xarray.ufuncs.floor

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xarray.ufuncs.floor#

xarray.ufuncs.floor = <xarray.ufuncs._unary_ufunc object>#

xarray specific variant of numpy.floor(). Handles xarray objects by dispatching to the appropriate function for the underlying array type.

Documentation from numpy:

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 \(\lfloor x \rfloor\).

Parameters

  • x (array_like) – Input data.

  • 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 out array will be set to the ufunc result. Elsewhere, the out array will retain its original value. Note that if an uninitialized 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.

Returns

y (ndarray or scalar) – The floor of each element in x. This is a scalar if x is a scalar.

See also

ceil, trunc, rint, fix

Notes

Some spreadsheet programs calculate the “floor-towards-zero”, where floor(-2.5) == -2. NumPy instead uses the definition of floor where floor(-2.5) == -3. The “floor-towards-zero” function is called fix in NumPy.

Examples

>>> a = np.array([-1.7, -1.5, -0.2, 0.2, 1.5, 1.7, 2.0])
>>> np.floor(a)
array([-2., -2., -1.,  0.,  1.,  1.,  2.])
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