Remove unused allclose and assert_allclose helpers

array_api_tests/array_helpers.py

@@ -10,10 +10,6 @@
 from . import _array_module as xp
 from . import dtype_helpers as dh
 
-from ndindex import iter_indices
-
-import math
-
 __all__ = ['all', 'any', 'logical_and', 'logical_or', 'logical_not', 'less',
            'less_equal', 'greater', 'subtract', 'negative', 'floor', 'ceil',
            'where', 'isfinite', 'equal', 'not_equal', 'zero', 'one', 'NaN',
@@ -150,43 +146,6 @@ def exactly_equal(x, y):
 
     return equal(x, y)
 
-def allclose(x, y, rel_tol=0.25, abs_tol=1, return_indices=False):
-    """
-    Return True all elements of x and y are within tolerance
-
-    If return_indices=True, returns (False, (i, j)) when the arrays are not
-    close, where i and j are the indices into x and y of corresponding
-    non-close elements.
-    """
-    for i, j in iter_indices(x.shape, y.shape):
-        i, j = i.raw, j.raw
-        a = x[i]
-        b = y[j]
-        if not (math.isfinite(a) and math.isfinite(b)):
-            # TODO: If a and b are both infinite, require the same type of infinity
-            continue
-        close = math.isclose(a, b, rel_tol=rel_tol, abs_tol=abs_tol)
-        if not close:
-            if return_indices:
-                return (False, (i, j))
-            return False
-    return True
-
-def assert_allclose(x, y, rel_tol=1, abs_tol=0.):
-    """
-    Test that x and y are approximately equal to each other.
-
-    Also asserts that x and y have the same shape and dtype.
-    """
-    assert x.shape == y.shape, f"The input arrays do not have the same shapes ({x.shape} != {y.shape})"
-
-    assert x.dtype == y.dtype, f"The input arrays do not have the same dtype ({x.dtype} != {y.dtype})"
-
-    c = allclose(x, y, rel_tol=rel_tol, abs_tol=abs_tol, return_indices=True)
-    if c is not True:
-        _, (i, j) = c
-        raise AssertionError(f"The input arrays are not close with {rel_tol = } and {abs_tol = } at indices {i = } and {j = }")
-
 def notequal(x, y):
     """
     Same as not_equal(x, y) except it gives False when both values are nan.