Running a python script in matlab
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Hi, I tried to run a python script in matlab. I used the function system.So fa so good.
The pyhton script uses two input variables. In matlab I can enter one and then it runs without problems but when I try to enter two separate variables I always get an error.
systemCommand = ['python sqd.py ',num2str(a),num2str(omtrek)]
[status, result] = system(systemCommand);
This is the error:
status =
1
result =
Traceback (most recent call last):
File "sqd.py", line 10, in <module>
sys.stdout.write(str(squared(x)))
TypeError: squared() takes exactly 2 arguments (1 given)
Can someone help me?
Thanks!
1 Commento
Charles
il 29 Ago 2017
This is interesting I am new to python, and I am trying to to do the dame thing Does the solution in fact work? I am keen to try it. I literally do not know python at all, neither am I am a programmer but I find it all fascinating and I move forward by trail and error. Some how I make progress. I will try this, but what infrastructure do you have? I have Matlab, 2017a and Python 3.6 Do i need anything else? I am reading that the former does not support the latter. Any thoughts?
Risposta accettata
Più risposte (7)
Bo Li
il 18 Apr 2016
Why not using Python Interface?
The MATLAB statement can be as simple as following:
>> b=py.sqd.squared(10,30)
1 Commento
M Al Mamun
il 14 Ott 2021
This is easy to apply and works perfectly.
Shashank Prasanna
il 15 Gen 2013
0 voti
Could you try the above with a space between the two arguments?
systemCommand = ['python sqd.py ',num2str(a),' ',num2str(omtrek)]
Tom Leblicq
il 16 Gen 2013
Tom Leblicq
il 16 Gen 2013
Aysha Ashraf
il 21 Dic 2017
0 voti
Can any one help me how to integrate this python code to matlab, i want to run this python program in matlab...
#Load dependencies import pandas as pd import numpy as np from sklearn.preprocessing import StandardScaler from matplotlib import* import matplotlib.pyplot as plt from matplotlib.cm import register_cmap from matplotlib.mlab import PCA from sklearn.decomposition import PCA
from scipy import stats #from wpca import PCA from sklearn.decomposition import PCA as sklearnPCA import seaborn
#Load movie names and movie ratings movies = pd.read_csv('movies.csv') ratings = pd.read_csv('ratings.csv') ratings.drop(['timestamp'], axis=1, inplace=True) # def replace_name(x): return movies[movies['movieId']==x].title.values[0] # ratings.movieId = ratings.movieId.map(replace_name) # M = ratings.pivot_table(index=['userId'], columns=['movieId'], values='rating') m = M.shape #posesall = pd.read_csv('FileName_Poses.csv') df1 = M.replace(np.nan, 0, regex=True) X_std = StandardScaler().fit_transform(movies) #Step 2: Covariance Matrix and Eigendecomposition mean_vec = np.mean(X_std, axis=0) cov_mat = (X_std - mean_vec).T.dot((X_std - mean_vec)) / (X_std.shape[0]-1) print('Covariance matrix \n%s' %cov_mat) print('NumPy covariance matrix: \n%s' %np.cov(X_std.T)) #Perform eigendecomposition on covariance matrix cov_mat = np.cov(X_std.T) eig_vals, eig_vecs = np.linalg.eig(cov_mat) print('Eigenvectors \n%s' %eig_vecs) print('\nEigenvalues \n%s' %eig_vals) # Step 3: Selecting Principal Components # Visually confirm that the list is correctly sorted by decreasing eigenvalues eig_pairs = [(np.abs(eig_vals[i]), eig_vecs[:,i]) for i in range(len(eig_vals))] print('Eigenvalues in descending order:') for i in eig_pairs: print(i[0]) pca = PCA(n_components = 93) All_poses_pca = pca.fit_transform(movies) Variance = (pca.explained_variance_ratio_)
#Explained variance pca = PCA().fit(X_std) plt.plot(np.cumsum(pca.explained_variance_ratio_)) plt.title('Scree Plot') plt.xlabel('Number of principal components') plt.ylabel('Cumulative explained variance') plt.show()
Yodish
il 12 Apr 2018
0 voti
It works for me as well, but it is very slow. It takes 0.2 sec to call a sum function from Python
Any ideas on how to speed it up? Where is the bottle neck?
Agapi Dav
il 31 Lug 2018
0 voti
Hello everyone! I have some images read in matlab and I want to process them in python and them return them to matlab for further processing.
Everything with the systemCommand works, however, even though I can import variables from matlab to python, because they are already in the workspace, I cannot return variables (e.g. images) back to matlab, when running the python script. Till now, in order to make it work, I save the python-processed images and then read them again from matlab.
I would like to ask if there is a more efficient way. In other words, in the example of Tom Leblicq, I would like to return the parameter b in matlab for further processing.
Thank you in advance!
1 Commento
Abdelwahab Afifi
il 12 Gen 2021
The following command will return b in the workspace of MATLAB
b=py.sqd.squared(2)
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