Miscellaneous

Module: pycsou.util.misc

Miscellaneous functions.

Miscellaneous functions.

is_range_broadcastable(shape1, shape2)	Check if two shapes satisfy Numpy’s broadcasting rules.
range_broadcast_shape(shape1, shape2)	Given two shapes, determine broadcasting shape.
peaks(x, y)	Matlab 2D peaks function.

is_range_broadcastable(shape1: Tuple[int, int], shape2: Tuple[int, int]) → bool

Check if two shapes satisfy Numpy’s broadcasting rules.

Parameters

• shape1 (Tuple[int, int]) –

• shape2 (Tuple[int, int]) –

Returns

True if broadcastable, False otherwise.

Return type

bool

Examples

>>> is_range_broadcastable((3,2), (1,2))
True
>>> is_range_broadcastable((3,2), (4,2))
False

range_broadcast_shape(shape1: Tuple[int, int], shape2: Tuple[int, int]) → Tuple[int, int]

Given two shapes, determine broadcasting shape.

Parameters

• shape1 (Tuple[int, int]) –

• shape2 (Tuple[int, int]) –

Returns

Broadcasting shape.

Return type

Tuple[int, int]

Raises

ValueError – If the two shapes cannot be broadcasted.

Examples

>>> range_broadcast_shape((3,2), (1,2))
(3, 2)

peaks(x: numpy.ndarray, y: numpy.ndarray) → numpy.ndarray

Matlab 2D peaks function.

Peaks is a function of two variables, obtained by translating and scaling Gaussian distributions (see Matlab’s peaks function <https://www.mathworks.com/help/matlab/ref/peaks.html>). This function is useful for testing purposes.

Parameters

• x (np.ndarray) – X coordinates.

• y (np.ndarray) – Y coordinates.

Returns

Values of the 2D function peaks at the points specified by the entries of x and y.

Return type

np.ndarray

Examples

import numpy as np
import matplotlib.pyplot as plt
from pycsou.util.misc import peaks

x = np.linspace(-3,3, 1000)
X,Y = np.meshgrid(x,x)
Z = peaks(X,Y)
plt.figure()
plt.imshow(Z)

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