This repository was forked from https://bitbucket.org/amitibo/cyipopt and is now considered the primary repository. The fork includes a SciPy-style interface, ability to handle exceptions in the callback functions, and docker container for easy usage.
Ipopt (Interior Point OPTimizer, pronounced eye-pea-opt) is a software package for large-scale nonlinear optimization. Ipopt is available from the COIN-OR initiative, under the Eclipse Public License (EPL).
cyipopt is a Python wrapper around Ipopt. It enables using Ipopt from the comfort of the Python programming language.
For simple cases where you do not need the full power of sparse and structured
Jacobians etc, cyipopt provides the function minimize_ipopt which has
the same behaviour as scipy.optimize.minimize, for example:
from scipy.optimize import rosen, rosen_der
from ipopt import minimize_ipopt
x0 = [1.3, 0.7, 0.8, 1.9, 1.2]
res = minimize_ipopt(rosen, x0, jac=rosen_der)
print(res)The Anaconda Python Distribution is one of the easiest ways to install Python and associated packages for Linux, Mac, and Windows. Once Anaconda (or miniconda) is installed, you can install cyipopt on Linux and Mac from the Conda Forge channel with:
$ conda install -c conda-forge cyipopt
The above command will install binary versions of all the necessary dependencies and cyipopt. Note that there currently are no Windows binaries. You will have to install from source from Windows or if you want a customized installation, e.g. with MKL, HSL, etc.
To begin installing from source you will need to install the following dependencies:
- C/C++ compiler
- pkg-config [only for Linux and Mac]
- Ipopt
- Python 2.7 or 3.4+
- setuptools
- cython
- numpy
- six
- future
- scipy [optiional]
The binaries and header files of the Ipopt package can be obtained from http://www.coin-or.org/download/binary/Ipopt/. These include a version compiled against the MKL library. Or you can build Ipopt from source. The remaining dependencies can be installed with conda or other package managers.
Download the source files of cyipopt and update setup.py to point to the
header files and binaries of the Ipopt package, if LD_LIBRARY_PATH and
pkg_config are not setup to find ipopt on their own.
Then, execute:
$ python setup.py install
All of the dependencies can be installed with Ubuntu's package manager:
sudo apt install build-essential python-dev python-six cython python-numpy coinor-libipopt1v5 coinor-libipopt-dev
Note that six, cython, and numpy could alternatively be installed using Python
specific package managers, e.g. pip install six cython numpy.
The NumPy and IPOPT libs and headers are installed in standard locations, so
you should not need to set LD_LIBRARY_PATH or PKG_CONFIG_PATH.
Now run python setup.py build to compile cyipopt. In the output of this
command you should see two calls to gcc for compiling and linking. Make
sure both of these are pointing to the correct libraries and headers. They will
look something like this (formatted and commented for easy viewing here):
$ python setup.py build ... x86_64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -Wstrict-prototypes -fno-strict-aliasing -Wdate-time -D_FORTIFY_SOURCE=2 -g -fdebug-prefix-map=/build/python2.7-3hk45v/python2.7-2.7.15~rc1=. -fstack-protector-strong -Wformat -Werror=format-security -fPIC -I/usr/local/include/coin # points to IPOPT headers -I/usr/local/include/coin/ThirdParty # points to IPOPT third party headers -I/usr/lib/python2.7/dist-packages/numpy/core/include # points to NumPy headers -I/usr/include/python2.7 # points to Python 2.7 headers -c src/cyipopt.c -o build/temp.linux-x86_64-2.7/src/cyipopt.o x86_64-linux-gnu-gcc -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-Bsymbolic-functions -Wl,-z,relro -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2 -Wall -Wstrict-prototypes -Wdate-time -D_FORTIFY_SOURCE=2 -g -fdebug-prefix-map=/build/python2.7-3hk45v/python2.7-2.7.15~rc1=. -fstack-protector-strong -Wformat -Werror=format-security -Wl,-Bsymbolic-functions -Wl,-z,relro -Wdate-time -D_FORTIFY_SOURCE=2 -g -fdebug-prefix-map=/build/python2.7-3hk45v/python2.7-2.7.15~rc1=. -fstack-protector-strong -Wformat -Werror=format-security build/temp.linux-x86_64-2.7/src/cyipopt.o -L/usr/local/lib -L/lib/../lib -L/usr/lib/../lib -L/usr/lib/gcc/x86_64-linux-gnu/5 -L/usr/lib/gcc/x86_64-linux-gnu/5/../../.. -L/usr/lib/gcc/x86_64-linux-gnu/5/../../../../lib -L/usr/lib/gcc/x86_64-linux-gnu/5/../../../x86_64-linux-gnu -lipopt -llapack -lblas -lm -ldl -lcoinmumps -lblas -lgfortran -lm -lquadmath # linking to relevant libs -lcoinhsl -llapack -lblas -lgfortran -lm -lquadmath -lcoinmetis # linking to relevant libs -o build/lib.linux-x86_64-2.7/cyipopt.so ...
