I have a matrix X and a list centres. I want to create a new numpy matrix td_X.
I want to populate td_X with the which is made up of the rows of X where the index is equal to centres. In pseudocode:
for each in centers:
td_X.append(X[eacj])
How can I do this using Python?
Since that middle dimension is size 1, just reshape or squeeze it.
x = np.array(alist)
x = np.squeeze(x) # or
x = x.reshape(45, 5785) # or
x = x[:,0,:]
You can remove the extra layer of nesting in the list, but this kind of reshaping is so much easier with arrays.
From x[0], you have an extra level of list wrapped around. Removing it by indexing should get you there:
x = np.array([l[0] for l in x])
Here is a small example:
x = [[[1,2]], [[2,3]], [[4,5]]]
np.array(x).shape
# (3, 1, 2)
np.array([l[0] for l in x]).shape
# (3, 2)
np.array([l[0] for l in x])
# array([[1, 2],
# [2, 3],
# [4, 5]])
(45, 1, 5785)
x?
np.array(x)???