A RetroSearch Logo

Home - News ( United States | United Kingdom | Italy | Germany ) - Football scores

Search Query:

Showing content from http://docs.scipy.org/doc/numpy/reference/generated/numpy.place.html below:

numpy.place — NumPy v2.3 Manual

numpy.place#
numpy.place(arr, mask, vals)[source]#

Change elements of an array based on conditional and input values.

Similar to np.copyto(arr, vals, where=mask), the difference is that place uses the first N elements of vals, where N is the number of True values in mask, while copyto uses the elements where mask is True.

Note that extract does the exact opposite of place.

Parameters:
arrndarray

Array to put data into.

maskarray_like

Boolean mask array. Must have the same size as a.

vals1-D sequence

Values to put into a. Only the first N elements are used, where N is the number of True values in mask. If vals is smaller than N, it will be repeated, and if elements of a are to be masked, this sequence must be non-empty.

Examples

>>> import numpy as np
>>> arr = np.arange(6).reshape(2, 3)
>>> np.place(arr, arr>2, [44, 55])
>>> arr
array([[ 0,  1,  2],
       [44, 55, 44]])

RetroSearch is an open source project built by @garambo | Open a GitHub Issue

Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo

HTML: 3.2 | Encoding: UTF-8 | Version: 0.7.4