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1 #!/usr/bin/env python
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2
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3 """
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4 Run kernel PCA using kpca() from R 'kernlab' package
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5
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6 usage: %prog [options]
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7 -i, --input=i: Input file
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8 -o, --output1=o: Summary output
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9 -p, --output2=p: Figures output
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10 -c, --var_cols=c: Variable columns
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11 -k, --kernel=k: Kernel function
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12 -f, --features=f: Number of principal components to return
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13 -s, --sigma=s: sigma
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14 -d, --degree=d: degree
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15 -l, --scale=l: scale
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16 -t, --offset=t: offset
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17 -r, --order=r: order
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18
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19 usage: %prog input output1 output2 var_cols kernel features sigma(or_None) degree(or_None) scale(or_None) offset(or_None) order(or_None)
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20 """
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21
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22 import sys, string
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23 from rpy import *
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24 import numpy
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25 from bx.cookbook import doc_optparse
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26
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27
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28 def stop_err(msg):
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29 sys.stderr.write(msg)
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30 sys.exit()
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31
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32 #Parse Command Line
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33 options, args = doc_optparse.parse( __doc__ )
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34 #{'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'}
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35
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36 infile = options.input
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37 x_cols = options.var_cols.split(',')
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38 kernel = options.kernel
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39 outfile = options.output1
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40 outfile2 = options.output2
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41 ncomps = int(options.features)
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42 fout = open(outfile,'w')
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43
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44 elems = []
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45 for i, line in enumerate( file ( infile )):
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46 line = line.rstrip('\r\n')
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47 if len( line )>0 and not line.startswith( '#' ):
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48 elems = line.split( '\t' )
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49 break
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50 if i == 30:
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51 break # Hopefully we'll never get here...
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52
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53 if len( elems )<1:
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54 stop_err( "The data in your input dataset is either missing or not formatted properly." )
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55
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56 x_vals = []
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57
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58 for k,col in enumerate(x_cols):
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59 x_cols[k] = int(col)-1
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60 x_vals.append([])
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61
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62 NA = 'NA'
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63 skipped = 0
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64 for ind,line in enumerate( file( infile )):
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65 if line and not line.startswith( '#' ):
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66 try:
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67 fields = line.strip().split("\t")
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68 for k,col in enumerate(x_cols):
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69 try:
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70 xval = float(fields[col])
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71 except:
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72 #xval = r('NA')
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73 xval = NaN#
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74 x_vals[k].append(xval)
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75 except:
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76 skipped += 1
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77
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78 x_vals1 = numpy.asarray(x_vals).transpose()
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79 dat= r.list(array(x_vals1))
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80
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81 print r('library("kernlab")')
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82
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83 try:
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84 r.suppressWarnings(r.library('kernlab'))
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85 except:
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86 stop_err('Missing R library kernlab')
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87
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88 set_default_mode(NO_CONVERSION)
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89 if kernel=="rbfdot" or kernel=="anovadot":
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90 pars = r.list(sigma=float(options.sigma))
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91 elif kernel=="polydot":
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92 pars = r.list(degree=float(options.degree),scale=float(options.scale),offset=float(options.offset))
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93 elif kernel=="tanhdot":
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94 pars = r.list(scale=float(options.scale),offset=float(options.offset))
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95 elif kernel=="besseldot":
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96 pars = r.list(degree=float(options.degree),sigma=float(options.sigma),order=float(options.order))
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97 elif kernel=="anovadot":
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98 pars = r.list(degree=float(options.degree),sigma=float(options.sigma))
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99 else:
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100 pars = r.list()
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101
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102 try:
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103 kpc = r.kpca(x=r.na_exclude(dat), kernel=kernel, kpar=pars, features=ncomps)
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104 except RException, rex:
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105 stop_err("Encountered error while performing kPCA on the input data: %s" %(rex))
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106 set_default_mode(BASIC_CONVERSION)
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107
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108 eig = r.eig(kpc)
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109 pcv = r.pcv(kpc)
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110 rotated = r.rotated(kpc)
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111
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112 comps = eig.keys()
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113 eigv = eig.values()
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114 for i in range(ncomps):
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115 eigv[comps.index('Comp.%s' %(i+1))] = eig.values()[i]
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116
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117 print >>fout, "#Component\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
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118
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119 print >>fout, "#Eigenvalue\t%s" %("\t".join(["%.4g" % el for el in eig.values()]))
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120
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121 print >>fout, "#Principal component vectors\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
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122 for obs,val in enumerate(pcv):
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123 print >>fout, "%s\t%s" %(obs+1, "\t".join(["%.4g" % el for el in val]))
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124
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125 print >>fout, "#Rotated values\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
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126 for obs,val in enumerate(rotated):
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127 print >>fout, "%s\t%s" %(obs+1, "\t".join(["%.4g" % el for el in val]))
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128
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129 r.pdf( outfile2, 8, 8 )
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130 if ncomps != 1:
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131 r.pairs(rotated,labels=r.list(range(1,ncomps+1)),main="Scatterplot of rotated values")
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132 else:
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133 r.plot(rotated, ylab='Comp.1', main="Scatterplot of rotated values")
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134 r.dev_off() |
