flopscope.numpy.setdiff1d

fnp.setdiff1d(ar1, ar2, assume_unique=False)[flopscope source][numpy source]

Find the set difference of two arrays.

Adapted from NumPy docs np.setdiff1d

Areacore

Typecustom

Cost

per-operation

Flopscope Context

Set difference; cost = (n+m)*ceil(log2(n+m)).

Return the unique values in ar1 that are not in ar2.

Parameters

ar1:array_like: Input array.
ar2:array_like: Input comparison array.
assume_unique:bool: If True, the input arrays are both assumed to be unique, which can speed up the calculation. Default is False.

setdiff1d:ndarray: 1D array of values in ar1 that are not in ar2. The result is sorted when assume_unique=False, but otherwise only sorted if the input is sorted.

>>> import flopscope.numpy as fnp
>>> a = flops.array([1, 2, 3, 2, 4, 1])
>>> b = flops.array([3, 4, 5, 6])
>>> flops.setdiff1d(a, b)
array([1, 2])