# Copyright (C) 2020 NumS Development Team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# pylint: disable = redefined-builtin, too-many-lines, anomalous-backslash-in-string, unused-wildcard-import, wildcard-import
from nums.core.application_manager import instance as _instance
from nums.core.array.blockarray import BlockArray
from nums.numpy.api.logic import *
############################################
# Arithmetic Ops
############################################
[docs]def sum(
a: BlockArray,
axis=None,
dtype=None,
out=None,
keepdims=False,
initial=None,
where=None,
) -> BlockArray:
"""Sum of array elements over a given axis.
This docstring was copied from numpy.sum.
Some inconsistencies with the NumS version may exist.
Parameters
----------
a : BlockArray
Elements to sum.
axis : None or int or tuple of ints, optional
Axis or axes along which a sum is performed. The default,
axis=None, will sum all of the elements of the input array. If
axis is negative it counts from the last to the first axis.
If axis is a tuple of ints, a sum is performed on all of the axes
specified in the tuple instead of a single axis or all the axes as
before.
dtype : dtype, optional
The type of the returned array and of the accumulator in which the
elements are summed. The dtype of `a` is used by default unless `a`
has an integer dtype of less precision than the default platform
integer. In that case, if `a` is signed then the platform integer
is used while if `a` is unsigned then an unsigned integer of the
same precision as the platform integer is used.
out : BlockArray, optional
Alternative output array in which to place the result. It must have
the same shape as the expected output, but the type of the output
values will be cast if necessary.
keepdims : bool, optional
If this is set to True, the axes which are reduced are left
in the result as dimensions with size one. With this option,
the result will broadcast correctly against the input array.
If the default value is passed, then `keepdims` will not be
passed through to the `sum` method of sub-classes of
`BlockArray`, however any non-default value will be. If the
sub-class' method does not implement `keepdims` any
exceptions will be raised.
initial : scalar, optional
Starting value for the sum.
where : BlockArray of bool, optional
Elements to include in the sum.
Returns
-------
sum_along_axis : BlockArray
An array with the same shape as `a`, with the specified
axis removed. If `a` is a 0-d array, or if `axis` is None, a scalar
is returned. If an output array is specified, a reference to
`out` is returned.
See Also
--------
mean, average
Notes
-----
'initial' is currently not supported.
'where' is currently not supported.
'out' is currently not supported.
Examples
--------
The doctests shown below are copied from NumPy.
They won’t show the correct result until you operate ``get()``.
>>> nps.sum(nps.array([0.5, 1.5])).get() # doctest: +SKIP
array(2.)
>>> nps.sum(nps.array([[0, 1], [0, 5]])).get() # doctest: +SKIP
array(6)
>>> nps.sum(nps.array([[0, 1], [0, 5]]), axis=0).get() # doctest: +SKIP
array([0, 6])
>>> nps.sum(nps.array([[0, 1], [0, 5]]), axis=1).get() # doctest: +SKIP
array([1, 5])
"""
if initial is not None:
raise NotImplementedError("'initial' is currently not supported.")
if where is not None:
raise NotImplementedError("'where' is currently not supported.")
if out is not None:
raise NotImplementedError("'out' is currently not supported.")
return _instance().sum(a, axis=axis, keepdims=keepdims, dtype=dtype)