Mercurial > repos > anmoljh > rcaret_classification_model

comparison modelBuilding.py @ 0:2cb81da69c73 draft

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planemo upload commit a1f4dd8eb560c649391ada1a6bb9505893a35272
author anmoljh
date Thu, 31 May 2018 11:58:59 -0400
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-1:000000000000 0:2cb81da69c73
1 def __inputArguments():
2
3 import argparse
4 parser = argparse.ArgumentParser()
5
6 parser.add_argument("--method", nargs='?',default ='pls',help="Name of the method on which model will build; \
7 Available Methods are:- pls, glm , glmboost ")
8 parser.add_argument("rdata",help="Descriptor file for model building")
9 parser.add_argument("--getdatainfoeval",nargs='?',default='TRUE',help="Validation of the data ")
10 parser.add_argument("--getdatainfoecho",nargs='?',default='FALSE',help="print on consol about Validity of the data ")
11 parser.add_argument("--getdatainforesult",nargs='?',default='hide',help="print in output file about Validity of the data ")
12 parser.add_argument("--missingfiltereval",nargs='?',default='FALSE',help="Processing step :: removal of missing value ")
13 parser.add_argument("--missingfilterecho",nargs='?',default='FALSE',help="print Processing step :: removal of missing value ")
14 parser.add_argument("--missingfilterresult",nargs='?',default='hide',help="print in output file about Processing step :: removal of missing value ")
15 parser.add_argument("--missingfilterthreshc",nargs='?',default=0.20,type=float,help="info about highly missing column data")
16 parser.add_argument("--missingfilterthreshr",nargs='?',default=0.20,type=float,help="info about highly missing row number")
17 parser.add_argument("--pcaeval",nargs='?',default='FALSE',help="PCA of data ")
18 parser.add_argument("--pcaecho",nargs='?',default='FALSE',help="PCA of data ")
19 parser.add_argument("--pcaresult",nargs='?',default='hide',help="print in file about PCA of data ")
20 parser.add_argument("--pcacomp",nargs='?',default=3,type=int,help="Number of PCA componant will be plotted ")
21 parser.add_argument("--pcaploteval",nargs='?',default='FALSE',help="PCA plot of data ")
22 parser.add_argument("--pcaplotecho",nargs='?',default='FALSE',help="print PCA plot of data ")
23 parser.add_argument("--pcaplotresult",nargs='?',default='hide',help="write in output file about PCA plot of data")
24 parser.add_argument("--pcaplotfig",nargs='?',default='TRUE',help="make figure file for integration in output file")
25 parser.add_argument("--initialdataspliteval",nargs='?',default='TRUE',help="data splitting in test and train set ")
26 parser.add_argument("--initialdatasplitecho",nargs='?',default='FALSE',help="print about data splitting in test and train set")
27 parser.add_argument("--initialdatasplitresult",nargs='?',default='hide',help="write in outputfile about data splitting in test and train set")
28 parser.add_argument("--saampling",nargs='?',default="garBage",help="Perform sampling from data")
29 parser.add_argument("--percent",nargs='?',default=0.8,type=float,help="percent value at which data splitting is done")
30 parser.add_argument("--nzveval",nargs='?',default='FALSE',help="remove near zero values")
31 parser.add_argument("--nzvresult",nargs='?',default='hide',help="write in outputfile about removing near zero values")
32 parser.add_argument("--nzvecho",nargs='?',default='FALSE',help="print about removing near zero values")
33 parser.add_argument("--corrfiltereval",nargs='?',default='FALSE',help="remove higly correlated values")
34 parser.add_argument("--corrfilterresult",nargs='?',default='hide',help="write in outputfile about removing highly correlated values")
35 parser.add_argument("--corrfilterecho",nargs='?',default='FALSE',help="print about removing correlated values")
