mars.tensor.floor

mars.tensor.floor(x, out=None, where=None, **kwargs)[source]

Return the floor of the input, element-wise.

The floor of the scalar x is the largest integer i, such that i <= x. It is often denoted as \(\lfloor x \rfloor\).

x : array_like
Input data.
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

y : Tensor or scalar
The floor of each element in x.

ceil, trunc, rint

Some spreadsheet programs calculate the “floor-towards-zero”, in other words floor(-2.5) == -2. NumPy instead uses the definition of floor where floor(-2.5) == -3.

>>> import mars.tensor as mt
>>> a = mt.array([-1.7, -1.5, -0.2, 0.2, 1.5, 1.7, 2.0])
>>> mt.floor(a).execute()
array([-2., -2., -1.,  0.,  1.,  1.,  2.])