xorbits.numpy.expand_dims#
- xorbits.numpy.expand_dims(a, axis)[源代码]#
Expand the shape of an array.
Insert a new axis that will appear at the axis position in the expanded array shape.
- 参数
a (array_like) – Input array.
axis (int or tuple of ints) –
Position in the expanded axes where the new axis (or axes) is placed.
1.13.0(numpy) 版后已移除: Passing an axis where
axis > a.ndim
will be treated asaxis == a.ndim
, and passingaxis < -a.ndim - 1
will be treated asaxis == 0
. This behavior is deprecated.在 1.18.0(numpy) 版更改: A tuple of axes is now supported. Out of range axes as described above are now forbidden and raise an AxisError.
- 返回
result – View of a with the number of dimensions increased.
- 返回类型
ndarray
参见
squeeze
The inverse operation, removing singleton dimensions
reshape
Insert, remove, and combine dimensions, and resize existing ones
doc.indexing
,atleast_1d
,atleast_2d
,atleast_3d
实际案例
>>> x = np.array([1, 2]) >>> x.shape (2,)
The following is equivalent to
x[np.newaxis, :]
orx[np.newaxis]
:>>> y = np.expand_dims(x, axis=0) >>> y array([[1, 2]]) >>> y.shape (1, 2)
The following is equivalent to
x[:, np.newaxis]
:>>> y = np.expand_dims(x, axis=1) >>> y array([[1], [2]]) >>> y.shape (2, 1)
axis
may also be a tuple:>>> y = np.expand_dims(x, axis=(0, 1)) >>> y array([[[1, 2]]])
>>> y = np.expand_dims(x, axis=(2, 0)) >>> y array([[[1], [2]]])
Note that some examples may use
None
instead ofnp.newaxis
. These are the same objects:>>> np.newaxis is None True
This docstring was copied from numpy.