automatic import of python-pydynamicopeneuler20.03

3 files changed, 769 insertions, 0 deletions

diff --git a/.gitignore b/.gitignore
index e69de29..fabc8ec 100644
--- a/.gitignore
+++ b/.gitignore
@@ -0,0 +1 @@
+/PyDynamic-2.4.0.tar.gz
diff --git a/python-pydynamic.spec b/python-pydynamic.spec
new file mode 100644
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--- /dev/null
+++ b/python-pydynamic.spec
@@ -0,0 +1,767 @@
+%global _empty_manifest_terminate_build 0
+Name:		python-PyDynamic
+Version:	2.4.0
+Release:	1
+Summary:	A software package for the analysis of dynamic measurements
+License:	GNU Lesser General Public License v3 or later (LGPLv3+)
+URL:		https://ptb-m4d.github.io/PyDynamic/
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/cf/71/7e6aa3ccafff569b1631bf86ff902b26473e99d96247c5cb9281905ed264/PyDynamic-2.4.0.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-matplotlib
+Requires:	python3-numpy
+Requires:	python3-pandas
+Requires:	python3-scipy
+Requires:	python3-sympy
+Requires:	python3-PyWavelets
+Requires:	python3-time-series-buffer
+Requires:	python3-notebook
+
+%description
+<img src="https://raw.githubusercontent.com/PTB-M4D/PyDynamic/main/docs/PyDynamic_logo.svg" alt="the logo of PyDynamic" title="PyDynamic logo">
+<p align="center">
+  <!-- CircleCI Tests -->
+  <a href="https://circleci.com/gh/PTB-M4D/PyDynamic"><img alt="CircleCI pipeline status badge" src="https://circleci.com/gh/PTB-M4D/PyDynamic.svg?style=shield"></a>
+  <!-- ReadTheDocs Documentation -->
+  <a href="https://pydynamic.readthedocs.io/en/latest/index.html">
+    <img src="https://readthedocs.org/projects/pydynamic/badge/?version=latest" alt="PyDynamic's ReadTheDocs status">
+  </a>
+  <!-- CodeCov(erage) -->
+  <a href="https://codecov.io/gh/PTB-M4D/PyDynamic">
+    <img src="https://codecov.io/gh/PTB-M4D/PyDynamic/branch/main/graph/badge.svg" alt=" PyDynamic's CodeCov badge">
+  </a>
+  <!-- Codacy -->
+  <a href="https://www.codacy.com/gh/PTB-M4D/PyDynamic/dashboard?utm_source=github.com&amp;utm_medium=referral&amp;utm_content=PTB-M4D/PyDynamic&amp;utm_campaign=Badge_Grade">
+    <img src="https://app.codacy.com/project/badge/Grade/db86b58d6fa5446e8408644c8196f5e2" alt=" PyDynamic's Codacy badge">
+  </a>
+  <!-- PyPI Version -->
+  <a href="https://pypi.org/project/pydynamic">
+    <img src="https://img.shields.io/pypi/v/pydynamic.svg?label=release&color=blue&style=flat-square" alt=" PyDynamic's PyPI version number">
+  </a>
+  <!-- PyPI License -->
+  <a href="https://www.gnu.org/licenses/lgpl-3.0.en.html">
+    <img alt="PyPI - license badge" src="https://img.shields.io/pypi/l/pydynamic?color=bright">
+  </a>
+  <!-- Zenodo DOI -->
+  <a href="https://doi.org/10.5281/zenodo.1489877">
+    <img src="https://zenodo.org/badge/DOI/10.5281/zenodo.1489877.svg" alt="DOI"></a>
+</p>
+
+# Python library for the analysis of dynamic measurements
+
+<p align="justify">
+The goal of this library is to provide a starting point for users in metrology and
+related areas who deal with time-dependent i.e., <i>dynamic</i>, measurements. The
+initial version of this software was developed as part of a joint research project of
+the national metrology institutes from Germany and the UK, i.e.
+<a href="https://www.ptb.de/cms/en.html">Physikalisch-Technische Bundesanstalt</a> 
+and the <a href="https://www.npl.co.uk">National Physical Laboratory</a>.
+</p>
+
+<p align="justify">
+Further development and explicit use of PyDynamic was part of the European research
+project <a href="https://www.ptb.de/empir2018/met4fof/home/">EMPIR 17IND12 
+Met4FoF</a> and the German research project <a href="https://famous-project.
+eu">FAMOUS</a>. Since the end of these two projects, development of PyDynamic continues mostly based on feature requests and smaller collaborations.
