# Source code for mars.tensor.statistics.ptp

```
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright 1999-2021 Alibaba Group Holding Ltd.
#
# 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.
from ..utils import validate_axis, check_out_param
from ..datasource import tensor as astensor
from ..base.ravel import ravel
from ..core import Tensor
[docs]def ptp(a, axis=None, out=None, keepdims=None):
"""
Range of values (maximum - minimum) along an axis.
The name of the function comes from the acronym for 'peak to peak'.
Parameters
----------
a : array_like
Input values.
axis : int, optional
Axis along which to find the peaks. By default, flatten the
array.
out : array_like
Alternative output tensor in which to place the result. It must
have the same shape and buffer length 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 `ptp` method of sub-classes of
`Tensor`, however any non-default value will be. If the
sub-class' method does not implement `keepdims` any
exceptions will be raised.
Returns
-------
ptp : Tensor
A new tensor holding the result, unless `out` was
specified, in which case a reference to `out` is returned.
Examples
--------
>>> import mars.tensor as mt
>>> x = mt.arange(4).reshape((2,2))
>>> x.execute()
array([[0, 1],
[2, 3]])
>>> mt.ptp(x, axis=0).execute()
array([2, 2])
>>> mt.ptp(x, axis=1).execute()
array([1, 1])
"""
a = astensor(a)
if axis is None:
a = ravel(a)
else:
validate_axis(a.ndim, axis)
t = a.max(axis=axis, keepdims=keepdims) - a.min(axis=axis, keepdims=keepdims)
if out is not None:
if not isinstance(out, Tensor):
raise TypeError(f"out should be Tensor object, got {type(out)} instead")
check_out_param(out, t, "same_kind")
out.data = t.data
return out
return t
```