Cython optimized rainflow algorithm
Project description
README
======
This package provides a cython optimized rainflow algorithm. Data can be
provided as hdf5-table or as numpy array.
Installation
------------
For installing this package just run the setup.py.
Requirements:
* numpy
* tables
* pandas
* cython
* numexpr
Or use the pypi-package and install it via pip.
pip install inqbus.rainflow
Examples and Usage
------------------
There are examples included in
inqbus.rainflow/src/inqbus/rainflow/examples
The main mehtods are located and described in
inqbus.rainflow/src/inqbus/rainflow/run_rainflow
HISTORY
=======
1.5
---
* Corrected datatypes
1.4
---
* api parameter to decide between counting from 1 or from 0 for binning the data
1.1 - BugFixes
--------------
* Corrected classes when calculating binning as table because RFC classes always start counting on 0 .. max_bin, no negative classes anymore
0.9 - BugFixes and Tests
------------------------
* BugFixes on counting pairs
* Tests for core functions
0.8 - BugFixes
--------------
* BugFixes to reduce differences between table and matrix of counted pairs
0.7 - Remove small cycles option
--------------------------------
* During normal rainflow cycles like 1 to 1 can not exist, but with the classification afterwards small cycles will lead to such pairs. They will be removed now
0.6 - Add Axis to matrix
------------------------
* You can store axis to matrix if you want using parameter axis
0.5 - BugFixes
--------------
* Fixed Bug on filtering data with pairs
0.4 - Added Matrix-calculation
-------------------------------
* User can decide between matrix and table format for classification
* Added examples for both
* BugFix in count-method
* Style improvements
* Filter outliers in binning
0.2 - Syntax Improvement
------------------------
* Better documentation
* Improved parameters of functions
0.1 - Initial release
---------------------
* Rainflow for HDF5 and Numpy-Arrays
* Classification before and after algorithm
* Removing peaks from data before calculation
LICENSE
=======
Copyright (c) 2012, Continuum Analytics, Inc.
All rights reserved.
Redistribution and use in source and binary forms, with or without modification,
are permitted provided that the following conditions are met:
Redistributions of source code must retain the above copyright notice,
this list of conditions and the following disclaimer.
Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.
Neither the name of Continuum Analytics nor the names of any contributors
may be used to endorse or promote products derived from this software
without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF
THE POSSIBILITY OF SUCH DAMAGE.
======
This package provides a cython optimized rainflow algorithm. Data can be
provided as hdf5-table or as numpy array.
Installation
------------
For installing this package just run the setup.py.
Requirements:
* numpy
* tables
* pandas
* cython
* numexpr
Or use the pypi-package and install it via pip.
pip install inqbus.rainflow
Examples and Usage
------------------
There are examples included in
inqbus.rainflow/src/inqbus/rainflow/examples
The main mehtods are located and described in
inqbus.rainflow/src/inqbus/rainflow/run_rainflow
HISTORY
=======
1.5
---
* Corrected datatypes
1.4
---
* api parameter to decide between counting from 1 or from 0 for binning the data
1.1 - BugFixes
--------------
* Corrected classes when calculating binning as table because RFC classes always start counting on 0 .. max_bin, no negative classes anymore
0.9 - BugFixes and Tests
------------------------
* BugFixes on counting pairs
* Tests for core functions
0.8 - BugFixes
--------------
* BugFixes to reduce differences between table and matrix of counted pairs
0.7 - Remove small cycles option
--------------------------------
* During normal rainflow cycles like 1 to 1 can not exist, but with the classification afterwards small cycles will lead to such pairs. They will be removed now
0.6 - Add Axis to matrix
------------------------
* You can store axis to matrix if you want using parameter axis
0.5 - BugFixes
--------------
* Fixed Bug on filtering data with pairs
0.4 - Added Matrix-calculation
-------------------------------
* User can decide between matrix and table format for classification
* Added examples for both
* BugFix in count-method
* Style improvements
* Filter outliers in binning
0.2 - Syntax Improvement
------------------------
* Better documentation
* Improved parameters of functions
0.1 - Initial release
---------------------
* Rainflow for HDF5 and Numpy-Arrays
* Classification before and after algorithm
* Removing peaks from data before calculation
LICENSE
=======
Copyright (c) 2012, Continuum Analytics, Inc.
All rights reserved.
Redistribution and use in source and binary forms, with or without modification,
are permitted provided that the following conditions are met:
Redistributions of source code must retain the above copyright notice,
this list of conditions and the following disclaimer.
Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.
Neither the name of Continuum Analytics nor the names of any contributors
may be used to endorse or promote products derived from this software
without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF
THE POSSIBILITY OF SUCH DAMAGE.
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