numpy.real_if_close¶
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numpy.
real_if_close
(a, tol=100)[source]¶ 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.
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
>>> np.finfo(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])