+</p>
+
+## Table of content
+
+- [Quickstart](#quickstart)
+- [Features](#features)
+- [Module diagram](#module-diagram)
+- [Documentation](#documentation)
+- [Installation](#installation)
+- [Contributing](#contributing)
+- [Examples](#examples)
+- [Roadmap](#roadmap)
+- [Citation](#citation)
+- [Acknowledgement](#acknowledgement)
+- [Disclaimer](#disclaimer)
+- [License](#license)
+
+## Quickstart
+
+To dive right into it, install PyDynamic and execute one of the examples:
+
+```shell
+(my_PyDynamice_venv) $ pip install PyDynamic
+Collecting PyDynamic
+[...]
+Successfully installed PyDynamic-[...]
+(my_PyDynamice_venv) $ python
+Python 3.9.7 (default, Aug 31 2021, 13:28:12) 
+[GCC 11.1.0] on linux
+Type "help", "copyright", "credits" or "license" for more information.
+```
+```python
+>>> from PyDynamic.examples.uncertainty_for_dft.deconv_DFT import DftDeconvolutionExample
+>>> DftDeconvolutionExample()
+Propagating uncertainty associated with measurement through DFT
+Propagating uncertainty associated with calibration data to real and imag part
+Propagating uncertainty through the inverse system
+Propagating uncertainty through the low-pass filter
+Propagating uncertainty associated with the estimate back to time domain
+```
+
+You will see a couple of plots opening up to observe the results. For 
+further information just read on and visit our 
+[tutorial section](#examples). 
+
+## Features
+
+PyDynamic offers propagation of *uncertainties* for
+
+- application of the discrete Fourier transform and its inverse
+- filtering with an FIR or IIR filter with uncertain coefficients
+- design of a FIR filter as the inverse of a frequency response with
+  uncertain coefficients
+- design on an IIR filter as the inverse of a frequency response with
+  uncertain coefficients
+- deconvolution in the frequency domain by division
+- multiplication in the frequency domain
+- transformation from amplitude and phase to a representation by real and
+  imaginary parts
+- 1-dimensional interpolation
+
+For the validation of the propagation of uncertainties, the Monte-Carlo
+method can be applied using a memory-efficient implementation of Monte-Carlo
+for digital filtering.
+
+## Module diagram
+
+The fundamental structure of PyDynamic is shown in the following figure.
+
+![PyDynamic module diagram](https://raw.githubusercontent.com/PTB-M4D/PyDynamic/main/docs/PyDynamic_module_diagram.png)
+
+However, imports should generally be possible without explicitly naming all packages
+and modules in the path, so that for example the following import statements are all
+equivalent.
+
+```python
+from PyDynamic.uncertainty.propagate_filter import FIRuncFilter
+from PyDynamic.uncertainty import FIRuncFilter
+from PyDynamic import FIRuncFilter
+```
+
+## Documentation
+
+The documentation for PyDynamic can be found on
+[ReadTheDocs](http://pydynamic.readthedocs.io)
+
+## Installation
+
+The installation of PyDynamic is as straightforward as the Python ecosystem suggests.
+Detailed instructions on different options to install PyDynamic you can find in the 
+[installation section of the docs](https://pydynamic.readthedocs.io/en/latest/INSTALL.html).
+
+## Contributing
+
+Whenever you are involved with PyDynamic, please respect our [Code of Conduct
+](https://github.com/PTB-M4D/PyDynamic/blob/main/CODE_OF_CONDUCT.md).
+If you want to contribute back to the project, after reading our Code of Conduct,
+take a look at our open developments in the [project board
+](https://github.com/PTB-M4D/PyDynamic/projects/1), [pull requests
+](https://github.com/PTB-M4D/PyDynamic/pulls) and search [the issues
+](https://github.com/PTB-M4D/PyDynamic/issues). If you find something similar to
+your ideas or troubles, let us know by leaving a comment or remark. If you have
+something new to tell us, feel free to open a feature request or bug report in the
+issues. If you want to contribute code or improve our documentation, please check our
+[contribution advices and tips](https://pydynamic.readthedocs.io/en/latest/CONTRIBUTING.html).
+
+If you have downloaded this software, we would be very thankful for letting
+us know. You may, for instance, drop an email to one of the [authors
+](https://github.com/PTB-M4D/PyDynamic/graphs/contributors) (e.g.