36 parser.add_argument("--threshholdcor",nargs='?',default=0.75,type=float,help="percent value at which correlated values ommitted ")
37 parser.add_argument("--preproceval",nargs='?',default='FALSE',help="pre proccesing")
38 parser.add_argument("--preprocecho",nargs='?',default='FALSE',help="print about pre proccesing")
39 parser.add_argument("--preprocresult",nargs='?',default='hide',help="write in output file about pre proccesing")
40 parser.add_argument("--setupworkersecho",nargs='?',default='FALSE',help="print about number of processors")
41 parser.add_argument("--setupworkersresult",nargs='?',default='tex',help="write about number of processors in output file")
42 parser.add_argument("--numworkers",nargs='?',default=1,type=int,help="defines used processors")
43 parser.add_argument("--setupresamplingecho",nargs='?',default='FALSE',help="print resampling rules")
44 parser.add_argument("--setupresamplingresult",nargs='?',default='hide',help="write resampling rules in output file")
45 parser.add_argument("--resampname",nargs='?',default='boot632',help="choose type of resampling")
46 parser.add_argument("--resamplenumber",nargs='?',default=10,type=int,help="set number of resampling")
47 parser.add_argument("--numrepeat",nargs='?',default=3,type=int,help="set times of repeat")
48 parser.add_argument("--resamplenumberpercent",nargs='?',default=0.75,type=float,help="set PERCENT resampling")
49 parser.add_argument("--setupgridresult",nargs='?',default='hide',help="write about number of grids in output file")
50 parser.add_argument("--setupgridecho",nargs='?',default='FALSE',help="print about number of grids")
51 parser.add_argument("--setupgridsize",nargs='?',default=3,type=int,help="set number of grids")
52 parser.add_argument("--fitmodelresult",nargs='?',default='hide',help="write about model")
53 parser.add_argument("--fitmodelecho",nargs='?',default='FALSE',help="print about model")
54 parser.add_argument("--fitmodeleval",nargs='?',default='TRUE',help="start model building")
55 parser.add_argument("--modeldescrecho",nargs='?',default='FALSE',help="print model description")
56 parser.add_argument("--modeldescrresult",nargs='?',default='hide',help="write model description in outout file")
57 parser.add_argument("--resamptableecho",nargs='?',default='FALSE',help="print resample table")
58 parser.add_argument("--resamptableresult",nargs='?',default='tex',help="write resample table in output file")
59 parser.add_argument("--profileplotecho",nargs='?',default='FALSE',help="print about profile plots")
60 parser.add_argument("--profileplotfig",nargs='?',default='TRUE',help=" profile plots")
61 parser.add_argument("--stopworkersecho",nargs='?',default='FALSE',help="stop workers ie processors")
62 parser.add_argument("--stopworkersresult",nargs='?',default='hide',help="write about workers ie processors used")
63 parser.add_argument("--testpredresult",nargs='?',default='tex',help="write about statistical measure")
64 parser.add_argument("--testpredecho",nargs='?',default='FALSE',help="print about statistical measure")
65 parser.add_argument("--classprobstexresult",nargs='?',default='tex',help="paste various figure of statistical measure in outputfile")
66 parser.add_argument("--classprobstexecho",nargs='?',default='FALSE',help="print various figure of statistical measure")
67 parser.add_argument("--classprobstexresult1",nargs='?',default='hide',help="create roc curve in outputfile")
68 parser.add_argument("--classprobstexecho1",nargs='?',default='FALSE',help="print figure of statistical measure")
69 parser.add_argument("--savedataecho",nargs='?',default='FALSE',help="information about completion of model building ")
70 parser.add_argument("--savedataresult",nargs='?',default='hide',help="write information about completion of model building in outputfile ")
71 parser.add_argument("--datasets", help="name of the generated datasets")
