numpy.testing.assert_equal

numpy.testing.assert_equal(actual, desired, err_msg='', verbose=True) [source]

Raises an AssertionError if two objects are not equal.

Given two objects (scalars, lists, tuples, dictionaries or numpy arrays), check that all elements of these objects are equal. An exception is raised at the first conflicting values.

This function handles NaN comparisons as if NaN was a “normal” number. That is, no assertion is raised if both objects have NaNs in the same positions. This is in contrast to the IEEE standard on NaNs, which says that NaN compared to anything must return False.

Parameters:	actual : array_like The object to check. desired : array_like The expected object. 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.

Examples

>>> np.testing.assert_equal([4,5], [4,6])
Traceback (most recent call last):
    ...
AssertionError:
Items are not equal:
item=1
 ACTUAL: 5
 DESIRED: 6

The following comparison does not raise an exception. There are NaNs in the inputs, but they are in the same positions.

>>> np.testing.assert_equal(np.array([1.0, 2.0, np.nan]), [1, 2, np.nan])