#
# * The source code in this file is based on the soure code of NumPy.
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# (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
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import operator
import numpy
import nlcpy
from nlcpy.request import request
from numpy import AxisError
[ドキュメント]def flip(m, axis=None):
"""Reverses the order of elements in an array along the given axis.
The shape of the array is preserved, but the elements are reordered.
Parameters
----------
m : array_like
Input array.
axis : None or int or tuple of ints, optional
Axis or axes along which to flip over. The default, axis=None, will flip over
all of the axes of the input array. If axis is negative it counts from the
last to the first axis.
If axis is a tuple of ints, flipping is performed on all of the axes
specified in the tuple.
Returns
-------
out : ndarray
A view of m with the entries of axis reversed. Since a view is returned, this
operation is done in constant time.
Note
----
flip(m, 0) is equivalent to flipud(m).
flip(m, 1) is equivalent to fliplr(m).
flip(m, n) corresponds to ``m[...,::-1,...]`` with ``::-1`` at position n.
flip(m) corresponds to ``m[::-1,::-1,...,::-1]`` with ``::-1`` at all positions.
flip(m, (0, 1)) corresponds to ``m[::-1,::-1,...]`` with ``::-1`` at position 0 and
position 1.
See Also
--------
flipud : Flips array in the up/down direction.
fliplr : Flips array in the left/right direction.
Examples
--------
>>> import nlcpy as vp
>>> A = vp.arange(8).reshape((2,2,2))
>>> A
array([[[0, 1],
[2, 3]],
<BLANKLINE>
[[4, 5],
[6, 7]]])
>>> vp.flip(A, 0)
array([[[4, 5],
[6, 7]],
<BLANKLINE>
[[0, 1],
[2, 3]]])
>>> vp.flip(A, 1)
array([[[2, 3],
[0, 1]],
<BLANKLINE>
[[6, 7],
[4, 5]]])
>>> vp.flip(A)
array([[[7, 6],
[5, 4]],
<BLANKLINE>
[[3, 2],
[1, 0]]])
>>> vp.flip(A, (0, 2))
array([[[5, 4],
[7, 6]],
<BLANKLINE>
[[1, 0],
[3, 2]]])
>>> A = vp.random.randn(3, 4, 5)
>>> vp.all(vp.flip(A, 2) == A[:, :, ::-1, ...])
array(True)
"""
m = nlcpy.asanyarray(m)
if axis is None:
indexer = (slice(None, None, -1),) * m.ndim
else:
if type(axis) is nlcpy.ndarray:
axis = axis.get()
if type(axis) not in (tuple, list):
try:
axis = [operator.index(axis)]
except TypeError:
pass
_axis = []
for ax in axis:
if type(ax) is nlcpy.ndarray:
ax = ax.get()
if type(ax) is numpy.ndarray:
if ax.size > 1:
raise TypeError(
'only size-1 arrays can be converted to Python scalars')
else:
ax = ax.item()
_axis.append(ax + m.ndim if ax < 0 else ax)
axis = _axis
if len(axis) != len(set(axis)):
raise ValueError('repeated axis')
indexer = [slice(None) for i in range(m.ndim)]
for ax in axis:
if ax >= m.ndim or ax < 0:
raise AxisError(
'axis {0} is out of bounds for array of dimension {1}'
.format(ax, m.ndim))
indexer[ax] = slice(None, None, -1)
indexer = tuple(indexer)
return m[indexer]
[ドキュメント]def flipud(m):
"""Flips array in the up/down direction.
Flip the entries in each column in the up/down direction. Rows are preserved, but
appear in a different order than before.
Parameters
----------
m : array_like
Input array.
Returns
-------
out : `ndarray`
A view of *m* with the rows reversed. Since a view is returned, this operation
is done in constant time.
Note
----
Equivalent to ``m[::-1,...]``. Does not require the array to be two-dimensional.
See Also
--------
fliplr : Flips array in the left/right direction.
Examples
--------
>>> import nlcpy as vp
>>> A = vp.diag([1.0, 2, 3])
>>> A
array([[1., 0., 0.],
[0., 2., 0.],
[0., 0., 3.]])
>>> vp.flipud(A)
array([[0., 0., 3.],
[0., 2., 0.],
[1., 0., 0.]])
>>> A = vp.random.randn(2, 3, 5)
>>> vp.all(vp.flipud(A) == A[::-1, ...])
array(True)
>>> vp.flipud([1,2])
array([2, 1])
"""
m = nlcpy.asanyarray(m)
if m.ndim < 1:
raise ValueError("Input must be >= 1-d.")
return m[::-1, ...]
