location of array of values in numpy array

Question

Here is a small code to illustrate the problem.

A = array([[1,2], [1,0], [5,3]])
f_of_A = f(A)   # this is precomputed and expensive


values = array([[1,2], [1,         


        

Answer 1

You can use np.in1d over a view of your original array with all coordinates collapsed into a single variable of dtype np.void:

import numpy as np

A = np.array([[1,2], [1,0], [5,3]])
values = np.array([[1,2], [1,0]])

# Make sure both arrays are contiguous and have common dtype
common_dtype = np.common_type(A, values)
a = np.ascontiguousarray(A, dtype=common_dtype)
vals = np.ascontiguousarray(values, dtype=common_dtype)

a_view = A.view((np.void, A.dtype.itemsize*A.shape[1])).ravel()
values_view = values.view((np.void,
                           values.dtype.itemsize*values.shape[1])).ravel()

Now each item of a_view and values_view is all coordinates for one point packed together, so you can do whatever 1D magic you would use. I don't see how to use np.in1d to find indices though, so I would go the np.searchsorted route:

sort_idx = np.argsort(a_view)
locations = np.searchsorted(a_view, values_view, sorter=sort_idx)
locations = sort_idx[locations]

>>> locations
array([0, 1], dtype=int64)