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diff --git a/python-climetlab-maelstrom-radiation.spec b/python-climetlab-maelstrom-radiation.spec new file mode 100644 index 0000000..7c78895 --- /dev/null +++ b/python-climetlab-maelstrom-radiation.spec @@ -0,0 +1,195 @@ +%global _empty_manifest_terminate_build 0 +Name: python-climetlab-maelstrom-radiation +Version: 0.7.4 +Release: 1 +Summary: A dataset plugin for climetlab for the dataset maelstrom-radiation. +License: Apache License Version 2.0 +URL: https://git.ecmwf.int/projects/MLFET/repos/maelstrom-radiation +Source0: https://mirrors.aliyun.com/pypi/web/packages/3a/30/02b7605fe0317c47cbe595613643c8a4417bba4c7e8718c12ef42f6d3fe7/climetlab_maelstrom_radiation-0.7.4.tar.gz +BuildArch: noarch + +Requires: python3-climetlab +Requires: python3-tensorflow +Requires: python3-deep500 + +%description +## maelstrom-radiation + +A dataset plugin for climetlab (https://climetlab.readthedocs.io/en/latest/) + for the dataset maelstrom-radiation. + +## Datasets description + +This data is for learning the +emulation of the ECMWF radiation scheme, using the McICA solver, found in the ecRad package +(https://github.com/ecmwf/ecrad). Building an accurate emulator of radiative heating +could accelerate weather and climate models partially by enabling the use of GPU +hardware within our models. + +There are two datasets, allowing different views on the same data: + +### 1 : `maelstom-radiation` +Supports the `to_xarray` method and allows users to explore the data with all structure kept intact. + +### 2 : `maelstrom-radiation-tf` +Loads the same data but from a shuffled and repacked into the TFRecord format. This dataset supports +`to_tfdataset` which uses Tensorflow's dataset object. + + +## Using climetlab to access the data + +Both datasets and downloaded and explained in the demo notebook here +https://git.ecmwf.int/projects/MLFET/repos/maelstrom-radiation/browse/notebooks/demo_radiation.ipynb + +The climetlab python package allows easy access to the data with a few lines of code such as: +``` + +!pip install climetlab climetlab_maelstrom_radiation +import climetlab as cml +cml_ds = cml.load_dataset("maelstrom-radiation", subset="tier-1") +ds = cml_ds.to_xarray() + +!or for the TFdataset version +cml_ds = cml.load_dataset("maelstrom-radiation-tf", subset="tier-1") +ds = cml_ds.to_tfdataset(batch_size=256) +``` + + +%package -n python3-climetlab-maelstrom-radiation +Summary: A dataset plugin for climetlab for the dataset maelstrom-radiation. +Provides: python-climetlab-maelstrom-radiation +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-climetlab-maelstrom-radiation +## maelstrom-radiation + +A dataset plugin for climetlab (https://climetlab.readthedocs.io/en/latest/) + for the dataset maelstrom-radiation. + +## Datasets description + +This data is for learning the +emulation of the ECMWF radiation scheme, using the McICA solver, found in the ecRad package +(https://github.com/ecmwf/ecrad). Building an accurate emulator of radiative heating +could accelerate weather and climate models partially by enabling the use of GPU +hardware within our models. + +There are two datasets, allowing different views on the same data: + +### 1 : `maelstom-radiation` +Supports the `to_xarray` method and allows users to explore the data with all structure kept intact. + +### 2 : `maelstrom-radiation-tf` +Loads the same data but from a shuffled and repacked into the TFRecord format. This dataset supports +`to_tfdataset` which uses Tensorflow's dataset object. + + +## Using climetlab to access the data + +Both datasets and downloaded and explained in the demo notebook here +https://git.ecmwf.int/projects/MLFET/repos/maelstrom-radiation/browse/notebooks/demo_radiation.ipynb + +The climetlab python package allows easy access to the data with a few lines of code such as: +``` + +!pip install climetlab climetlab_maelstrom_radiation +import climetlab as cml +cml_ds = cml.load_dataset("maelstrom-radiation", subset="tier-1") +ds = cml_ds.to_xarray() + +!or for the TFdataset version +cml_ds = cml.load_dataset("maelstrom-radiation-tf", subset="tier-1") +ds = cml_ds.to_tfdataset(batch_size=256) +``` + + +%package help +Summary: Development documents and examples for climetlab-maelstrom-radiation +Provides: python3-climetlab-maelstrom-radiation-doc +%description help +## maelstrom-radiation + +A dataset plugin for climetlab (https://climetlab.readthedocs.io/en/latest/) + for the dataset maelstrom-radiation. + +## Datasets description + +This data is for learning the +emulation of the ECMWF radiation scheme, using the McICA solver, found in the ecRad package +(https://github.com/ecmwf/ecrad). Building an accurate emulator of radiative heating +could accelerate weather and climate models partially by enabling the use of GPU +hardware within our models. + +There are two datasets, allowing different views on the same data: + +### 1 : `maelstom-radiation` +Supports the `to_xarray` method and allows users to explore the data with all structure kept intact. + +### 2 : `maelstrom-radiation-tf` +Loads the same data but from a shuffled and repacked into the TFRecord format. This dataset supports +`to_tfdataset` which uses Tensorflow's dataset object. + + +## Using climetlab to access the data + +Both datasets and downloaded and explained in the demo notebook here +https://git.ecmwf.int/projects/MLFET/repos/maelstrom-radiation/browse/notebooks/demo_radiation.ipynb + +The climetlab python package allows easy access to the data with a few lines of code such as: +``` + +!pip install climetlab climetlab_maelstrom_radiation +import climetlab as cml +cml_ds = cml.load_dataset("maelstrom-radiation", subset="tier-1") +ds = cml_ds.to_xarray() + +!or for the TFdataset version +cml_ds = cml.load_dataset("maelstrom-radiation-tf", subset="tier-1") +ds = cml_ds.to_tfdataset(batch_size=256) +``` + + +%prep +%autosetup -n climetlab_maelstrom_radiation-0.7.4 + +%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-climetlab-maelstrom-radiation -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Tue Jun 20 2023 Python_Bot <Python_Bot@openeuler.org> - 0.7.4-1 +- Package Spec generated |