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From lewi...@apache.org
Subject [39/50] [abbrv] git commit: Move docsgit status
Date Thu, 16 Oct 2014 17:17:35 GMT
Move docsgit status


Project: http://git-wip-us.apache.org/repos/asf/climate/repo
Commit: http://git-wip-us.apache.org/repos/asf/climate/commit/37d837f2
Tree: http://git-wip-us.apache.org/repos/asf/climate/tree/37d837f2
Diff: http://git-wip-us.apache.org/repos/asf/climate/diff/37d837f2

Branch: refs/heads/master
Commit: 37d837f2edbab90bd71848f4f73e56a8315c6da2
Parents: ce04f72
Author: Lewis John McGibbney <lewis.j.mcgibbney@jpl.nasa.gov>
Authored: Mon Aug 25 10:56:57 2014 -0700
Committer: Lewis John McGibbney <lewis.j.mcgibbney@jpl.nasa.gov>
Committed: Wed Oct 15 15:18:05 2014 -0700

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 mccsearch/README.md                   |   0
 mccsearch/docs/README.docx            | Bin 0 -> 192118 bytes
 mccsearch/docs/mccsearch.md           |  58 +++++++++++++++++++++++++++++
 mccsearch/docs/mccsearch_workflow.png | Bin 0 -> 132430 bytes
 4 files changed, 58 insertions(+)
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http://git-wip-us.apache.org/repos/asf/climate/blob/37d837f2/mccsearch/README.md
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http://git-wip-us.apache.org/repos/asf/climate/blob/37d837f2/mccsearch/docs/README.docx
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http://git-wip-us.apache.org/repos/asf/climate/blob/37d837f2/mccsearch/docs/mccsearch.md
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+#Graph-based Search for the Identification and Chatacterization of Mesoscale Convective Complexes
+
+##Very Brief Introduction
+If you are in this file it means that you wish to use the mccSearch.py program, or learn
more about it. 
+
+##What is this project about?
+This program searches for a weather feature known as a Mesoscale Convective Complex (MCC)
in gridded infrared and precipitation rate satellite data (MERG and TRMM datasets have been
tested). 
+The data is read from netCDF files into arrays with the dimensions time, latitude, longitude,
value. 
+
+##What is needed?
+ * Python 2.7.4 (We used Anaconda 1.5.1 64 bit libraries, which installed most of the dependencies.)
Other module dependences: 
+ * Nio
+ * netCDF
+ * sciPy
+ * NumPy
+ * Networkx
+ * matplotlib
+ * GrADS (We used OpenGrADS grads2 Version 2.0.1.oga.1)
+ * LATS4D
+
+##Download the source code and store in a folder
+ (1) mccSearch.py contains all the function needed 
+ (2) mccSearchUI.py contains a wizard type Q&A for running the program
+ (3) process.py contains some needed functions (from older version of Apache OCW)
+ (4) file.py contains some needed functions (from older version of Apache OCW)
+ (5) mainProg.py contains a sample of the  general workflow of the order the modules should
be called. There are three main inputs you will have to supply:
+     * mainDirStr : this is the directory where you wish all the output files –images,
textfiles, clipped netCDF files- to be store
+     * TRMMdirName : this is the directory where the original TRMM data in netCDF format
is stored
+     * CEoriDirName : this is the directory where the original MERG data in netCDF format
is stored
+ (6) Store the GrADsScripts folder (and contents) in a separate folder in the same main directory
as the source code folder.  
+
+##Download data in one folder (with only the data files)
+This is a very crude program. The following assumptions are made:
+ (1) input data are in one folder. For MERG data this is CEoriDirName and for the TRMM data
this is TRMMdirName in mainProg.py.  These directories cannot be the same.
+ (2) THERE IS NO FILE CHECKING. So please ensure ALL your files are there in netCDF format.

+ (3)  THERE IS NO FILE ERROR HANDLING. Please ensure that the MERG data and the TRMM data
files are correlated temporally and spatially
+
+##Run mccSearchUI.py
+As a first try to determine the workflow, run the mccSearchUI.py wizard. 
+
+##Configure mainProg.py
+Guidance on the workflow can be seen in the figure below. More details on individual functions
in mccSearch.py can be found in the DocStrings. 
+
+![](./mccsearch_workflow.png)
+The general workflow of the program. The dashed lines indicate optional paths. 
+
+##Run mainProg.py
+Keep your fingers & toes crossed!! Once everything went well, the directory you indicated
where outputs should be stored will be generated, and four folders should appear in it. 
+ * The image folder will store all images generated from plots.
+ * The textFiles folder will store all the text files generated during the run, e.g. cloudElementsUserFile.txt
that contains information about each cloud element identified
+ * The MERGnetcdfCEs folder contains the infrared data in clipped netCDF files that have
been generated for each cloud element identified
+ * The TRMMnetcdfCEs folder contains the precipitation data in clipped netCDF files that
have been generated for each cloud element identified.
+
+##Anticipated future work
+ * Implement functionality for file checking to ensure all files are there
+ * Create a user interface based on mainProg.py. 
+ * Plug the project into the Regional Climate Model Evaluation Database (RCMED) that is available
at Apache OCW. 
+With increased usage, it is anticipated that more metrics and visualizations will be provided.


http://git-wip-us.apache.org/repos/asf/climate/blob/37d837f2/mccsearch/docs/mccsearch_workflow.png
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