You can check that everything linked correctly with ldd:
$ ldd build/lib.linux-x86_64-2.7/cyipopt.so linux-vdso.so.1 (0x00007ffc1677c000) libipopt.so.0 => /usr/local/lib/libipopt.so.0 (0x00007fcdc8668000) libc.so.6 => /lib/x86_64-linux-gnu/libc.so.6 (0x00007fcdc8277000) libcoinmumps.so.0 => /usr/local/lib/libcoinmumps.so.0 (0x00007fcdc7eef000) libcoinhsl.so.0 => /usr/local/lib/libcoinhsl.so.0 (0x00007fcdc7bb4000) liblapack.so.3 => /usr/lib/x86_64-linux-gnu/liblapack.so.3 (0x00007fcdc732e000) libblas.so.3 => /usr/lib/x86_64-linux-gnu/libblas.so.3 (0x00007fcdc70d3000) libdl.so.2 => /lib/x86_64-linux-gnu/libdl.so.2 (0x00007fcdc6ecf000) libstdc++.so.6 => /usr/lib/x86_64-linux-gnu/libstdc++.so.6 (0x00007fcdc6b46000) libm.so.6 => /lib/x86_64-linux-gnu/libm.so.6 (0x00007fcdc67a8000) /lib64/ld-linux-x86-64.so.2 (0x00007fcdc8d20000) libgcc_s.so.1 => /lib/x86_64-linux-gnu/libgcc_s.so.1 (0x00007fcdc6590000) libcoinmetis.so.0 => /usr/local/lib/libcoinmetis.so.0 (0x00007fcdc6340000) libgfortran.so.3 => /usr/lib/x86_64-linux-gnu/libgfortran.so.3 (0x00007fcdc600f000) libopenblas.so.0 => /usr/lib/x86_64-linux-gnu/libopenblas.so.0 (0x00007fcdc3d69000) libgfortran.so.4 => /usr/lib/x86_64-linux-gnu/libgfortran.so.4 (0x00007fcdc398a000) libquadmath.so.0 => /usr/lib/x86_64-linux-gnu/libquadmath.so.0 (0x00007fcdc374a000) libpthread.so.0 => /lib/x86_64-linux-gnu/libpthread.so.0 (0x00007fcdc352b000)
And finally:
$ python setup.py install
Note that you may or may not want to install this package system wide. It is
best to install into your user space, i.e. what pip install --user does, or
setup a virtual environment with tools like venv or conda. If you use virtual
environments you will need to be careful about selecting headers and libraries
for packages in or out of the virtual environments in the build step.
Before start, make sure pip is installed. If not, please install it:
$ sudo apt install python-pip
Then use pip install the following packages:
$ pip2 install pkgconfig numpy scipy cython six future wget
- Compile Ipopt
- Download ipopt source code, choose the verison that you would like to have from this page <https://www.coin-or.org/download/source/Ipopt/>.
Here I used Ipopt-3.12.11
Extract ipopt and put it in the floder you want (I put it at Home folder).
Create the Ipopt directory: export IPOPTDIR=/home/huawei/Ipopt-3.12.11
Download external packages using
wget:cd $IPOPTDIR/ThirdParty/Blas ./get.Blas cd ../Lapack && ./get.Lapack cd ../ASL && ./get.ASL cd ../Mumps && ./get.Mumps cd ../Metis && ./get.Metis
To use ma27, ma57, ma86 solvers, HSL package are needed. HSL can be get from its official website <http://www.hsl.rl.ac.uk/ipopt/>, academic license is free.
Extract ''HSL'' source code after you get it. Rename the extracted folder to coinhsl and copy it in the HSL folder: Ipopt-3.12.11/ThirdParty/HSL
Install Ipopt using
./configure, make, make installcommands:$ mkdir $IPOPTDIR/build $ cd $IPOPTDIR/build $ IPOPTDIR/configure $ make $ make test $ make install
I used the ipopt document as reference, and it descrips the compile process in a very detail way. If you get errors in this process, please check it <https://www.coin-or.org/Ipopt/documentation/node14.html>
Set environment path:
$ export IPOPTPATH="/home/huawei/Ipopt-3.12.11/build" # make sure this one starts with the Home path $ export PKG_CONFIG_PATH=$PKG_CONFIG_PATH:$IPOPTPATH/lib/pkgconfig $ export PATH=$PATH:$IPOPTPATH/bin
Get help from this web-page if you get errors in setting environments. <https://stackoverflow.com/questions/13428910/how-to-set-the-environmental-variable-ld-library-path-in-linux>
- Compile cyipopt
- Download
cyipoptsource code from this github: <https://github.com/matthias-k/cyipopt>
Extract cyipopt and put it at the place you want (I put it at Home directory).
