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For some time now, this has been bugging me - so I thought to gather some more feedback/information/opinions on this.
What would you classify Recursion? As a loop or as a vectorized section of code?
For context, this query occured to me while creating Cody problems involving strict (so to speak) vectorization - (Everyone is more than welcome to check my recent Cody questions).
To make problems interesting and/or difficult, I (and other posters) ban functions and functionalities - such as for loops, while loops, if-else statements, arrayfun() and the rest of the fun() family functions. However, some of the solutions including the reference solution I came up with for my latest problem, contained recursion.
I am rather divided on how to categorize it. What do you think?
Have you ever been enrolled in a course that uses an LMS and there is an assignment that invovles posting a question to, or answering a question in, a discussion group? This discussion group is meant to simulate that experience.
The functionality would allow report generation straight from live scripts that could be shared without exposing the code. This could be useful for cases where the recipient of the report only cares about the results and not the code details, or when the methodology is part of a company know how, e.g. Engineering services companies.
In order for it to be practical for use it would also require that variable values could be inserted into the text blocks, e.g. #var_name# would insert the value of the variable "var_name" and possibly selecting which code blocks to be hidden.
Modern engineering requires both robust hardware and powerful simulation tools. MATLAB and Simulink are widely used for data analysis, control design, and embedded system development. At the same time, Kasuo offers a wide range of components—from sensors and connectors to circuit protection devices—that engineers rely on to build real-world systems.
By combining these tools, developers can bridge the gap between simulation and implementation, ensuring their designs are reliable and ready for deployment.
Example Use Case: Sensor Data Acquisition and Processing
- Kasuo Hardware Setup
- Select a Kasuo sensor (e.g., temperature, microphone, or motion sensor).
- Connect it to a DAQ or microcontroller board for data collection.
- Data Acquisition in MATLAB
- Use MATLAB’s Data Acquisition Toolbox to stream sensor data directly.
- Example snippet:
s = daq("ni");
addinput(s,
"Dev1", "ai0", "Voltage");
data = read(s, seconds(
5), "OutputFormat", "Matrix");
plot(data);
- Signal Processing with Simulink
- Build a Simulink model to filter noise, detect anomalies, or design control logic.
- Simulink enables real-time visualization and iterative tuning.
- Validation & Protection Simulation
- Add Kasuo’s circuit protection components (e.g., TVS diodes, surge suppressors) in the physical design.
- Use Simulink to simulate stress conditions, validating system robustness before hardware testing.
Benefits of the Workflow
- Faster prototyping with MATLAB & Simulink.
- Greater reliability by incorporating Kasuo protection devices.
- Seamless transition from model to hardware implementation.
Conclusion
Kasuo’s electronic components provide the hardware foundation for many embedded and signal processing applications. When combined with MATLAB and Simulink, engineers can design, simulate, and validate systems more efficiently—reducing risks and development time.
With AI agents dev coding on other languages has become so easy.
Im waiting for matlab to build something like warp but for matlab.
I know they have the current ai but with all respect it's rubbish compared to vibe coding tools in others sectors.
Matlab leads AI so it really should be leading this space.
When you compare MATLAB Plot Gallery with matplotlib gallery, you can see that matplotlib gallery contains a lot of nice graphs which are easy to create in MATLAB but not listed in MATLAB Plot Gallery.
For example, "Data Distribution Plots" section in the MATLAB Plot Gallery includes example for pie function instead of examples for piechart and donutchart functions, etc.
mlapp being a binary is a pain point for source control. It means that you either have to:
- have hooks in your source control system to zip/unzip a mlapp. However, The Mathworks have informed users not to rely on this as the mlapp format may change.
- do all your source control in MATLAB. This is non standard behaviour. Source code and source control should be independent of each other. Web front-ends to source control systems, 3rd party source control apps, CI/CD systems and much more are extremely limited in what they can do with mlapps.
I wish an mlapp could just be a directory full of the required text/other files.
Requested to post this here from reddit.
There is no call to rescan audio devices in audioPlayerRecorder, even though PortAudio has such a call. I have a measurement environment that takes a long time to initialise. If I forget to plug in my audio device, I have to do it all over again...
Share your ideas, suggestions, and wishlists for improving MathWorks products. What would make the software absolutely perfect for you? Discuss your idea(s) with other community users.
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Hey cody fellows :-) !
I recently created two problem groups, but as you can see I struggle to set their cover images :
What is weird given :
- I already did it successfully twice in the past for my previous groups ;
- If you take one problem specifically, Problem 60984. Mesh the icosahedron for instance, you can normally see the icon of the cover image in the top right hand corner, can't you ?
