def run(self):
# Use newer local version of RNAfold
call('RNALfold -T '+str(foldTemp)+' -d2 --noLP -L '+str(hairpinLength)+' < data/tmp/'+self.inPath+' > data/tmp/'+self.inPath+'.folds', shell=True)
# Use older version of RNAfold
# call('progs/ViennaRNA-1.8.5/Progs/RNALfold -T '+str(foldTemp)+' -d2 -noLP -L '+str(hairpinLength)+' < data/tmp/'+self.inPath+' > data/tmp/'+self.inPath+'.folds', shell=True)
FoldOps.filter_hairpins('data/tmp/'+self.inPath+'.folds', 'data/tmp/'+self.inPath+'.hairpins', minMFE, basePairs)
FileConversion.RNAL_to_fasta('data/tmp/'+self.inPath+'.hairpins', 'data/tmp/folds_from_'+self.inPath)
sl = SequenceList()
sl.load_fasta('data/tmp/folds_from_'+self.inPath)
# sl.remove_all_redundant()
sl.export_fasta('data/tmp/'+self.inPath+'nrhairpins')
# Step one: turn the fasta into something that RNALfold will work with
FastaOps.remove_newlines('data/'+inPath, 'data/tmp/'+inPath+'.fixed')
FastaOps.convert_DNA_to_RNA('data/tmp/'+inPath+'.fixed', 'data/tmp/'+inPath+'.rna')
# Step two: split the fasta for mutli-threaded processing
FastaOps.split_fasta('data/tmp/'+inPath+'.rna', numThreads)
# Step three: Launch threads
threadPath = inPath
threadExt = 'rna'
threads = []
for i in range(numThreads):
threads.append(myThread(threadPath+'.'+str(i)+'.'+threadExt))
for thread in threads:
thread.start()
for thread in threads:
thread.join()
FastaOps.merge_fasta('data/tmp/'+inPath+'.rnanrhairpins', numThreads)
FastaOps.remove_AU('data/tmp/'+inPath+'.rnanrhairpins', 'data/tmp/'+inPath+'.hairpins.noAU', 5)
