问在scikit-learn中将GMM拟合到3D直方图

EN

import numpy as np
# create the co-ordinate values
X, Y = np.mgrid[0:Z.shape[0], 0:Z.shape[1]]

# artificially create a list of points from your histogram
data_points = []
for x, y, z in zip(X.ravel(), Y.ravel(), Z.ravel()):
    # add the data point / voxel (x, y) as many times as it occurs
    # in the histogram
    for iz in z:
        data_points.append((x, y))

# now fit your GMM
from sklearn.mixture import GMM
gmm = GMM()
gmm.fit(data_points)