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How to run .m file in python?

  I have a .m code what I want to run in python. Is it any easy way? 1. this code is not a function. 2. don't want to show the matlab window. NOTE:- Matlabsolutions.com  provide latest  MatLab Homework Help, MatLab Assignment Help  ,  Finance Assignment Help  for students, engineers and researchers in Multiple Branches like ECE, EEE, CSE, Mechanical, Civil with 100% output.Matlab Code for B.E, B.Tech,M.E,M.Tech, Ph.D. Scholars with 100% privacy guaranteed. Get MATLAB projects with source code for your learning and research. T his is not a big deal. The python code looks like: import matlab.engine eng = matlab.engine.start_matlab() eng.simple_script(nargout=0) eng.quit() The Matlab script would be perhaps this one line saved as simple_script.m: a = 'it works easily...' Make sure that the script is saved in a folder matlab knows as a search folder. Then run your python script and get the answer:   SEE COMPLETE ANSWER CLICK THE LINK https://www.matlabsolu...
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Why is noise required to get expected Magnitude Squared Coherence (mscohere)

 I am missing something with magnitude Squared Coherence and/or its algorithm. If two signals are compared without or with little noise I get unexpected results. As an example taking from the ML help page:

 
Fs = 1000; t = 0:1/Fs:1-1/Fs;
 
x = cos(2*pi*100*t)+sin(2*pi*200*t)+0.5*randn(size(t)); y = 0.5*cos(2*pi*100*t-pi/4)+0.35*sin(2*pi*200*t-pi/2)+ ... 0.5*randn(size(t)); [Pxy,F] = mscohere(x,y,hamming(100),80,100,Fs);
 
gives the expected two peak response. I would have thought that with no noise the mscohere would be similar and even stronger but it is not. Run the same  code without the noise
 
x = cos(2*pi*100*t)+sin(2*pi*200*t); y = 0.5*cos(2*pi*100*t-pi/4)+0.35*sin(2*pi*200*t-pi/2);
 
[Pxy,F] = mscohere(x,y,hamming(100),80,100,Fs);
 
and rather than getting two strong peaks and the rest near or at zero, you get unity for all frequencies.
 
You don't need much noise, 0.5% or -46dB will do. Below this and the results get real funky.
 
Furthermore, without some noise the algorithm sees harmonics very strongly even though they are not in both signals:
 
x = cos(2*pi*100*t)+sin(2*pi*200*t)+0.5*randn(size(t)); y = 0.5*cos(2*pi*100*t-pi/4);
 
still gives two strong peaks at 100 and 200 unless y has noise. Then all is as expected.

ANSWER



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You might be thinking of CPSD instead of MSCOHERE. MSCOHERE will normalize CPSD by the PSD of each signal (i.e. Cxy = (abs(Pxy).^2)./(Pxx.*Pyy), where Pxy is the CPSD. When the spectrum of Pxy, Pxx and Pyy are very near zero, you'll be looking at division of two numbers very close to zero. Adding the noise decouples them somewhat.

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