numpy.modf
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numpy.modf(x, [out1, out2, ]/, [out=(None, None), ]*, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'modf'>
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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
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Fractional part of
x
. This is a scalar ifx
is a scalar. -
y2 : ndarray
-
Integral part of
x
. This is a scalar ifx
is a scalar.
See also
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divmod
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divmod(x, 1)
is equivalent tomodf
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)
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Licensed under the 3-clause BSD License.
https://docs.scipy.org/doc/numpy-1.16.1/reference/generated/numpy.modf.html