Mercurial > repos > anmoljh > rcaret_classification_model

diff 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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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/modelBuilding.py	Thu May 31 11:58:59 2018 -0400
@@ -0,0 +1,182 @@
+def __inputArguments():
+
+	import argparse
+	parser = argparse.ArgumentParser()
+
+	parser.add_argument("--method", nargs='?',default ='pls',help="Name of the method on which model will build; \
+	Available Methods are:- pls, glm , glmboost ")
+	parser.add_argument("rdata",help="Descriptor file for model building")
+	parser.add_argument("--getdatainfoeval",nargs='?',default='TRUE',help="Validation of the data ")
+	parser.add_argument("--getdatainfoecho",nargs='?',default='FALSE',help="print on consol about Validity of the data ")
+	parser.add_argument("--getdatainforesult",nargs='?',default='hide',help="print in output file about Validity of the data ")
+	parser.add_argument("--missingfiltereval",nargs='?',default='FALSE',help="Processing step :: removal of missing value ")
+	parser.add_argument("--missingfilterecho",nargs='?',default='FALSE',help="print Processing step :: removal of missing value ")
+	parser.add_argument("--missingfilterresult",nargs='?',default='hide',help="print in output file about Processing step :: removal of missing value ")
+	parser.add_argument("--missingfilterthreshc",nargs='?',default=0.20,type=float,help="info about highly missing column data")
+	parser.add_argument("--missingfilterthreshr",nargs='?',default=0.20,type=float,help="info about highly missing row number")
+	parser.add_argument("--pcaeval",nargs='?',default='FALSE',help="PCA of data ")
+	parser.add_argument("--pcaecho",nargs='?',default='FALSE',help="PCA of data ")
+	parser.add_argument("--pcaresult",nargs='?',default='hide',help="print in file about PCA of data ")
+	parser.add_argument("--pcacomp",nargs='?',default=3,type=int,help="Number of PCA componant will be plotted ")
+	parser.add_argument("--pcaploteval",nargs='?',default='FALSE',help="PCA plot of data ")
+	parser.add_argument("--pcaplotecho",nargs='?',default='FALSE',help="print PCA plot of data ")
+	parser.add_argument("--pcaplotresult",nargs='?',default='hide',help="write in output file about PCA plot of data")
+	parser.add_argument("--pcaplotfig",nargs='?',default='TRUE',help="make figure file for integration in output file")
+	parser.add_argument("--initialdataspliteval",nargs='?',default='TRUE',help="data splitting in test and train set ")
+	parser.add_argument("--initialdatasplitecho",nargs='?',default='FALSE',help="print about data splitting in test and train set")
+	parser.add_argument("--initialdatasplitresult",nargs='?',default='hide',help="write in outputfile about data splitting in test and train set")
+        parser.add_argument("--saampling",nargs='?',default="garBage",help="Perform sampling from data")
+	parser.add_argument("--percent",nargs='?',default=0.8,type=float,help="percent value at which data splitting is done")
+	parser.add_argument("--nzveval",nargs='?',default='FALSE',help="remove near zero values")
+	parser.add_argument("--nzvresult",nargs='?',default='hide',help="write in outputfile about removing near zero values")
+	parser.add_argument("--nzvecho",nargs='?',default='FALSE',help="print about removing near zero values")
+	parser.add_argument("--corrfiltereval",nargs='?',default='FALSE',help="remove higly correlated values")
+	parser.add_argument("--corrfilterresult",nargs='?',default='hide',help="write in outputfile about removing highly correlated values")
+	parser.add_argument("--corrfilterecho",nargs='?',default='FALSE',help="print about removing correlated values")
+	parser.add_argument("--threshholdcor",nargs='?',default=0.75,type=float,help="percent value at which correlated values ommitted ")
