[GRASS-SVN] r67109 - grass-addons/grass7/vector/v.mrmr
svn_grass at osgeo.org
svn_grass at osgeo.org
Sun Dec 13 20:24:22 PST 2015
Author: spawley
Date: 2015-12-13 20:24:22 -0800 (Sun, 13 Dec 2015)
New Revision: 67109
Removed:
grass-addons/grass7/vector/v.mrmr/Makefile
grass-addons/grass7/vector/v.mrmr/v.mrmr.html
grass-addons/grass7/vector/v.mrmr/v.mrmr.py
Log:
Deleted: grass-addons/grass7/vector/v.mrmr/Makefile
===================================================================
--- grass-addons/grass7/vector/v.mrmr/Makefile 2015-12-14 04:12:04 UTC (rev 67108)
+++ grass-addons/grass7/vector/v.mrmr/Makefile 2015-12-14 04:24:22 UTC (rev 67109)
@@ -1,7 +0,0 @@
-MODULE_TOPDIR = ../..
-
-PGM = v.mrmr
-
-include $(MODULE_TOPDIR)/include/Make/Script.make
-
-default: script
Deleted: grass-addons/grass7/vector/v.mrmr/v.mrmr.html
===================================================================
--- grass-addons/grass7/vector/v.mrmr/v.mrmr.html 2015-12-14 04:12:04 UTC (rev 67108)
+++ grass-addons/grass7/vector/v.mrmr/v.mrmr.html 2015-12-14 04:24:22 UTC (rev 67109)
@@ -1,53 +0,0 @@
-<h2>DESCRIPTION</h2>
-
-<em><b>v.mrmr</b></em> is a simple GUI for exporting data to the Minimum
-Redundancy Maximum Relevance (mRMR) feature selection command line tool
-(Peng et al., 2005). mRMR is designed to select features that have the
-maximal statistical "dependency" on the classification variable, while
-simultaneously minimizing the redundancy among the selected features.
-
-<h2>NOTES</h2>
-
-<p>The command line tool needs to be installed separately in a
-location that is recognized by the system or in the PATH. The command
-line tool can be installed on windows (binaries available), linux and OS
-X (needs compilation). Installation instructions are provided on <a
-href="http://penglab.janelia.org/proj/mRMR/">Peng's Website</a>.
-
-<p>The module requires data within a vector attribute table to be
-arranged in a specific order. The classification variable (i.e., class
-labels) need to be in the first column, except for the cat attribute
-which is not exported. The class label also needs to be in numerical
-form, i.e., 1, 2, 3.... rather than 'forest' or 'urban'.
-
-<p>The algorithm outputs a tab-separated list of attributes, ranked
-by the most important feature first. The <i> method </i> parameter
-allows a choice between the Maximum Information Difference (MID) and
-Mutual Information Quotient (MIQ) feature evaluation criteria, which
-respectively represent the relevancy and redundancy of the features. The
-algorithm also shows the ranking of the features based on the
-conventional maximum relevance method. Additional user options include
-<i>nfeatures</i> which specifies the number of features that you want to
-select; <i>nsamples</i> limits the maximum number of samples to base the
-feature selection, and <i>maxvar</i> limits the maximum number of
-attributes, both of which can therefore reduce the computation for very
-large datasets. <i>threshold</i> is the discretization threshold to
-apply to the continuous variable data, i.e., mean +/- threshold *
-standard deviation. <i> layer </i> is the attribute layer to be used in
-the feature selection process.
-
-<h2>EXAMPLE</h2>
-
-v.mrmr.py vector=vector_layer layer=1 thres=1.0
-nfeatures=50 nsamples=10000 maxvar=10000 method=MID
-
-<h2>REFERENCES</h2>
-
-Peng, H.; Fulmi Long; Ding, C., "Feature selection
-based on mutual information criteria of max-dependency, max-relevance,
-and min-redundancy," in Pattern Analysis and Machine Intelligence, IEEE
-Transactions on , vol.27, no.8, pp.1226-1238, Aug. 2005
-
-<h2>AUTHOR</h2>
-
-Steven Pawley <br><i>Last changed: Saturday 12 December 2015</i>
\ No newline at end of file
Deleted: grass-addons/grass7/vector/v.mrmr/v.mrmr.py
===================================================================
--- grass-addons/grass7/vector/v.mrmr/v.mrmr.py 2015-12-14 04:12:04 UTC (rev 67108)
+++ grass-addons/grass7/vector/v.mrmr/v.mrmr.py 2015-12-14 04:24:22 UTC (rev 67109)
@@ -1,122 +0,0 @@
-#!/usr/bin/env python
-#
-##############################################################################
-#
-# MODULE: Minimum Redundancy Maximum Relevance Feature Selection
-#
-# AUTHOR(S): Steven Pawley
-#
-##############################################################################
-#%module
-#% description: Perform Minimum Redundancy Maximum Relevance Feature Selection on a GRASS Attribute Table
-#%end
-
-#%option G_OPT_V_INPUT
-#% description: Vector features
-#% key: table
-#% required : yes
-#%end
-
-#%option G_OPT_V_FIELD
-#% key: layer
-#% required : yes
-#%end
-
-#%option
-#% description: Discretization threshold
-#% key: threshold
-#% type: double
-#% answer: 1.0
-#% required : no
-#% guisection: Options
-#%end
-
-#%option
-#% description: Number of features (attributes)
-#% key: nfeatures
-#% type: integer
-#% answer: 50
-#% required : yes
-#% guisection: Options
-#%end
-
-#%option
-#% description: Maximum number of samples
-#% key: nsamples
-#% type: integer
-#% answer: 1000
-#% required : yes
-#% guisection: Options
-#%end
-
-#%option
-#% description: Maximum number of variables/attributes
-#% key: maxvar
-#% type: integer
-#% answer: 10000
-#% required : yes
-#% guisection: Options
-#%end
-
-#%option
-#% description: Feature selection method
-#% key: method
-#% type: string
-#% options: MID,MIQ
-#% answer: MID
-#% required : yes
-#% guisection: Options
-#%end
-
-import sys
-import os
-import subprocess
-import shutil
-
-import grass.script as grass
-import tempfile
-import atexit
-import os.path
-
-# env = grass.gisenv()
-# gisdbase = env['GISDBASE']
-# location = env['LOCATION_NAME']
-# mapset = env['MAPSET']
-# path = os.path.join(gisdbase, location, mapset, 'sqlite.db')
-
-tmpdir = tempfile.mkdtemp()
-tmptable = "mrmrdat.csv"
-
-def cleanup():
- shutil.rmtree(tmpdir)
- return 0
-
-def main():
- table = options['table']
- layer = options['layer']
- threshold = options['threshold']
- nfeatures = options['nfeatures']
- maxvar = options['maxvar']
- nsamples = options['nsamples']
- method = options['method']
-
- os.chdir(tmpdir)
-
- grass.run_command("v.out.ogr",
- input = table,
- layer= layer,
- type = 'auto',
- output = tmpdir + '/' + tmptable,
- format = 'CSV',
- flags = 's')
-
- mrmrcmd = 'mrmr -i ' + tmptable +' -m ' + method + ' -t ' + threshold + ' -n ' + nfeatures + ' -s ' + nsamples + ' -v ' + maxvar
-
- subprocess.call(mrmrcmd, shell=True)
-
- return 0
-
-if __name__ == "__main__":
- options, flags = grass.parser()
- atexit.register(cleanup)
- sys.exit(main())
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