Source code for maxframe.tensor.arithmetic.modf

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import numpy as np

from maxframe import opcodes
from maxframe.tensor.arithmetic.core import TensorOutBinOp
from maxframe.tensor.datasource import tensor as astensor


class TensorModf(TensorOutBinOp):
    _op_type_ = opcodes.MODF

    def __init__(self, casting="same_kind", dtype=None, sparse=False, **kw):
        super().__init__(casting=casting, dtype=dtype, sparse=sparse, **kw)

    @property
    def _fun(self):
        return np.modf

    @classmethod
    def _is_sparse(cls, x):
        if hasattr(x, "issparse") and x.issparse():
            return True
        return False




def modf(x, out1=None, out2=None, out=None, where=None, **kwargs):
    """
    Return the fractional and integral parts of a tensor, element-wise.

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

    Parameters
    ----------
    x : array_like
        Input tensor.
    out : Tensor, None, or tuple of Tensor 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 tensor 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

    Returns
    -------
    y1 : Tensor
        Fractional part of `x`.
    y2 : Tensor
        Integral part of `x`.

    Notes
    -----
    For integer input the return values are floats.

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

    Examples
    --------
    >>> import maxframe.tensor as mt

    >>> mt.modf([0, 3.5]).execute()
    (array([ 0. ,  0.5]), array([ 0.,  3.]))
    >>> mt.modf(-0.5).execute()
    (-0.5, -0)
    """
    x = astensor(x)
    op = TensorModf(**kwargs)
    return op(x, out1=out1, out2=out2, out=out, where=where)