xorbits.numpy.real_if_close#
- xorbits.numpy.real_if_close(a, tol=100)#
If input is complex with all imaginary parts close to zero, return real parts.
“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 – If a is real, the type of a is used for the output. If a has complex elements, the returned type is float.
- Return type
ndarray
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 # may vary
>>> 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 + 3e-15j])
Warning
This method has not been implemented yet. Xorbits will try to execute it with numpy.
This docstring was copied from numpy.