+	parser.add_argument("--preproceval",nargs='?',default='FALSE',help="pre proccesing")
+	parser.add_argument("--preprocecho",nargs='?',default='FALSE',help="print about pre proccesing")
+	parser.add_argument("--preprocresult",nargs='?',default='hide',help="write in output file about pre proccesing")
+	parser.add_argument("--setupworkersecho",nargs='?',default='FALSE',help="print about number of processors")
+	parser.add_argument("--setupworkersresult",nargs='?',default='tex',help="write about number of processors in output file")
+	parser.add_argument("--numworkers",nargs='?',default=1,type=int,help="defines used processors")
+	parser.add_argument("--setupresamplingecho",nargs='?',default='FALSE',help="print resampling rules")
+	parser.add_argument("--setupresamplingresult",nargs='?',default='hide',help="write resampling rules in output file")
+	parser.add_argument("--resampname",nargs='?',default='boot632',help="choose type of resampling")
+	parser.add_argument("--resamplenumber",nargs='?',default=10,type=int,help="set number of resampling")
+	parser.add_argument("--numrepeat",nargs='?',default=3,type=int,help="set times of repeat")
+	parser.add_argument("--resamplenumberpercent",nargs='?',default=0.75,type=float,help="set PERCENT resampling")
+	parser.add_argument("--setupgridresult",nargs='?',default='hide',help="write about number of grids in output file")
+	parser.add_argument("--setupgridecho",nargs='?',default='FALSE',help="print about number of grids")
+	parser.add_argument("--setupgridsize",nargs='?',default=3,type=int,help="set number of grids")
+	parser.add_argument("--fitmodelresult",nargs='?',default='hide',help="write about model")
+	parser.add_argument("--fitmodelecho",nargs='?',default='FALSE',help="print about model")
+	parser.add_argument("--fitmodeleval",nargs='?',default='TRUE',help="start model building")
+	parser.add_argument("--modeldescrecho",nargs='?',default='FALSE',help="print model description")
+	parser.add_argument("--modeldescrresult",nargs='?',default='hide',help="write model description in outout file")
+	parser.add_argument("--resamptableecho",nargs='?',default='FALSE',help="print resample table")
+	parser.add_argument("--resamptableresult",nargs='?',default='tex',help="write resample table in output file")
+	parser.add_argument("--profileplotecho",nargs='?',default='FALSE',help="print about profile plots")
+	parser.add_argument("--profileplotfig",nargs='?',default='TRUE',help=" profile plots")
+	parser.add_argument("--stopworkersecho",nargs='?',default='FALSE',help="stop workers ie processors")
+	parser.add_argument("--stopworkersresult",nargs='?',default='hide',help="write about workers ie processors used")
+	parser.add_argument("--testpredresult",nargs='?',default='tex',help="write about statistical measure")
+	parser.add_argument("--testpredecho",nargs='?',default='FALSE',help="print about statistical measure")
+	parser.add_argument("--classprobstexresult",nargs='?',default='tex',help="paste various figure of statistical measure in outputfile")
+	parser.add_argument("--classprobstexecho",nargs='?',default='FALSE',help="print various figure of statistical measure")
+	parser.add_argument("--classprobstexresult1",nargs='?',default='hide',help="create roc curve in outputfile")
+	parser.add_argument("--classprobstexecho1",nargs='?',default='FALSE',help="print figure of statistical measure")
+	parser.add_argument("--savedataecho",nargs='?',default='FALSE',help="information about completion of model building ")
+	parser.add_argument("--savedataresult",nargs='?',default='hide',help="write information about completion of model building in outputfile ")
+	parser.add_argument("--datasets", help="name of the generated datasets")		
+	parser.add_argument("--outputmodel", help="give name for the generated model")		
