[yt-svn] commit/yt-doc: 3 new changesets

[Bitbucket]

3 new commits in yt-doc:

https://bitbucket.org/yt_analysis/yt-doc/commits/00572a4b2e0f/
changeset:   00572a4b2e0f
user:        chummels
date:        2013-02-16 01:17:38
summary:     Merged yt_analysis/yt-doc into default
affected #:  1 file

diff -r 89f4db1b6ff95b7f044cb894c0e6a97ea1b0ab9e -r 00572a4b2e0f799249f4d3026776ee4b5c0e02d8 source/api/api.rst
--- a/source/api/api.rst
+++ b/source/api/api.rst
@@ -395,6 +395,7 @@
    ~yt.visualization.image_writer.strip_colormap_data
    ~yt.visualization.image_writer.splat_points
    ~yt.visualization.image_writer.annotate_image
+   ~yt.visualization.image_writer.scale_image
 
 We also provide a module that is very good for generating EPS figures,
 particularly with complicated layouts.


https://bitbucket.org/yt_analysis/yt-doc/commits/df8f1eb9c75e/
changeset:   df8f1eb9c75e
user:        chummels
date:        2013-02-16 02:28:32
summary:     Merged yt_analysis/yt-doc into default
affected #:  0 files



https://bitbucket.org/yt_analysis/yt-doc/commits/671b010e4f51/
changeset:   671b010e4f51
user:        chummels
date:        2013-02-16 04:13:16
summary:     Modifying the parallel docs a bit to elaborate more on basic usage.
affected #:  1 file

diff -r df8f1eb9c75eaf83b50b2fbe820997da354b7c9f -r 671b010e4f51d170d7a44612fcf2357d88786531 source/advanced/parallel_computation.rst
--- a/source/advanced/parallel_computation.rst
+++ b/source/advanced/parallel_computation.rst
@@ -13,8 +13,7 @@
 Capabilities
 ------------
 
-Currently, YT is able to
-perform the following actions in parallel:
+Currently, YT is able to perform the following actions in parallel:
 
  * Projections (:ref:`projection-plots`)
  * Slices (:ref:`slice-plots`)
@@ -39,10 +38,60 @@
 
 To run scripts in parallel, you must first install
 `mpi4py <http://code.google.com/p/mpi4py>`_.
-Instructions for doing so are provided on the mpi4py website.  Once that has
-been accomplished, you're all done!  You just need to launch your scripts with
-``mpirun`` (or equivalent) and signal to YT
-that you want to run them in parallel.
+Instructions for doing so are provided on the mpi4py website, but you may
+have luck by just running: 
+
+.. code-block:: bash
+
+    $ pip install mpi4py
+
+Once that has been installed, you're all done!  You just need to launch your 
+scripts with ``mpirun`` (or equivalent) and signal to YT that you want to run 
+them in parallel.  In general, that's all it takes to get a speed benefit on a 
+multi-core machine.  Here is an example on an 8-core desktop:
+
+.. code-block:: bash
+
+    $ mpirun -np 8 python script.py --parallel
+
+Throughout its normal operation, yt keeps you aware of what is happening with
+regular messages to the stderr usually prefaced with: 
+
+.. code-block:: bash
+
+    yt : [INFO   ] YYY-MM-DD HH:MM:SS
+
+However, when operating in parallel mode, yt outputs information from each
+of your processors to this log mode, as in:
+
+.. code-block:: bash
+
+    P000 yt : [INFO   ] YYY-MM-DD HH:MM:SS
+    P001 yt : [INFO   ] YYY-MM-DD HH:MM:SS
+
+in the case of two cores being used.
+
+It's important to note that all of the processes listed in `capabilities` work
+-- and no additional work is necessary to parallelize those processes.
+Furthermore, the ``yt`` command itself recognizes the ``--parallel`` option, so
+those commands will work in parallel as well.
+
+The Derived Quantities and Profile objects must both have the ``lazy_reader``
+option set to ``True`` when they are instantiated.  What this does is to
+operate on a grid-by-grid decomposed basis.  In ``yt`` version 1.5 and the
+trunk, this has recently been set to be the default.
+
+.. warning:: If you manually interact with the filesystem, not through YT, you
+   will have to ensure that you only execute your functions on the root
+   processor.  You can do this with the function :func:`only_on_root`.
+
+yt.pmods
+--------
+
+yt.pmods is a replacement module for yt.mods, which can be enabled in
+the ``from yt.mods import *`` calls in yt scripts.  It should enable 
+more efficient use of parallel filesystems, if you are running on such a 
+system.
 
 For instance, the following script, which we'll save as ``my_script.py``:
 
@@ -55,35 +104,19 @@
    p = ProjectionPlot(pf, "x", "Density")
    p.save()
 
-Will execute the finding of the maximum density and the projection in parallel
-if launched in parallel.
-Note that the usual ``from yt.mods import *`` has been replaced by 
-``from yt.pmods import *``.
-The pmods option gives the same result as reglar mods, but it can speed up
-the initialization process when running in parallel.
-To do so, at the command line you would execute
+will execute the finding of the maximum density and the projection in parallel
+if launched in parallel.  Note that the usual ``from yt.mods import *`` has 
+been replaced by ``from yt.pmods import *``.
+To run this script at the command line you would execute:
 
 .. code-block:: bash
 
    $ mpirun -np 16 python2.7 my_script.py --parallel
 
-if you wanted it to run in parallel.  If you run into problems, the you can use
+if you wanted it to run in parallel on 16 cores (you can always the number of 
+cores you want to run on).  If you run into problems, the you can use
 :ref:`remote-debugging` to examine what went wrong.
 
-.. warning:: If you manually interact with the filesystem, not through YT, you
-   will have to ensure that you only execute your functions on the root
-   processor.  You can do this with the function :func:`only_on_root`.
-
-It's important to note that all of the processes listed in `capabilities` work
--- and no additional work is necessary to parallelize those processes.
-Furthermore, the ``yt`` command itself recognizes the ``--parallel`` option, so
-those commands will work in parallel as well.
-
-The Derived Quantities and Profile objects must both have the ``lazy_reader``
-option set to ``True`` when they are instantiated.  What this does is to
-operate on a grid-by-grid decomposed basis.  In ``yt`` version 1.5 and the
-trunk, this has recently been set to be the default.
-
 Types of Parallelism
 --------------------

Repository URL: https://bitbucket.org/yt_analysis/yt-doc/

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