How do you unroll a Numpy array of (mxn) dimentions into a single vector
matlab, numpy, python
Solution
Is this what you have in mind?
Edit: As Patrick points out, one has to be careful with translating A(:) to Python.
Of course if you just want to flatten out a matrix or 2-D array of zeros it does not matter.
So here is a way to get behavior like matlab's.
>>> a = np.array([[1,2,3], [4,5,6]])
>>> a
array([[1, 2, 3],
[4, 5, 6]])
>>> # one way to get Matlab behaivor
... (a.T).ravel()
array([1, 4, 2, 5, 3, 6])
`numpy.ravel` does flatten 2D array, but does not do it the same way matlab's `(:)` does.
>>> import numpy as np
>>> a = np.array([[1,2,3], [4,5,6]])
>>> a
array([[1, 2, 3],
[4, 5, 6]])
>>> a.ravel()
array([1, 2, 3, 4, 5, 6])
Problem
I just want to know if there is a short cut to unrolling numpy arrays into a single vector. For instance (convert the following Matlab code to python): Matlab way: A = zeros(10,10) % A_unroll = A(:) % <- How can I do this in python Thank in advance.