Function assert_array_compare

numpy/testing/_private/utils.py:738–996

(comparison, x, y, err_msg='', verbose=True, header='',
                         precision=6, equal_nan=True, equal_inf=True,
                         *, strict=False, names=('ACTUAL', 'DESIRED'))

def assert_array_compare(comparison, x, y, err_msg='', verbose=True, header='',
                         precision=6, equal_nan=True, equal_inf=True,
                         *, strict=False, names=('ACTUAL', 'DESIRED')):
    __tracebackhide__ = True  # Hide traceback for py.test
    from numpy._core import all, array2string, errstate, inf, isnan, max, object_

    x = np.asanyarray(x)
    y = np.asanyarray(y)

    # original array for output formatting
    ox, oy = x, y

    def isnumber(x):
        return type(x.dtype)._is_numeric

    def istime(x):
        return x.dtype.char in "Mm"

    def isvstring(x):
        return x.dtype.char == "T"

    def robust_any_difference(x, y):
        # We include work-arounds here to handle three types of slightly
        # pathological ndarray subclasses:
        # (1) all() on fully masked arrays returns np.ma.masked, so we use != True
        #     (np.ma.masked != True evaluates as np.ma.masked, which is falsy).
        # (2) __eq__ on some ndarray subclasses returns Python booleans
        #     instead of element-wise comparisons, so we cast to np.bool() in
        #     that case (or in case __eq__ returns some other value with no
        #     all() method).
        # (3) subclasses with bare-bones __array_function__ implementations may
        #     not implement np.all(), so favor using the .all() method
        # We are not committed to supporting cases (2) and (3), but it's nice to
        # support them if possible.
        result = x == y
        if not hasattr(result, "all") or not callable(result.all):
            result = np.bool(result)
        return result.all() != True

    def func_assert_same_pos(x, y, func=isnan, hasval='nan'):
        """Handling nan/inf.

        Combine results of running func on x and y, checking that they are True
        at the same locations.

        """
        __tracebackhide__ = True  # Hide traceback for py.test

        x_id = func(x)
        y_id = func(y)
        if robust_any_difference(x_id, y_id):
            msg = build_err_msg(
                [x, y],
                err_msg + f'\n{hasval} location mismatch:',
                verbose=verbose, header=header,
                names=names,
                precision=precision)
            raise AssertionError(msg)