summaryrefslogtreecommitdiff
diff options
context:
space:
mode:
authorCoprDistGit <infra@openeuler.org>2023-04-11 09:55:12 +0000
committerCoprDistGit <infra@openeuler.org>2023-04-11 09:55:12 +0000
commitfaf3472095d488f031c3a1759f5d99e622a5a155 (patch)
tree11a40b93d6901b4cd5cba4e5866533437cbc7da2
parentc01e988cb399529006747a63c59dac61190f6698 (diff)
automatic import of python-gekko
-rw-r--r--.gitignore1
-rw-r--r--python-gekko.spec160
-rw-r--r--sources1
3 files changed, 162 insertions, 0 deletions
diff --git a/.gitignore b/.gitignore
index e69de29..999b23f 100644
--- a/.gitignore
+++ b/.gitignore
@@ -0,0 +1 @@
+/gekko-1.0.6.tar.gz
diff --git a/python-gekko.spec b/python-gekko.spec
new file mode 100644
index 0000000..9a46e47
--- /dev/null
+++ b/python-gekko.spec
@@ -0,0 +1,160 @@
+%global _empty_manifest_terminate_build 0
+Name: python-gekko
+Version: 1.0.6
+Release: 1
+Summary: Machine learning and optimization for dynamic systems
+License: MIT
+URL: https://github.com/BYU-PRISM/GEKKO
+Source0: https://mirrors.nju.edu.cn/pypi/web/packages/f9/9e/e34c5eb9943a1e8b089577cbd924a46f51164c0af64fd15e815bd468ca51/gekko-1.0.6.tar.gz
+BuildArch: noarch
+
+Requires: python3-numpy
+
+%description
+GEKKO is a python package for machine learning and optimization, specializing in
+dynamic optimization of differential algebraic equations (DAE) systems. It is coupled
+with large-scale solvers APOPT and IPOPT for linear, quadratic, nonlinear, and mixed integer
+programming. Capabilities include machine learning, discrete or continuous state space
+models, simulation, estimation, and control.
+Gekko models consist of equations and variables that create a symbolic representation of the
+problem for a single data point or single time instance. Solution modes then create the full model
+over all data points or time horizon. Gekko supports a wide range of problem types, including:
+- Linear Programming (LP)
+- Quadratic Programming (QP)
+- Nonlinear Programming (NLP)
+- Mixed-Integer Linear Programming (MILP)
+- Mixed-Integer Quadratic Programming (MIQP)
+- Mixed-Integer Nonlinear Programming (MINLP)
+- Differential Algebraic Equations (DAEs)
+- Mathematical Programming with Complementarity Constraints (MPCCs)
+- Data regression / Machine learning
+- Moving Horizon Estimation (MHE)
+- Model Predictive Control (MPC)
+- Real-Time Optimization (RTO)
+- Sequential or Simultaneous DAE solution
+Gekko compiles the model into byte-code and provides sparse derivatives to the solver with
+automatic differentiation. Gekko includes data cleansing functions and standard tag actions for industrially
+hardened control and optimization on Windows, Linux, MacOS, ARM processors, or any other platform that
+runs Python. Options are available for local, edge, and cloud solutions to manage memory or compute
+resources.
+- [Gekko Homepage](https://machinelearning.byu.edu)
+- [Gekko Documentation](https://gekko.readthedocs.io/en/latest/)
+- [Gekko Examples](https://apmonitor.com/wiki/index.php/Main/GekkoPythonOptimization)
+- [Get Gekko Help on Stack Overflow](https://stackoverflow.com/questions/tagged/gekko)
+
+%package -n python3-gekko
+Summary: Machine learning and optimization for dynamic systems
+Provides: python-gekko
+BuildRequires: python3-devel
+BuildRequires: python3-setuptools
+BuildRequires: python3-pip
+%description -n python3-gekko
+GEKKO is a python package for machine learning and optimization, specializing in
+dynamic optimization of differential algebraic equations (DAE) systems. It is coupled
+with large-scale solvers APOPT and IPOPT for linear, quadratic, nonlinear, and mixed integer
+programming. Capabilities include machine learning, discrete or continuous state space
+models, simulation, estimation, and control.
