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

Some inconsistencies with the Dask version may exist.

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

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

Notes

For integer input the return values are floats.

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

This condition is broadcast over the input. At locations where the condition is True, the :None:None:`out` array will be set to the ufunc result. Elsewhere, the :None:None:`out` array will retain its original value. Note that if an uninitialized :None:None:`out` array is created via the default out=None , locations within it where the condition is False will remain uninitialized.

**kwargs :

For other keyword-only arguments, see the ufunc docs <ufuncs.kwargs> .

Returns

y1 : ndarray

Fractional part of x. This is a scalar if x is a scalar.

y2 : ndarray

Integral part of x. This is a scalar if x is a scalar.

This docstring was copied from numpy.modf.

See Also

divmod

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

Examples

This example is valid syntax, but we were not able to check execution

>>> np.modf([0, 3.5])  # doctest: +SKIP
(array([ 0. ,  0.5]), array([ 0.,  3.]))

This example is valid syntax, but we were not able to check execution

>>> np.modf(-0.5)  # doctest: +SKIP
(-0.5, -0)

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

dask.array.ufunc.divmod

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