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Merge pull request #646 from enthought/feature/update-docs-for-0.6
Update docs for 0.6
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docs/sphinx/source/build-the-docs.rst

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Dependencies to build the documentation:
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* Sphinx
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* sphinxcontrib.napoleon
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* Sphinx >= 1.3
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* sphinxcontrib.programoutput
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If you have the dependencies listed above, and you want to build the

docs/sphinx/source/conf.py

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# -- General configuration -----------------------------------------------------
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# If your documentation needs a minimal Sphinx version, state it here.
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needs_sphinx = '1.3'
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needs_sphinx = '1.3' # so we have sphinx.ext.napoleon
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# otherwise you could install and use
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# sphinxcontrib.napoleon
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# Add any Sphinx extension module names here, as strings. They can be extensions
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# coming with Sphinx (named 'sphinx.ext.*') or your custom ones.

docs/sphinx/source/environment-modules-notes.rst

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Notes on building environment-modules
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=====================================
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Update 2015-10-05
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-----------------
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Below are Mark Kness' notes on building and using ``environment-modules``. I
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have since found lmod_ to be a slightly better documented and supported
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alternative.
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- Bob Grant
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.. _lmod: https://www.tacc.utexas.edu/research-development/tacc-projects/lmod
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Environment Modules
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-------------------
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environment-modules is a tool, written with Tcl, that makes it convenient to
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switch environment settings. It is not required to use DistArray, but we find
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it useful in development. It is a difficult name to google. I had to build it

docs/sphinx/source/getting-started.rst

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To see some examples of what DistArray can do, check out our IPython notebooks
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on nbviewer (also in the ``examples`` directory of the DistArray source).
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* `DistArray Features <http://nbviewer.ipython.org/github/enthought/distarray/blob/master/examples/features.ipynb>`_
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* `DistArray Features <http://nbviewer.ipython.org/github/enthought/distarray/blob/master/examples/features.ipynb>`_
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* `Seismic Volume <http://nbviewer.ipython.org/github/enthought/distarray/blob/master/examples/seismic_volume/seismic_volume.ipynb>`_
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* `Julia Set <http://nbviewer.ipython.org/github/enthought/distarray/blob/master/examples/julia_set/julia_set.ipynb>`_
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* `Gaussian Elimination <http://nbviewer.ipython.org/github/enthought/distarray/blob/master/examples/gauss_elimination/ge_notebook.ipynb>`_

docs/sphinx/source/hdf5-notes.rst

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Building HDF5 and h5py for DistArray
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====================================
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If you want to use DistArray's parallel IO capabilities on HDF5 files,
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parallel-enabled HDF5 and h5py installations are required. Unfortunately,
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installing these can be somewhat of a pain.
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Update 2015-10-05
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-----------------
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The "Original Notes" below are pretty old at this point. Recently I have had
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success installing a parallel-enabled HDF5 (1.8.15) using Homebrew on OS X::
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$ brew install hdf5 --with-mpi
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The instructions for building ``h5py`` on top of a parallel hdf5 have also
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changed, but are available
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`here <http://docs.h5py.org/en/latest/mpi.html#building-against-parallel-hdf5>`_.
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Original Notes
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--------------
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These are notes from trying to build HDF5 1.8.12 and h5py 2.2.1 against mpi4py
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1.3 and openmpi-1.6.5 on OS X 10.8.5.
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This gives me an error about "MPI Message" addressed here::
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https://github.com/h5py/h5py/issues/401
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After patching api_compat.h as suggested, it builds. One could also use the
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``master`` version of h5py from GitHub instead of the latest release.
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docs/sphinx/source/history.rst

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-------
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DistArray was started by Brian Granger in 2008 and is currently being developed
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at Enthought by a team led by Kurt Smith, in partnership with Bill Spotz from
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Sandia's (Py)Trilinos project and Brian Granger and Min RK from the IPython
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project.
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by Enthought in partnership with Bill Spotz from Sandia's (Py)Trilinos project
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and Brian Granger and Min RK from the IPython project.

docs/sphinx/source/installation.rst

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DistArray requires the following Python libraries:
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* `NumPy`_,
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* `IPython`_, and
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* `Mpi4Py`_.
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* `numpy`_,
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* `ipyparallel`_, and
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* `mpi4py`_.
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.. _NumPy: http://www.numpy.org
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.. _IPython: http://ipython.org
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.. _Mpi4Py: http://mpi4py.scipy.org
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.. _numpy: http://www.numpy.org
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.. _ipyparallel: https://github.com/ipython/ipyparallel
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.. _mpi4py: http://mpi4py.scipy.org
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Optionally, DistArray can make use of:
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pip install distarray
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Experimental conda-quickstart
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-----------------------------
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Alternatively, we have an experimental `conda-quickstart` script in the
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``quickstart`` directory of the root of this source tree. Given an Anaconda
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installation, this script will attempt to install create a conda environment
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for you, installing MPI, mpi4py, and the above Python dependencies as
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necessary. See ``README.rst`` in that directory for more information.
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Testing Your Installation
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-------------------------
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To test your installation, you will first need to start an IPython.parallel
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cluster with MPI enabled. The easist way is to use use the ``dacluster``
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command that comes with DistArray::
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cluster with MPI enabled. The easist way is to use the ``dacluster`` command
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that comes with DistArray::
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dacluster start
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See ``dacluster``'s help for more::
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dacluster --help
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You should then be able to run all the tests from the DistArray source

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