Python testing.build_err_msg方法代碼示例

# 需要導入模塊: from numpy import testing [as 別名]
# 或者: from numpy.testing import build_err_msg [as 別名]
def assert_almost_equal(a, b, rtol=None, atol=None, names=('a', 'b'), equal_nan=False):
    """Test that two numpy arrays are almost equal. Raise exception message if not.

    Parameters
    ----------
    a : np.ndarray
    b : np.ndarray
    threshold : None or float
        The checking threshold. Default threshold will be used if set to ``None``.
    """
    rtol = get_rtol(rtol)
    atol = get_atol(atol)
    if almost_equal(a, b, rtol, atol, equal_nan=equal_nan):
        return
    index, rel = find_max_violation(a, b, rtol, atol)
    np.set_printoptions(threshold=4, suppress=True)
    msg = npt.build_err_msg([a, b],
                            err_msg="Error %f exceeds tolerance rtol=%f, atol=%f. "
                                    " Location of maximum error:%s, a=%f, b=%f"
                            % (rel, rtol, atol, str(index), a[index], b[index]),
                            names=names)
    raise AssertionError(msg) 

# 需要導入模塊: from numpy import testing [as 別名]
# 或者: from numpy.testing import build_err_msg [as 別名]
def _assert_floatstr_lines_equal(actual_lines, expected_lines):
    """A string comparison function that also works on Windows + Python 2.5.

    This is necessary because Python 2.5 on Windows inserts an extra 0 in
    the exponent of the string representation of floating point numbers.

    Only used in TestSaveTxt.test_complex_arrays, no attempt made to make this
    more generic.

    Once Python 2.5 compatibility is dropped, simply use `assert_equal` instead
    of this function.
    """
    for actual, expected in zip(actual_lines, expected_lines):
        if actual != expected:
            expected_win25 = expected.replace("e+00", "e+000")
            if actual != expected_win25:
                msg = build_err_msg([actual, expected], '', verbose=True)
                raise AssertionError(msg) 

# 需要導入模塊: from numpy import testing [as 別名]
# 或者: from numpy.testing import build_err_msg [as 別名]
def assert_almost_equal(a, b, rtol=None, atol=None, names=('a', 'b'), equal_nan=False):
    """Test that two numpy arrays are almost equal. Raise exception message if not.

    Parameters
    ----------
    a : np.ndarray
    b : np.ndarray
    threshold : None or float
        The checking threshold. Default threshold will be used if set to ``None``.
    """
    rtol = get_rtol(rtol)
    atol = get_atol(atol)

    if almost_equal(a, b, rtol, atol, equal_nan=equal_nan):
        return

    index, rel = find_max_violation(a, b, rtol, atol)
    np.set_printoptions(threshold=4, suppress=True)
    msg = npt.build_err_msg([a, b],
                            err_msg="Error %f exceeds tolerance rtol=%f, atol=%f. "
                                    " Location of maximum error:%s, a=%f, b=%f"
                            % (rel, rtol, atol, str(index), a[index], b[index]),
                            names=names)
    raise AssertionError(msg) 

# 需要導入模塊: from numpy import testing [as 別名]
# 或者: from numpy.testing import build_err_msg [as 別名]
def assert_array_compare(self, comparison, x, y, err_msg='', header='',
                         fill_value=True):
        """
        Assert that a comparison of two masked arrays is satisfied elementwise.

        """
        xf = self.filled(x)
        yf = self.filled(y)
        m = self.mask_or(self.getmask(x), self.getmask(y))

        x = self.filled(self.masked_array(xf, mask=m), fill_value)
        y = self.filled(self.masked_array(yf, mask=m), fill_value)
        if (x.dtype.char != "O"):
            x = x.astype(float_)
            if isinstance(x, np.ndarray) and x.size > 1:
                x[np.isnan(x)] = 0
            elif np.isnan(x):
                x = 0
        if (y.dtype.char != "O"):
            y = y.astype(float_)
            if isinstance(y, np.ndarray) and y.size > 1:
                y[np.isnan(y)] = 0
            elif np.isnan(y):
                y = 0
        try:
            cond = (x.shape == () or y.shape == ()) or x.shape == y.shape
            if not cond:
                msg = build_err_msg([x, y],
                                    err_msg
                                    + '\n(shapes %s, %s mismatch)' % (x.shape,
                                                                      y.shape),
                                    header=header,
                                    names=('x', 'y'))
                assert cond, msg
            val = comparison(x, y)
            if m is not self.nomask and fill_value:
                val = self.masked_array(val, mask=m)
            if isinstance(val, bool):
                cond = val
                reduced = [0]
            else:
                reduced = val.ravel()
                cond = reduced.all()
                reduced = reduced.tolist()
            if not cond:
                match = 100-100.0*reduced.count(1)/len(reduced)
                msg = build_err_msg([x, y],
                                    err_msg
                                    + '\n(mismatch %s%%)' % (match,),
                                    header=header,
                                    names=('x', 'y'))
                assert cond, msg
        except ValueError:
            msg = build_err_msg([x, y], err_msg, header=header, names=('x', 'y'))
            raise ValueError(msg)