def _assertPreciseEqual(self, first, second, prec='exact', ulps=1,
                            msg=None, ignore_sign_on_zero=False,
                            abs_tol=None):

        def _assertNumberEqual(first, second, delta=None):
            if (delta is None or first == second == 0.0
                or math.isinf(first) or math.isinf(second)):
                self.assertEqual(first, second, msg=msg)
                # For signed zeros
                if not ignore_sign_on_zero:
                    try:
                        if math.copysign(1, first) != math.copysign(1, second):
                            self.fail(
                                self._formatMessage(msg,
                                                    "%s != %s" %
                                                    (first, second)))
                    except TypeError:
                        pass
            else:
                self.assertAlmostEqual(first, second, delta=delta, msg=msg)

        first_family = self._detect_family(first)
        second_family = self._detect_family(second)

        assertion_message = "Type Family mismatch. (%s != %s)" % (first_family,
            second_family)
        if msg:
            assertion_message += ': %s' % (msg,)
        self.assertEqual(first_family, second_family, msg=assertion_message)

        # We now know they are in the same comparison family
        compare_family = first_family

        # For recognized sequences, recurse
        if compare_family == "ndarray":
            dtype = self._fix_dtype(first.dtype)
            self.assertEqual(dtype, self._fix_dtype(second.dtype))
            self.assertEqual(first.ndim, second.ndim,
                             "different number of dimensions")
            self.assertEqual(first.shape, second.shape,
                             "different shapes")
            self.assertEqual(first.flags.writeable, second.flags.writeable,
                             "different mutability")
            # itemsize is already checked by the dtype test above
            self.assertEqual(self._fix_strides(first),
                self._fix_strides(second), "different strides")
            if first.dtype != dtype:
                first = first.astype(dtype)
            if second.dtype != dtype:
                second = second.astype(dtype)
            for a, b in zip(first.flat, second.flat):
                self._assertPreciseEqual(a, b, prec, ulps, msg,
                                         ignore_sign_on_zero, abs_tol)
            return

        elif compare_family == "sequence":
            self.assertEqual(len(first), len(second), msg=msg)
            for a, b in zip(first, second):
                self._assertPreciseEqual(a, b, prec, ulps, msg,
                                         ignore_sign_on_zero, abs_tol)
            return

        elif compare_family == "exact":
            exact_comparison = True

        elif compare_family in ["complex", "approximate"]:
            exact_comparison = False

        elif compare_family == "enum":
            self.assertIs(first.__class__, second.__class__)
            self._assertPreciseEqual(first.value, second.value,
                                     prec, ulps, msg,
                                     ignore_sign_on_zero, abs_tol)
            return

        elif compare_family == "unknown":
            # Assume these are non-numeric types: we will fall back
            # on regular unittest comparison.
            self.assertIs(first.__class__, second.__class__)
            exact_comparison = True

        else:
            assert 0, "unexpected family"

        # If a Numpy scalar, check the dtype is exactly the same too
        # (required for datetime64 and timedelta64).
        if hasattr(first, 'dtype') and hasattr(second, 'dtype'):
            self.assertEqual(first.dtype, second.dtype)

        # Mixing bools and non-bools should always fail
        if (isinstance(first, self._bool_types) !=
            isinstance(second, self._bool_types)):
            assertion_message = ("Mismatching return types (%s vs. %s)"
                                 % (first.__class__, second.__class__))
            if msg:
                assertion_message += ': %s' % (msg,)
            self.fail(assertion_message)

        try:
            if cmath.isnan(first) and cmath.isnan(second):
                # The NaNs will compare unequal, skip regular comparison
                return
        except TypeError:
            # Not floats.
            pass

        # if absolute comparison is set, use it
        if abs_tol is not None:
            if abs_tol == "eps":
                rtol = np.finfo(type(first)).eps
            elif isinstance(abs_tol, float):
                rtol = abs_tol
            else:
                raise ValueError("abs_tol is not \"eps\" or a float, found %s"
                    % abs_tol)
            if abs(first - second) < rtol:
                return

        exact_comparison = exact_comparison or prec == 'exact'

        if not exact_comparison and prec != 'exact':
            if prec == 'single':
                bits = 24
            elif prec == 'double':
                bits = 53
            else:
                raise ValueError("unsupported precision %r" % (prec,))
            k = 2 ** (ulps - bits - 1)
            delta = k * (abs(first) + abs(second))
        else:
            delta = None
        if isinstance(first, self._complex_types):
            _assertNumberEqual(first.real, second.real, delta)
            _assertNumberEqual(first.imag, second.imag, delta)
        else:
            _assertNumberEqual(first, second, delta)
Recursive workhorse for assertPreciseEqual().
dataset/ETHPy150Open numba/numba/numba/tests/support.py/TestCase._assertPreciseEqual