Change the path of terminal to cyipopt: cd ~/cyipopt
Compile cyipopt using the command: python setup.py build
If there is no error, then you have compiled cyipopt successfully
check that everything linked correctly with
ldd$ ldd build/lib.linux-x86_64-2.7/cyipopt.so linux-vdso.so.1 (0x00007ffe895e1000) libipopt.so.1 => /home/huawei/Ipopt-3.12.11/build/lib/libipopt.so.1 (0x00007f74efc2a000) libc.so.6 => /lib/x86_64-linux-gnu/libc.so.6 (0x00007f74ef839000) libcoinmumps.so.1 => /home/huawei/Ipopt-3.12.11/build/lib/libcoinmumps.so.1 (0x00007f74ef4ae000) libcoinhsl.so.1 => /home/huawei/Ipopt-3.12.11/build/lib/libcoinhsl.so.1 (0x00007f74ef169000) liblapack.so.3 => /usr/lib/x86_64-linux-gnu/liblapack.so.3 (0x00007f74ee8cb000) libblas.so.3 => /usr/lib/x86_64-linux-gnu/libblas.so.3 (0x00007f74ee65e000) libdl.so.2 => /lib/x86_64-linux-gnu/libdl.so.2 (0x00007f74ee45a000) libstdc++.so.6 => /usr/lib/x86_64-linux-gnu/libstdc++.so.6 (0x00007f74ee0d1000) libm.so.6 => /lib/x86_64-linux-gnu/libm.so.6 (0x00007f74edd33000) /lib64/ld-linux-x86-64.so.2 (0x00007f74f02c0000) libgcc_s.so.1 => /lib/x86_64-linux-gnu/libgcc_s.so.1 (0x00007f74edb1b000) libcoinmetis.so.1 => /home/huawei/Ipopt-3.12.11/build/lib/libcoinmetis.so.1 (0x00007f74ed8ca000) libgfortran.so.4 => /usr/lib/x86_64-linux-gnu/libgfortran.so.4 (0x00007f74ed4eb000)
Install
Cyipopt:$ python setup.py install
Before try the test code, add Ipopt
libpath toLD_LIBRARY_PATH:$ export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/home/huawei/Ipopt-3.12.11/build/lib
To make this path works for all terminal, it can be added to .bashrc
$ echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/home/huawei/Ipopt-3.12.11/build/lib' >> ~/.bashrc
Now you can run the test code:
$ cd test $ python -c "import ipopt" $ python examplehs071.py
If it could be run successfully, the optimization will start with the following descriptions:
******************************************************************************
This program contains Ipopt, a library for large-scale nonlinear optimization.
Ipopt is released as open source code under the Eclipse Public License (EPL).
For more information visit http://projects.coin-or.org/Ipopt
******************************************************************************
This is Ipopt version 3.12.11, running with linear solver ma27.
The subdirectory docker contains a docker container with preinstalled ipopt
and cyipopt. To build the container, cd into the docker directory and run
make. Then you can start the container by:
$ docker run -it matthiask/ipopt /bin/bash
and either call ipopt directly or start a ipython shell and import ipopt.
The subdirectory vagrant contains a Vagrantfile that installs ipopt and
cyipopt in OS provision. To build the environment, cd into the vagrant
directory and run vagrant up (Requires that you have Vagrant+VirtualBox
installed). Then you can access the system by:
$ vagrant ssh
and either call ipopt directly or start a python shell and import
ipopt. Also, if you get source files
<http://www.coin-or.org/download/binary/Ipopt/> of coinhsl and put it in the
vagrant directory, the vagrant provision will detect and add them in the
ipopt compiling process, and then you will have ma57, ma27, and other solvers
available on ipopt binary (ma97 and mc68 were removed to avoid compilation
errors).
After installing:
$ cd doc $ make html
Then, direct your browser to build/html/index.html.
You can test the installation by running the examples under the folder test\.
cyipopt is open-source code released under the EPL license.
For bug reports use the github issue tracker. You can also send wishes, comments, patches, etc. to matthias.kuemmerer@bethgelab.org