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# numpy.modf

`numpy.``modf`(x, [out1, out2, ]/, [out=(None, None), ]*, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'modf'>

  Return the fractional and integral parts of an array, element-wise.

  The fractional and integral parts are negative if the given number is negative.

  Parameters: | x : array_like Input array. out : ndarray, None, or tuple of ndarray and None, optional A location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs. where : array_like, optional Values of True indicate to calculate the ufunc at that position, values of False indicate to leave the value in the output alone. **kwargs For other keyword-only arguments, see the ufunc docs.
  Returns: | y1 : ndarray Fractional part of x. y2 : ndarray Integral part of x.

  See also

  `divmod`
    `divmod(x, 1)` is equivalent to `modf` with the return values switched, except it always has a positive remainder.

  Notes

  For integer input the return values are floats.

  Examples

      >>> np.modf([0, 3.5])
      (array([ 0. ,  0.5]), array([ 0.,  3.]))
      >>> np.modf(-0.5)
      (-0.5, -0)