You cannot select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
242 lines
7.3 KiB
Python
242 lines
7.3 KiB
Python
"""
|
|
Functions for acting on a axis of an array.
|
|
"""
|
|
import numpy as np
|
|
|
|
|
|
def axis_slice(a, start=None, stop=None, step=None, axis=-1):
|
|
"""Take a slice along axis 'axis' from 'a'.
|
|
|
|
Parameters
|
|
----------
|
|
a : numpy.ndarray
|
|
The array to be sliced.
|
|
start, stop, step : int or None
|
|
The slice parameters.
|
|
axis : int, optional
|
|
The axis of `a` to be sliced.
|
|
|
|
Examples
|
|
--------
|
|
>>> a = array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
|
|
>>> axis_slice(a, start=0, stop=1, axis=1)
|
|
array([[1],
|
|
[4],
|
|
[7]])
|
|
>>> axis_slice(a, start=1, axis=0)
|
|
array([[4, 5, 6],
|
|
[7, 8, 9]])
|
|
|
|
Notes
|
|
-----
|
|
The keyword arguments start, stop and step are used by calling
|
|
slice(start, stop, step). This implies axis_slice() does not
|
|
handle its arguments the exactly the same as indexing. To select
|
|
a single index k, for example, use
|
|
axis_slice(a, start=k, stop=k+1)
|
|
In this case, the length of the axis 'axis' in the result will
|
|
be 1; the trivial dimension is not removed. (Use numpy.squeeze()
|
|
to remove trivial axes.)
|
|
"""
|
|
a_slice = [slice(None)] * a.ndim
|
|
a_slice[axis] = slice(start, stop, step)
|
|
b = a[tuple(a_slice)]
|
|
return b
|
|
|
|
|
|
def axis_reverse(a, axis=-1):
|
|
"""Reverse the 1-D slices of `a` along axis `axis`.
|
|
|
|
Returns axis_slice(a, step=-1, axis=axis).
|
|
"""
|
|
return axis_slice(a, step=-1, axis=axis)
|
|
|
|
|
|
def odd_ext(x, n, axis=-1):
|
|
"""
|
|
Odd extension at the boundaries of an array
|
|
|
|
Generate a new ndarray by making an odd extension of `x` along an axis.
|
|
|
|
Parameters
|
|
----------
|
|
x : ndarray
|
|
The array to be extended.
|
|
n : int
|
|
The number of elements by which to extend `x` at each end of the axis.
|
|
axis : int, optional
|
|
The axis along which to extend `x`. Default is -1.
|
|
|
|
Examples
|
|
--------
|
|
>>> from scipy.signal._arraytools import odd_ext
|
|
>>> a = np.array([[1, 2, 3, 4, 5], [0, 1, 4, 9, 16]])
|
|
>>> odd_ext(a, 2)
|
|
array([[-1, 0, 1, 2, 3, 4, 5, 6, 7],
|
|
[-4, -1, 0, 1, 4, 9, 16, 23, 28]])
|
|
|
|
Odd extension is a "180 degree rotation" at the endpoints of the original
|
|
array:
|
|
|
|
>>> t = np.linspace(0, 1.5, 100)
|
|
>>> a = 0.9 * np.sin(2 * np.pi * t**2)
|
|
>>> b = odd_ext(a, 40)
|
|
>>> import matplotlib.pyplot as plt
|
|
>>> plt.plot(arange(-40, 140), b, 'b', lw=1, label='odd extension')
|
|
>>> plt.plot(arange(100), a, 'r', lw=2, label='original')
|
|
>>> plt.legend(loc='best')
|
|
>>> plt.show()
|
|
"""
|
|
if n < 1:
|
|
return x
|
|
if n > x.shape[axis] - 1:
|
|
raise ValueError(("The extension length n (%d) is too big. " +
|
|
"It must not exceed x.shape[axis]-1, which is %d.")
|
|
% (n, x.shape[axis] - 1))
|
|
left_end = axis_slice(x, start=0, stop=1, axis=axis)
|
|
left_ext = axis_slice(x, start=n, stop=0, step=-1, axis=axis)
|
|
right_end = axis_slice(x, start=-1, axis=axis)
|
|
right_ext = axis_slice(x, start=-2, stop=-(n + 2), step=-1, axis=axis)
|
|
ext = np.concatenate((2 * left_end - left_ext,
|
|
x,
|
|
2 * right_end - right_ext),
|
|
axis=axis)
|
|
return ext
|
|
|
|
|
|
def even_ext(x, n, axis=-1):
|
|
"""
|
|
Even extension at the boundaries of an array
|
|
|
|
Generate a new ndarray by making an even extension of `x` along an axis.
|
|
|
|
Parameters
|
|
----------
|
|
x : ndarray
|
|
The array to be extended.
|
|
n : int
|
|
The number of elements by which to extend `x` at each end of the axis.
|
|
axis : int, optional
|
|
The axis along which to extend `x`. Default is -1.
