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clean up documentation on IPOPT (#468)
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doc/index.rst

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@@ -10,6 +10,12 @@ Some key features of pyOptSparse include:
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- The optimization histories can be stored during the optimization process, and a partial history can also be used to hot-restart the optimization
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- A post-processing GUI utility called OptView to analyze optimization results
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The list of supported optimizers is shown on the sidebar to the left.
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Of those, the following are not installed by default:
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- SNOPT and NLPQLP are proprietary and must be obtained from their respective authors
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- IPOPT and ParOpt must be installed separately
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pyOptSparse is a fork of `pyOpt <http://www.pyopt.org/>`_.
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However, it is not backwards compatible with pyOpt and thus optimization scripts will need to be modified to use pyOptSparse.

doc/install.rst

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@@ -11,7 +11,7 @@ Conda packages are available on ``conda-forge`` and can be installed via
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conda install -c conda-forge pyoptsparse
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This would install pyOptSparse with the built-in optimizers, as well as IPOPT.
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This would install pyOptSparse with the built-in optimizers.
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If you wish to use optimizers not packaged by ``conda``, e.g. SNOPT, then you must either build the package from source or use the installation script below.
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If you have the SNOPT precompiled library available, it is possible to dynamically link it to pyOptSparse following the instructions on the :ref:`SNOPT installation page<snopt_by_conda>`.
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If this throws a ``missing symbol`` error, then there is likely a linking issue at compile time.
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If, on the other hand, this throws a ``error while loading shared libraries``, then it's probably a runtime issue with a shared library.
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Check to make sure that the ``$LD_LIBRARY_PATH`` is set correctly, for example when running IPOPT.
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Update or Uninstall

doc/optimizers/IPOPT.rst

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@@ -8,9 +8,12 @@ The source code can be found `here <https://github.com/coin-or/Ipopt>`_.
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Installation
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------------
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IPOPT and its Python interface `cyipopt <https://github.com/mechmotum/cyipopt>` must be installed separately.
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Follow the instructions `here <https://cyipopt.readthedocs.io/en/stable/install.html>`_.
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OpenMDAO also has a very helpful `script <https://github.com/OpenMDAO/build_pyoptsparse/>`_ which can be used to install IPOPT with other linear solvers,
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but it does not install ``cyipopt`` for you.
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There are several ways to install IPOPT and its Python bindings:
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#. The simplest option is to use conda-forge to install ``cyipopt``. This is recommended for most people.
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#. Either compile IPOPT yourself or use a pre-built binary, then install ``cyipopt`` from source.
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Follow the instructions `here <https://cyipopt.readthedocs.io/en/stable/install.html>`_.
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#. Use the helper script `build_pyoptsparse <https://github.com/OpenMDAO/build_pyoptsparse/>` by the team at OpenMDAO.
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This will install IPOPT and ``cyipopt`` for you.
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Options
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-------

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