numpy.real_if_close#

numpy.real_if_close(a, tol=100)[source]#

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:

aarray_like: Input array.
tolfloat: 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:

outndarray: 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(float).eps’ to print out the machine epsilon for floats.

Examples

>>> import numpy as np
>>> 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])