`numpy:real_if_close`

source: /dev/numpy/build-install/usr/lib/python3.14/site-packages/numpy/lib/_type_check_impl.py:500

Signature

def real_if_close(a, tol = 100)

Summary

If input is complex with all imaginary parts close to zero, return real parts.

Extended Summary

"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. If the tolerance is <=1, then the absolute tolerance is used.

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.

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(float).eps' to print out the machine epsilon for floats.

Examples

import numpy as np

✓

np.finfo(float).eps

✗

np.float64(2.220446049250313e-16)

np.real_if_close([2.1 + 4e-14j, 5.2 + 3e-15j], tol=1000)

✓

array([2.1, 5.2])

np.real_if_close([2.1 + 4e-13j, 5.2 + 3e-15j], tol=1000)

✗

array([2.1+4.e-13j, 5.2+3.e-15j])

Aliases

numpy.real_if_close