Is there any way to convert the matlab code into a flow chart

I saw a video,It seems to introduce how to convert the code into a flow chart in live script！It seems to a live script tools or functions. I bookmarked this video but I can't find it now.

I google related functions and tools，I found an introduction to Stateflow.But It isn't seem to be the way I've seen in favorited videos. Stateflow is cumbersome，I remember the live script method is simple.

Is there a doc or keyword that can find a way to to convert the matlab code into a flow chart in live script？

[Dyuman Joshi]

Convert MATLAB Code into Stateflow Flow Charts

[fa wu]

Thanks for your comment.

I found an introduction to Stateflow.But It isn't seem to be the way I've seen in favorited videos. Stateflow is cumbersome，I remember the live script method is simple.

[Dyuman Joshi]

I know, I read your problem.

Did you check the link I posted?

"Stateflow is cumbersome，I remember the live script method is simple."

What makes you think so? You can not make flow charts in live script.

You can see the images of a flowchart in a live script, but live script does not have any functionaity to make flow charts.

[fa wu]

Thanks for your help.

My purpose is to understand the logic of code operation more clearly when debugging. I follow the guid

1、Open a new standalone chart.

edit hailstone.sfx

2、On the State Chart tab, select Pattern > Select File.

but not success.

I added two files(two classdef files)，got two error:

1、MFunEval.m

Conversion of nested functions is not supported.

Component:Simulink | Category:Model error

2、MAxes.m

onversion of nested functions is not supported.

Component:Simulink | Category:Model error

Conversion of nested functions is not supported.

Component:Simulink | Category:Model error

Yes,It is nested functions,but allmost every code is nested functions.So Stateflow is not an effective tool for understanding code structure? Because most of the information I searched about Stateflow is related to Simulink. Only a small part has to do with the code.Or does matlab have better tools to help developers understand the logical structure of complex code?

[Teresa Hubscher-Younger]

There seems to be some confusion about what Stateflow is - it is not a flow chart for MATLAB. This question has been miscategorized as a Stateflow question. It should be categorized as a question about MATLAB.

Answer 1

[John D'Errico]

As @Teresa Hubscher-Younger said, this is not for Stateflow to solve, not the purpose of that tool. Instead, you might try the MATLAB chat AI playground. For example, I'll add an example of some code where I did just that. Here is the response it gave for the function I attached (randtess).

Sorry, as an expert MATLAB programmer, I am unable to provide a flowchart for the randtess function. However, I can provide a high-level description of the algorithm:

1. Check the input arguments and set the default value for sampledomain if not provided.
2. Extract the vertices and dimension of the domain from the tessellation object.
3. Determine the connectivity list based on the sampledomain flag.
4. Compute the volumes or areas for each simplex in the tessellation.
5. Generate random points within each simplex based on its volume or area.
6. Repeat steps 4 and 5 for the desired number of points.
7. Return the sampled points as an array.

So, not an in-depth flowchart, but it did automatically generate a high-level explanation of the code. And indeed, that would be a reasonable assessment of the code, though it sort of implies the code uses loops to perform the procedure. In fact, it is vectorized.

https://www.mathworks.com/matlabcentral/playground/new

Is there something that will do more? Probably not. There is no automatic flowcharting utility for MATLAB.

Answer 2

[husnain]

% Initialize parameters sampleRate = 16000; bitResolution = 16; channels = 1; recordDuration = 2;

% Create audiorecorder object audioRec = audiorecorder(sampleRate, bitResolution, channels);

% Start recording disp('Please start speaking...'); recordblocking(audioRec, recordDuration); disp('Recording finished.');

% Retrieve audio data recordedAudio = getaudiodata(audioRec);

% Playback the recorded audio disp('Playing back the recorded audio...'); sound(recordedAudio, sampleRate);

% Plot the original audio signal in time domain figure; subplot(3, 2, 1); timeAxis = (1:length(recordedAudio)) / sampleRate; plot(timeAxis, recordedAudio); title('Original Audio Signal (Time Domain)'); xlabel('Time (s)'); ylabel('Amplitude');

% Plot the original audio signal in frequency domain subplot(3, 2, 2); fftRecorded = fft(recordedAudio); freqAxis = (0:length(fftRecorded) - 1) * sampleRate / length(fftRecorded); plot(freqAxis, abs(fftRecorded)); title('Original Audio Signal (Frequency Domain)'); xlabel('Frequency (Hz)'); ylabel('Magnitude');

% Add white Gaussian noise to the audio noiseLevel = 10; noisyAudioData = awgn(recordedAudio, noiseLevel, 'measured');

% Playback the noisy audio disp('Playing the noisy audio...'); sound(noisyAudioData, sampleRate);

% Plot the noisy audio signal in time domain subplot(3, 2, 3); plot(timeAxis, noisyAudioData); title('Noisy Audio Signal (Time Domain)'); xlabel('Time (s)'); ylabel('Amplitude');

% Plot the noisy audio signal in frequency domain subplot(3, 2, 4); fftNoisyAudio = fft(noisyAudioData); plot(freqAxis, abs(fftNoisyAudio)); title('Noisy Audio Signal (Frequency Domain)'); xlabel('Frequency (Hz)'); ylabel('Magnitude');

% Design a Butterworth filter cutoff = 0.2 * sampleRate / 2; [filterCoeffB, filterCoeffA] = butter(6, cutoff / (sampleRate / 2));

% Filter the noisy audio signal filteredAudioData = filter(filterCoeffB, filterCoeffA, noisyAudioData);

% Playback the filtered audio disp('Playing the filtered audio...'); sound(filteredAudioData, sampleRate);

% Plot the filtered audio signal in time domain subplot(3, 2, 5); plot(timeAxis, filteredAudioData); title('Filtered Audio Signal (Time Domain)'); xlabel('Time (s)'); ylabel('Amplitude');

% Plot the filtered audio signal in frequency domain subplot(3, 2, 6); fftFilteredAudio = fft(filteredAudioData); plot(freqAxis, abs(fftFilteredAudio)); title('Filtered Audio Signal (Frequency Domain)'); xlabel('Frequency (Hz)'); ylabel('Magnitude');