# HG changeset patch
# User devteam
# Date 1400517271 14400
# Node ID e9ebd4bfbdfcba7df079158804d12db27857c631

Imported from capsule None

diff -r 000000000000 -r e9ebd4bfbdfc kpca.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/kpca.py	Mon May 19 12:34:31 2014 -0400
@@ -0,0 +1,134 @@
+#!/usr/bin/env python
+
+"""
+Run kernel PCA using kpca() from R 'kernlab' package
+
+usage: %prog [options]
+   -i, --input=i: Input file
+   -o, --output1=o: Summary output
+   -p, --output2=p: Figures output
+   -c, --var_cols=c: Variable columns
+   -k, --kernel=k: Kernel function
+   -f, --features=f: Number of principal components to return
+   -s, --sigma=s: sigma
+   -d, --degree=d: degree
+   -l, --scale=l: scale
+   -t, --offset=t: offset
+   -r, --order=r: order
+
+usage: %prog input output1 output2 var_cols kernel features sigma(or_None) degree(or_None) scale(or_None) offset(or_None) order(or_None)
+"""
+
+import sys, string
+from rpy import *
+import numpy
+from bx.cookbook import doc_optparse
+
+
+def stop_err(msg):
+    sys.stderr.write(msg)
+    sys.exit()
+
+#Parse Command Line
+options, args = doc_optparse.parse( __doc__ )
+#{'options= kernel': 'rbfdot', 'var_cols': '1,2,3,4', 'degree': 'None', 'output2': '/afs/bx.psu.edu/home/gua110/workspace/galaxy_bitbucket/database/files/000/dataset_260.dat', 'output1': '/afs/bx.psu.edu/home/gua110/workspace/galaxy_bitbucket/database/files/000/dataset_259.dat', 'scale': 'None', 'offset': 'None', 'input': '/afs/bx.psu.edu/home/gua110/workspace/galaxy_bitbucket/database/files/000/dataset_256.dat', 'sigma': '1.0', 'order': 'None'}
+
+infile = options.input
+x_cols = options.var_cols.split(',')
+kernel = options.kernel
+outfile = options.output1
+outfile2 = options.output2
+ncomps = int(options.features)
+fout = open(outfile,'w')
+
+elems = []
+for i, line in enumerate( file ( infile )):
+    line = line.rstrip('\r\n')
+    if len( line )>0 and not line.startswith( '#' ):
+        elems = line.split( '\t' )
+        break 
+    if i == 30:
+        break # Hopefully we'll never get here...
+
+if len( elems )<1:
+    stop_err( "The data in your input dataset is either missing or not formatted properly." )
+
+x_vals = []
+
+for k,col in enumerate(x_cols):
+    x_cols[k] = int(col)-1
+    x_vals.append([])
+
+NA = 'NA'
+skipped = 0
+for ind,line in enumerate( file( infile )):
+    if line and not line.startswith( '#' ):
+        try:
+            fields = line.strip().split("\t")
+            for k,col in enumerate(x_cols):
+                try:
+                    xval = float(fields[col])
+                except:
+                    #xval = r('NA')
+                    xval = NaN#
+                x_vals[k].append(xval)
+        except:
+            skipped += 1
+
+x_vals1 = numpy.asarray(x_vals).transpose()
+dat= r.list(array(x_vals1))
+
+print r('library("kernlab")')
+
+try:
+    r.suppressWarnings(r.library('kernlab'))
+except:
+    stop_err('Missing R library kernlab')
+            
+set_default_mode(NO_CONVERSION)
+if kernel=="rbfdot" or kernel=="anovadot":
+    pars = r.list(sigma=float(options.sigma))
+elif kernel=="polydot":
+    pars = r.list(degree=float(options.degree),scale=float(options.scale),offset=float(options.offset))
+elif kernel=="tanhdot":
+    pars = r.list(scale=float(options.scale),offset=float(options.offset))
+elif kernel=="besseldot":
+    pars = r.list(degree=float(options.degree),sigma=float(options.sigma),order=float(options.order))
+elif kernel=="anovadot":
+    pars = r.list(degree=float(options.degree),sigma=float(options.sigma))
+else:
+    pars = r.list()
+    
+try:
+    kpc = r.kpca(x=r.na_exclude(dat), kernel=kernel, kpar=pars, features=ncomps)
+except RException, rex:
