I would like to ensure that the input arguments to a user-defined MATLAB function (contained in an m-file) are of a certain type. I understand that MATLAB automatically assigns data types to variables (to the liking of some and the dismay of others), but I would like to know if there is an option of "strict data typing" in MATLAB, or something of the sort, especially for input arguments for a user-defined function.
I found a helpful explanation of MATLAB's "fundamental classes" (data types) at these two webpages:
http://www.mathworks.com/help/matlab/matlab_prog/fundamental-matlab-classes.html
http://www.mathworks.com/help/matlab/data-types_data-types.html
However, I have been unable to find an answer to the question of strict data typing, particularly for function input arguments. I thought it would be a pretty basic question that already had been answered in numerous places, but after extensive searching I have not yet found a conclusive answer. For now, I have been manually checking the data type using the is[TYPE]() functions and displaying an error message if it does not comply, though this seems sloppy and I wish I could just get MATLAB to enforce it for me.
Below is an example of a function in which I would like to specify the input argument data type. It resides in a file called strict_data_type_test.m in MATLAB's current path. In this function, I would like to force the variable yes_or_no to be of MATLAB's logical data type. I know I can use the islogical() function to manually check, but my question is if it is possible to have MATLAB enforce it for me. I also know that any non-zero double evaluates to true and a zero evaluates to false, but I want to force the user to send a logical to make sure the wrong argument was not sent in by accident, for example. Here is the example function:
function y = strict_data_type_test( x, yes_or_no )
% manual data type check can go here, but manual check is not desirable
if (yes_or_no)
y = 2 .* x;
else
y = -5 .* x;
end
end
Adding the data type before the input argument variable name (like in most programming languages) treats the data type text as another variable name instead of a data type identifier. From that it would seem that strict data typing is not possible in MATLAB by any means, but maybe one of you many gurus knows a useful trick, feature, or syntax that I have not been able to find.
validateattributes might also work for you, if there is an appropriate attribute for your case. For example if you want to enforce that yes_or_no is a logical scalar, you could try:
validateattributes(yes_or_no,{'logical'},{'scalar'})
Otherwise maybe an attribute like 'nonempty'.
I've gotten some great responses so I can't pick just one as the "accepted answer", but to summarize what I've learned from you all so far:
No, MATLAB does not have built-in strict data typing for function input arguments
MATLAB compiles the code before running, so manual validation checking should not be very taxing on performance (the profiler can be used to assess this)
Many helpful methods of doing the manual validation checking exist, listed here in order of most relevant to least relevant for what I was trying to do:
inputParser class
validateattributes()
Error/exception handling (throw(), error(), assert(), etc.)
MATLAB's built-in state detection functions (a.k.a predicate functions)
I can look through some MathWorks-provided MATLAB functions (or Statistics toolbox functions) for ideas on how to validate input arguments by typing edit followed by the function name. Two suggested functions to look at are normpdf() (from the Statistics toolbox) and integral(). Some other functions I found helpful to look at are dot() and cross().
Other thoughts:
It would appear that the inputParser class was the overall concensus on the most professional way to validate input arguments. It was noted on a related (but not duplicate) stackoverflow post that the newer MathWorks functions tend to make use of this class, suggesting that it may be the best and most up-to-date choice.
Since the MathWorks-provided MATLAB functions do not appear to enforce strict input argument data typing, this further suggests that even if it was possible to do so, it may not be a recommended approach.
MATLAB seems to regard "error handling" and "exception handling" as two different concepts. For example, here are two links to MATLAB's Documentation Center that show how MathWorks considers "error handling" and "exception handling" differently: MathWorks Documentation Center article on Error Handling, MathWorks Documentation Center article on Exception Handling. A relevant StackOverflow post has been made on this topic and can be found here (link). I contacted MathWorks and added some new information about this topic to that post, so if you are interested you may read more by following that link.
Matlab provides an 'inputParser' which allows to check inputs. Besides this you can use assertions:
assert(islogical(yes_or_no),'logical input expected')
To ensure the correct number of input arguments, use narginchk.
btw: Take a look in some Matlab functions like edit integral and check how tmw deals with this.