[ドキュメント]def fliplr(m):
"""Flips array in the left/right direction.
Flip the entries in each row in the left/right direction. Columns are preserved, but
appear in a different order than before.
Parameters
----------
m : array_like
Input array, must be at least 2-D.
Returns
-------
out : ndarray
A view of *m* with the columns reversed. Since a view is returned, this
operation is done in constant time.
Note
----
Equivalent to ``m[:,::-1]``. Requires the array to be at least 2-D.
See Also
--------
flipud : Flips array in the up/down direction.
Examples
--------
>>> import nlcpy as vp
>>> A = vp.diag([1., 2., 3.])
>>> A
array([[1., 0., 0.],
[0., 2., 0.],
[0., 0., 3.]])
>>> vp.fliplr(A)
array([[0., 0., 1.],
[0., 2., 0.],
[3., 0., 0.]])
>>> A = vp.random.randn(2, 3, 5)
>>> vp.all(vp.fliplr(A) == A[:, ::-1, ...])
array(True)
"""
m = nlcpy.asanyarray(m)
if m.ndim < 2:
raise ValueError("Input must be >= 2-d.")
return m[:, ::-1]
[ドキュメント]def roll(a, shift, axis=None):
"""Rolls array elements along a given axis.
Elements that roll beyond the last position are re-introduced at the first.
Parameters
----------
a : array_like
Input array.
shift : int or tuple of ints
The number of places by which elements are shifted. If a tuple, then *axis* must
be a tuple of the same size, and each of the given axes is shifted by the
corresponding number. If an int while *axis* is a tuple of ints, then the
same value is used for all given axes.
axis : int or tuple of ints, optional
Axis or axes along which elements are shifted. By default, the array is
flattened before shifting, after which the original shape is restored.
Returns
-------
res : ndarray
Output array, with the same shape as *a*.
See Also
--------
rollaxis : Rolls the specified axis backwards, until it lies in a given position.
Examples
--------
>>> import nlcpy as vp
>>> x = vp.arange(10)
>>> vp.roll(x, 2)
array([8, 9, 0, 1, 2, 3, 4, 5, 6, 7])
>>> vp.roll(x, -2)
array([2, 3, 4, 5, 6, 7, 8, 9, 0, 1])
>>> x2 = vp.reshape(x, (2,5))
>>> x2
array([[0, 1, 2, 3, 4],
[5, 6, 7, 8, 9]])
>>> vp.roll(x2, 1)
array([[9, 0, 1, 2, 3],
[4, 5, 6, 7, 8]])
>>> vp.roll(x2, -1)
array([[1, 2, 3, 4, 5],
[6, 7, 8, 9, 0]])
>>> vp.roll(x2, 1, axis=0)
array([[5, 6, 7, 8, 9],
[0, 1, 2, 3, 4]])
>>> vp.roll(x2, -1, axis=0)
array([[5, 6, 7, 8, 9],
[0, 1, 2, 3, 4]])
>>> vp.roll(x2, 1, axis=1)
array([[4, 0, 1, 2, 3],
[9, 5, 6, 7, 8]])
>>> vp.roll(x2, -1, axis=1)
array([[1, 2, 3, 4, 0],
[6, 7, 8, 9, 5]])
"""
a = nlcpy.asanyarray(a)
if axis is None:
return roll(a.ravel(), shift, 0).reshape(a.shape)
if type(axis) not in (tuple, list):
try:
axis = [operator.index(axis)]
except TypeError:
pass
_axis = axis.get() if isinstance(axis, nlcpy.ndarray) else axis
axis = [ax + a.ndim if ax < 0 else ax for ax in _axis]
for ax in axis:
if ax < 0 or ax >= a.ndim:
raise AxisError(
'axis {} is out of bounds for array of dimension {}'
.format(ax, a.ndim))
shift = nlcpy.asanyarray(shift)
axis = nlcpy.asanyarray(axis)
if shift.ndim > 1 or axis.ndim > 1:
raise ValueError(
"'shift' and 'axis' should be scalars or 1D sequences")
if shift.size > axis.size:
axis = nlcpy.broadcast_to(axis, shift.shape)
else:
shift = nlcpy.broadcast_to(shift, axis.shape)
shift = nlcpy.array(shift, dtype='l')
axis = nlcpy.array(axis, dtype='l')
result = nlcpy.empty(a.shape, dtype=a.dtype)
work = nlcpy.zeros(a.ndim, dtype='l')
request._push_request(
'nlcpy_roll',
'manipulation_op',
(a, shift, axis, work, result)
)
return result