Index: branches/weighted-transfer/apertium-weights-learner/learner.py
===================================================================
--- branches/weighted-transfer/apertium-weights-learner/learner.py	(revision 70826)
+++ branches/weighted-transfer/apertium-weights-learner/learner.py	(revision 70827)
@@ -74,7 +74,7 @@
     pattern_line += '      </pattern>\n'
     return pattern_line
 
-def get_weights(rule_group, pattern, sent_line, tixfname, binfname, output_stream):
+def get_weights(rule_group, pattern, sent_line, tixfname, binfname):
     total = 0.
     weights_list = []
     
@@ -90,7 +90,7 @@
         weights_line += '  </rule-group>\n' + weights_tail
         with open('tmpweights.w1x', 'w', encoding='utf-8') as wfile:
             wfile.write(weights_line)
-        translation = translate(sent_line, tixfname, binfname, 'tmpweights.w1x', output_stream)
+        translation = translate(sent_line, tixfname, binfname, 'tmpweights.w1x')
         score = model.score(translation.lower(), bos = True, eos = True)
         weights_list.append([translation, math.exp(score), focus_rule[1]])
     for translation, score, rule_id in weights_list:
@@ -113,7 +113,7 @@
             wfile.write('  </rule-group>\n')
         wfile.write(weights_tail)            
 
-def translate(sent_line, tixfname, binfname, weightsfname, output_stream):
+def translate(sent_line, tixfname, binfname, weightsfname):
     pipe = pipes.Template()
     pipe.append('lt-proc -b {}'.format('.'.join((binfname, 'autobil.bin'))), '--')
     pipe.append('apertium-transfer -bw {} {} {}'.format(weightsfname, '.'.join((tixfname, 't1x')), '.'.join((binfname, 't1x.bin'))), '--')
@@ -177,8 +177,7 @@
             if '*' not in sent_line:
                 coverage_list, parsed_line = coverage.process_line(sent_line,
                                         cat_dict, pattern_FST,
-                                        output_stream,
-                                        False, True, False)
+                                        None, False, True, False)
                 # check if any rule in any coverage is ambiguous,
                 # take first coverage and first rule if any
                 for coverage_item in coverage_list:
@@ -188,7 +187,7 @@
                         #for item in parsed_line:
                         #    print(str(item) + '\n')
                         #print(coverage.coverage_to_groups(coverage_item) + '\n\n')
-                        weights_list = get_weights(ambiguous_rules[rule_number], pattern, sent_line, tixfname, binfname, output_stream)
+                        weights_list = get_weights(ambiguous_rules[rule_number], pattern, sent_line, tixfname, binfname)
                         #print(weights_list)
                         for translation, score, rule_id in weights_list:
                             weights_dict[rule_number][rule_id].setdefault(tuple(pattern), 0.)