+    stop_err("Encountered error while performing kPCA on the input data: %s" %(rex))
+set_default_mode(BASIC_CONVERSION)
+    
+eig = r.eig(kpc)
+pcv = r.pcv(kpc)
+rotated = r.rotated(kpc)
+
+comps = eig.keys()
+eigv = eig.values()
+for i in range(ncomps):
+    eigv[comps.index('Comp.%s' %(i+1))] = eig.values()[i]
+
+print >>fout, "#Component\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
+
+print >>fout, "#Eigenvalue\t%s" %("\t".join(["%.4g" % el for el in eig.values()]))
+    
+print >>fout, "#Principal component vectors\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
+for obs,val in enumerate(pcv):
+    print >>fout, "%s\t%s" %(obs+1, "\t".join(["%.4g" % el for el in val]))
+
+print >>fout, "#Rotated values\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
+for obs,val in enumerate(rotated):
+    print >>fout, "%s\t%s" %(obs+1, "\t".join(["%.4g" % el for el in val]))
+
+r.pdf( outfile2, 8, 8 )
+if ncomps != 1:
+    r.pairs(rotated,labels=r.list(range(1,ncomps+1)),main="Scatterplot of rotated values")
+else:
+    r.plot(rotated, ylab='Comp.1', main="Scatterplot of rotated values")
+r.dev_off()
\ No newline at end of file
diff -r 000000000000 -r e9ebd4bfbdfc kpca.xml
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/kpca.xml	Mon May 19 12:34:31 2014 -0400
@@ -0,0 +1,144 @@
+<tool id="kpca1" name="Kernel Principal Component Analysis" version="1.0.0">
+  <description> </description>
+  <requirements>
+    <requirement type="package" version="1.0.3">rpy</requirement>
+    <requirement type="package" version="2.11.0">R</requirement>
+    <requirement type="package" version="0.1-4">kernlab</requirement>
+    <requirement type="package" version="1.7.1">numpy</requirement>
+    <requirement type="package" version="0.7.1">bx-python</requirement>
+  </requirements>
+  <command interpreter="python">
+    kpca.py 
+      --input=$input1
+      --output1=$out_file1
+      --output2=$out_file2
+      --var_cols=$var_cols
+      --kernel=$kernelChoice.kernel
+      --features=$features
+      #if $kernelChoice.kernel == "rbfdot" or $kernelChoice.kernel == "anovadot":
+      --sigma=$kernelChoice.sigma
+      --degree="None"
+      --scale="None"
+      --offset="None"
+      --order="None"
+      #elif $kernelChoice.kernel == "polydot":
+      --sigma="None"
+      --degree=$kernelChoice.degree
+      --scale=$kernelChoice.scale
+      --offset=$kernelChoice.offset
+      --order="None"
+      #elif $kernelChoice.kernel == "tanhdot":
+      --sigma="None"
+      --degree="None"
+      --scale=$kernelChoice.scale
+      --offset=$kernelChoice.offset
+      --order="None"
+      #elif $kernelChoice.kernel == "besseldot":
+      --sigma=$kernelChoice.sigma
+      --degree=$kernelChoice.degree
+      --scale="None"
+      --offset="None"
+      --order=$kernelChoice.order
+      #elif $kernelChoice.kernel == "anovadot":
+      --sigma=$kernelChoice.sigma
+      --degree=$kernelChoice.degree
+      --scale="None"
+      --offset="None"
+      --order="None"
+      #else:
+      --sigma="None"
+      --degree="None"
+      --scale="None"
+      --offset="None"
+      --order="None"
+      #end if
+  </command>
+  <inputs>
+    <param format="tabular" name="input1" type="data" label="Select data" help="Dataset missing? See TIP below."/>
+    <param name="var_cols" label="Select columns containing input variables " type="data_column" data_ref="input1" numerical="True" multiple="true" >
+        <validator type="no_options" message="Please select at least one column."/>
+    </param>
+    <param name="features" size="10" type="integer" value="2" label="Number of principal components to return" help="To return all, enter 0"/>
+    <conditional name="kernelChoice">