+[Sascha Eichstädt](mailto:sascha.eichstaedt@ptb.de), [Björn Ludwig
+](mailto:bjoern.ludwig@ptb.de) or [Maximilian Gruber
+](mailto:maximilian.gruber@ptb.de))
+
+## Examples
+
+We have collected extended material for an easier introduction to PyDynamic in the
+package _examples_. Detailed assistance on getting started you can find in the
+corresponding sections of the docs:
+
+* [examples](https://pydynamic.readthedocs.io/en/latest/Examples.html)
+* [tutorials](https://pydynamic.readthedocs.io/en/latest/Tutorials.html)
+
+In various Jupyter Notebooks and scripts we demonstrate the use of
+the provided methods to aid the first steps in PyDynamic. New features are introduced
+with an example from the beginning if feasible. We are currently moving this supporting
+collection to an external repository on GitHub. They will be available at
+[github.com/PTB-M4D/PyDynamic_tutorials](https://github.com/PTB-M4D/PyDynamic_tutorials) 
+in the near future.
+
+## Roadmap
+
+1. Implementation of robust measurement (sensor) models
+1. Extension to more complex noise and uncertainty models
+1. Introducing uncertainty propagation for Kalman filters
+
+For a comprehensive overview of current development activities and upcoming tasks,
+take a look at the [project board](https://github.com/PTB-M4D/PyDynamic/projects/1),
+[issues](https://github.com/PTB-M4D/PyDynamic/issues) and
+[pull requests](https://github.com/PTB-M4D/PyDynamic/pulls).
+
+## Citation
+
+If you publish results obtained with the help of PyDynamic, please use the above linked
+[Zenodo DOI](https://doi.org/10.5281/zenodo.1489877) for the code itself or cite
+
+Sascha Eichstädt, Clemens Elster, Ian M. Smith, and Trevor J. Esward
+*Evaluation of dynamic measurement uncertainty – an open-source software
+package to bridge theory and practice*
+**J. Sens. Sens. Syst.**, 6, 97-105, 2017, DOI: [10.5194/jsss-6-97-2017
+](https://doi.org/10.5194/jsss-6-97-2017)
+
+## Acknowledgement
+
+Part of this work is developed as part of the Joint Research Project [17IND12 Met4FoF
+](http://met4fof.eu) of the European Metrology Programme for Innovation and
+Research (EMPIR).
+
+This work was part of the Joint Support for Impact project
+[14SIP08](https://www.euramet.org/research-innovation/search-research-projects/details/project/standards-and-software-to-maximise-end-user-uptake-of-nmi-calibrations-of-dynamic-force-torque-and/)
+of the European Metrology Programme for Innovation and Research (EMPIR). The
+[EMPIR](http://msu.euramet.org) is jointly funded by the EMPIR participating 
+countries within EURAMET and the European Union.
+
+## Disclaimer
+
+This software is developed at Physikalisch-Technische Bundesanstalt (PTB). The
+software is made available "as is" free of cost. PTB assumes no responsibility
+whatsoever for its use by other parties, and makes no guarantees, expressed or
+implied, about its quality, reliability, safety, suitability or any other
+characteristic. In no event will PTB be liable for any direct, indirect or
+consequential damage arising in connection with the use of this software.
+
+## License
+
+PyDynamic is distributed under the [LGPLv3 license
+](https://github.com/PTB-M4D/PyDynamic/blob/main/licence.txt)
+except for the module [`impinvar.py`
+](https://github.com/PTB-M4D/PyDynamic/blob/main/src/PyDynamic/misc/impinvar.py) 
+in the package [`misc`
+](https://pydynamic.readthedocs.io/en/main/PyDynamic.misc.html), 
+which is distributed under the [GPLv3 license
+](https://github.com/PTB-M4D/PyDynamic/blob/main/src/PyDynamic/misc/impinvar_license.txt).