+Gekko models consist of equations and variables that create a symbolic representation of the
+problem for a single data point or single time instance. Solution modes then create the full model
+over all data points or time horizon. Gekko supports a wide range of problem types, including:
+- Linear Programming (LP)
+- Quadratic Programming (QP)
+- Nonlinear Programming (NLP)
+- Mixed-Integer Linear Programming (MILP)
+- Mixed-Integer Quadratic Programming (MIQP)
+- Mixed-Integer Nonlinear Programming (MINLP)
+- Differential Algebraic Equations (DAEs)
+- Mathematical Programming with Complementarity Constraints (MPCCs)
+- Data regression / Machine learning
+- Moving Horizon Estimation (MHE)
+- Model Predictive Control (MPC)
+- Real-Time Optimization (RTO)
+- Sequential or Simultaneous DAE solution
+Gekko compiles the model into byte-code and provides sparse derivatives to the solver with
+automatic differentiation. Gekko includes data cleansing functions and standard tag actions for industrially
+hardened control and optimization on Windows, Linux, MacOS, ARM processors, or any other platform that
+runs Python. Options are available for local, edge, and cloud solutions to manage memory or compute
+resources.
+- [Gekko Homepage](https://machinelearning.byu.edu)
+- [Gekko Documentation](https://gekko.readthedocs.io/en/latest/)
+- [Gekko Examples](https://apmonitor.com/wiki/index.php/Main/GekkoPythonOptimization)
+- [Get Gekko Help on Stack Overflow](https://stackoverflow.com/questions/tagged/gekko)
+
+%package help
+Summary: Development documents and examples for gekko
+Provides: python3-gekko-doc
+%description help
+GEKKO is a python package for machine learning and optimization, specializing in
+dynamic optimization of differential algebraic equations (DAE) systems. It is coupled
+with large-scale solvers APOPT and IPOPT for linear, quadratic, nonlinear, and mixed integer
+programming. Capabilities include machine learning, discrete or continuous state space
+models, simulation, estimation, and control.
+Gekko models consist of equations and variables that create a symbolic representation of the
+problem for a single data point or single time instance. Solution modes then create the full model
+over all data points or time horizon. Gekko supports a wide range of problem types, including:
+- Linear Programming (LP)
+- Quadratic Programming (QP)
+- Nonlinear Programming (NLP)
+- Mixed-Integer Linear Programming (MILP)
+- Mixed-Integer Quadratic Programming (MIQP)
+- Mixed-Integer Nonlinear Programming (MINLP)
+- Differential Algebraic Equations (DAEs)
+- Mathematical Programming with Complementarity Constraints (MPCCs)
+- Data regression / Machine learning
+- Moving Horizon Estimation (MHE)
+- Model Predictive Control (MPC)
+- Real-Time Optimization (RTO)
+- Sequential or Simultaneous DAE solution
+Gekko compiles the model into byte-code and provides sparse derivatives to the solver with
+automatic differentiation. Gekko includes data cleansing functions and standard tag actions for industrially
+hardened control and optimization on Windows, Linux, MacOS, ARM processors, or any other platform that
+runs Python. Options are available for local, edge, and cloud solutions to manage memory or compute
+resources.
+- [Gekko Homepage](https://machinelearning.byu.edu)
+- [Gekko Documentation](https://gekko.readthedocs.io/en/latest/)
+- [Gekko Examples](https://apmonitor.com/wiki/index.php/Main/GekkoPythonOptimization)
+- [Get Gekko Help on Stack Overflow](https://stackoverflow.com/questions/tagged/gekko)
+
+%prep
+%autosetup -n gekko-1.0.6
+
+%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-gekko -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Tue Apr 11 2023 Python_Bot <Python_Bot@openeuler.org> - 1.0.6-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..d787f62
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+7f1df29cb056202c39e6e85f943e8196 gekko-1.0.6.tar.gz