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# numpy.allclose

`numpy.``allclose`(a, b, rtol=1.0000000000000001e-05, atol=1e-08)

  Returns True if two arrays are element-wise equal within a tolerance.

  The tolerance values are positive, typically very small numbers. The relative difference (rtol * abs(b)) and the absolute difference atol are added together to compare against the absolute difference between a and b.

  Parameters : | a, b : array_like Input arrays to compare. rtol : float The relative tolerance parameter (see Notes). atol : float The absolute tolerance parameter (see Notes).
  Returns : | y : bool Returns True if the two arrays are equal within the given tolerance; False otherwise. If either array contains NaN, then False is returned.

  See also

  `all`, `any`, `alltrue`, `sometrue`

  Notes

  If the following equation is element-wise True, then allclose returns True.

  > absolute(a - b) <= (atol + rtol * absolute(b))

  The above equation is not symmetric in a and b, so that allclose(a, b) might be different from allclose(b, a) in some rare cases.

  Examples

      >>> np.allclose([1e10,1e-7], [1.00001e10,1e-8])
      False
      >>> np.allclose([1e10,1e-8], [1.00001e10,1e-9])
      True
      >>> np.allclose([1e10,1e-8], [1.0001e10,1e-9])
      False
      >>> np.allclose([1.0, np.nan], [1.0, np.nan])
      False

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