Metadata-Version: 2.1
Name: ipopt
Version: 0.3.0
Summary: A Cython wrapper to the IPOPT optimization package
Home-page: https://github.com/matthias-k/cyipopt
Author: Matthias Kümmerer
Author-email: matthias.kuemmerer@bethgelab.org
License: EPL-1.0
Keywords: optimization
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: Eclipse Public License 1.0 (EPL-1.0)
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Dist: numpy
Requires-Dist: cython
Requires-Dist: six
Requires-Dist: future
Requires-Dist: setuptools

**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.

==================
README for cyipopt
==================

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.

.. _Ipopt: https://projects.coin-or.org/Ipopt
.. _COIN-OR: https://projects.coin-or.org/

Status
======

.. list-table::

   * - Anaconda
     - .. image:: https://anaconda.org/conda-forge/cyipopt/badges/version.svg
          :target: https://anaconda.org/conda-forge/cyipopt
       .. image:: https://anaconda.org/conda-forge/cyipopt/badges/downloads.svg
          :target: https://anaconda.org/conda-forge/cyipopt
   * - PyPi
     - .. image:: https://badge.fury.io/py/ipopt.svg
          :target: https://pypi.org/project/ipopt
       .. image:: https://pepy.tech/badge/ipopt
          :target: https://pypi.org/project/ipopt
   * - Travis CI
     - .. image:: https://api.travis-ci.org/matthias-k/cyipopt.svg?branch=master
          :target: https://travis-ci.org/matthias-k/cyipopt
   * - Appveyor
     - .. image:: https://ci.appveyor.com/api/projects/status/0o5yuogn3jx157ee?svg=true
          :target: https://ci.appveyor.com/project/moorepants/cyipopt

Usage
=====

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:

.. code:: python

    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)

Installation
============

Using conda
-----------

The `Anaconda Python Distribution <https://www.continuum.io/why-anaconda>`_ is
one of the easiest ways to install Python and associated pre-complied 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.

From source
-----------

To begin installing from source you will need to install the following
dependencies:

  * C/C++ compiler
  * pkg-config [only for Linux and Mac]
  * Ipopt [>3.13.0 for Windows]
  * Python 2.7 or 3.6+
  * setuptools
  * cython
  * numpy
  * six
  * future
  * scipy [optional]

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.

On Linux and Mac
~~~~~~~~~~~~~~~~

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

From source on Windows
~~~~~~~~~~~~~~~~~~~~~~

Install the dependencies with conda (Anaconda or Miniconda)::

   conda.exe install -c conda-forge numpy cython future six setuptools

Or alternatively with pip::

   pip install numpy cython future six setuptools

Additionally, make sure you have a C compiler setup to compile Python C
extensions, e.g. Visual C++. Build tools for VS2019
https://visualstudio.microsoft.com/downloads/#build-tools-for-visual-studio-2019
have been tested to work for conda Python 3.7 (see
https://github.com/matthias-k/cyipopt/issues/52).

Download and extract the cyipopt source code from Github or PyPi.

Obtain IPOPT one of two ways:

1. Using official IPOPTs binaries:

Download the latest precompiled version of Ipopt that includes the DLL files from
https://github.com/coin-or/Ipopt/releases. Note that the current setup only
supports Ipopt >= 3.13.0. The build 3.13.3 of Ipopt has been confirmed to work and
can be downloaded from `Ipopt-3.13.3-win64-msvs2019-md.zip
<https://github.com/coin-or/Ipopt/releases/download/releases%2F3.13.3/Ipopt-3.13.3-win64-msvs2019-md.zip>`_
. After Ipopt is extracted, the ``bin``, ``lib`` and ``include`` folders should
be in the root cyipopt directory, i.e. adjacent to the ``setup.py`` file.
Alternatively, you can set the environment variable ``IPOPTWINDIR`` to point to
the Ipopt directory that contains the ``bin``, ``lib`` and ``include`` directories.

2. Using Conda Forge's IPOPT binary:

If using conda, you can install an IPOPT binary from Conda Forge::

    conda.exe install -c conda-forge ipopt

The environment variable ``IPOPTWINDIR`` should then be set to ``USECONDAFORGEIPOPT``.

Finally, execute::

   python setup.py install

**NOTE:** It is advised to use the Anaconda or Miniconda distributions and *not* the
official python.org distribution. Even though it has been tested to work with the
latest builds, it is well-known for causing issues. (see
https://github.com/matthias-k/cyipopt/issues/52).

