CloneSet351

Bio/NeuralNetwork/Gene/Schema.py

Bio/NeuralNetwork/Gene/Schema.py

        # convert the genome into a string
        seq_motif = genome.toseq( ) 
        motif = seq_motif.data 

        # get the counts in the positive examples
        num_pos = 0 
        for seq_record in self._pos_seqs: 
             cur_counts = self._schema_eval.num_matches(motif,seq_record.seq.data) 

             num_pos+=cur_counts 

         # get the counts in the negative examples

        # convert the genome into a string
        seq_motif = genome.toseq( ) 
        motif = seq_motif.data 

        # find the number of times the genome matches
        num_times = 0 
        for seq_record in self._records: 
             cur_counts = self._evaluator.num_matches(motif,seq_record.seq.data) 

             num_times+=cur_counts 

# convert the genome into a string
seq_motif = genome.toseq( ) 
motif = seq_motif.data 
 [[#variable77b729e0]]= 0 
for seq_record in self. [[#variable2e7c77e0]]:
  cur_counts = self. [[#variable77b72a00]].num_matches(motif,seq_record.seq.data) 
   [[#variable77b729e0]]+=cur_counts 
  # get the counts in the negative examples
 

# find the number of times the genome matches
num_times 

# get the counts in the positive examples
num_pos 

_records 

_pos_seqs 

_evaluator 

_schema_eval