|
|
|
|
Examples
|
|
--------
|
|
>>> from scipy.signal._arraytools import even_ext
|
|
>>> a = np.array([[1, 2, 3, 4, 5], [0, 1, 4, 9, 16]])
|
|
>>> even_ext(a, 2)
|
|
array([[ 3, 2, 1, 2, 3, 4, 5, 4, 3],
|
|
[ 4, 1, 0, 1, 4, 9, 16, 9, 4]])
|
|
|
|
Even extension is a "mirror image" at the boundaries of the original array:
|
|
|
|
>>> t = np.linspace(0, 1.5, 100)
|
|
>>> a = 0.9 * np.sin(2 * np.pi * t**2)
|
|
>>> b = even_ext(a, 40)
|
|
>>> import matplotlib.pyplot as plt
|
|
>>> plt.plot(arange(-40, 140), b, 'b', lw=1, label='even extension')
|
|
>>> plt.plot(arange(100), a, 'r', lw=2, label='original')
|
|
>>> plt.legend(loc='best')
|
|
>>> plt.show()
|
|
"""
|
|
if n < 1:
|
|
return x
|
|
if n > x.shape[axis] - 1:
|
|
raise ValueError(("The extension length n (%d) is too big. " +
|
|
"It must not exceed x.shape[axis]-1, which is %d.")
|
|
% (n, x.shape[axis] - 1))
|
|
left_ext = axis_slice(x, start=n, stop=0, step=-1, axis=axis)
|
|
right_ext = axis_slice(x, start=-2, stop=-(n + 2), step=-1, axis=axis)
|
|
ext = np.concatenate((left_ext,
|
|
x,
|
|
right_ext),
|
|
axis=axis)
|
|
return ext
|
|
|
|
|
|
def const_ext(x, n, axis=-1):
|
|
"""
|
|
Constant extension at the boundaries of an array
|
|
|
|
Generate a new ndarray that is a constant extension of `x` along an axis.
|
|
|
|
The extension repeats the values at the first and last element of
|
|
the axis.
|
|
|
|
Parameters
|
|
----------
|
|
x : ndarray
|
|
The array to be extended.
|
|
n : int
|
|
The number of elements by which to extend `x` at each end of the axis.
|
|
axis : int, optional
|
|
The axis along which to extend `x`. Default is -1.
|
|
|
|
Examples
|
|
--------
|
|
>>> from scipy.signal._arraytools import const_ext
|
|
>>> a = np.array([[1, 2, 3, 4, 5], [0, 1, 4, 9, 16]])
|
|
>>> const_ext(a, 2)
|
|
array([[ 1, 1, 1, 2, 3, 4, 5, 5, 5],
|
|
[ 0, 0, 0, 1, 4, 9, 16, 16, 16]])
|
|
|
|
Constant extension continues with the same values as the endpoints of the
|
|
array:
|
|
|
|
>>> t = np.linspace(0, 1.5, 100)
|
|
>>> a = 0.9 * np.sin(2 * np.pi * t**2)
|
|
>>> b = const_ext(a, 40)
|
|
>>> import matplotlib.pyplot as plt
|
|
>>> plt.plot(arange(-40, 140), b, 'b', lw=1, label='constant extension')
|
|
>>> plt.plot(arange(100), a, 'r', lw=2, label='original')
|
|
>>> plt.legend(loc='best')
|
|
>>> plt.show()
|
|
"""
|
|
if n < 1:
|
|
return x
|
|
left_end = axis_slice(x, start=0, stop=1, axis=axis)
|
|
ones_shape = [1] * x.ndim
|
|
ones_shape[axis] = n
|
|
ones = np.ones(ones_shape, dtype=x.dtype)
|
|
left_ext = ones * left_end
|
|
right_end = axis_slice(x, start=-1, axis=axis)
|
|
right_ext = ones * right_end
|
|
ext = np.concatenate((left_ext,
|
|
x,
|
|
right_ext),
|
|
axis=axis)
|
|
return ext
|
|
|
|
|
|
def zero_ext(x, n, axis=-1):
|
|
"""
|
|
Zero padding at the boundaries of an array
|
|
|
|
Generate a new ndarray that is a zero-padded extension of `x` along
|
|
an axis.
|
|
|
|
Parameters
|
|
----------
|
|
x : ndarray
|
|
The array to be extended.
|
|
n : int
|
|
The number of elements by which to extend `x` at each end of the
|
|
axis.
|
|
axis : int, optional
|
|
The axis along which to extend `x`. Default is -1.
|
|
|
|
Examples
|
|
--------
|
|
>>> from scipy.signal._arraytools import zero_ext
|
|
>>> a = np.array([[1, 2, 3, 4, 5], [0, 1, 4, 9, 16]])
|
|
>>> zero_ext(a, 2)
|
|
array([[ 0, 0, 1, 2, 3, 4, 5, 0, 0],
|
|
[ 0, 0, 0, 1, 4, 9, 16, 0, 0]])
|
|
"""
|
|
if n < 1:
|
|
return x
|
|
zeros_shape = list(x.shape)
|
|
zeros_shape[axis] = n
|
|
zeros = np.zeros(zeros_shape, dtype=x.dtype)
|
|
ext = np.concatenate((zeros, x, zeros), axis=axis)
|
|
return ext
|