+
+
+
+
+%package -n python3-PyDynamic
+Summary:	A software package for the analysis of dynamic measurements
+Provides:	python-PyDynamic
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-PyDynamic
+<img src="https://raw.githubusercontent.com/PTB-M4D/PyDynamic/main/docs/PyDynamic_logo.svg" alt="the logo of PyDynamic" title="PyDynamic logo">
+<p align="center">
+  <!-- CircleCI Tests -->
+  <a href="https://circleci.com/gh/PTB-M4D/PyDynamic"><img alt="CircleCI pipeline status badge" src="https://circleci.com/gh/PTB-M4D/PyDynamic.svg?style=shield"></a>
+  <!-- ReadTheDocs Documentation -->
+  <a href="https://pydynamic.readthedocs.io/en/latest/index.html">
+    <img src="https://readthedocs.org/projects/pydynamic/badge/?version=latest" alt="PyDynamic's ReadTheDocs status">
+  </a>
+  <!-- CodeCov(erage) -->
+  <a href="https://codecov.io/gh/PTB-M4D/PyDynamic">
+    <img src="https://codecov.io/gh/PTB-M4D/PyDynamic/branch/main/graph/badge.svg" alt=" PyDynamic's CodeCov badge">
+  </a>
+  <!-- Codacy -->
+  <a href="https://www.codacy.com/gh/PTB-M4D/PyDynamic/dashboard?utm_source=github.com&amp;utm_medium=referral&amp;utm_content=PTB-M4D/PyDynamic&amp;utm_campaign=Badge_Grade">
+    <img src="https://app.codacy.com/project/badge/Grade/db86b58d6fa5446e8408644c8196f5e2" alt=" PyDynamic's Codacy badge">
+  </a>
+  <!-- PyPI Version -->
+  <a href="https://pypi.org/project/pydynamic">
+    <img src="https://img.shields.io/pypi/v/pydynamic.svg?label=release&color=blue&style=flat-square" alt=" PyDynamic's PyPI version number">
+  </a>
+  <!-- PyPI License -->
+  <a href="https://www.gnu.org/licenses/lgpl-3.0.en.html">
+    <img alt="PyPI - license badge" src="https://img.shields.io/pypi/l/pydynamic?color=bright">
+  </a>
+  <!-- Zenodo DOI -->
+  <a href="https://doi.org/10.5281/zenodo.1489877">
+    <img src="https://zenodo.org/badge/DOI/10.5281/zenodo.1489877.svg" alt="DOI"></a>
+</p>
+
+# Python library for the analysis of dynamic measurements
+
+<p align="justify">
+The goal of this library is to provide a starting point for users in metrology and
+related areas who deal with time-dependent i.e., <i>dynamic</i>, measurements. The
+initial version of this software was developed as part of a joint research project of
+the national metrology institutes from Germany and the UK, i.e.
+<a href="https://www.ptb.de/cms/en.html">Physikalisch-Technische Bundesanstalt</a> 
+and the <a href="https://www.npl.co.uk">National Physical Laboratory</a>.
+</p>
+
+<p align="justify">
+Further development and explicit use of PyDynamic was part of the European research
+project <a href="https://www.ptb.de/empir2018/met4fof/home/">EMPIR 17IND12 
+Met4FoF</a> and the German research project <a href="https://famous-project.
+eu">FAMOUS</a>. Since the end of these two projects, development of PyDynamic continues mostly based on feature requests and smaller collaborations.
+</p>
+
+## Table of content
+
+- [Quickstart](#quickstart)
+- [Features](#features)
+- [Module diagram](#module-diagram)
+- [Documentation](#documentation)
+- [Installation](#installation)
+- [Contributing](#contributing)
+- [Examples](#examples)
+- [Roadmap](#roadmap)
+- [Citation](#citation)
+- [Acknowledgement](#acknowledgement)
+- [Disclaimer](#disclaimer)
+- [License](#license)
+
+## Quickstart
+
+To dive right into it, install PyDynamic and execute one of the examples:
+
+```shell
+(my_PyDynamice_venv) $ pip install PyDynamic
+Collecting PyDynamic
+[...]
+Successfully installed PyDynamic-[...]
+(my_PyDynamice_venv) $ python
+Python 3.9.7 (default, Aug 31 2021, 13:28:12) 
+[GCC 11.1.0] on linux
+Type "help", "copyright", "credits" or "license" for more information.
+```
+```python
+>>> from PyDynamic.examples.uncertainty_for_dft.deconv_DFT import DftDeconvolutionExample
+>>> DftDeconvolutionExample()
+Propagating uncertainty associated with measurement through DFT
+Propagating uncertainty associated with calibration data to real and imag part
+Propagating uncertainty through the inverse system
+Propagating uncertainty through the low-pass filter
+Propagating uncertainty associated with the estimate back to time domain
+```
+
+You will see a couple of plots opening up to observe the results. For 
+further information just read on and visit our 
+[tutorial section](#examples). 
+
+## Features
+
+PyDynamic offers propagation of *uncertainties* for
+
+- application of the discrete Fourier transform and its inverse
+- filtering with an FIR or IIR filter with uncertain coefficients
+- design of a FIR filter as the inverse of a frequency response with
+  uncertain coefficients
+- design on an IIR filter as the inverse of a frequency response with
+  uncertain coefficients
+- deconvolution in the frequency domain by division
+- multiplication in the frequency domain
+- transformation from amplitude and phase to a representation by real and
+  imaginary parts
+- 1-dimensional interpolation
+
+For the validation of the propagation of uncertainties, the Monte-Carlo
+method can be applied using a memory-efficient implementation of Monte-Carlo
+for digital filtering.