72 parser.add_argument("--outputmodel", help="give name for the generated model")
73 parser.add_argument("--outputresultpdf", help="give name for the output pdf file")
74
75 args = parser.parse_args()
76 return args
77
78 def generateRnwScript():
79
80 import templateLibrary
81 t = templateLibrary.__template4Rnw()
82
83 from string import Template
84 s = Template(t)
85
86 args = __inputArguments()
87
88 templt = s.safe_substitute(METHOD=args.method,
89 RDATA=args.rdata,
90 GETDATAINFOEVAL=args.getdatainfoeval,
91 GETDATAINFOECHO=args.getdatainfoecho,
92 GETDATAINFORESULT=args.getdatainforesult,
93 MISSINGFILTEREVAL=args.missingfiltereval,
94 MISSINGFILTERECHO=args.missingfilterecho,
95 MISSINGFILTERRESULT=args.missingfilterresult,
96 MISSINGFILTERTHRESHC=args.missingfilterthreshc,
97 MISSINGFILTERTHRESHR=args.missingfilterthreshr,
98 PCAEVAL=args.pcaeval,
99 PCAECHO=args.pcaecho,
100 PCARESULT=args.pcaresult,
101 PCACOMP=args.pcacomp,
102 PCAPLOTEVAL=args.pcaploteval,
103 PCAPLOTECHO=args.pcaplotecho,
104 PCAPLOTRESULT=args.pcaplotresult,
105 PCAPLOTFIG=args.pcaplotfig,
106 INITIALDATASPLITEVAL=args.initialdataspliteval,
107 INITIALDATASPLITECHO=args.initialdatasplitecho,
108 INITIALDATASPLITRESULT=args.initialdatasplitresult,
109 SAAMPLING=args.saampling,
110 PERCENT=args.percent,
111 NZVEVAL=args.nzveval,
112 NZVRESULT=args.nzvresult,
113 NZVECHO=args.nzvecho,
114 CORRFILTEREVAL=args.corrfiltereval,
115 CORRFILTERRESULT=args.corrfilterresult,
116 CORRFILTERECHO=args.corrfilterecho,
117 THRESHHOLDCOR=args.threshholdcor,
118 PREPROCEVAL=args.preproceval,
119 PREPROCECHO=args.preprocecho,
120 PREPROCRESULT=args.preprocresult,
121 SETUPWORKERSECHO=args.setupworkersecho,
122 SETUPWORKERSRESULT=args.setupworkersresult,
123 NUMWORKERS=args.numworkers,
124 SETUPRESAMPLINGECHO=args.setupresamplingecho,
125 SETUPRESAMPLINGRESULT=args.setupresamplingresult,
126 RESAMPNAME=args.resampname,
127 RESAMPLENUMBER=args.resamplenumber,
128 NUMREPEAT=args.numrepeat,
129 RESAMPLENUMBERPERCENT=args.resamplenumberpercent,
130 SETUPGRIDRESULT=args.setupgridresult,
131 SETUPGRIDECHO=args.setupgridecho,
132 SETUPGRIDSIZE=args.setupgridsize,
133 FITMODELRESULT=args.fitmodelresult,
134 FITMODELECHO=args.fitmodelecho,
135 FITMODELEVAL=args.fitmodeleval,
136 MODELDESCRECHO=args.modeldescrecho,
137 MODELDESCRRESULT=args.modeldescrresult,
138 RESAMPTABLEECHO=args.resamptableecho,
139 RESAMPTABLERESULT=args.resamptableresult,
140 PROFILEPLOTECHO=args.profileplotecho,
141 PROFILEPLOTFIG=args.profileplotfig,
142 STOPWORKERSECHO=args.stopworkersecho,
143 STOPWORKERSRESULT=args.stopworkersresult,
144 TESTPREDRESULT=args.testpredresult,
145 TESTPREDECHO=args.testpredecho,
146 CLASSPROBSTEXRESULT=args.classprobstexresult,
147 CLASSPROBSTEXECHO=args.classprobstexecho,
148 CLASSPROBSTEXRESULT1=args.classprobstexresult1,
149 CLASSPROBSTEXECHO1=args.classprobstexecho1,
150 SAVEDATAECHO=args.savedataecho,
151 SAVEDATARESULT=args.savedataresult )
152
153
154 f = open('result-doc.Rnw','w')
155 f.write(templt)
156 f.close()
157
158 def modelBuilding():
159
160 import os
161 os.system('R CMD Sweave result-doc.Rnw > cmd.log.1 2>&1')
162 os.system('R CMD pdflatex result-doc.tex > cmd.log.2 2>&1')
163 os.system('R CMD pdflatex result-doc.tex > cmd.log.2 2>&1')
164 args = __inputArguments()
165
166 from string import Template
167 s1 = Template('cp $METHOD-Fit.RData $OUTPUTMODEL')
168 s2 = Template('cp result-doc.pdf $OUTPUTRESULTPDF')
169 s3 = Template('cp datasets.RData $DATASETS')
170
171 cmd1 = s1.safe_substitute(METHOD=args.method, OUTPUTMODEL=args.outputmodel)
172 cmd2 = s2.safe_substitute(OUTPUTRESULTPDF=args.outputresultpdf)
173 cmd3 = s3.safe_substitute(DATASETS=args.datasets)
174
175 os.system(cmd1)
176 os.system(cmd2)
177 os.system(cmd3)
178
179 if __name__ == "__main__" :
180
181 generateRnwScript()
182 modelBuilding()