+        <param name="kernel" type="select" label="Kernel function">
+            <option value="rbfdot" selected="true">Gaussian Radial Basis Function</option>
+            <option value="polydot">Polynomial</option>
+            <option value="vanilladot">Linear</option>
+            <option value="tanhdot">Hyperbolic</option>
+            <option value="laplacedot">Laplacian</option>
+            <option value="besseldot">Bessel</option>
+            <option value="anovadot">ANOVA Radial Basis Function</option>
+            <option value="splinedot">Spline</option>
+        </param>
+        <when value="vanilladot" />
+        <when value="splinedot" />
+        <when value="rbfdot">
+            <param name="sigma" size="10" type="float" value="1" label="sigma (inverse kernel width)" />
+        </when>
+        <when value="laplacedot">
+            <param name="sigma" size="10" type="float" value="1" label="sigma (inverse kernel width)" />
+        </when>
+        <when value="polydot">
+            <param name="degree" size="10" type="integer" value="1" label="degree" />
+            <param name="scale" size="10" type="integer" value="1" label="scale" />
+            <param name="offset" size="10" type="integer" value="1" label="offset" />
+        </when>
+        <when value="tanhdot">
+            <param name="scale" size="10" type="integer" value="1" label="scale" />
+            <param name="offset" size="10" type="integer" value="1" label="offset" />
+        </when>
+        <when value="besseldot">
+            <param name="sigma" size="10" type="integer" value="1" label="sigma" />
+            <param name="order" size="10" type="integer" value="1" label="order" />
+            <param name="degree" size="10" type="integer" value="1" label="degree" />
+        </when>
+        <when value="anovadot">
+            <param name="sigma" size="10" type="integer" value="1" label="sigma" />
+            <param name="degree" size="10" type="integer" value="1" label="degree" />
+        </when>
+    </conditional>    
+  </inputs>
+  <outputs>
+    <data format="input" name="out_file1" metadata_source="input1" />
+    <data format="pdf" name="out_file2" />
+  </outputs>
+  <tests>
+    <test>
+        <param name="input1" value="iris.tabular"/>
+        <param name="var_cols" value="1,2,3,4"/>
+        <param name="kernel" value="polydot"/>
+        <param name="features" value="2"/>
+        <param name="offset" value="0"/>
+        <param name="scale" value="1"/>
+        <param name="degree" value="2"/>
+        <output name="out_file1" file="kpca_out1.tabular"/>
+        <output name="out_file2" file="kpca_out2.pdf"/>
+    </test>
+  </tests>
+  <help>
+
+
+.. class:: infomark
+
+**TIP:** If your data is not TAB delimited, use *Edit Datasets-&gt;Convert characters*
+
+-----
+
+.. class:: infomark
+
+**What it does**
+
+This tool uses functions from 'kernlab' library from R statistical package to perform Kernel Principal Component Analysis (kPCA) on the input data. It outputs two files, one containing the summary statistics of the performed kPCA, and the other containing a scatterplot matrix of rotated values reported by kPCA.   
+
+*Alexandros Karatzoglou, Alex Smola, Kurt Hornik, Achim Zeileis (2004). kernlab - An S4 Package for Kernel Methods in R. Journal of Statistical Software 11(9), 1-20. URL http://www.jstatsoft.org/v11/i09/*
+
+-----
+
+.. class:: warningmark
+
+**Note**
+
+This tool currently treats all variables as continuous numeric variables. Running the tool on categorical variables might result in incorrect results. Rows containing non-numeric (or missing) data in any of the chosen columns will be skipped from the analysis.