+
+## Module diagram
+
+The fundamental structure of PyDynamic is shown in the following figure.
+
+![PyDynamic module diagram](https://raw.githubusercontent.com/PTB-M4D/PyDynamic/main/docs/PyDynamic_module_diagram.png)
+
+However, imports should generally be possible without explicitly naming all packages
+and modules in the path, so that for example the following import statements are all
+equivalent.
+
+```python
+from PyDynamic.uncertainty.propagate_filter import FIRuncFilter
+from PyDynamic.uncertainty import FIRuncFilter
+from PyDynamic import FIRuncFilter
+```
+
+## Documentation
+
+The documentation for PyDynamic can be found on
+[ReadTheDocs](http://pydynamic.readthedocs.io)
+
+## Installation
+
+The installation of PyDynamic is as straightforward as the Python ecosystem suggests.
+Detailed instructions on different options to install PyDynamic you can find in the 
+[installation section of the docs](https://pydynamic.readthedocs.io/en/latest/INSTALL.html).
+
+## Contributing
+
+Whenever you are involved with PyDynamic, please respect our [Code of Conduct
+](https://github.com/PTB-M4D/PyDynamic/blob/main/CODE_OF_CONDUCT.md).
+If you want to contribute back to the project, after reading our Code of Conduct,
+take a look at our open developments in the [project board
+](https://github.com/PTB-M4D/PyDynamic/projects/1), [pull requests
+](https://github.com/PTB-M4D/PyDynamic/pulls) and search [the issues
+](https://github.com/PTB-M4D/PyDynamic/issues). If you find something similar to
+your ideas or troubles, let us know by leaving a comment or remark. If you have
+something new to tell us, feel free to open a feature request or bug report in the
+issues. If you want to contribute code or improve our documentation, please check our
+[contribution advices and tips](https://pydynamic.readthedocs.io/en/latest/CONTRIBUTING.html).
+
+If you have downloaded this software, we would be very thankful for letting
+us know. You may, for instance, drop an email to one of the [authors
+](https://github.com/PTB-M4D/PyDynamic/graphs/contributors) (e.g.
+[Sascha Eichstädt](mailto:sascha.eichstaedt@ptb.de), [Björn Ludwig
+](mailto:bjoern.ludwig@ptb.de) or [Maximilian Gruber
+](mailto:maximilian.gruber@ptb.de))
+
+## Examples
+
+We have collected extended material for an easier introduction to PyDynamic in the
+package _examples_. Detailed assistance on getting started you can find in the
+corresponding sections of the docs:
+
+* [examples](https://pydynamic.readthedocs.io/en/latest/Examples.html)
+* [tutorials](https://pydynamic.readthedocs.io/en/latest/Tutorials.html)
+
+In various Jupyter Notebooks and scripts we demonstrate the use of
+the provided methods to aid the first steps in PyDynamic. New features are introduced
+with an example from the beginning if feasible. We are currently moving this supporting
+collection to an external repository on GitHub. They will be available at
+[github.com/PTB-M4D/PyDynamic_tutorials](https://github.com/PTB-M4D/PyDynamic_tutorials) 
+in the near future.
+
+## Roadmap
+
+1. Implementation of robust measurement (sensor) models
+1. Extension to more complex noise and uncertainty models
+1. Introducing uncertainty propagation for Kalman filters
+
+For a comprehensive overview of current development activities and upcoming tasks,
+take a look at the [project board](https://github.com/PTB-M4D/PyDynamic/projects/1),
+[issues](https://github.com/PTB-M4D/PyDynamic/issues) and
+[pull requests](https://github.com/PTB-M4D/PyDynamic/pulls).
+
+## Citation
+
+If you publish results obtained with the help of PyDynamic, please use the above linked
+[Zenodo DOI](https://doi.org/10.5281/zenodo.1489877) for the code itself or cite
+
+Sascha Eichstädt, Clemens Elster, Ian M. Smith, and Trevor J. Esward
+*Evaluation of dynamic measurement uncertainty – an open-source software
+package to bridge theory and practice*
+**J. Sens. Sens. Syst.**, 6, 97-105, 2017, DOI: [10.5194/jsss-6-97-2017
+](https://doi.org/10.5194/jsss-6-97-2017)
+
+## Acknowledgement
+
+Part of this work is developed as part of the Joint Research Project [17IND12 Met4FoF
+](http://met4fof.eu) of the European Metrology Programme for Innovation and
+Research (EMPIR).
