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Until now, the software building and analysis steps of the pipeline were
intertwined. However, these steps (of how to build a software, and how to
use it) are logically completely independent.
Therefore with this commit, the pipeline now has a new architecture
(particularly in the `reproduce' directory) to emphasize this distinction:
The `reproduce' directory now has the two `software' and `analysis'
subdirectories and the respective parts of the previous architecture have
been broken up between these two based on their function. There is also no
more `src' directory. The `config' directory for software and analysis is
now mixed with the language-specific directories.
Also, some of the software versions were also updated after some checks
with their webpages.
This new architecture will allow much more focused work on each part of the
pipeline (to install the software and to run them for an analysis).
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Until now, the files where the people were meant to change didn't have a
proper copyright notice (for example `Copyright (C) YOUR NAME.'). This was
wrong because the license does not convey copyright ownership. So the name
of the file's original author must always be included and when people
modify it (and add their own copyright-able modifications).
With this commit, the file's original author (and email) are added to the
copyright notice and when more than one person modified a file, both names
have their individual copyright notice.
Based on this, the description for adding a copyright notice in
`README-hacking.md' has also been modified.
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Until now, for short files, we only had a license notice, not an actual
copyright notice. With this commit, a copyright notice has also been
added. We use this new command to find these files, suggested by
`ineiev@gnu.org'.
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In most analysis situations (except for simulations), an input dataset is
necessary, but that part of the pipeline was just left out and a general
`SURVEY' variable was set and never used. So with this commit, we actually
use a sample FITS file from the FITS standard webpage, show it (as well as
its histogram) and do some basic calculations on it.
This preparation of the input datasets is done in a generic way to enable
easy addition of more datasets if necessary.
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