Fron Python to Matlab

Question

Pouyan Msgn 2018-11-14

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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/429806-fron-python-to-matlab

评论： Nour Sd 2018-12-8

采纳的回答： Adam Danz

在 MATLAB Online 中打开

I got a code in Python that I will write it again in Matlab and get the same plot:

The code is :

npts = 1000 # number of points in uncorrelated data set
Emax = 10.  # energy goes from zero to Emax
Ec = 0.1 # correlation energy
kT = 0.25
# create discrete values of Energy
E = np.linspace(0, Emax, npts)
E_extra = np.linspace(0, Emax, 2*npts-1) #sometimes we need this size to convolve
#PLOT 1: Tbar correlated
Tbar = np.random.normal(loc=0., scale=1.0, size=2*npts-1 )
y = np.exp(- ((E-Emax/2.)/Ec)**2)
#convolution between Tbar and correlation energy
Tbar_c = np.convolve(y, Tbar, mode='valid') #valid = no edge effects
# normalize the data (maximum=1, minimum=0)
Tbar_c = Tbar_c - Tbar_c.min()
Tbar_c = Tbar_c/Tbar_c.max()
# plot the correlated data set
ax1.plot(E, Tbar_c)

The plot is (I need the first plot (the one at the top T(E)))

Here is what I have done yet:

clc
clear all
Emax=10;
Ec=0.01;
E=0:0.01:10;
g=exp(-0.5.*((E-Emax).^2)./Ec);
y=rand(1,length(E));
%y=rand(size(E))
T1=conv(y,g,'same');
T=T1./norm(T1);
subplot(3,1,1);
plot(E,T)

The problem is for me here:

Draw random samples from a normal (Gaussian) distribution. in Python we can do it by :

Tbar = np.random.normal(loc=0., scale=1.0, size=2*npts-1 )

4 个评论
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Adam Danz 2018-12-8

编辑：Adam Danz 2018-12-8

Check out the convolution weight function convwf(). Carefully read the documentation to make sure this is doing what your python function does and that inputs are the same and in the same order (or not).

https://www.mathworks.com/help/deeplearning/ref/convwf.html

If this isn't want you're looking for, I suggest you open a new question. I'd rather not this thread turn into a Python --> Matlab conversion forum.

Nour Sd 2018-12-8

Okay thank you very much :)

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Answer 1

Adam Danz 2018-11-14

1
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/429806-fron-python-to-matlab#answer_346914

编辑：Adam Danz 2018-11-14

在 MATLAB Online 中打开

I can't run your code right now in python so I can't compare the results but most of these lines should be the correct conversion.

See help normrnd to pull numbers from a given gaussian distribution.

npts = 1000; % number of points in uncorrelated data set
Emax = 10;  % energy goes from zero to Emax
Ec = 0.1; % correlation energy
kT = 0.25;
% create discrete values of Energy
E = linspace(0, Emax, npts);
E_extra = linspace(0, Emax, 2*npts-1); %sometimes we need this size to convolve
%PLOT 1: Tbar correlated
Tbar = normrnd(0, 1, 1, 2*npts-1)
y = exp(- ((E-Emax/2.)/Ec).*2);
%convolution between Tbar and correlation energy
Tbar_c = conv(y, Tbar, 'same'); %valid = no edge effects
% normalize the data (maximum=1, minimum=0)
Tbar_c = Tbar_c - min(Tbar_c);
Tbar_c = Tbar_c/max(Tbar_c);
% plot the correlated data set
plot(E, Tbar_c)