diff pca.py @ 0:f568051cdf2e draft default tip

Imported from capsule None

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/pca.py	Mon May 19 12:34:43 2014 -0400
@@ -0,0 +1,129 @@
+#!/usr/bin/env python
+
+import sys, string
+from rpy import *
+import numpy
+
+def stop_err(msg):
+    sys.stderr.write(msg)
+    sys.exit()
+
+infile = sys.argv[1]
+x_cols = sys.argv[2].split(',')
+method = sys.argv[3]
+outfile = sys.argv[4]
+outfile2 = sys.argv[5]
+
+if method == 'svd':
+    scale = center = "FALSE"
+    if sys.argv[6] == 'both':
+        scale = center = "TRUE"
+    elif sys.argv[6] == 'center':
+        center = "TRUE"
+    elif sys.argv[6] == 'scale':
+        scale = "TRUE"
+    
+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")
+            valid_line = True
+            for k,col in enumerate(x_cols):
+                try:
+                    xval = float(fields[col])
+                except:
+                    skipped += 1 
+                    valid_line = False
+                    break
+            if valid_line:
+                for k,col in enumerate(x_cols):
+                    xval = float(fields[col])
+                    x_vals[k].append(xval)
+        except:
+            skipped += 1
+
+x_vals1 = numpy.asarray(x_vals).transpose()
+dat= r.list(array(x_vals1))
+
+set_default_mode(NO_CONVERSION)
+try:
+    if method == "cor":
+        pc = r.princomp(r.na_exclude(dat), cor = r("TRUE"))
+    elif method == "cov":
+        pc = r.princomp(r.na_exclude(dat), cor = r("FALSE"))
+    elif method=="svd":
+        pc = r.prcomp(r.na_exclude(dat), center = r(center), scale = r(scale))
+except RException, rex:
+    stop_err("Encountered error while performing PCA on the input data: %s" %(rex))
+
+set_default_mode(BASIC_CONVERSION)
+summary = r.summary(pc, loadings="TRUE")
+ncomps = len(summary['sdev'])
+
+if type(summary['sdev']) == type({}):
+    comps_unsorted = summary['sdev'].keys()
+    comps=[]
+    sd = summary['sdev'].values()
+    for i in range(ncomps):
+        sd[i] = summary['sdev'].values()[comps_unsorted.index('Comp.%s' %(i+1))]
+        comps.append('Comp.%s' %(i+1))
+elif type(summary['sdev']) == type([]):
+    comps=[]
+    for i in range(ncomps):
+        comps.append('Comp.%s' %(i+1))
+        sd = summary['sdev']
+
+print >>fout, "#Component\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
+print >>fout, "#Std. deviation\t%s" %("\t".join(["%.4g" % el for el in sd]))
+total_var = 0
+vars = []
+for s in sd:
+    var = s*s
+    total_var += var
+    vars.append(var)
+for i,var in enumerate(vars):
+    vars[i] = vars[i]/total_var
+       
+print >>fout, "#Proportion of variance explained\t%s" %("\t".join(["%.4g" % el for el in vars]))
+
+print >>fout, "#Loadings\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
+xcolnames = ["c%d" %(el+1) for el in x_cols]
+if 'loadings' in summary: #in case of princomp
+    loadings = 'loadings'
+elif 'rotation' in summary: #in case of prcomp
+    loadings = 'rotation'
+for i,val in enumerate(summary[loadings]):
+    print >>fout, "%s\t%s" %(xcolnames[i], "\t".join(["%.4g" % el for el in val]))
+
+print >>fout, "#Scores\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
+if 'scores' in summary: #in case of princomp
+    scores = 'scores'
+elif 'x' in summary: #in case of prcomp
+    scores = 'x'
+for obs,sc in enumerate(summary[scores]):
+    print >>fout, "%s\t%s" %(obs+1, "\t".join(["%.4g" % el for el in sc]))
+
+r.pdf( outfile2, 8, 8 )
+r.biplot(pc)
+r.dev_off()
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