Unwanted extra dimensions in NumPy array

Question

I've opened a .fits image:

scaled_flat1 = pyfits.open('scaled_flat1.fit')   
scaled_flat1a = scaled_flat1[0].data

and when I print its shape:

print scaled_flat1a.shape

I get the following:

(1, 1, 510, 765)

I want it to read:

(510, 765)

How do I get rid of the two ones before it?

Answer 1

There is the method called squeeze which does just what you want:

Remove single-dimensional entries from the shape of an array.

Parameters

a : array_like
    Input data.
axis : None or int or tuple of ints, optional
    .. versionadded:: 1.7.0

    Selects a subset of the single-dimensional entries in the
    shape. If an axis is selected with shape entry greater than
    one, an error is raised.

Returns

squeezed : ndarray
    The input array, but with with all or a subset of the
    dimensions of length 1 removed. This is always `a` itself
    or a view into `a`.

for example:

import numpy as np

extra_dims = np.random.randint(0, 10, (1, 1, 5, 7))
minimal_dims = extra_dims.squeeze()

print minimal_dims.shape
# (5, 7)