- I always manage to set cover images to my contributions (mostly in the filexchange).
I already tried several image formats, included .png 4/3 ratio, but still the cover images don't set.
Could you please help me to correctly set my cover images ?
Thank you.
Nicolas
Nice to have - function output argument provide code assist when said function is called
This is a feature which doesn't apear to currently exist, but I think alot of matlab users would like, particularly ones who write alot of custom classes.
Imagine i have a custom class with some properties:
classdef CustomClass < handle
properties
name (1,1) string = "default name"
varOne (1,1) double = 0
end
methods
function obj = CustomClass(name,varOne)
obj.name = name;
obj.VarOne = varOne;
end
end
end
Then imagine I have a function which returns one of these custom class objects:
function [obj] = Calculation(Var1,Var2,name)
arguments (Input)
Var1 (1,1) double
Var2 (1,1) double
end
arguments (Output)
obj (1,1) CustomClass
end
results = Var1 + Var2;
obj = CustomClass(name,result);
end
With this class and this function which returns one of these class objects, I would like the fact that I provided "(1,1) CustomClass" in the output arguemnts block of function "Calculation(Var1,Var2,name)" to trigger code assist automaticaly show me, when writing code that the retuned value from this funciton has properties "name" and "varOne" in the object.
For istance, if I write the following code with this function and the class in the Matlab search path
testObj = Calculation(1,1,"test");
testObj.varOne = 10; %the property "varOne" doesn't apear in code assist when writing this line of code
I would like that the fact function "Calcuation(Var1,Var2,name) has the output arguments block enforcing that this function must return an object of "CustomClass" to make code assist recognise that "testObj" is a "CustomClass" object, just as if testObj was an input argument to another function which had an input argument requiring that "testObj" was a "CustomClass" object.
Maybe this is a feature that may be added to matlab in future releases? (please and thank you LOL)
This is a feature which doesn't apear to currently exist, but I think alot of matlab users would like, particularly ones who write alot of custom classes.
Imagine i have a custom class with some properties:
classdef CustomClass < handle
properties
name (1,1) string = "default name"
varOne (1,1) double = 0
end
methods
function obj = CustomClass(name,varOne)
obj.name = name;
obj.VarOne = varOne;
end
end
end
Then imagine I have a function which returns one of these custom class objects:
function [obj] = Calculation(Var1,Var2,name)
arguments (Input)
Var1 (1,1) double
Var2 (1,1) double
end
arguments (Output)
obj (1,1) CustomClass
end
results = Var1 + Var2;
obj = CustomClass(name,result);
end
With this class and this function which returns one of these class objects, I would like the fact that I provided "(1,1) CustomClass" in the output arguemnts block of function "Calculation(Var1,Var2,name)" to trigger code assist automaticaly show me, when writing code that the retuned value from this funciton has properties "name" and "varOne" in the object.
For istance, if I write the following code with this function and the class in the Matlab search path
testObj = Calculation(1,1,"test");
testObj.varOne = 10; %the property "varOne" doesn't apear in code assist when writing this line of code
I would like that the fact function "Calcuation(Var1,Var2,name) has the output arguments block enforcing that this function must return an object of "CustomClass" to make code assist recognise that "testObj" is a "CustomClass" object, just as if testObj was an input argument to another function which had an input argument requiring that "testObj" was a "CustomClass" object.
Maybe this is a feature that may be added to matlab in future releases? (please and thank you LOL)
Untapped Potential for Output-arguments Block
MATLAB has a very powerful feature in its arguments blocks. For example, the following code for a function (or method):
- clearly outlines all the possible inputs
- provides default values for each input
- will produce auto-complete suggestions while typing in the Editor (and Command Window in newer versions)
- checks each input against validation functions to enforce size, shape (e.g., column vs. row vector), type, and other options (e.g., being a member of a set)
function [out] = sample_fcn(in)
arguments(Input)
in.x (:, 1) = []
in.model_type (1, 1) string {mustBeMember(in.model_type, ...
["2-factor", "3-factor", "4-factor"])} = "2-factor"
in.number_of_terms (1, 1) {mustBeMember(in.number_of_terms, 1:5)} = 1
in.normalize_fit (1, 1) logical = false
end
% function logic ...
end
If you do not already use the arguments block for function (or method) inputs, I strongly suggest that you try it out.
The point of this post, though, is to suggest improvements for the output-arguments block, as it is not nearly as powerful as its input-arguments counterpart. I have included two function examples: the first can work in MATLAB while the second does not, as it includes suggestions for improvements. Commentary specific to each function is provided completely before the code. While this does necessitate navigating back and forth between functions and text, this provides for an easy comparison between the two functions which is my main goal.