You may find writing this sort of code tedious or worry that it degrades performance:
if ~islogical(yes_or_no) && ~isscalar(yes_or_no)
error('test:NotLogicalType','Second argument must be logical (Boolean).');
end
if yes_or_no
y = 2 .* x;
else
y = -5 .* x;
end
Recall, however, that Matlab compiles the code before running so even if you need to test many conditions it will be quite fast. Run the profiler to see.
Another option in some cases (maybe not your example) is to use a lazier method. This option lets your code run with whatever inputs were provided, but uses a try/catch block to trap any error:
try
if yes_or_no
y = 2 .* x;
else
y = -5 .* x;
end
catch me
...
error('test:NotLogicalType','Second argument must be logical (Boolean).');
% rethrow(me);
end
The code above would produce an error if yes_or_no was a cell array for example (it will still allow non-Boolean, non-scalar, etc. values for yes_or_no though, but Matlab is often overly permissive). You can then either generate a custom error message, detect, what kind of error was thrown and try something else, etc. Many of the functions in the Statistics toolbox use this approach (e.g., type edit normpdf in your command window) for better or worse.
Related
I forgot commas between some returns of a function in MATLAB and it did not complain.
function [returnA, returnB]=foo(paramA)
returnA=ones(1,10).*paramA;
returnB=magic(4);
end
function[]=voo()
%typing the return as this
[A,B]=foo(5);
%gives the same result as
[A B]=foo(5);
end
My question is: is it exactly the same behavior? I was not able to find it in documentation
Yes, it is the same behavior, as seen with the code you provide in your question.
As #LuisMendo points out in the comments, if you look at the MATLAB's lint (aka Code Analyzer) message in the editor you'll see:
Best practice is to separate output variables with commas
Which implies that both syntaxes are valid. As to why this is the case I'm not sure, and I can't really find anything specific which tends to point towards "just because." As #rayryeng points out in the comments, it could also have to do with aligning syntax with MATLAB's comma-separated lists.
I am writing a set of customized plot functions in MATLAB, whose aim is to ensure a more consistent look of our company charts and to be fast.
In these customized functions, I would like to reproduce MATLAB's variability in allowing multiple syntax options for function calls, similar to the syntax options available for MATLAB's plot function.
So, say my function is plotFun.m, then the following function calls should all work:
plotFun(y)
plotFun(x,y)
plotFun(ax,_)
plotFun(_,Name,Value)
I am familiar with inputParser and several other techniques to parse name-value pairs passed as varargin, yet I cannot figure out how to parse the first arguments, that is ax, x and y...
I have scanned the file exchange and found several contributions for parsing name-value pairs (somehow overlapping with the inputParser functionality), but none of them seems to do the trick in this case.
EDIT:
In reply to thewaywewalk 's comment, here are some more details regarding what the syntax options should do.
Suppose plotFun does something similar as the line function (but with other defaults and a different set of allowed options).
y should be validated to be a numerical vector
x (if present) should be validated to be a numerical or datetime vector
plotFun(x,y)
If x is of class datetime, x = datenum(x), then
call line(x,y, 'Parent',gca)
plotFun(y)
should set x = 1:numel(y), then call line(x,y, 'Parent',gca) as above
plotFun(ax,_)
should do the same as above, but call line(x,y, 'Parent',ax) instead of gca
plotFun(_,Name,Value)
should parse and validate the name-value pairs and pass them to the call of line. I solved this task with the help of inputParser.
EDIT 2
In the world of my dreams, hitting Ctrl + F1 for plotFun would show the function hints, that is, a list of allowed syntax options (like the one I typed in the code block above), as opposed to showing a more cryptic plotFun(varargin)...
I am trying to run code similar to the following, I replaced the function I had with one much smaller, to provide a minimum working example:
clear
syms k m
n=2;
symsum(symsum(k*m,m,0,min(k,n-k)),k,0,n)
I receive the following error message:
"Error using sym/min (line 86)
Input arguments must be convertible to floating-point numbers."
I think this means that the min function cannot be used with symbolic arguments. However, I was hoping that MATLAB would be substituting in actual numbers through its iterations of k=0:n.
Is there a way to get this to work? Any help much appreciated. So far I the most relevant page I found was here, but I am somewhat hesitant as I find it difficult to understand what this function does.