+
+  </help>
+</tool>
diff -r 000000000000 -r e9ebd4bfbdfc test-data/1.tabular
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/1.tabular	Mon May 19 12:34:31 2014 -0400
@@ -0,0 +1,6 @@
+chr22	1000	NM_17
+chr22	2000	NM_18
+chr10	2200	NM_10
+chr10	hap	test
+chr10	1200	NM_11
+chr22	1600	NM_19
\ No newline at end of file
diff -r 000000000000 -r e9ebd4bfbdfc test-data/iris.tabular
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/iris.tabular	Mon May 19 12:34:31 2014 -0400
@@ -0,0 +1,151 @@
+5.1	3.5	1.4	0.2	Iris-setosa
+4.9	3.0	1.4	0.2	Iris-setosa
+4.7	3.2	1.3	0.2	Iris-setosa
+4.6	3.1	1.5	0.2	Iris-setosa
+5.0	3.6	1.4	0.2	Iris-setosa
+5.4	3.9	1.7	0.4	Iris-setosa
+4.6	3.4	1.4	0.3	Iris-setosa
+5.0	3.4	1.5	0.2	Iris-setosa
+4.4	2.9	1.4	0.2	Iris-setosa
+4.9	3.1	1.5	0.1	Iris-setosa
+5.4	3.7	1.5	0.2	Iris-setosa
+4.8	3.4	1.6	0.2	Iris-setosa
+4.8	3.0	1.4	0.1	Iris-setosa
+4.3	3.0	1.1	0.1	Iris-setosa
+5.8	4.0	1.2	0.2	Iris-setosa
+5.7	4.4	1.5	0.4	Iris-setosa
+5.4	3.9	1.3	0.4	Iris-setosa
+5.1	3.5	1.4	0.3	Iris-setosa
+5.7	3.8	1.7	0.3	Iris-setosa
+5.1	3.8	1.5	0.3	Iris-setosa
+5.4	3.4	1.7	0.2	Iris-setosa
+5.1	3.7	1.5	0.4	Iris-setosa
+4.6	3.6	1.0	0.2	Iris-setosa
+5.1	3.3	1.7	0.5	Iris-setosa
+4.8	3.4	1.9	0.2	Iris-setosa
+5.0	3.0	1.6	0.2	Iris-setosa
+5.0	3.4	1.6	0.4	Iris-setosa
+5.2	3.5	1.5	0.2	Iris-setosa
+5.2	3.4	1.4	0.2	Iris-setosa
+4.7	3.2	1.6	0.2	Iris-setosa
+4.8	3.1	1.6	0.2	Iris-setosa
+5.4	3.4	1.5	0.4	Iris-setosa
+5.2	4.1	1.5	0.1	Iris-setosa
+5.5	4.2	1.4	0.2	Iris-setosa
+4.9	3.1	1.5	0.1	Iris-setosa
+5.0	3.2	1.2	0.2	Iris-setosa
+5.5	3.5	1.3	0.2	Iris-setosa
+4.9	3.1	1.5	0.1	Iris-setosa
+4.4	3.0	1.3	0.2	Iris-setosa
+5.1	3.4	1.5	0.2	Iris-setosa
+5.0	3.5	1.3	0.3	Iris-setosa
+4.5	2.3	1.3	0.3	Iris-setosa
+4.4	3.2	1.3	0.2	Iris-setosa
+5.0	3.5	1.6	0.6	Iris-setosa
+5.1	3.8	1.9	0.4	Iris-setosa
+4.8	3.0	1.4	0.3	Iris-setosa
+5.1	3.8	1.6	0.2	Iris-setosa
+4.6	3.2	1.4	0.2	Iris-setosa
+5.3	3.7	1.5	0.2	Iris-setosa
+5.0	3.3	1.4	0.2	Iris-setosa
+7.0	3.2	4.7	1.4	Iris-versicolor
+6.4	3.2	4.5	1.5	Iris-versicolor
+6.9	3.1	4.9	1.5	Iris-versicolor
+5.5	2.3	4.0	1.3	Iris-versicolor
+6.5	2.8	4.6	1.5	Iris-versicolor
+5.7	2.8	4.5	1.3	Iris-versicolor
+6.3	3.3	4.7	1.6	Iris-versicolor
+4.9	2.4	3.3	1.0	Iris-versicolor
+6.6	2.9	4.6	1.3	Iris-versicolor
+5.2	2.7	3.9	1.4	Iris-versicolor
+5.0	2.0	3.5	1.0	Iris-versicolor
+5.9	3.0	4.2	1.5	Iris-versicolor
+6.0	2.2	4.0	1.0	Iris-versicolor
