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diff --git a/python-pitchplots.spec b/python-pitchplots.spec new file mode 100644 index 0000000..9dda50c --- /dev/null +++ b/python-pitchplots.spec @@ -0,0 +1,306 @@ +%global _empty_manifest_terminate_build 0 +Name: python-pitchplots +Version: 1.4.2 +Release: 1 +Summary: A package containing representation tools for musical purposes +License: MIT License +URL: https://github.com/DCMLab/pitchplots +Source0: https://mirrors.aliyun.com/pypi/web/packages/1e/a4/6e04a2ec0d04473702e3f37c3d850b0056d0ed70ca0f5b9a61d3b368712a/pitchplots-1.4.2.tar.gz +BuildArch: noarch + +Requires: python3-matplotlib +Requires: python3-pandas +Requires: python3-numpy + +%description +# pitchplots + +library plotting charts for different tonal representations + +## Getting Started + +The program consist in the following files: functions.py, reader.py, modified_musicxml_parser.py, parser.py and static.py + +### Prerequisites + +What things you need to install the software and how to install them + +``` +You will need python on your computer and the following libaries: matplotlib, pandas and numpy +``` + +note that if you are using anaconda, these libraries are already installed + +### Installing + +You can download the pitchplots package on pypi with pip using the following command in the prompt: + +``` +python3 -m pip install pitchplots +``` + +or if you're using anaconda prompt + +``` +pip install pitchplots +``` + +## Running the tests + +you can first try to parse xml/musicScore xml files to csv or DataFrame, that is the Gymnopédie from Sati with: + +```python +import pitchplots.parser as ppp + +# If no filepath is specified, will automatically charge data_example.mxl +df_data_example = ppp.xml_to_csv(save_csv=True) +``` + +then you can try the static module by passing csv files or Dataframe: + +``` +import pitchplots.static as pps + +pps.tonnetz(df_data_example) +``` +or +``` +import pitchplots.static as pps + +pps.circle('csv/data_example.csv') +``` + +to try the dynamic videos: +``` +import pitchplots.dynamic as ppd + +ppd.tonnetz_animation(df_data_example) +``` + +## Authors + +* **Timothy Loayza**, **Fabian Moss** + +## Use of magenta's code + +The [modified_musicxml_parser.py](modified_musicxml_parser.py) file is taken from the [magenta](https://github.com/tensorflow/magenta) project and has been modified. Therefore the modifications are listed in the [magenta_musicxml_code_modifications.md](magenta_musicxml_code_modifications.md) file and there is the [magenta_LICENSE.md](magenta_LICENSE.md). + +## License + +This project is licensed under the MIT License - see the [LICENSE.md](LICENSE.md) file for details + + + + +%package -n python3-pitchplots +Summary: A package containing representation tools for musical purposes +Provides: python-pitchplots +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-pitchplots +# pitchplots + +library plotting charts for different tonal representations + +## Getting Started + +The program consist in the following files: functions.py, reader.py, modified_musicxml_parser.py, parser.py and static.py + +### Prerequisites + +What things you need to install the software and how to install them + +``` +You will need python on your computer and the following libaries: matplotlib, pandas and numpy +``` + +note that if you are using anaconda, these libraries are already installed + +### Installing + +You can download the pitchplots package on pypi with pip using the following command in the prompt: + +``` +python3 -m pip install pitchplots +``` + +or if you're using anaconda prompt + +``` +pip install pitchplots +``` + +## Running the tests + +you can first try to parse xml/musicScore xml files to csv or DataFrame, that is the Gymnopédie from Sati with: + +```python +import pitchplots.parser as ppp + +# If no filepath is specified, will automatically charge data_example.mxl +df_data_example = ppp.xml_to_csv(save_csv=True) +``` + +then you can try the static module by passing csv files or Dataframe: + +``` +import pitchplots.static as pps + +pps.tonnetz(df_data_example) +``` +or +``` +import pitchplots.static as pps + +pps.circle('csv/data_example.csv') +``` + +to try the dynamic videos: +``` +import pitchplots.dynamic as ppd + +ppd.tonnetz_animation(df_data_example) +``` + +## Authors + +* **Timothy Loayza**, **Fabian Moss** + +## Use of magenta's code + +The [modified_musicxml_parser.py](modified_musicxml_parser.py) file is taken from the [magenta](https://github.com/tensorflow/magenta) project and has been modified. Therefore the modifications are listed in the [magenta_musicxml_code_modifications.md](magenta_musicxml_code_modifications.md) file and there is the [magenta_LICENSE.md](magenta_LICENSE.md). + +## License + +This project is licensed under the MIT License - see the [LICENSE.md](LICENSE.md) file for details + + + + +%package help +Summary: Development documents and examples for pitchplots +Provides: python3-pitchplots-doc +%description help +# pitchplots + +library plotting charts for different tonal representations + +## Getting Started + +The program consist in the following files: functions.py, reader.py, modified_musicxml_parser.py, parser.py and static.py + +### Prerequisites + +What things you need to install the software and how to install them + +``` +You will need python on your computer and the following libaries: matplotlib, pandas and numpy +``` + +note that if you are using anaconda, these libraries are already installed + +### Installing + +You can download the pitchplots package on pypi with pip using the following command in the prompt: + +``` +python3 -m pip install pitchplots +``` + +or if you're using anaconda prompt + +``` +pip install pitchplots +``` + +## Running the tests + +you can first try to parse xml/musicScore xml files to csv or DataFrame, that is the Gymnopédie from Sati with: + +```python +import pitchplots.parser as ppp + +# If no filepath is specified, will automatically charge data_example.mxl +df_data_example = ppp.xml_to_csv(save_csv=True) +``` + +then you can try the static module by passing csv files or Dataframe: + +``` +import pitchplots.static as pps + +pps.tonnetz(df_data_example) +``` +or +``` +import pitchplots.static as pps + +pps.circle('csv/data_example.csv') +``` + +to try the dynamic videos: +``` +import pitchplots.dynamic as ppd + +ppd.tonnetz_animation(df_data_example) +``` + +## Authors + +* **Timothy Loayza**, **Fabian Moss** + +## Use of magenta's code + +The [modified_musicxml_parser.py](modified_musicxml_parser.py) file is taken from the [magenta](https://github.com/tensorflow/magenta) project and has been modified. Therefore the modifications are listed in the [magenta_musicxml_code_modifications.md](magenta_musicxml_code_modifications.md) file and there is the [magenta_LICENSE.md](magenta_LICENSE.md). + +## License + +This project is licensed under the MIT License - see the [LICENSE.md](LICENSE.md) file for details + + + + +%prep +%autosetup -n pitchplots-1.4.2 + +%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-pitchplots -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Tue Jun 20 2023 Python_Bot <Python_Bot@openeuler.org> - 1.4.2-1 +- Package Spec generated |