nums.numpy.expand_dims

nums.numpy.expand_dims(a: nums.core.array.blockarray.BlockArray, axis)

Expand the shape of an array.

This docstring was copied from numpy.expand_dims.

Some inconsistencies with the NumS version may exist.

Insert a new axis that will appear at the axis position in the expanded array shape.

aBlockArray

Input array.

axisint or tuple of ints

Position in the expanded axes where the new axis (or axes) is placed.

resultBlockArray

View of a with the number of dimensions increased.

squeeze : The inverse operation, removing singleton dimensions reshape : Insert, remove, and combine dimensions, and resize existing ones atleast_1d, atleast_2d, atleast_3d

The doctests shown below are copied from NumPy. They won’t show the correct result until you operate get().

>>> x = nps.array([1, 2])  
>>> x.shape  
(2,)

The following is equivalent to x[nps.newaxis, :] or x[nps.newaxis]:

>>> y = nps.expand_dims(x, axis=0)  
>>> y.get()  
array([[1, 2]])
>>> y.shape  
(1, 2)

The following is equivalent to x[:, nps.newaxis]:

>>> y = nps.expand_dims(x, axis=1)  
>>> y.get()  
array([[1],
       [2]])
>>> y.shape  
(2, 1)

axis may also be a tuple:

>>> y = nps.expand_dims(x, axis=(0, 1))  
>>> y.get()  
array([[[1, 2]]])

>>> y = nps.expand_dims(x, axis=(2, 0))  
>>> y.get()  
array([[[1],
        [2]]])