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numpy.empty_like

# numpy.empty

`numpy.``empty`(shape, dtype=float, order='C')

  Return a new array of given shape and type, without initializing entries.

  Parameters: | shape : int or tuple of int Shape of the empty array dtype : data-type, optional Desired output data-type. order : {‘C’, ‘F’}, optional Whether to store multi-dimensional data in C (row-major) or Fortran (column-major) order in memory.
  Returns: | out : ndarray Array of uninitialized (arbitrary) data with the given shape, dtype, and order.

  See also

  `empty_like`, `zeros`, `ones`

  Notes

  `empty`, unlike `zeros`, does not set the array values to zero, and may therefore be marginally faster. On the other hand, it requires the user to manually set all the values in the array, and should be used with caution.

  Examples

      >>> np.empty([2, 2])
      array([[ -9.74499359e+001,   6.69583040e-309],
             [  2.13182611e-314,   3.06959433e-309]])         #random

      >>> np.empty([2, 2], dtype=int)
      array([[-1073741821, -1067949133],
             [  496041986,    19249760]])                     #random