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# numpy.all

`numpy.``all`(a, axis=None, out=None)

  Test whether all array elements along a given axis evaluate to True.

  Parameters : | a : array_like Input array or object that can be converted to an array. axis : int, optional Axis along which a logical AND is performed. The default (axis = None) is to perform a logical AND over a flattened input array. axis may be negative, in which case it counts from the last to the first axis. out : ndarray, optional Alternate output array in which to place the result. It must have the same shape as the expected output and its type is preserved (e.g., if `dtype(out)` is float, the result will consist of 0.0’s and 1.0’s). See doc.ufuncs (Section “Output arguments”) for more details.
  Returns : | all : ndarray, bool A new boolean or array is returned unless out is specified, in which case a reference to out is returned.

  See also

  `ndarray.all`
    equivalent method
  `any`
    Test whether any element along a given axis evaluates to True.

  Notes

  Not a Number (NaN), positive infinity and negative infinity evaluate to True because these are not equal to zero.

  Examples

      >>> np.all([[True,False],[True,True]])
      False

      >>> np.all([[True,False],[True,True]], axis=0)
      array([ True, False], dtype=bool)

      >>> np.all([-1, 4, 5])
      True

      >>> np.all([1.0, np.nan])
      True

      >>> o=np.array([False])
      >>> z=np.all([-1, 4, 5], out=o)
      >>> id(z), id(o), z
      (28293632, 28293632, array([ True], dtype=bool))

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