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)