Current Implementation
The input-arguments block for sample_fcn begins the function and has already been discussed. A simple output-arguments block is also included. I like to use a single output so that additional fields may be added at a later point. Using this approach simplifies future development, as the function signature, wherever it may be used, does not need to be changed. I can simply add another output field within the function and refer to that additional field wherever the function output is used.
Before beginning any logic, sample_fcn first assigns default values to four fields of out. This is a simple and concise way to ensure that the function will not error when returning early.
The function then performs two checks. The first is for an empty input (x) vector. If that is the case, nothing needs to be done, as the function simply returns early with the default output values that happen to apply to the inability to fit any data.
The second check is for edge cases for which input combinations do not work. In this case, the status is updated, but default values for all other output fields (which are already assigned) still apply, so no additional code is needed.
Then, the function performs the fit based on the specified model_type. Note that an otherwise case is not needed here, since the argument validation for model_type would not allow any other value.
At this point, the total_error is calculated and a check is then made to determine if it is valid. If not, the function again returns early with another specific status value.
Finally, the R^2 value is calculated and a fourth check is performed. If this one fails, another status value is assigned with an early return.
If the function has passed all the checks, then a set of assertions ensure that each of the output fields are valid. In this case, there are eight specific checks, two for each field.
If all of the assertions also pass, then the final (successful) status is assigned and the function returns normally.
function [out] = sample_fcn(in)
arguments(Input)
in.x (:, 1) = []
in.model_type (1, 1) string {mustBeMember(in.model_type, ...
["2-factor", "3-factor", "4-factor"])} = "2-factor"
in.number_of_terms (1, 1) {mustBeMember(in.number_of_terms, 1:5)} = 1
in.normalize_fit (1, 1) logical = false
end
arguments(Output)
out struct
end
%%
out.fit = [];
out.total_error = [];
out.R_squared = NaN;
out.status = "Fit not possible for supplied inputs.";
%%
if isempty(in.x)
return
end
%%
if ((in.model_type == "2-factor") && (in.number_of_terms == 5)) || ... % other possible logic
out.status = "Specified combination of model_type and number_of_terms is not supported.";
return
end
%%
switch in.model_type
case "2-factor"
out.fit = % code for 2-factor fit
case "3-factor"
out.fit = % code for 3-factor fit
case "4-factor"
out.fit = % code for 4-factor fit
end
%%
out.total_error = % calculation of error
if ~isfinite(out.total_error)
out.status = "The total_error could not be calculated.";
return
end
%%
out.R_squared = % calculation of R^2
if out.R_squared > 1
out.status = "The R^2 value is out of bounds.";
return
end
%%
assert(iscolumn(out.fit), "The fit vector is not a column vector.");
assert(size(out.fit) == size(in.x), "The fit vector is not the same size as the input x vector.");
assert(isscalar(out.total_error), "The total_error is not a scalar.");
assert(isfinite(out.total_error), "The total_error is not finite.");
assert(isscalar(out.R_squared), "The R^2 value is not a scalar.");
assert(isfinite(out.R_squared), "The R^2 value is not finite.");
assert(isscalar(out.status), "The status is not a scalar.");
assert(isstring(out.status), "The status is not a string.");
%%
out.status = "The fit was successful.";
end
Potential Implementation
The second function, sample_fcn_output_arguments, provides essentially the same functionality in about half the lines of code. It is also much clearer with respect to the output. As a reminder, this function structure does not currently work in MATLAB, but hopefully it will in the not-too-distant future.
This function uses the same input-arguments block, which is then followed by a comparable output-arguments block. The first unsupported feature here is the use of name-value pairs for outputs. I would much prefer to make these assignments here rather than immediately after the block as in the sample_fcn above, which necessitates four more lines of code.
The mustBeSameSize validation function that I use for fit does not exist, but I really think it should; I would use it a lot. In this case, it provides a very succinct way of ensuring that the function logic did not alter the size of the fit vector from what is expected.
The mustBeFinite validation function for out.total_error does not work here simply because of the limitation on name-value pairs; it does work for regular outputs.
Finally, the assignment of default values to output arguments is not supported.
The next three sections of sample_fcn_output_arguments match those of sample_fcn: check if x is empty, check input combinations, and perform fit logic. Following that, though, the functions diverge heavily, as you might expect. The two checks for total_error and R^2 are not necessary, as those are covered by the output-arguments block. While there is a slight difference, in that the specific status values I assigned in sample_fcn are not possible, I would much prefer to localize all these checks in the arguments block, as is already done for input arguments.