+6.1	2.9	4.7	1.4	Iris-versicolor
+5.6	2.9	3.6	1.3	Iris-versicolor
+6.7	3.1	4.4	1.4	Iris-versicolor
+5.6	3.0	4.5	1.5	Iris-versicolor
+5.8	2.7	4.1	1.0	Iris-versicolor
+6.2	2.2	4.5	1.5	Iris-versicolor
+5.6	2.5	3.9	1.1	Iris-versicolor
+5.9	3.2	4.8	1.8	Iris-versicolor
+6.1	2.8	4.0	1.3	Iris-versicolor
+6.3	2.5	4.9	1.5	Iris-versicolor
+6.1	2.8	4.7	1.2	Iris-versicolor
+6.4	2.9	4.3	1.3	Iris-versicolor
+6.6	3.0	4.4	1.4	Iris-versicolor
+6.8	2.8	4.8	1.4	Iris-versicolor
+6.7	3.0	5.0	1.7	Iris-versicolor
+6.0	2.9	4.5	1.5	Iris-versicolor
+5.7	2.6	3.5	1.0	Iris-versicolor
+5.5	2.4	3.8	1.1	Iris-versicolor
+5.5	2.4	3.7	1.0	Iris-versicolor
+5.8	2.7	3.9	1.2	Iris-versicolor
+6.0	2.7	5.1	1.6	Iris-versicolor
+5.4	3.0	4.5	1.5	Iris-versicolor
+6.0	3.4	4.5	1.6	Iris-versicolor
+6.7	3.1	4.7	1.5	Iris-versicolor
+6.3	2.3	4.4	1.3	Iris-versicolor
+5.6	3.0	4.1	1.3	Iris-versicolor
+5.5	2.5	4.0	1.3	Iris-versicolor
+5.5	2.6	4.4	1.2	Iris-versicolor
+6.1	3.0	4.6	1.4	Iris-versicolor
+5.8	2.6	4.0	1.2	Iris-versicolor
+5.0	2.3	3.3	1.0	Iris-versicolor
+5.6	2.7	4.2	1.3	Iris-versicolor
+5.7	3.0	4.2	1.2	Iris-versicolor
+5.7	2.9	4.2	1.3	Iris-versicolor
+6.2	2.9	4.3	1.3	Iris-versicolor
+5.1	2.5	3.0	1.1	Iris-versicolor
+5.7	2.8	4.1	1.3	Iris-versicolor
+6.3	3.3	6.0	2.5	Iris-virginica
+5.8	2.7	5.1	1.9	Iris-virginica
+7.1	3.0	5.9	2.1	Iris-virginica
+6.3	2.9	5.6	1.8	Iris-virginica
+6.5	3.0	5.8	2.2	Iris-virginica
+7.6	3.0	6.6	2.1	Iris-virginica
+4.9	2.5	4.5	1.7	Iris-virginica
+7.3	2.9	6.3	1.8	Iris-virginica
+6.7	2.5	5.8	1.8	Iris-virginica
+7.2	3.6	6.1	2.5	Iris-virginica
+6.5	3.2	5.1	2.0	Iris-virginica
+6.4	2.7	5.3	1.9	Iris-virginica
+6.8	3.0	5.5	2.1	Iris-virginica
+5.7	2.5	5.0	2.0	Iris-virginica
+5.8	2.8	5.1	2.4	Iris-virginica
+6.4	3.2	5.3	2.3	Iris-virginica
+6.5	3.0	5.5	1.8	Iris-virginica
+7.7	3.8	6.7	2.2	Iris-virginica
+7.7	2.6	6.9	2.3	Iris-virginica
+6.0	2.2	5.0	1.5	Iris-virginica
+6.9	3.2	5.7	2.3	Iris-virginica
+5.6	2.8	4.9	2.0	Iris-virginica
+7.7	2.8	6.7	2.0	Iris-virginica
+6.3	2.7	4.9	1.8	Iris-virginica
+6.7	3.3	5.7	2.1	Iris-virginica
+7.2	3.2	6.0	1.8	Iris-virginica
+6.2	2.8	4.8	1.8	Iris-virginica
+6.1	3.0	4.9	1.8	Iris-virginica
+6.4	2.8	5.6	2.1	Iris-virginica
+7.2	3.0	5.8	1.6	Iris-virginica
+7.4	2.8	6.1	1.9	Iris-virginica
+7.9	3.8	6.4	2.0	Iris-virginica
+6.4	2.8	5.6	2.2	Iris-virginica
+6.3	2.8	5.1	1.5	Iris-virginica
+6.1	2.6	5.6	1.4	Iris-virginica
