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# numpy.isinf

`numpy.``isinf`(x[, out]) = <ufunc 'isinf'>

  Test element-wise for positive or negative infinity.

  Return a bool-type array, the same shape as x, True where `x == +/-inf`, False everywhere else.

  Parameters : | x : array_like Input values out : array_like, optional An array with the same shape as x to store the result.
  Returns : | y : bool (scalar) or bool-type ndarray For scalar input, the result is a new boolean with value True if the input is positive or negative infinity; otherwise the value is False. For array input, the result is a boolean array with the same shape as the input and the values are True where the corresponding element of the input is positive or negative infinity; elsewhere the values are False. If a second argument was supplied the result is stored there. If the type of that array is a numeric type the result is represented as zeros and ones, if the type is boolean then as False and True, respectively. The return value y is then a reference to that array.

  See also

  `isneginf`, `isposinf`, `isnan`, `isfinite`

  Notes

  Numpy uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754).

  Errors result if the second argument is supplied when the first argument is a scalar, or if the first and second arguments have different shapes.

  Examples

      >>> np.isinf(np.inf)
      True
      >>> np.isinf(np.nan)
      False
      >>> np.isinf(np.NINF)
      True
      >>> np.isinf([np.inf, -np.inf, 1.0, np.nan])
      array([ True,  True, False, False], dtype=bool)

      >>> x = np.array([-np.inf, 0., np.inf])
      >>> y = np.array([2, 2, 2])
      >>> np.isinf(x, y)
      array([1, 0, 1])
      >>> y
      array([1, 0, 1])

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