在Python中比较两个2D元组和numpy

Question

I have two nested tuples named coord and coord2 and I want to see if one set of coordinates in the first tuple match another in the other tuple regardless of the index.

For example,

coord[0][1] = 127,
coord[0][2] = 128,
coord[0] = 127,128,129....
coord[1][0] = 302,
coord[1] = 302,303,304 ....

Right now I can see if each index matches the other tuple's index exactly, but not whether one set exists in the other. Here is my code:

for i in range(60):
if (coord[0][i]) == (coord2[0][i]) and (coord[1][i]) == (coord2[1][i]):
    print(coord[0][i])
    print(coord[1][i])
    count += 1
    total += 1
else:
    total += 1

How should I go about doing this? I am pretty new to using numpy arrays in python

I have written some new code like so,

for i in range(60):
    if coord2[0][i] and coord2[1][i] in coord:
        count += 1
        total += 1
    else:
        total += 1

In my mind this should tell me if any set of coordinates in the second tuple is in the first one. But I am running into an error saying, ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

Answer 1

Actually figured it out.

for i in range(200):
    if (coord2[0][i]) in coord[0] and coord2[1][i] in coord[1]:
        count += 1
        total += 1
    else:
        total += 1

Answer 2

If you simply want to know if any of the coordinates of one matrix exist in another then this is one way of doing it.

import itertools
import numpy

First let's get all possible index combinations for the matrices

idx = tuple(e for e in itertools.product(range(len(coord)), repeat=2))

((0, 0),
 (0, 1),
 (0, 2),
 (0, 3),
 (1, 0),
 (1, 1),
 (1, 2),
 (1, 3),
 (2, 0),
 (2, 1),
 (2, 2),
 (2, 3),
 (3, 0),
 (3, 1),
 (3, 2),
 (3, 3))

Then let's compare the two indexed matrices and see if any of the points exist in the other

coord = np.arange(16).reshape(4,4)

coord1 = np.random.randint(1, size=(4,4))

np.equal([coord[_idx] for _idx in idx],[coord1[_idx] for _idx in idx])

array([ True, False, False, False, False, False, False, False, False,
       False, False, False, False, False, False, False], dtype=bool)

Edit: If you simply want the number of occurrences then it becomes this

np.sum(np.equal([coord[_idx] for _idx in idx],[coord1[_idx] for _idx in idx]))

>>1