+7.7	3.0	6.1	2.3	Iris-virginica
+6.3	3.4	5.6	2.4	Iris-virginica
+6.4	3.1	5.5	1.8	Iris-virginica
+6.0	3.0	4.8	1.8	Iris-virginica
+6.9	3.1	5.4	2.1	Iris-virginica
+6.7	3.1	5.6	2.4	Iris-virginica
+6.9	3.1	5.1	2.3	Iris-virginica
+5.8	2.7	5.1	1.9	Iris-virginica
+6.8	3.2	5.9	2.3	Iris-virginica
+6.7	3.3	5.7	2.5	Iris-virginica
+6.7	3.0	5.2	2.3	Iris-virginica
+6.3	2.5	5.0	1.9	Iris-virginica
+6.5	3.0	5.2	2.0	Iris-virginica
+6.2	3.4	5.4	2.3	Iris-virginica
+5.9	3.0	5.1	1.8	Iris-virginica
+
diff -r 000000000000 -r e9ebd4bfbdfc test-data/kpca_out1.tabular
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/kpca_out1.tabular	Mon May 19 12:34:31 2014 -0400
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diff -r 000000000000 -r e9ebd4bfbdfc test-data/kpca_out2.pdf
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/kpca_out2.pdf	Mon May 19 12:34:31 2014 -0400
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diff -r 000000000000 -r e9ebd4bfbdfc test-data/pca_out1.tabular
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/pca_out1.tabular	Mon May 19 12:34:31 2014 -0400
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diff -r 000000000000 -r e9ebd4bfbdfc tool_dependencies.xml
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/tool_dependencies.xml	Mon May 19 12:34:31 2014 -0400
@@ -0,0 +1,18 @@
+<?xml version="1.0"?>
+<tool_dependency>
+  <package name="rpy" version="1.0.3">
+      <repository changeset_revision="82170c94ca7c" name="package_rpy_1_0_3" owner="devteam" toolshed="http://toolshed.g2.bx.psu.edu" />
+    </package>
+    <package name="R" version="2.11.0">
+      <repository changeset_revision="5824d2b3bc8b" name="package_r_2_11_0" owner="devteam" toolshed="http://toolshed.g2.bx.psu.edu" />
+    </package>
+    <package name="numpy" version="1.7.1">
+      <repository changeset_revision="0c288abd2a1e" name="package_numpy_1_7" owner="devteam" toolshed="http://toolshed.g2.bx.psu.edu" />
+    </package>
+    <package name="bx-python" version="0.7.1">
+      <repository changeset_revision="2d0c08728bca" name="package_bx_python_0_7" owner="devteam" toolshed="http://toolshed.g2.bx.psu.edu" />
+    </package>
+    <package name="kernlab" version="0.1-4">
+      <repository changeset_revision="ea1da94c31c2" name="package_cran_kernlab_0_1_4" owner="devteam" toolshed="http://toolshed.g2.bx.psu.edu" />
+    </package>
+</tool_dependency>