from XGram.Generator.Prebuilt import RNA import XGram.Run import XGram.Parser if __name__ == "__main__": t0 = time.time() ## file with initial values for pfold parameters = XGram.PATH_DATA + "/pfold.eg" data = XGram.PATH_DATA + "/ncrna.FBtr0081064.stk" symmetric = False xgram = XGram.XGram() generated_model = RNA.buildPFold() data_model = XGram.Parser.parseGrammar( open( parameters, "r").readlines() ) ## load PFold parameterization generated_model.mGrammar.copyParameters( data_model.mGrammar, remove_missing = True) print data_model.getGrammar() print generated_model.getGrammar() result = xgram.annotate( generated_model, data, tree_model = generated_model ) print "".join(result.mLog) print "".join(result.mData)
if __name__ == "__main__": t0 = time.time() data = XGram.PATH_DATA + "/rf00013_withtree.stk" data = XGram.PATH_DATA + "/rf00013.stk" data = XGram.PATH_DATA + "/rf00503.stk" data = XGram.PATH_DATA + "/rf00001.stk" ref_data = XGram.PATH_DATA + "/pfold.eg" tree_model = XGram.PATH_DATA + "/pfold.eg" input_model = RNA.buildPFold(strand_symmetric=True, weak_strong=True, copy_parameters=ref_data) xgram = XGram.XGram() xgram.setDebug(True) iterator = Iteration(xgram=xgram) iterator.setTreeModel(tree_model) iterator.setLogLevel(5) iterator.setDumpPatternModel("/home/aheger/iterations/rf00001/%s.eg") iterator.setDumpPatternLog("/home/aheger/iterations/rf00001/%s.log") iterator.setDumpPatternData("/home/aheger/iterations/rf00001/%s.data") results = iterator.run(input_model, data) print "# retrieved %i results" % len(results)
if __name__ == "__main__": t0 = time.time() data = XGram.PATH_DATA + "/rf00013_withtree.stk" data = XGram.PATH_DATA + "/rf00013.stk" data = XGram.PATH_DATA + "/rf00503.stk" data = XGram.PATH_DATA + "/rf00001.stk" ref_data = XGram.PATH_DATA + "/pfold.eg" tree_model = XGram.PATH_DATA + "/pfold.eg" input_model = RNA.buildPFold( strand_symmetric=True, weak_strong = True, copy_parameters=ref_data) xgram = XGram.XGram() xgram.setDebug( True ) iterator = Iteration( xgram = xgram ) iterator.setTreeModel( tree_model ) iterator.setLogLevel( 5 ) iterator.setDumpPatternModel( "/home/aheger/iterations/rf00001/%s.eg" ) iterator.setDumpPatternLog( "/home/aheger/iterations/rf00001/%s.log" ) iterator.setDumpPatternData( "/home/aheger/iterations/rf00001/%s.data" ) results = iterator.run( input_model, data ) print "# retrieved %i results" % len(results)
from XGram.Generator.Prebuilt import RNA import XGram.Run import XGram.Parser if __name__ == "__main__": t0 = time.time() ## file with initial values for pfold parameters = XGram.PATH_DATA + "/pfold.eg" data = XGram.PATH_DATA + "/ncrna.FBtr0081064.stk" symmetric = False xgram = XGram.XGram() generated_model = RNA.buildPFold() data_model = XGram.Parser.parseGrammar(open(parameters, "r").readlines()) ## load PFold parameterization generated_model.mGrammar.copyParameters(data_model.mGrammar, remove_missing=True) print data_model.getGrammar() print generated_model.getGrammar() result = xgram.annotate(generated_model, data, tree_model=generated_model) print "".join(result.mLog) print "".join(result.mData)