How to subset Numpy array with exclusion

Question

In Numpy you can subset certain columns by giving a list or integer. For example:

a = np.ones((10, 5))

a[:,2] or a[:,[1,3,4]]

But how to do exclusion ? Where it return all other columns except 2 or [1,3,4].

The reason is that I want to make all other columns zeros except one or a list of selected columns, for example:

a[:, exclude(1)] *= 0

I can generate a new zeros array with the same shape then just assign the specific column to the new variable. But I wonder if there is any more efficient way

Thanks

Answer 1

One way is to generate the index list yourself:

>>> a[:,list(i for i in range(a.shape[1]) if i not in set((2,1,3,4)))]
array([[ 0.],
       [ 0.],
       [ 0.],
       [ 0.],
       [ 0.],
       [ 0.],
       [ 0.],
       [ 0.],
       [ 0.],
       [ 0.]])

or to exclude a single column (following your edit):

>>> a[:,list(i for i in range(a.shape[1]) if i != 1)]*= 0

or if you use this often, and want to use a function (which will not be called except, since that is a Python keyword:

def exclude(size,*args):
    return [i for i in range(size) if i not in set(args)] #Supports multiple exclusion

so now

a[:,exclude(a.shape[1],1)]

works.

@jdehesa mentions from Numpy 1.13 you can use

a[:, np.isin(np.arange(a.shape[1]), [2, 1, 3, 4], invert=True)]

as well for something within Numpy itself.