Mercurial > repos > devteam > rcve
comparison rcve.py @ 0:d8c414b9d774 draft default tip
Imported from capsule None
author | devteam |
---|---|
date | Tue, 01 Apr 2014 09:13:06 -0400 |
parents | |
children |
comparison
equal
deleted
inserted
replaced
-1:000000000000 | 0:d8c414b9d774 |
---|---|
1 #!/usr/bin/env python | |
2 | |
3 import sys | |
4 from rpy import * | |
5 import numpy | |
6 | |
7 def stop_err(msg): | |
8 sys.stderr.write(msg) | |
9 sys.exit() | |
10 | |
11 | |
12 def sscombs(s): | |
13 if len(s) == 1: | |
14 return [s] | |
15 else: | |
16 ssc = sscombs(s[1:]) | |
17 return [s[0]] + [s[0]+comb for comb in ssc] + ssc | |
18 | |
19 | |
20 infile = sys.argv[1] | |
21 y_col = int(sys.argv[2])-1 | |
22 x_cols = sys.argv[3].split(',') | |
23 outfile = sys.argv[4] | |
24 | |
25 print "Predictor columns: %s; Response column: %d" % ( x_cols, y_col+1 ) | |
26 fout = open(outfile,'w') | |
27 | |
28 for i, line in enumerate( file ( infile )): | |
29 line = line.rstrip('\r\n') | |
30 if len( line )>0 and not line.startswith( '#' ): | |
31 elems = line.split( '\t' ) | |
32 break | |
33 if i == 30: | |
34 break # Hopefully we'll never get here... | |
35 | |
36 if len( elems )<1: | |
37 stop_err( "The data in your input dataset is either missing or not formatted properly." ) | |
38 | |
39 y_vals = [] | |
40 x_vals = [] | |
41 | |
42 for k, col in enumerate(x_cols): | |
43 x_cols[k] = int(col)-1 | |
44 x_vals.append([]) | |
45 """ | |
46 try: | |
47 float( elems[x_cols[k]] ) | |
48 except: | |
49 try: | |
50 msg = "This operation cannot be performed on non-numeric column %d containing value '%s'." % ( col, elems[x_cols[k]] ) | |
51 except: | |
52 msg = "This operation cannot be performed on non-numeric data." | |
53 stop_err( msg ) | |
54 """ | |
55 NA = 'NA' | |
56 for ind, line in enumerate( file( infile )): | |
57 if line and not line.startswith( '#' ): | |
58 try: | |
59 fields = line.split("\t") | |
60 try: | |
61 yval = float(fields[y_col]) | |
62 except Exception, ey: | |
63 yval = r('NA') | |
64 #print >>sys.stderr, "ey = %s" %ey | |
65 y_vals.append(yval) | |
66 for k, col in enumerate(x_cols): | |
67 try: | |
68 xval = float(fields[col]) | |
69 except Exception, ex: | |
70 xval = r('NA') | |
71 #print >>sys.stderr, "ex = %s" %ex | |
72 x_vals[k].append(xval) | |
73 except: | |
74 pass | |
75 | |
76 x_vals1 = numpy.asarray(x_vals).transpose() | |
77 dat = r.list( x=array(x_vals1), y=y_vals ) | |
78 | |
79 set_default_mode(NO_CONVERSION) | |
80 try: | |
81 full = r.lm( r("y ~ x"), data=r.na_exclude(dat) ) #full model includes all the predictor variables specified by the user | |
82 except RException, rex: | |
83 stop_err("Error performing linear regression on the input data.\nEither the response column or one of the predictor columns contain no numeric values.") | |
84 set_default_mode(BASIC_CONVERSION) | |
85 | |
86 summary = r.summary(full) | |
87 fullr2 = summary.get('r.squared','NA') | |
88 | |
89 if fullr2 == 'NA': | |
90 stop_err("Error in linear regression") | |
91 | |
92 if len(x_vals) < 10: | |
93 s = "" | |
94 for ch in range(len(x_vals)): | |
95 s += str(ch) | |
96 else: | |
97 stop_err("This tool only works with less than 10 predictors.") | |
98 | |
99 print >> fout, "#Model\tR-sq\tRCVE_Terms\tRCVE_Value" | |
100 all_combos = sorted(sscombs(s), key=len) | |
101 all_combos.reverse() | |
102 for j, cols in enumerate(all_combos): | |
103 #if len(cols) == len(s): #Same as the full model above | |
104 # continue | |
105 if len(cols) == 1: | |
106 x_vals1 = x_vals[int(cols)] | |
107 else: | |
108 x_v = [] | |
109 for col in cols: | |
110 x_v.append(x_vals[int(col)]) | |
111 x_vals1 = numpy.asarray(x_v).transpose() | |
112 dat = r.list(x=array(x_vals1), y=y_vals) | |
113 set_default_mode(NO_CONVERSION) | |
114 red = r.lm(r("y ~ x"), data= dat) #Reduced model | |
115 set_default_mode(BASIC_CONVERSION) | |
116 summary = r.summary(red) | |
117 redr2 = summary.get('r.squared','NA') | |
118 try: | |
119 rcve = (float(fullr2)-float(redr2))/float(fullr2) | |
120 except: | |
121 rcve = 'NA' | |
122 col_str = "" | |
123 for col in cols: | |
124 col_str = col_str + str(int(x_cols[int(col)]) + 1) + " " | |
125 col_str.strip() | |
126 rcve_col_str = "" | |
127 for col in s: | |
128 if col not in cols: | |
129 rcve_col_str = rcve_col_str + str(int(x_cols[int(col)]) + 1) + " " | |
130 rcve_col_str.strip() | |
131 if len(cols) == len(s): #full model | |
132 rcve_col_str = "-" | |
133 rcve = "-" | |
134 try: | |
135 redr2 = "%.4f" % (float(redr2)) | |
136 except: | |
137 pass | |
138 try: | |
139 rcve = "%.4f" % (float(rcve)) | |
140 except: | |
141 pass | |
142 print >> fout, "%s\t%s\t%s\t%s" % ( col_str, redr2, rcve_col_str, rcve ) |