eic-opticks/ana/np_max.py

0001 #!/usr/bin/env python
0002 #
0003 # Copyright (c) 2019 Opticks Team. All Rights Reserved.
0004 #
0005 # This file is part of Opticks
0006 # (see https://bitbucket.org/simoncblyth/opticks).
0007 #
0008 # Licensed under the Apache License, Version 2.0 (the "License");
0009 # you may not use this file except in compliance with the License.
0010 # You may obtain a copy of the License at
0011 #
0012 #   http://www.apache.org/licenses/LICENSE-2.0
0013 #
0014 # Unless required by applicable law or agreed to in writing, software
0015 # distributed under the License is distributed on an "AS IS" BASIS,
0016 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
0017 # See the License for the specific language governing permissions and
0018 # limitations under the License.
0019 #
0020
0021 """
0022
0023
0024
0025 ::
0026
0027
0028     In [19]: M = np.random.random((10, 4, 4))
0029
0030     In [20]: M
0031     Out[20]:
0032     array([[[0.26  , 0.8375, 0.65  , 0.9379],
0033             [0.425 , 0.5007, 0.0893, 0.9828],
0034             [0.7195, 0.5231, 0.0094, 0.8324],
0035             [0.7935, 0.9463, 0.4482, 0.071 ]],
0036
0037            ...
0038
0039            [[0.4159, 0.5709, 0.0778, 0.8898],
0040             [0.7658, 0.8104, 0.5436, 0.6296],
0041             [0.7726, 0.5003, 0.7588, 0.5328],
0042             [0.3231, 0.4282, 0.5839, 0.8149]]])
0043
0044     In [21]: M.max(axis=(1,2))
0045     Out[21]: array([0.9828, 0.9816, 0.9906, 0.9307, 0.7959, 0.9424, 0.9273, 0.9979, 0.9815, 0.8898])
0046
0047     In [22]: M.max(axis=(1,2)).shape
0048     Out[22]: (10,)
0049
0050
0051
0052     In [24]: np.amax?
0053
0054     Signature: np.amax(a, axis=None, out=None, keepdims=<class 'numpy._globals._NoValue'>)
0055     Docstring:
0056     Return the maximum of an array or maximum along an axis.
0057
0058     Parameters
0059     ----------
0060     a : array_like
0061         Input data.
0062     axis : None or int or tuple of ints, optional
0063         Axis or axes along which to operate.  By default, flattened input is
0064         used.
0065
0066         .. versionadded:: 1.7.0
0067
0068         If this is a tuple of ints, the maximum is selected over multiple axes,
0069         instead of a single axis or all the axes as before.
0070
0071
0072
0073
0074 * https://jakevdp.github.io/PythonDataScienceHandbook/02.04-computation-on-arrays-aggregates.html
0075
0076 The way the axis is specified here can be confusing to users coming from other
0077 languages. The axis keyword specifies the dimension of the array that will be
0078 collapsed, rather than the dimension that will be returned. So specifying
0079 axis=0 means that the first axis will be collapsed: for two-dimensional arrays,
0080 this means that values within each column will be aggregated.
0081
0082
0083
0084 """
0085 import numpy as np
0086
0087
0088 M = np.random.random((3, 4))
0089
0090
0091
0092
0093