numpy.testing.assert_allclose#

testing.assert_allclose(actual,desired,rtol=1e-07,atol=0,equal_nan=True,err_msg='',verbose=True,*,strict=False)[source]#

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

Given two array_like objects, check that their shapes and all elementsare equal (but see the Notes for the special handling of a scalar). Anexception is raised if the shapes mismatch or any values conflict. Incontrast to the standard usage in numpy, NaNs are compared like numbers,no assertion is raised if both objects have NaNs in the same positions.

The test is equivalent toallclose(actual,desired,rtol,atol) (notethatallclose has different default values). It compares the differencebetweenactual anddesired toatol+rtol*abs(desired).

Parameters:
actualarray_like

Array obtained.

desiredarray_like

Array desired.

rtolfloat, optional

Relative tolerance.

atolfloat, optional

Absolute tolerance.

equal_nanbool, optional.

If True, NaNs will compare equal.

err_msgstr, optional

The error message to be printed in case of failure.

verbosebool, optional

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

strictbool, optional

If True, raise anAssertionError when either the shape or the datatype of the arguments does not match. The special handling of scalarsmentioned in the Notes section is disabled.

New in version 2.0.0.

Raises:
AssertionError

If actual and desired are not equal up to specified precision.

Notes

When one ofactual anddesired is a scalar and the other isarray_like, the function performs the comparison as if the scalar werebroadcasted to the shape of the array.This behaviour can be disabled with thestrict parameter.

Examples

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

As mentioned in the Notes section,assert_allclose has specialhandling for scalars. Here, the test checks that the value ofnumpy.sinis nearly zero at integer multiples of π.

>>>x=np.arange(3)*np.pi>>>np.testing.assert_allclose(np.sin(x),0,atol=1e-15)

Usestrict to raise anAssertionError when comparing an arraywith one or more dimensions against a scalar.

>>>np.testing.assert_allclose(np.sin(x),0,atol=1e-15,strict=True)Traceback (most recent call last):...AssertionError:Not equal to tolerance rtol=1e-07, atol=1e-15(shapes (3,), () mismatch) ACTUAL: array([ 0.000000e+00,  1.224647e-16, -2.449294e-16]) DESIRED: array(0)

Thestrict parameter also ensures that the array data types match:

>>>y=np.zeros(3,dtype=np.float32)>>>np.testing.assert_allclose(np.sin(x),y,atol=1e-15,strict=True)Traceback (most recent call last):...AssertionError:Not equal to tolerance rtol=1e-07, atol=1e-15(dtypes float64, float32 mismatch) ACTUAL: array([ 0.000000e+00,  1.224647e-16, -2.449294e-16]) DESIRED: array([0., 0., 0.], dtype=float32)