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# numpy.testing.assert_allclose

`numpy.testing.``assert_allclose`(actual, desired, rtol=1e-07, atol=0, equal_nan=True, err_msg='', verbose=True)

  Raises an AssertionError if two objects are not equal up to desired tolerance.

  The test is equivalent to `allclose(actual, desired, rtol, atol)`. It compares the difference between actual and desired to `atol + rtol * abs(desired)`.

  New in version 1.5.0.

  Parameters: | actual : array_like Array obtained. desired : array_like Array desired. rtol : float, optional Relative tolerance. atol : float, optional Absolute tolerance. equal_nan : bool, optional. If True, NaNs will compare equal. err_msg : str, optional The error message to be printed in case of failure. verbose : bool, optional If True, the conflicting values are appended to the error message.
  Raises: | AssertionError If actual and desired are not equal up to specified precision.

  See also

  `assert_array_almost_equal_nulp`, `assert_array_max_ulp`

  Examples

      >>> x = [1e-5, 1e-3, 1e-1]
      >>> y = np.arccos(np.cos(x))
      >>> assert_allclose(x, y, rtol=1e-5, atol=0)