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import cupy
from cupy import _core
def column_stack(tup):
"""Stacks 1-D and 2-D arrays as columns into a 2-D array.
A 1-D array is first converted to a 2-D column array. Then, the 2-D arrays
are concatenated along the second axis.
Args:
tup (sequence of arrays): 1-D or 2-D arrays to be stacked.
Returns:
cupy.ndarray: A new 2-D array of stacked columns.
.. seealso:: :func:`numpy.column_stack`
"""
if any(not isinstance(a, cupy.ndarray) for a in tup):
raise TypeError('Only cupy arrays can be column stacked')
lst = list(tup)
for i, a in enumerate(lst):
if a.ndim == 1:
a = a[:, cupy.newaxis]
lst[i] = a
elif a.ndim != 2:
raise ValueError(
'Only 1 or 2 dimensional arrays can be column stacked')
return concatenate(lst, axis=1)
def concatenate(tup, axis=0, out=None, *, dtype=None, casting='same_kind'):
"""Joins arrays along an axis.
Args:
tup (sequence of arrays): Arrays to be joined. All of these should have
same dimensionalities except the specified axis.
axis (int or None): The axis to join arrays along.
If axis is None, arrays are flattened before use.
Default is 0.
out (cupy.ndarray): Output array.
dtype (str or dtype): If provided, the destination array will have this
dtype. Cannot be provided together with ``out``.
casting ({‘no’, ‘equiv’, ‘safe’, ‘same_kind’, ‘unsafe’}, optional):
Controls what kind of data casting may occur. Defaults to
``'same_kind'``.
Returns:
cupy.ndarray: Joined array.
.. seealso:: :func:`numpy.concatenate`
"""
if axis is None:
tup = [m.ravel() for m in tup]
axis = 0
return _core.concatenate_method(tup, axis, out, dtype, casting)
def dstack(tup):
"""Stacks arrays along the third axis.
Args:
tup (sequence of arrays): Arrays to be stacked. Each array is converted
by :func:`cupy.atleast_3d` before stacking.
Returns:
cupy.ndarray: Stacked array.
.. seealso:: :func:`numpy.dstack`
"""
return concatenate([cupy.atleast_3d(m) for m in tup], 2)
def hstack(tup, *, dtype=None, casting='same_kind'):
"""Stacks arrays horizontally.
If an input array has one dimension, then the array is treated as a
horizontal vector and stacked along the first axis. Otherwise, the array is
stacked along the second axis.
Args:
tup (sequence of arrays): Arrays to be stacked.
dtype (str or dtype): If provided, the destination array will have this
dtype.
casting ({‘no’, ‘equiv’, ‘safe’, ‘same_kind’, ‘unsafe’}, optional):
Controls what kind of data casting may occur. Defaults to
``'same_kind'``.
Returns:
cupy.ndarray: Stacked array.
.. seealso:: :func:`numpy.hstack`
"""
arrs = [cupy.atleast_1d(a) for a in tup]
axis = 1
if arrs[0].ndim == 1:
axis = 0
return concatenate(arrs, axis, dtype=dtype, casting=casting)
def vstack(tup, *, dtype=None, casting='same_kind'):
"""Stacks arrays vertically.
If an input array has one dimension, then the array is treated as a
horizontal vector and stacked along the additional axis at the head.
Otherwise, the array is stacked along the first axis.
Args:
tup (sequence of arrays): Arrays to be stacked. Each array is converted
by :func:`cupy.atleast_2d` before stacking.
dtype (str or dtype): If provided, the destination array will have this
dtype.
casting ({‘no’, ‘equiv’, ‘safe’, ‘same_kind’, ‘unsafe’}, optional):
Controls what kind of data casting may occur. Defaults to
``'same_kind'``.
Returns:
cupy.ndarray: Stacked array.
.. seealso:: :func:`numpy.dstack`
"""
return concatenate([cupy.atleast_2d(m) for m in tup], 0,
dtype=dtype, casting=casting)
def stack(tup, axis=0, out=None, *, dtype=None, casting='same_kind'):
"""Stacks arrays along a new axis.
Args:
tup (sequence of arrays): Arrays to be stacked.
axis (int): Axis along which the arrays are stacked.
out (cupy.ndarray): Output array.
dtype (str or dtype): If provided, the destination array will have this
dtype. Cannot be provided together with ``out``.
casting ({‘no’, ‘equiv’, ‘safe’, ‘same_kind’, ‘unsafe’}, optional):
Controls what kind of data casting may occur. Defaults to
``'same_kind'``.
Returns:
cupy.ndarray: Stacked array.
.. seealso:: :func:`numpy.stack`
"""
return concatenate([cupy.expand_dims(x, axis) for x in tup], axis, out,
dtype=dtype, casting=casting)
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