def generateRules(self):
       learnedRules = fieldlearner.learn(self._sourceField, self._markedUpEvents, self._counterExamples)

       # keep edited rules
       editedRules = [r for r in self._rules if r.isEdited()]
       # empty existing rules
       self._rules = []
       # for each learned rule
       for lrule in learnedRules:
          pattern = lrule.getPattern()
          fieldinfo = lrule.getFieldValues()
          # for each edited rule, if we have a match with the newly learned rule, don't add it
          for r in editedRules:
             if r._pattern() == pattern:
                break
          else: # add rule that doesn't match any edited rule
             rule = Rule(pattern, fieldinfo)
             self._rules.append(rule)
       self._rules.extend(editedRules)
Example #2
0
    def generateRules(self):
       learnedRules = fieldlearner.learn(self._sourceField, self._markedUpEvents, self._counterExamples)

       # keep edited rules
       editedRules = [r for r in self._rules if r.isEdited()]
       # empty existing rules
       self._rules = []
       # for each learned rule
       for lrule in learnedRules:
          pattern = lrule.getPattern()
          fieldinfo = lrule.getFieldValues()
          # for each edited rule, if we have a match with the newly learned rule, don't add it
          for r in editedRules:
             if r._pattern() == pattern:
                break
          else: # add rule that doesn't match any edited rule
             rule = Rule(pattern, fieldinfo)
             self._rules.append(rule)
       self._rules.extend(editedRules)
                            pos = 0
                            vals = splitExampleValues(exampleSet)
                            # PREVENT ABUSE
                            if len(vals) > MAX_FIELDS:
                                addMessage(args, _("Too many fields specified for extraction.  Using first %s values.") % MAX_FIELDS, CWARN)
                                vals = vals[:MAX_FIELDS] 
                            for example in vals:
                                pos += 1
                                llog("EXAMPLE: %s" % example)
                                if example in raw:
                                    llog("FOUND: example %s raw %s" % (example, raw))
                                    markedEvent["FIELDNAME%s" % pos] = example
                        markedEvents[i] = markedEvent
                    for i, me in markedEvents.items():
                        llog("ME: %s" % me)
                    rules = mfl.learn("_raw", markedEvents, counterExamples)

                    regexes = [rule.getPattern() for rule in rules]
                    llog("EXAMPLES: %s %s" % (examples, type(examples)))
                    llog("REGEXES: %s" % regexes)
                    # for id, e in markedEvents.items():
                    #    for rule in rules:
                    #        extractions = rule.findExtractions(e)
                    # regexes, extractions = mfl.learn(events, examples, args['counterexamples'])
                    if len(regexes) > 0:
                        regex = regexes[0]
                    
            except Exception, e:
                llog("PROBLEM: %s" % e)
                import traceback
                llog(traceback.format_exc())
Example #4
0
                        raw = event
                        markedEvent["_event"] = { sourceField : raw } 
                        for exampleSet in examples:
                            #  !! hack
                            pos = 0
                            vals = splitExampleValues(exampleSet)
                            for example in vals:
                                pos += 1
                                llog("EXAMPLE: %s" % example)
                                if example in raw:
                                    llog("FOUND: example %s raw %s" % (example, raw))
                                    markedEvent["FIELDNAME%s" % pos] = example
                        markedEvents[i] = markedEvent
                    for i, me in markedEvents.items():
                        llog("ME: %s" % me)
                    rules = mfl.learn("_raw", markedEvents, counterExamples)

                    regexes = [rule.getPattern() for rule in rules]
                    llog("EXAMPLES: %s %s" % (examples, type(examples)))
                    llog("REGEXES: %s" % regexes)
                    # for id, e in markedEvents.items():
                    #    for rule in rules:
                    #        extractions = rule.findExtractions(e)
                    # regexes, extractions = mfl.learn(events, examples, args['counterexamples'])
                    if len(regexes) > 0:
                        regex = regexes[0]
                    
            except Exception, e:
                llog("PROBLEM: %s" % e)
                import traceback
                llog(traceback.format_exc())