+
+This work was part of the Joint Support for Impact project
+[14SIP08](https://www.euramet.org/research-innovation/search-research-projects/details/project/standards-and-software-to-maximise-end-user-uptake-of-nmi-calibrations-of-dynamic-force-torque-and/)
+of the European Metrology Programme for Innovation and Research (EMPIR). The
+[EMPIR](http://msu.euramet.org) is jointly funded by the EMPIR participating 
+countries within EURAMET and the European Union.
+
+## Disclaimer
+
+This software is developed at Physikalisch-Technische Bundesanstalt (PTB). The
+software is made available "as is" free of cost. PTB assumes no responsibility
+whatsoever for its use by other parties, and makes no guarantees, expressed or
+implied, about its quality, reliability, safety, suitability or any other
+characteristic. In no event will PTB be liable for any direct, indirect or
+consequential damage arising in connection with the use of this software.
+
+## License
+
+PyDynamic is distributed under the [LGPLv3 license
+](https://github.com/PTB-M4D/PyDynamic/blob/main/licence.txt)
+except for the module [`impinvar.py`
+](https://github.com/PTB-M4D/PyDynamic/blob/main/src/PyDynamic/misc/impinvar.py) 
+in the package [`misc`
+](https://pydynamic.readthedocs.io/en/main/PyDynamic.misc.html), 
+which is distributed under the [GPLv3 license
+](https://github.com/PTB-M4D/PyDynamic/blob/main/src/PyDynamic/misc/impinvar_license.txt).
+
+
+
+
+%package help
+Summary:	Development documents and examples for PyDynamic
+Provides:	python3-PyDynamic-doc
+%description help
+<img src="https://raw.githubusercontent.com/PTB-M4D/PyDynamic/main/docs/PyDynamic_logo.svg" alt="the logo of PyDynamic" title="PyDynamic logo">
+<p align="center">
+  <!-- CircleCI Tests -->
+  <a href="https://circleci.com/gh/PTB-M4D/PyDynamic"><img alt="CircleCI pipeline status badge" src="https://circleci.com/gh/PTB-M4D/PyDynamic.svg?style=shield"></a>
+  <!-- ReadTheDocs Documentation -->
+  <a href="https://pydynamic.readthedocs.io/en/latest/index.html">
+    <img src="https://readthedocs.org/projects/pydynamic/badge/?version=latest" alt="PyDynamic's ReadTheDocs status">
+  </a>
+  <!-- CodeCov(erage) -->
+  <a href="https://codecov.io/gh/PTB-M4D/PyDynamic">
+    <img src="https://codecov.io/gh/PTB-M4D/PyDynamic/branch/main/graph/badge.svg" alt=" PyDynamic's CodeCov badge">
+  </a>
+  <!-- Codacy -->
+  <a href="https://www.codacy.com/gh/PTB-M4D/PyDynamic/dashboard?utm_source=github.com&amp;utm_medium=referral&amp;utm_content=PTB-M4D/PyDynamic&amp;utm_campaign=Badge_Grade">
+    <img src="https://app.codacy.com/project/badge/Grade/db86b58d6fa5446e8408644c8196f5e2" alt=" PyDynamic's Codacy badge">
+  </a>
+  <!-- PyPI Version -->
+  <a href="https://pypi.org/project/pydynamic">
+    <img src="https://img.shields.io/pypi/v/pydynamic.svg?label=release&color=blue&style=flat-square" alt=" PyDynamic's PyPI version number">
+  </a>
+  <!-- PyPI License -->
+  <a href="https://www.gnu.org/licenses/lgpl-3.0.en.html">
+    <img alt="PyPI - license badge" src="https://img.shields.io/pypi/l/pydynamic?color=bright">
+  </a>
+  <!-- Zenodo DOI -->
+  <a href="https://doi.org/10.5281/zenodo.1489877">
+    <img src="https://zenodo.org/badge/DOI/10.5281/zenodo.1489877.svg" alt="DOI"></a>
+</p>
+
+# Python library for the analysis of dynamic measurements
+
+<p align="justify">
+The goal of this library is to provide a starting point for users in metrology and
+related areas who deal with time-dependent i.e., <i>dynamic</i>, measurements. The
+initial version of this software was developed as part of a joint research project of
+the national metrology institutes from Germany and the UK, i.e.
+<a href="https://www.ptb.de/cms/en.html">Physikalisch-Technische Bundesanstalt</a> 
+and the <a href="https://www.npl.co.uk">National Physical Laboratory</a>.
+</p>
+
+<p align="justify">
+Further development and explicit use of PyDynamic was part of the European research
+project <a href="https://www.ptb.de/empir2018/met4fof/home/">EMPIR 17IND12 
+Met4FoF</a> and the German research project <a href="https://famous-project.
