numpy.real_if_close

numpy.real_if_close(a, tol=100)

If complex input returns a real array if complex parts are close to zero.

“Close to zero” is defined as tol * (machine epsilon of the type for a).

Parameters:

a : array_like

Input array.

tol : float

Tolerance in machine epsilons for the complex part of the elements in the array.

Returns:

out : ndarray

If a is real, the type of a is used for the output. If a has complex elements, the returned type is float.

See also

real, imag, angle

Notes

Machine epsilon varies from machine to machine and between data types but Python floats on most platforms have a machine epsilon equal to 2.2204460492503131e-16. You can use ‘np.finfo(np.float).eps’ to print out the machine epsilon for floats.

Examples

>>> np.finfo(np.float).eps
2.2204460492503131e-16

>>> np.real_if_close([2.1 + 4e-14j], tol=1000)
array([ 2.1])
>>> np.real_if_close([2.1 + 4e-13j], tol=1000)
array([ 2.1 +4.00000000e-13j])