Mercurial > repos > xuebing > sharplabtool
diff tools/regVariation/best_regression_subsets.py @ 0:9071e359b9a3
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author | xuebing |
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date | Fri, 09 Mar 2012 19:37:19 -0500 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/tools/regVariation/best_regression_subsets.py Fri Mar 09 19:37:19 2012 -0500 @@ -0,0 +1,90 @@ +#!/usr/bin/env python + +from galaxy import eggs + +import sys, string +from rpy import * +import numpy + +def stop_err(msg): + sys.stderr.write(msg) + sys.exit() + +infile = sys.argv[1] +y_col = int(sys.argv[2])-1 +x_cols = sys.argv[3].split(',') +outfile = sys.argv[4] +outfile2 = sys.argv[5] +print "Predictor columns: %s; Response column: %d" %(x_cols,y_col+1) +fout = open(outfile,'w') + +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." ) + +y_vals = [] +x_vals = [] + +for k,col in enumerate(x_cols): + x_cols[k] = int(col)-1 + x_vals.append([]) + +NA = 'NA' +for ind,line in enumerate( file( infile )): + if line and not line.startswith( '#' ): + try: + fields = line.split("\t") + try: + yval = float(fields[y_col]) + except Exception, ey: + yval = r('NA') + y_vals.append(yval) + for k,col in enumerate(x_cols): + try: + xval = float(fields[col]) + except Exception, ex: + xval = r('NA') + x_vals[k].append(xval) + except: + pass + +response_term = "" + +x_vals1 = numpy.asarray(x_vals).transpose() + +dat= r.list(x=array(x_vals1), y=y_vals) + +r.library("leaps") + +set_default_mode(NO_CONVERSION) +try: + leaps = r.regsubsets(r("y ~ x"), data= r.na_exclude(dat)) +except RException, rex: + stop_err("Error performing linear regression on the input data.\nEither the response column or one of the predictor columns contain no numeric values.") +set_default_mode(BASIC_CONVERSION) + +summary = r.summary(leaps) +tot = len(x_vals) +pattern = "[" +for i in range(tot): + pattern = pattern + 'c' + str(int(x_cols[int(i)]) + 1) + ' ' +pattern = pattern.strip() + ']' +print >>fout, "#Vars\t%s\tR-sq\tAdj. R-sq\tC-p\tbic" %(pattern) +for ind,item in enumerate(summary['outmat']): + print >>fout, "%s\t%s\t%s\t%s\t%s\t%s" %(str(item).count('*'), item, summary['rsq'][ind], summary['adjr2'][ind], summary['cp'][ind], summary['bic'][ind]) + + +r.pdf( outfile2, 8, 8 ) +r.plot(leaps, scale="Cp", main="Best subsets using Cp Criterion") +r.plot(leaps, scale="r2", main="Best subsets using R-sq Criterion") +r.plot(leaps, scale="adjr2", main="Best subsets using Adjusted R-sq Criterion") +r.plot(leaps, scale="bic", main="Best subsets using bic Criterion") + +r.dev_off()