numpy.real_if_close()

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:

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.

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(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])

Links:

https://docs.scipy.org/doc/numpy-1.11.0/reference/generated/numpy.real_if_close.html

doc_NumPy

2017-01-10 18:18:23

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