I am using numpy. I have a matrix with 1 column and N rows and I want to get an array from with N elements.
For example, if i have
M = matrix([, , , ]), I want to get
A = array([1,2,3,4]).
To achieve it, I use
A = np.array(M.T). Does anyone know a more elegant way to get the same result?
If you’d like something a bit more readable, you can do this:
A = np.squeeze(np.asarray(M))
Equivalently, you could also do:
A = np.asarray(M).reshape(-1), but that’s a bit less easy to read.
result = M.A1
matrix.A1 1-d base array
A, = np.array(M.T)
depends what you mean by elegance i suppose but thats what i would do
You can try the following variant:
If you care for speed; But if you care for memory:
Or you could try to avoid some temps with
A = M.view(np.ndarray) A.shape = -1
Mv = numpy.asarray(M.T), which gives you a 4×1 but 2D array.
A = Mv[0,:], which gives you what you want. You could put them together, as
This will convert the matrix into array
A = np.ravel(M).T