+eu">FAMOUS</a>. Since the end of these two projects, development of PyDynamic continues mostly based on feature requests and smaller collaborations.
+</p>
+
+## Table of content
+
+- [Quickstart](#quickstart)
+- [Features](#features)
+- [Module diagram](#module-diagram)
+- [Documentation](#documentation)
+- [Installation](#installation)
+- [Contributing](#contributing)
+- [Examples](#examples)
+- [Roadmap](#roadmap)
+- [Citation](#citation)
+- [Acknowledgement](#acknowledgement)
+- [Disclaimer](#disclaimer)
+- [License](#license)
+
+## Quickstart
+
+To dive right into it, install PyDynamic and execute one of the examples:
+
+```shell
+(my_PyDynamice_venv) $ pip install PyDynamic
+Collecting PyDynamic
+[...]
+Successfully installed PyDynamic-[...]
+(my_PyDynamice_venv) $ python
+Python 3.9.7 (default, Aug 31 2021, 13:28:12) 
+[GCC 11.1.0] on linux
+Type "help", "copyright", "credits" or "license" for more information.
+```
+```python
+>>> from PyDynamic.examples.uncertainty_for_dft.deconv_DFT import DftDeconvolutionExample
+>>> DftDeconvolutionExample()
+Propagating uncertainty associated with measurement through DFT
+Propagating uncertainty associated with calibration data to real and imag part
+Propagating uncertainty through the inverse system
+Propagating uncertainty through the low-pass filter
+Propagating uncertainty associated with the estimate back to time domain
+```
+
+You will see a couple of plots opening up to observe the results. For 
+further information just read on and visit our 
+[tutorial section](#examples). 
+
+## Features
+
+PyDynamic offers propagation of *uncertainties* for
+
+- application of the discrete Fourier transform and its inverse
+- filtering with an FIR or IIR filter with uncertain coefficients
+- design of a FIR filter as the inverse of a frequency response with
+  uncertain coefficients
+- design on an IIR filter as the inverse of a frequency response with
+  uncertain coefficients
+- deconvolution in the frequency domain by division
+- multiplication in the frequency domain
+- transformation from amplitude and phase to a representation by real and
+  imaginary parts
+- 1-dimensional interpolation
+
+For the validation of the propagation of uncertainties, the Monte-Carlo
+method can be applied using a memory-efficient implementation of Monte-Carlo
+for digital filtering.
+
+## Module diagram
+
+The fundamental structure of PyDynamic is shown in the following figure.
+
+![PyDynamic module diagram](https://raw.githubusercontent.com/PTB-M4D/PyDynamic/main/docs/PyDynamic_module_diagram.png)
+
+However, imports should generally be possible without explicitly naming all packages
+and modules in the path, so that for example the following import statements are all
+equivalent.
+
+```python
+from PyDynamic.uncertainty.propagate_filter import FIRuncFilter
+from PyDynamic.uncertainty import FIRuncFilter
+from PyDynamic import FIRuncFilter
+```
+
+## Documentation
+
+The documentation for PyDynamic can be found on
+[ReadTheDocs](http://pydynamic.readthedocs.io)
+
+## Installation
+
+The installation of PyDynamic is as straightforward as the Python ecosystem suggests.
+Detailed instructions on different options to install PyDynamic you can find in the 
+[installation section of the docs](https://pydynamic.readthedocs.io/en/latest/INSTALL.html).
+
+## Contributing
+
+Whenever you are involved with PyDynamic, please respect our [Code of Conduct
+](https://github.com/PTB-M4D/PyDynamic/blob/main/CODE_OF_CONDUCT.md).
+If you want to contribute back to the project, after reading our Code of Conduct,
+take a look at our open developments in the [project board
+](https://github.com/PTB-M4D/PyDynamic/projects/1), [pull requests
+](https://github.com/PTB-M4D/PyDynamic/pulls) and search [the issues
+](https://github.com/PTB-M4D/PyDynamic/issues). If you find something similar to
+your ideas or troubles, let us know by leaving a comment or remark. If you have
+something new to tell us, feel free to open a feature request or bug report in the
+issues. If you want to contribute code or improve our documentation, please check our
+[contribution advices and tips](https://pydynamic.readthedocs.io/en/latest/CONTRIBUTING.html).
+
+If you have downloaded this software, we would be very thankful for letting
+us know. You may, for instance, drop an email to one of the [authors
+](https://github.com/PTB-M4D/PyDynamic/graphs/contributors) (e.g.
