Fron Python to Matlab

1 次查看（过去 30 天）
Pouyan Msgn
Pouyan Msgn 2018-11-14
评论： Nour Sd 2018-12-8
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
显示 2更早的评论
Adam Danz
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
Nour Sd 2018-12-8
Okay thank you very much :)

请先登录，再进行评论。

请先登录，再回答此问题。

采纳的回答

Adam Danz
Adam Danz 2018-11-14
编辑：Adam Danz 2018-11-14
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)
  4 个评论
显示 2更早的评论
Pouyan Msgn
Pouyan Msgn 2018-11-14
Thank you very much but one thing: y = np.exp(- ((E-Emax/2.)/Ec)**2) means exp(-((E-Emax/2)./Ec).^2)

请先登录，再进行评论。

更多回答（1 个）

dpb
dpb 2018-11-14
See
doc randn
When looking for something you don't know function name but have a clue about what is,
lookfor keyword
is useful; in this case either
lookfor random
lookfor normal
would lead you there...also just the venerable old
help
can show you what areas are in base Matlab plus the installed toolboxes available...

类别

在 Help Center 和 File Exchange 中查找有关 Call Python from MATLAB 的更多信息

标签

产品

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by