Looking for the fastest way to find the exact overlap between two arrays of equal length in numpy

Question

I am looking for the optimal (fastest) way to find the exact overlap between two arrays in numpy. Given two arrays x and y

x = array([1,0,3,0,5,0,7,4],dtype=         


        

Answer 1

try numpy.in1d... from the documentation....

Test whether each element of a 1D array is also present in a second array.

Returns a boolean array the same length as ar1 that is True where an element of ar1 is in ar2 and False otherwise.

Parameters

ar1 : array_like, shape (M,) Input array. ar2 : array_like The values against which to test each value of ar1. assume_unique : bool, optional If True, the input arrays are both assumed to be unique, which can speed up the calculation. Default is False.

Returns

mask : ndarray of bools, shape(M,) The values ar1[mask] are in ar2.

See Also

numpy.lib.arraysetops : Module with a number of other functions for performing set operations on arrays.

Notes

in1d can be considered as an element-wise function version of the python keyword in, for 1D sequences. in1d(a, b) is roughly equivalent to np.array([item in b for item in a]).

.. versionadded:: 1.4.0

Examples

test = np.array([0, 1, 2, 5, 0])
states = [0, 2]
mask = np.in1d(test, states)
mask
    array([ True, False,  True, False,  True], dtype=bool)
test[mask]
    array([0, 2, 0])