EDIT following #horchler, I messed around putting it in various places to try and make it work, and this one did:
clear
syms k m
n=2;
symsum(symsum(k*m,m,0,feval(symengine, 'min', k,n-k)),k,0,n)
Because I do not really understand this feval function, I was curious to whether there was a better, perhaps more commonly-used solution. Although it is a different function, there are many pieces online advising against the eval function, for example. I thought perhaps this one may also carry issues.
I agree that Matlab should be able to solve this as you expect, even though the documentation is clear that it won't.
Why the issue occurs
The problem is due the inner symbolic summation, and the min function itself, being evaluated first:
symsum(k*m,m,0,min(k,n-k))
In this case, the input arguments to sym/min are not "convertible to floating-point numbers" as k is a symbolic variable. It is only after you wrap the above in another symbolic summation that k becomes clearly defined and could conceivably be reduced to numbers, but the inner expression has already generated an error so it's too late.
I think that it's a poor choice for sym/min to return an error. Rather, it should just return itself. This is what the sym/int function does when it can't evaluate an integral symbolically or numerically. MuPAD (see below) and Mathematica 10 also do something like this as well for their min functions.
About the workaround
This directly calls a MuPAD's min function. Calling MuPAD functions from Matlab is discussed in more detail in this article from The MathWorks.
If you like, you can wrap it in a function or an anonymous function to make calling it cleaner, e.g.:
symmin = #(x,y)feval(symengine,'min',x,y);
Then, you code would simply be:
syms k m
n = 2;
symsum(symsum(k*m,m,0,symmin(k,n-k)),k,0,n)
If you look at the code for sym/min in the Symbolic Math toolbox (type edit sym/min in your Command Window), you'll see that it's based on a different function: symobj::maxmin. I don't know why it doesn't just call MuPAD's min, other than performance reasons perhaps. You might consider filing a service request with The MathWorks to ask about this issue.
Say I have a function foo that can return three values given an input:
function [a,b,c] = foo(input)
The calculations of variables b and c take a long time, so sometimes I may wish to ignore their calculation within foo. If I want to ignore both calculations, I simply call the function like this:
output1 = foo(input);
and then include nargout within foo:
if nargout == 1
% Code to calculate "a" only
else
% Code to calculate other variables
The problem occurs if I want to calculate the last output, but not the second. In that case my function call would be:
[output1,~,output3] = foo(input);
Now if I use nargout within foo to check how many outputs are in the function-call, it will always return 3 because the tilde operator (~) is considered a valid output. Therefore, I cannot use nargout to determine whether or not to calculate the second output, b, within foo.
Is there any other way to do this? I.e., is it possible to check which outputs of a function-call are discarded from within the function itself?
The commenters are basically right; this is not something that can be totally solved by the user unless The MathWorks adds functionality. However, I wrote a small function, istilde (Wayback Machine Archive), a while back that attempts to do what you ask. It works in many cases, but it's really a bit of hack and not a totally robust solution. For example, I did not attempt to get it to work for functions called from the Command Window directly (this could potentially be added with some work). Also, it relies on parsing the actual M-file, which can have issues. See the included demo file for how one might use istilde.
Feel free to edit my code for your needs – just don't use this in any production code due to the robustness issues. Any improvements would be welcome.
I've been working with matrices over GF(2) in Matlab. Well, I've been working with 0/1 matrices that I've been treating as being defined over GF(2). I was surprised/happy to see that Matlab provides some functionality in the Communications System Toolbox for working over finite fields. In particular, if I want to find the rank of a matrix over a finite field, there are a couple of methods: (1) use gfrank on the matrices that I already have defined, or (2) use rank on a Galois field array (created with gf). For matrices over GF(2), the former method seems to be significantly faster; however, there's a problem...
The documentation for gfrank says that the function doesn't work over fields of the form GF(2^m). I double checked on a toy example, and specifying GF(2) as the field to work over seems to output correct results. Moreover, the function's m-file specifies GF(2) as the default field (by specifying the second argument as 2 if nargin < 2). Something has to be wrong here, and it seems to be the documentation. However, I'd hate to assume that the documentation is wrong only to find out much later that the computation doesn't always work over GF(2^m). Does anybody know for sure what's wrong here? Thanks for your help.