SciPy

numpy.testing.assert_array_less

numpy.testing.assert_array_less(x, y, err_msg='', verbose=True)[source]

Raises an AssertionError if two array_like objects are not ordered by less than.

Given two array_like objects, check that the shape is equal and all elements of the first object are strictly smaller than those of the second object. An exception is raised at shape mismatch or incorrectly ordered values. Shape mismatch does not raise if an object has zero dimension. In contrast to the standard usage in numpy, NaNs are compared, no assertion is raised if both objects have NaNs in the same positions.

Parameters:

x : array_like

The smaller object to check.

y : array_like

The larger object to compare.

err_msg : string

The error message to be printed in case of failure.

verbose : bool

If True, the conflicting values are appended to the error message.

Raises:

AssertionError :

If actual and desired objects are not equal.

See also

assert_array_equal
tests objects for equality
assert_array_almost_equal
test objects for equality up to precision

Examples

>>> np.testing.assert_array_less([1.0, 1.0, np.nan], [1.1, 2.0, np.nan])
>>> np.testing.assert_array_less([1.0, 1.0, np.nan], [1, 2.0, np.nan])
...
<type 'exceptions.ValueError'>:
Arrays are not less-ordered
(mismatch 50.0%)
 x: array([  1.,   1.,  NaN])
 y: array([  1.,   2.,  NaN])
>>> np.testing.assert_array_less([1.0, 4.0], 3)
...
<type 'exceptions.ValueError'>:
Arrays are not less-ordered
(mismatch 50.0%)
 x: array([ 1.,  4.])
 y: array(3)
>>> np.testing.assert_array_less([1.0, 2.0, 3.0], [4])
...
<type 'exceptions.ValueError'>:
Arrays are not less-ordered
(shapes (3,), (1,) mismatch)
 x: array([ 1.,  2.,  3.])
 y: array([4])