Installation docs update (#350)

Co-authored-by: Marco Mangano <[email protected]>
Co-authored-by: Eirikur Jonsson <[email protected]>

doc/install.rst

@@ -12,7 +12,16 @@ Conda packages are available on ``conda-forge`` and can be installed via
   conda install -c conda-forge pyoptsparse
 
 This would install pyOptSparse with the built-in optimizers, as well as IPOPT.
-If you wish to use optimizers not packaged by ``conda``, e.g. SNOPT, then you must build the package from source.
+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.
+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>`.
+
+Using an installation script
+----------------------------
+You can build and install pyOptsparse using a `Python script <https://github.com/OpenMDAO/build_pyoptsparse/>`_ developed by the OpenMDAO team.
+For usage, see the instruction on the README of the repo.
+
+This script is particularly useful for installing :ref:`IPOPT<ipopt>` and its dependencies.
+It can also support SNOPT installation if you have access to the SNOPT source code.
 
 Building from source
 --------------------
@@ -37,6 +46,7 @@ The only exception is ``numpy``, which is required as part of the build process
   * In Linux, the python header files (``python-dev``) are also required.
   * **We do not support operating systems other than Linux.**
     For macOS users, the conda package may work out of the box if you do not need any non-default optimizers.
+    Also, the installation script by OpenMDAO likely works on macOS.
     For Windows users, a conda package is on the way, if it's not already in the repos.
     This comes with the same disclaimer as the macOS conda package.
     Alternatively, follow the :ref:`conda build instructions<conda build instruction>` below as this will work on any platform.

doc/optimizers/IPOPT.rst

@@ -1,3 +1,5 @@
+.. _ipopt:
+
 IPOPT
 =====
 IPOPT (Interior Point OPTimizer) is an open source interior point optimizer, designed for large-scale nonlinear optimization.

doc/optimizers/SNOPT.rst

@@ -25,6 +25,9 @@ We currently test v7.7.7 and v7.7.1.
 
 Installation by conda
 *********************
+
+.. _snopt_by_conda:
+
 When installing via conda, all pyoptsparse binaries are pre-compiled and installed as part of the package.
 However, the `snopt` binding module cannot be included as part of the package due to license restrictions.