calculus problems so it was not uncommon to see extremely long Excel spreadsheets.
Anyway, my friend is, with the help of a friend's past year MATLAB codes, trying to finish up his computational fluid dynamics assignment that's due soon. He finishes university in 2 weeks time.
Even though he knows that not every engineer has to use MATLAB in the workplace, he somehow wishes he was able to learn MATLAB at his glacial pace. I find it such a pity that he was never able to keep up with the pace of learning that was expected which begs the question: are students who are too slow at learning programming better of in a different field of study?
If you've managed to read to the end of this, thank you so much. I just don't know how to help my friend and I'm hoping some of you might be able to suggest how I can help him be better at it. I believe he has potential but needs special help when it comes to MATLAB.
All helpful and constructive suggestions considered,
Thank You All
Hi there! This is kind of an unusual question, but here it goes. I am a big time Matlab enthusiast and I met some of your representatives at Formula Student Germany back in August. There was a booth were your product was showcased but most importantly there was Matlab merchandise such as stickers, rub-on-tattoos and pens with the mathworks logo being handed out. This merchandise is increadibly popular with me and my nerdy friends. But sadly I didnt bring much with me from the event. Is it possible to get ahold some of it? Is it for sale? Are you willing to sponsor some geeky engineering students?
I am new in MATLAB programming. I want to learn matlab . I want to know about is any matlab or simulink contest available. Please answer me. Thanks
Summary:
Dynamically accessing variable names can negatively impact the readability of your code and can cause it to run slower by preventing MATLAB from optimizing it as well as it could if you used alternate techniques. The most common alternative is to use simple and efficient indexing.
Explanation:
Sometimes beginners (and some self-taught professors) think it would be a good idea to dynamically create or access variable names, the variables are often named something like these:
- matrix1, matrix2, matrix3, matrix4, ...
- test_20kmh, test_50kmh, test_80kmh, ...
- nameA, nameB, nameC, nameD,...
Good reasons why dynamic variable names should be avoided:
- Slow
- Buggy
- Security Risk
- Difficult to Work With
- Obfuscated Code Intent
- Confuses Data with Code
- Code Helper Tools do not Work
- Magically Making Variables Appear in a Workspace is Risky
There are much better alternatives to accessing dynamic variable names:
- Indexing into Cell Array or ND-Array
- Non-scalar Structures (with Indexing)
- Dynamic Field-Names in a Structure
- load into a Structure, not into the Workspace
- save the Fields of a Scalar Structure
- Use a table or timetable Array
- Use more Efficient Ways to Pass Variables Between Workspaces
Note that avoiding eval (and assignin, etc.) is not some esoteric MATLAB restriction, it also applies to many other programming languages as well:
MATLAB Documentation:
If you are not interested in reading the answers below then at least read MATLAB's own documentation on this topic Alternatives to the eval Function, which states "A frequent use of the eval function is to create sets of variables such as A1, A2, ..., An, but this approach does not use the array processing power of MATLAB and is not recommended. The preferred method is to store related data in a single array." Data in a single array can be accessed very efficiently using indexing.
Note that all of these problems and disadvantages also apply to functions load (without an output variable), assignin, evalin, and evalc, and the MATLAB documentation explicitly recommends to "Avoid functions such as eval, evalc, evalin, and feval(fname)".
The official MATLAB blogs explain why eval should be avoided, the better alternatives to eval, and clearly recommend against magically creating variables. Using eval comes out at position number one on this list of Top 10 MATLAB Code Practices That Make Me Cry. Experienced MATLAB users recommend avoiding using eval for trivial code, and have written extensively on this topic.
The community is very helpful, yet I feel really powerless that I cannot find the appropriate way to code, nor find the problems with the codes I have written. I have read numerous books on MATLAB, mostly related with science and engineering applications. Any advice to improve would be greatly appreciated. Thanks.
Some of Matlab's toolbox functions are affected by magic strings or magic numbers, which are strings or numbers with a deeper meaning besides the normal value. Both are considered as bad programming patters, because they provoke confusions, when the magic keys appear with the normal meaning by accident. See http://en.wikipedia.org/wiki/Anti-pattern
Example 1:
clear('myVariable')
clear('variables')
While the 1st clears the variable myVariable, the later clears all variables. Here 'variables' has a meta-meaning. The problem appears, when 'variables' is an existing variable:
a = 1;
variables = 2;
clear('variables')
disp(a) % >> 1
Only variables is cleared, which cannot be understood directly when its definition is 1000 lines before.
Example 2:
uicontrol('String', 'default')
This creates a button with the empty string '' instead of the expected 'default', because this is the magic string to invoke the default value get(0, 'DefaultUIControlString'). The same concerns properties of other graphic objects also, e.g. the 'name' property of figure or the string of uimenu. There is a workaround which allows the user to display 'default': Simply use '\default'. Unfortunately this is doubled magic, because in consequence it is impossible to display the string '\default'. Obviously a bad idea.
Example 3:
Graphic handles are doubles (although gobject of the new R2013a seems, like this is subject to changes? [EDITED: Yes, it changed with HG2 in R2014a]). But then a handle can be confused with data:
a = axes; % e.g. 0.0048828125
plot(a, 2, '+')
But you cannot draw the point [0.0048828125, 2] by this way, because the 1st input is considered as handle of the parent. Here all possible values of handles are magic. Collisions are very unlikely, but there is no way to avoid them reliably - as long as handles have the type double.
Question:
Which functions are concerned by magic values? What are the pitfalls and workarounds?
How do I can delete my account?
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