Furthermore, the entire section of eight assertions in sample_fcn is removed, as, again, that would be covered by the output-arguments block.
This function ends with the same status assignment. Again, this is not exactly the same as in sample_fcn, since any failed assertion would prevent that assignment. However, that would also halt execution, so it is a moot point.
function [out] = sample_fcn_output_arguments(in)
arguments(Input)
in.x (:, 1) = []
in.model_type (1, 1) string {mustBeMember(in.model_type, ...
["2-factor", "3-factor", "4-factor"])} = "2-factor"
in.number_of_terms (1, 1) {mustBeMember(in.number_of_terms, 1:5)} = 1
in.normalize_fit (1, 1) logical = false
end
arguments(Output)
out.fit (:, 1) {mustBeSameSize(out.fit, in.x)} = []
out.total_error (1, 1) {mustBeFinite(out.total_error)} = []
out.R_squared (1, 1) {mustBeLessThanOrEqual(out.R_squared, 1)} = NaN
out.status (1, 1) string = "Fit not possible for supplied inputs."
end
%%
if isempty(in.x)
return
end
%%
if ((in.model_type == "2-factor") && (in.number_of_terms == 5)) || ... % other possible logic
out.status = "Specified combination of model_type and number_of_terms is not supported.";
return
end
%%
switch in.model_type
case "2-factor"
out.fit = % code for 2-factor fit
case "3-factor"
out.fit = % code for 3-factor fit
case "4-factor"
out.fit = % code for 4-factor fit
end
%%
out.status = "The fit was successful.";
end
Final Thoughts
There is a significant amount of unrealized potential for the output-arguments block. Hopefully what I have provided is helpful for continued developments in this area.
What are your thoughts? How would you improve arguments blocks for outputs (or inputs)? If you do not already use them, I hope that you start to now.
w = logspace(-1,3,100);
[m,p] = bode(tf(1,[1 1]),w);
size(m)
and therefore plotting requires an explicit squeeze (or rehape, or colon)
% semilogx(w,squeeze(db(m)))
Similarly, I'm using page* functions more regularly and am now generating 3D results whereas my old code would generate 2D. For example
x = [1;1];
theta = reshape(0:.1:2*pi,1,1,[]);
Z = [cos(theta), sin(theta);-sin(theta),cos(theta)];
y = pagemtimes(Z,x);
Now, plotting requires squeezing the inputs
% plot(squeeze(theta),squeeze(y))
Would there be any drawbacks to having plot, et. al., automagically apply squeeze to its inputs?
The ability to plot multiple signals on a plot and then use the plot browser to interactively control which ones are displayed has been one of the most useful features of the plotting tools and many of my scripts embed the command to open it after results analysis and plotting. It's been removed in 2025A with the comment that the Property Inspector provides the alternative. It doesn't. Having to go back into the menu to select the plot edit features to get to the Property Inspector (which doesn't provide an efficient alternative to the plot browser) has made the workflow very inefficient. Please bring it back a.s.a.p. !!!!
I like this problem by James and have solved it in several ways. A solution by Natalie impressed me and introduced me to a new function conv2. However, it occured to me that the numerous test for the problem only cover cases of square matrices. My original solutions, and Natalie's, did niot work on rectangular matrices. I have now produced a solution which works on rectangular matrices. Thanks for this thought provoking problem James.
I have written, tested, and prepared a function with four subsunctions on my computer for solving one of the problems in the list of Cody problems in MathWorks in three days. Today, when I wanted to upload or copy paste the codes of the function and its subfunctions to the specified place of the problem of Cody page, I do not see a place to upload it, and the ability to copy past the codes. The total of the entire codes and their documentations is about 600 lines, which means that I cannot and it is not worth it to retype all of them in the relevent Cody environment after spending a few days. I would appreciate your guidance on how to enter the prepared codes to the desired environment in Cody.
I've long used the Tensor Toolbox from Sandia in order to use tensors in Matlab, but recently found myself wanting to apply it on symbolic arguments, which don't appear supported. Some google-fu'ing resulted in (non-free) Tensorlab and some file-exchange entries of mixed quality. And of course, there's the recent tensorprod, which a) doesn't support symbolics and b) arguments aren't strictly tensors (rather "representations of tensors in a matrix type").
This all got me to thinking that it would be mighty nice to have general / native / comprehensive support for a tensor class in official Matlab - even if it were in a separate toolbox.
Imagine you are developing a new toolbox for MATLAB. You have a folder full of a few .m files defining a bunch of functions and you are thinking 'This would be useful for others, I'm going to make it available to the world'
What process would you go through? What's the first thing you'd do?
I have my own opinions but don't want to pollute the start of the conversation :)