+[Sascha Eichstädt](mailto:sascha.eichstaedt@ptb.de), [Björn Ludwig
+](mailto:bjoern.ludwig@ptb.de) or [Maximilian Gruber
+](mailto:maximilian.gruber@ptb.de))
+
+## Examples
+
+We have collected extended material for an easier introduction to PyDynamic in the
+package _examples_. Detailed assistance on getting started you can find in the
+corresponding sections of the docs:
+
+* [examples](https://pydynamic.readthedocs.io/en/latest/Examples.html)
+* [tutorials](https://pydynamic.readthedocs.io/en/latest/Tutorials.html)
+
+In various Jupyter Notebooks and scripts we demonstrate the use of
+the provided methods to aid the first steps in PyDynamic. New features are introduced
+with an example from the beginning if feasible. We are currently moving this supporting
+collection to an external repository on GitHub. They will be available at
+[github.com/PTB-M4D/PyDynamic_tutorials](https://github.com/PTB-M4D/PyDynamic_tutorials) 
+in the near future.
+
+## Roadmap
+
+1. Implementation of robust measurement (sensor) models
+1. Extension to more complex noise and uncertainty models
+1. Introducing uncertainty propagation for Kalman filters
+
+For a comprehensive overview of current development activities and upcoming tasks,
+take a look at the [project board](https://github.com/PTB-M4D/PyDynamic/projects/1),
+[issues](https://github.com/PTB-M4D/PyDynamic/issues) and
+[pull requests](https://github.com/PTB-M4D/PyDynamic/pulls).
+
+## Citation
+
+If you publish results obtained with the help of PyDynamic, please use the above linked
+[Zenodo DOI](https://doi.org/10.5281/zenodo.1489877) for the code itself or cite
+
+Sascha Eichstädt, Clemens Elster, Ian M. Smith, and Trevor J. Esward
+*Evaluation of dynamic measurement uncertainty – an open-source software
+package to bridge theory and practice*
+**J. Sens. Sens. Syst.**, 6, 97-105, 2017, DOI: [10.5194/jsss-6-97-2017
+](https://doi.org/10.5194/jsss-6-97-2017)
+
+## Acknowledgement
+
+Part of this work is developed as part of the Joint Research Project [17IND12 Met4FoF
+](http://met4fof.eu) of the European Metrology Programme for Innovation and
+Research (EMPIR).
+
+This work was part of the Joint Support for Impact project
+[14SIP08](https://www.euramet.org/research-innovation/search-research-projects/details/project/standards-and-software-to-maximise-end-user-uptake-of-nmi-calibrations-of-dynamic-force-torque-and/)
+of the European Metrology Programme for Innovation and Research (EMPIR). The
+[EMPIR](http://msu.euramet.org) is jointly funded by the EMPIR participating 
+countries within EURAMET and the European Union.
+
+## Disclaimer
+
+This software is developed at Physikalisch-Technische Bundesanstalt (PTB). The
+software is made available "as is" free of cost. PTB assumes no responsibility
+whatsoever for its use by other parties, and makes no guarantees, expressed or
+implied, about its quality, reliability, safety, suitability or any other
+characteristic. In no event will PTB be liable for any direct, indirect or
+consequential damage arising in connection with the use of this software.
+
+## License
+
+PyDynamic is distributed under the [LGPLv3 license
+](https://github.com/PTB-M4D/PyDynamic/blob/main/licence.txt)
+except for the module [`impinvar.py`
+](https://github.com/PTB-M4D/PyDynamic/blob/main/src/PyDynamic/misc/impinvar.py) 
+in the package [`misc`
+](https://pydynamic.readthedocs.io/en/main/PyDynamic.misc.html), 
+which is distributed under the [GPLv3 license
+](https://github.com/PTB-M4D/PyDynamic/blob/main/src/PyDynamic/misc/impinvar_license.txt).
+
+
+
+
+%prep
+%autosetup -n PyDynamic-2.4.0
+
+%build
+%py3_build
+
+%install
+%py3_install
+install -d -m755 %{buildroot}/%{_pkgdocdir}
+if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
+if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
+if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
+if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
+pushd %{buildroot}
+if [ -d usr/lib ]; then
+	find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/lib64 ]; then
+	find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/bin ]; then
+	find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/sbin ]; then
+	find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+touch doclist.lst
+if [ -d usr/share/man ]; then
+	find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
+fi
+popd
+mv %{buildroot}/filelist.lst .
+mv %{buildroot}/doclist.lst .
+
+%files -n python3-PyDynamic -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 2.4.0-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..3a530ab
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+0d293502d9751ec7f11bd20e72767ac2  PyDynamic-2.4.0.tar.gz