flopscope.

flopscope.numpy.extract

fnp.extract(condition, arr)[flopscope source][numpy source]

Return the elements of an array that satisfy some condition.

Adapted from NumPy docs np.extract

Areacore
Typecustom
NumPy Refnp.extract
Cost
4×per-operation
Flopscope Context

Return elements satisfying condition. Cost: numel(input).

This is equivalent to flops.compress(ravel(condition), ravel(arr)). If condition is boolean flops.extract is equivalent to arr[condition].

Note that place does the exact opposite of extract.

Parameters

condition:array_like

An array whose nonzero or True entries indicate the elements of arr to extract.

arr:array_like

Input array of the same size as condition.

Returns

extract:ndarray

Rank 1 array of values from arr where condition is True.

See also

Examples

>>> import flopscope.numpy as fnp
>>> arr = flops.arange(12).reshape((3, 4))
>>> arr
array([[ 0,  1,  2,  3],
       [ 4,  5,  6,  7],
       [ 8,  9, 10, 11]])
>>> condition = flops.mod(arr, 3)==0
>>> condition
array([[ True, False, False,  True],
       [False, False,  True, False],
       [False,  True, False, False]])
>>> flops.extract(condition, arr)
array([0, 3, 6, 9])

If condition is boolean:

>>> arr[condition]
array([0, 3, 6, 9])