Example Installation on Ubuntu 18.04 Using Dependencies Installed Via APT
-------------------------------------------------------------------------

All of the dependencies can be installed with Ubuntu's package manager::

   sudo apt install build-essential pkg-config python-dev python-six cython python-numpy coinor-libipopt1v5 coinor-libipopt-dev

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 install the package into Python's default package directory::

   $ python setup.py install

Note that you may or may not want to install this package system wide, i.e.
prepend ``sudo`` to the above command, but it is safest 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. Note that six, cython,
and numpy could alternatively be installed using Python specific package
managers, e.g. ``pip install six cython numpy``.

Example Installation on Ubuntu 18.04 With Custom Compiled IPOPT
---------------------------------------------------------------

Install system wide dependencies::

   $ sudo apt install pkg-config python-dev wget
   $ sudo apt build-dep coinor-libipopt1v5

Install ``pip`` so all Python packages can be installed via ``pip``::

    $ sudo apt install python-pip

Then use ``pip`` to install the following packages::

    $ pip install --user numpy cython six future

Compile Ipopt
~~~~~~~~~~~~~

The Ipopt compilation instructions are derived from
https://www.coin-or.org/Ipopt/documentation/node14.html. If you get errors,
start there for help.

Download Ipopt source code. Choose the version that you would like to have from
<https://www.coin-or.org/download/source/Ipopt/>. For example::

   $ cd ~
   $ wget https://www.coin-or.org/download/source/Ipopt/Ipopt-3.12.11.tgz

Extract the Ipopt source code::

   $ tar -xvf Ipopt-3.12.11.tgz

Create a temporary environment variable pointing to the Ipopt directory::

   export IPOPTDIR=~/Ipopt-3.12.11

To use linear solvers other than the default mumps, e.g. ``ma27, ma57, ma86``
solvers, the ``HSL`` package are needed. ``HSL`` can be downloaded from its
official website <http://www.hsl.rl.ac.uk/ipopt/>.

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``

Build Ipopt::

    $ mkdir $IPOPTDIR/build
    $ cd $IPOPTDIR/build
    $ ../configure
    $ make
    $ make test

Add ``make install`` if you want a system wide install.

Set environment variables::

    $ export IPOPT_PATH="~/Ipopt-3.12.11/build"
    $ export PKG_CONFIG_PATH=$PKG_CONFIG_PATH:$IPOPT_PATH/lib/pkgconfig
    $ export PATH=$PATH:$IPOPT_PATH/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

Now compile ``cyipopt``. Download the ``cyipopt`` source code from PyPi, for
example::

   $ cd ~
   $ wget https://files.pythonhosted.org/packages/05/57/a7c5a86a8f899c5c109f30b8cdb278b64c43bd2ea04172cbfed721a98fac/ipopt-0.1.9.tar.gz
   $ tar -xvf ipopt-0.1.8.tar.gz
   $ cd ipopt

Compile ``cyipopt``::

   $ 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/<username>/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/<username>/Ipopt-3.12.11/build/lib/libcoinmumps.so.1 (0x00007f74ef4ae000)
    libcoinhsl.so.1 => /home/<username>/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/<username>/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`` (prepend ``sudo`` if you want a system wide install)::

    $ python setup.py install

To use ``cyipopt`` you will need to set the ``LD_LIBRARY_PATH`` to point to
your Ipopt install if you did not install it to a standard location. For
example::

    $ export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:~/Ipopt-3.12.11/build/lib

You can add this to your shell's configuration file if you want it set every
time you open your shell, for example the following line can it can be added to
your ``~/.bashrc`` ::

    $ echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$HOME/Ipopt-3.12.11/build/lib' >> ~/.bashrc

Now you should be able to run a ``cyipopt`` example::

    $ 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.
    ...

Docker container
================

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``.

Vagrant environment
===================

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).

Reading the docs
================

After installing::

   $ cd doc
   $ make html

Then, direct your browser to ``build/html/index.html``.

Testing
=======

You can test the installation by running the examples under the folder ``test\``.

Conditions of use
=================

cyipopt is open-source code released under the EPL_ license.

.. _EPL: http://www.eclipse.org/legal/epl-v10.html

Contributing
============

For bug reports use the github issue tracker. You can also send wishes,
comments, patches, etc. to matthias.kuemmerer@bethgelab.org


