From c95690be792c5b06bd3771cd0a93c948b29df7fe Mon Sep 17 00:00:00 2001 From: CoprDistGit Date: Mon, 15 May 2023 09:33:54 +0000 Subject: automatic import of python-gym-discrete --- .gitignore | 1 + python-gym-discrete.spec | 181 +++++++++++++++++++++++++++++++++++++++++++++++ sources | 1 + 3 files changed, 183 insertions(+) create mode 100644 python-gym-discrete.spec create mode 100644 sources diff --git a/.gitignore b/.gitignore index e69de29..3fc62b6 100644 --- a/.gitignore +++ b/.gitignore @@ -0,0 +1 @@ +/gym_discrete-1.5.6.tar.gz diff --git a/python-gym-discrete.spec b/python-gym-discrete.spec new file mode 100644 index 0000000..016fd84 --- /dev/null +++ b/python-gym-discrete.spec @@ -0,0 +1,181 @@ +%global _empty_manifest_terminate_build 0 +Name: python-gym-discrete +Version: 1.5.6 +Release: 1 +Summary: A OpenAI Gym Env for discrete +License: MIT +URL: https://pypi.org/project/gym-discrete/ +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/73/45/0d3abf89b2522e1266da6048491349b8a0714b88b6755605383dc18b8e6e/gym_discrete-1.5.6.tar.gz +BuildArch: noarch + +Requires: python3-gym + +%description +# Gym-style API + +The domanin features a continuos state and a dicrete action space. + +The environment initializes: +- cross-sectional dataset with variables X_a, X_s, Y and N observations; +- logit model fitted on the dataset, retrieving parameters \theta_0, \theta_1, \theta_2; + +The agent: +- sees all patients; +- predict risk of admission \rho, using initialized parameters +- sample an action (50 possible values between -2 and 2) +- if risk > 0.2: + - replace Xa by g, where g(\rho, Xa) is obtained using the patient's risk and Xa value +- else: + - do not intervene, X_a stays the same +- give reward equal to average risk of admission, using predicted Y, initial parameters and sampled values + + +# To install +- git clone https://github.com/claudia-viaro/gym-discrete.git +- cd gym-discrete + +- !pip install gym-discrete +- import gym_discrete +- env =gym.make('discrete-v0') + +# To change version +- change version to, e.g., 1.0.7 from setup.py file +- git clone https://github.com/claudia-viaro/gym-discrete.git +- cd gym-discrete +- python setup.py sdist bdist_wheel +- twine check dist/* +- twine upload --repository-url https://upload.pypi.org/legacy/ dist/* + + + + +%package -n python3-gym-discrete +Summary: A OpenAI Gym Env for discrete +Provides: python-gym-discrete +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-gym-discrete +# Gym-style API + +The domanin features a continuos state and a dicrete action space. + +The environment initializes: +- cross-sectional dataset with variables X_a, X_s, Y and N observations; +- logit model fitted on the dataset, retrieving parameters \theta_0, \theta_1, \theta_2; + +The agent: +- sees all patients; +- predict risk of admission \rho, using initialized parameters +- sample an action (50 possible values between -2 and 2) +- if risk > 0.2: + - replace Xa by g, where g(\rho, Xa) is obtained using the patient's risk and Xa value +- else: + - do not intervene, X_a stays the same +- give reward equal to average risk of admission, using predicted Y, initial parameters and sampled values + + +# To install +- git clone https://github.com/claudia-viaro/gym-discrete.git +- cd gym-discrete + +- !pip install gym-discrete +- import gym_discrete +- env =gym.make('discrete-v0') + +# To change version +- change version to, e.g., 1.0.7 from setup.py file +- git clone https://github.com/claudia-viaro/gym-discrete.git +- cd gym-discrete +- python setup.py sdist bdist_wheel +- twine check dist/* +- twine upload --repository-url https://upload.pypi.org/legacy/ dist/* + + + + +%package help +Summary: Development documents and examples for gym-discrete +Provides: python3-gym-discrete-doc +%description help +# Gym-style API + +The domanin features a continuos state and a dicrete action space. + +The environment initializes: +- cross-sectional dataset with variables X_a, X_s, Y and N observations; +- logit model fitted on the dataset, retrieving parameters \theta_0, \theta_1, \theta_2; + +The agent: +- sees all patients; +- predict risk of admission \rho, using initialized parameters +- sample an action (50 possible values between -2 and 2) +- if risk > 0.2: + - replace Xa by g, where g(\rho, Xa) is obtained using the patient's risk and Xa value +- else: + - do not intervene, X_a stays the same +- give reward equal to average risk of admission, using predicted Y, initial parameters and sampled values + + +# To install +- git clone https://github.com/claudia-viaro/gym-discrete.git +- cd gym-discrete + +- !pip install gym-discrete +- import gym_discrete +- env =gym.make('discrete-v0') + +# To change version +- change version to, e.g., 1.0.7 from setup.py file +- git clone https://github.com/claudia-viaro/gym-discrete.git +- cd gym-discrete +- python setup.py sdist bdist_wheel +- twine check dist/* +- twine upload --repository-url https://upload.pypi.org/legacy/ dist/* + + + + +%prep +%autosetup -n gym-discrete-1.5.6 + +%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-gym-discrete -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Mon May 15 2023 Python_Bot - 1.5.6-1 +- Package Spec generated diff --git a/sources b/sources new file mode 100644 index 0000000..b768c1d --- /dev/null +++ b/sources @@ -0,0 +1 @@ +955e6d8e487ad90ff5b3cbe3676585e4 gym_discrete-1.5.6.tar.gz -- cgit v1.2.3