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# numpy.real_if_close

`numpy.``real_if_close`(a, tol=100)

  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 : scalar Tolerance 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.

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

  Examples

      >>> np.finfo(np.float).eps      # DOCTEST +skip
      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])

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