numpy.ma.expand_dims#

ma.expand_dims(a,axis)[source]#

Expand the shape of an array.

Insert a new axis that will appear at theaxis position in the expandedarray shape.

Parameters:

aarray_like

Input array.

axisint or tuple of ints

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

Deprecated since version 1.13.0:Passing an axis whereaxis>a.ndim will be treated asaxis==a.ndim, and passingaxis<-a.ndim-1 willbe treated asaxis==0. This behavior is deprecated.

Returns:

resultndarray

View ofa with the number of dimensions increased.

See also

squeeze

The inverse operation, removing singleton dimensions

reshape

Insert, remove, and combine dimensions, and resize existing ones

atleast_1d,atleast_2d,atleast_3d

Examples

Try it in your browser!

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

The following is equivalent tox[np.newaxis,:] orx[np.newaxis]:

>>>y=np.expand_dims(x,axis=0)>>>yarray([[1, 2]])>>>y.shape(1, 2)

The following is equivalent tox[:,np.newaxis]:

>>>y=np.expand_dims(x,axis=1)>>>yarray([[1],       [2]])>>>y.shape(2, 1)

axis may also be a tuple:

>>>y=np.expand_dims(x,axis=(0,1))>>>yarray([[[1, 2]]])

>>>y=np.expand_dims(x,axis=(2,0))>>>yarray([[[1],        [2]]])

Note that some examples may useNone instead ofnp.newaxis. Theseare the same objects:

>>>np.newaxisisNoneTrue

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