+	parser.add_argument("--outputresultpdf", help="give name for the output pdf file")		
+	
+	args = parser.parse_args()
+	return args
+
+def generateRnwScript():
+
+        import templateLibrary
+	t = templateLibrary.__template4Rnw()
+	
+	from string import Template
+	s = Template(t)
+        
+	args = __inputArguments()
+
+	templt = s.safe_substitute(METHOD=args.method,
+			RDATA=args.rdata, 
+			GETDATAINFOEVAL=args.getdatainfoeval, 
+			GETDATAINFOECHO=args.getdatainfoecho, 
+			GETDATAINFORESULT=args.getdatainforesult, 
+			MISSINGFILTEREVAL=args.missingfiltereval,
+			MISSINGFILTERECHO=args.missingfilterecho,
+			MISSINGFILTERRESULT=args.missingfilterresult,
+			MISSINGFILTERTHRESHC=args.missingfilterthreshc,
+			MISSINGFILTERTHRESHR=args.missingfilterthreshr,
+			PCAEVAL=args.pcaeval,
+			PCAECHO=args.pcaecho,
+			PCARESULT=args.pcaresult,
+                        PCACOMP=args.pcacomp,    
+			PCAPLOTEVAL=args.pcaploteval,
+			PCAPLOTECHO=args.pcaplotecho,
+			PCAPLOTRESULT=args.pcaplotresult,
+			PCAPLOTFIG=args.pcaplotfig,
+			INITIALDATASPLITEVAL=args.initialdataspliteval,
+			INITIALDATASPLITECHO=args.initialdatasplitecho,
+			INITIALDATASPLITRESULT=args.initialdatasplitresult,
+                        SAAMPLING=args.saampling,
+			PERCENT=args.percent,
+			NZVEVAL=args.nzveval,
+			NZVRESULT=args.nzvresult,
+			NZVECHO=args.nzvecho,
+			CORRFILTEREVAL=args.corrfiltereval,
+			CORRFILTERRESULT=args.corrfilterresult,
+			CORRFILTERECHO=args.corrfilterecho,
+			THRESHHOLDCOR=args.threshholdcor,
+			PREPROCEVAL=args.preproceval,
+			PREPROCECHO=args.preprocecho,
+			PREPROCRESULT=args.preprocresult,
+			SETUPWORKERSECHO=args.setupworkersecho,
+			SETUPWORKERSRESULT=args.setupworkersresult,
+			NUMWORKERS=args.numworkers,
+			SETUPRESAMPLINGECHO=args.setupresamplingecho,
+			SETUPRESAMPLINGRESULT=args.setupresamplingresult,
+			RESAMPNAME=args.resampname,
+			RESAMPLENUMBER=args.resamplenumber,
+                        NUMREPEAT=args.numrepeat,
+			RESAMPLENUMBERPERCENT=args.resamplenumberpercent,
+			SETUPGRIDRESULT=args.setupgridresult,
+			SETUPGRIDECHO=args.setupgridecho,
+			SETUPGRIDSIZE=args.setupgridsize,
+			FITMODELRESULT=args.fitmodelresult,
+			FITMODELECHO=args.fitmodelecho,
+			FITMODELEVAL=args.fitmodeleval,
+			MODELDESCRECHO=args.modeldescrecho,
+			MODELDESCRRESULT=args.modeldescrresult,
+			RESAMPTABLEECHO=args.resamptableecho,
+			RESAMPTABLERESULT=args.resamptableresult,
+			PROFILEPLOTECHO=args.profileplotecho,
+			PROFILEPLOTFIG=args.profileplotfig,
+			STOPWORKERSECHO=args.stopworkersecho,
+			STOPWORKERSRESULT=args.stopworkersresult,
+			TESTPREDRESULT=args.testpredresult,
+			TESTPREDECHO=args.testpredecho,
+			CLASSPROBSTEXRESULT=args.classprobstexresult,
+			CLASSPROBSTEXECHO=args.classprobstexecho,
+			CLASSPROBSTEXRESULT1=args.classprobstexresult1,
+			CLASSPROBSTEXECHO1=args.classprobstexecho1,
+			SAVEDATAECHO=args.savedataecho,
+			SAVEDATARESULT=args.savedataresult )
+
+	
+	f = open('result-doc.Rnw','w')
+	f.write(templt)
+	f.close()
+	
+def modelBuilding():
+
+	import os
+	os.system('R CMD Sweave result-doc.Rnw  > cmd.log.1 2>&1')
+	os.system('R CMD pdflatex result-doc.tex > cmd.log.2 2>&1')
+	os.system('R CMD pdflatex result-doc.tex > cmd.log.2 2>&1')
+	args = __inputArguments()
+
+        from string import Template
+        s1 = Template('cp $METHOD-Fit.RData $OUTPUTMODEL')
+        s2 = Template('cp result-doc.pdf $OUTPUTRESULTPDF')
+        s3 = Template('cp datasets.RData $DATASETS')
+
+        cmd1 = s1.safe_substitute(METHOD=args.method, OUTPUTMODEL=args.outputmodel)
+        cmd2 = s2.safe_substitute(OUTPUTRESULTPDF=args.outputresultpdf)
+        cmd3 = s3.safe_substitute(DATASETS=args.datasets)
+
+        os.system(cmd1)
+        os.system(cmd2)
+        os.system(cmd3)	
+
+if __name__ == "__main__" :
+	
+	generateRnwScript()
+	modelBuilding()