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| 1 | try: | |
| 2 | import numpypy as N | |
| 3 | except: | |
| 4 | import numpy as N | |
| 5 | ||
| 6 | def array_equal(a1, a2): | |
| 7 | """ | |
| 8 | True if two arrays have the same shape and elements, False otherwise. | |
| 9 | ||
| 10 | Parameters | |
| 11 | ---------- | |
| 12 | a1, a2 : array_like | |
| 13 | Input arrays. | |
| 14 | ||
| 15 | Returns | |
| 16 | ------- | |
| 17 | b : bool | |
| 18 | Returns True if the arrays are equal. | |
| 19 | ||
| 20 | See Also | |
| 21 | -------- | |
| 22 | allclose: Returns True if two arrays are element-wise equal within a | |
| 23 | tolerance. | |
| 24 | array_equiv: Returns True if input arrays are shape consistent and all | |
| 25 | elements equal. | |
| 26 | ||
| 27 | Examples | |
| 28 | -------- | |
| 29 | >>> np.array_equal([1, 2], [1, 2]) | |
| 30 | True | |
| 31 | >>> np.array_equal(np.array([1, 2]), np.array([1, 2])) | |
| 32 | True | |
| 33 | >>> np.array_equal([1, 2], [1, 2, 3]) | |
| 34 | False | |
| 35 | >>> np.array_equal([1, 2], [1, 4]) | |
| 36 | False | |
| 37 | ||
| 38 | """ | |
| 39 | try: | |
| 40 | #a1, a2 = asarray(a1), asarray(a2) | |
| 41 | # N.asarray(v) doesn't work - asarray is unimplemented yet, using walkaround instead. | |
| 42 | # TODO: may be comparison of numpy array with sparse matrix, maybe take care of it? | |
| 43 | # array(sparse matrix) in CPython numpy currently returns array of size one and dtype "object" | |
| 44 | if not isinstance(a1, N.ndarray): | |
| 45 | a1 = N.array(a1) | |
| 46 | if not isinstance(a2, N.ndarray): | |
| 47 | a2 = N.array(a2) | |
| 48 | except: | |
| 49 | return False | |
| 50 | if a1.shape != a2.shape: | |
| 51 | return False | |
| 52 | ||
| 53 | ||
| 54 | # CPython numpy version: | |
| 55 | #return bool(logical_and.reduce(equal(a1,a2).ravel())) | |
| 56 | ||
| 57 | # PyPy version: | |
| 58 | if a1.ndim == 0: # else bug with zero-size array indexation | |
| 59 | return a1 == a2 | |
| 60 | - | a1, a2 = a1.flat, a2.flat |
| 60 | + | |
| 61 | - | for i in range(Size): |
| 61 | + | f1, f2 = a1.flat, a2.flat |
| 62 | - | if a1[i] != a2[i]: return False |
| 62 | + | # TODO: replace xrange by range in Python3 |
| 63 | - | return True |
| 63 | + | for i in xrange(Size): |
| 64 | if f1.next() != f2.next(): return False | |
| 65 | return True | |
| 66 | ||
| 67 | if __name__ == '__main__': | |
| 68 | assert array_equal(1, 1) | |
| 69 | assert array_equal([1, 2], [1, 2]) | |
| 70 | assert array_equal(N.array([1, 2]), N.array([1, 2])) | |
| 71 | assert array_equal([1, 2], N.array([1, 2])) | |
| 72 | assert not array_equal([1, 2], [1, 2, 3]) | |
| 73 | assert array_equal(N.ones([2, 3, 4]), N.ones([2, 3, 4])) | |
| 74 | assert array_equal(N.ones([2, 3, 4]), N.ones([2, 3, 4], int)) | |
| 75 | assert not array_equal(N.ones([2, 3, 4]), N.zeros([2, 3, 4], int)) | |
| 76 | ||
| 77 | print('passed')
| |
| 78 | ||
| 79 | #from time import time | |
| 80 | #n = 100000 | |
| 81 | #m = 100 | |
| 82 | #a = N.zeros(n) | |
| 83 | #b = N.ones(n) | |
| 84 | #t = time() | |
| 85 | #for i in range(m): | |
| 86 | # N.array_equal(a, b) | |
| 87 | #print('classic numpy array_equal time elapsed (on different arrays): %0.5f' % (time()-t))
| |
| 88 | # | |
| 89 | # | |
| 90 | #t = time() | |
| 91 | #for i in range(m): | |
| 92 | # array_equal(a, b) | |
| 93 | #print('Alternative array_equal time elapsed (on different arrays): %0.5f' % (time()-t))
| |
| 94 | # | |
| 95 | #b = N.zeros(n) | |
| 96 | # | |
| 97 | #t = time() | |
| 98 | #for i in range(m): | |
| 99 | # N.array_equal(a, b) | |
| 100 | #print('classic numpy array_equal time elapsed (on same arrays): %0.5f' % (time()-t))
| |
| 101 | # | |
| 102 | #t = time() | |
| 103 | #for i in range(m): | |
| 104 | # array_equal(a, b) | |
| 105 | #print('Alternative array_equal time elapsed (on same arrays): %0.5f' % (time()-t)) |
