The numpy.compress() function returns selected slices of an array along mentioned axis, that satisfies an axis.
Syntax: numpy.compress(condition, array, axis = None, out = None)
Parameters :
condition : [array_like]Condition on the basis of which user extract elements.
Applying condition on input_array, if we print condition, it will return an arra
filled with either True or False. Array elements are extracted from the Indices having
True value.
array : Input array. User apply conditions on input_array elements
axis : [optional, int]Indicating which slice to select.
By Default, work on flattened array[1-D]
out : [optional, ndarray]Output_array with elements of input_array,
that satisfies condition
Return :
Copy of array with elements of input_array, that satisfies condition and along given axis
# Python Program illustrating # numpy.compress method import numpy as geek array = geek.arange(10).reshape(5, 2) print("Original array : \n", array) a = geek.compress([0, 1], array, axis=0) print("\nSliced array : \n", a) a = geek.compress([False, True], array, axis=0) print("\nSliced array : \n", a) |
Output :
Original array : [[0 1] [2 3] [4 5] [6 7] [8 9]] Sliced array : [[2 3]] Sliced array : [[2 3]]
References :
https://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.compress.html
Note :
This codes won’t run on online-ID. Please run them on your systems to explore the working.
.
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