def select_pred_words_effectiveness(self, numWords=None): assert self.resp_words is not None # Add Predictive Words if self._pred_data_tickers is None: self.__add_pred_data_tickers() self.create_data_sorting_array() # Select How Many Words if numWords is None: numWords = geometric(PRED_COUNT_GEOMETRIC_PARAM) + PRED_COUNT_FLOOR # Select Words count = 0 chosen = {} resp_word_names = [str(w) for w in self.resp_words] min_date = max([w.min_date for w in self.resp_words]) max_date = min([w.max_date for w in self.resp_words]) while (len(chosen) < numWords) and (count < numWords * 10): count += 1 # Avoid Infinite Loops # Select Words / Create Data Handle id_ = weighted_choice(self._pred_data_eff_array["prob"].iteritems(), self._total_prob) ticker = retrieve_DataSeriesTicker(self.hndl_DB.cursor, id_) hndl_Data = EMF_DataSeries_Handle(self.hndl_DB, ticker=ticker) # Select Words / Create Trans Handle hndl_Trns = EMF_Transformation_Handle(choice(self._pred_trns_ptrns)) # Select Words / Create Trans Handle / Add Parameters to Trans Handle hndl_Trns.parameters = self.__create_random_trns_params_pred() # Select Words / Create Word Handle hndl_Word = EMF_WordSeries_Handle(self.hndl_DB, hndl_Data, hndl_Trns) # Select Words / Ensure Word Validity # Select Words / Ensure Word Validity / Make sure Word Isn't Response Word wordName = str(hndl_Word) if wordName in resp_word_names: continue # Select Words / Ensure Word Validity / Make sure Word Isn't Already Taken if wordName in chosen: continue # Select Words / Ensure Word Validity / Make sure Dates Don't Conflict min_challenger = hndl_Word.min_date if min_challenger >= max_date: continue max_challenger = hndl_Word.max_date if max_challenger <= min_date: continue min_date = max(min_date, min_challenger) max_date = min(max_date, max_challenger) # Select Words / Add Word to Set chosen[wordName] = hndl_Word log.info("WORDSELECT: Predictive Words: Chose {0}".format(wordName)) # TEST: Delete log.info("WORDSELECT: Predictive Words: Chose {0}".format(chosen.keys())) self._pred_words = chosen.values() return self.pred_words
def select_pred_words_random(self, numWords=None): assert self.resp_words is not None # Add Predictive Words if self._pred_data_tickers is None: self.__add_pred_data_tickers() # Select How Many Words if numWords is None: numWords = geometric(PRED_COUNT_GEOMETRIC_PARAM) + PRED_COUNT_FLOOR log.info("WORDSELECT: Predictive Words: Choosing {0} words".format(numWords)) # Select Words count = 0 chosen = {} resp_word_names = [ str(w) for w in self.resp_words ] # TODO: Can make this a one-time calculation to avoid repitition min_date = max([w.min_date for w in self.resp_words]) max_date = min([w.max_date for w in self.resp_words]) while (len(chosen) < numWords) and (count < numWords * 10): count += 1 # Avoid Infinite Loops # Select Words / Create Data Handle hndl_Data = EMF_DataSeries_Handle(self.hndl_DB, ticker=choice(self._pred_data_tickers)) # Select Words / Create Trans Handle hndl_Trns = EMF_Transformation_Handle(choice(self._pred_trns_ptrns)) # Select Words / Create Trans Handle / Add Parameters to Trans Handle hndl_Trns.parameters = self.__create_random_trns_params_pred() # Select Words / Create Word Handle hndl_Word = EMF_WordSeries_Handle(self.hndl_DB, hndl_Data, hndl_Trns) # Select Words / Ensure Word Validity # Select Words / Ensure Word Validity / Make sure Word Isn't Response Word wordName = str(hndl_Word) if wordName in resp_word_names: continue # Select Words / Ensure Word Validity / Make sure Word Isn't Already Taken if wordName in chosen: continue # Select Words / Ensure Word Validity / Make sure Dates Don't Conflict min_challenger = hndl_Word.min_date if min_challenger >= max_date: continue max_challenger = hndl_Word.max_date if max_challenger <= min_date: continue min_date = max(min_date, min_challenger) max_date = min(max_date, max_challenger) # Select Words / Add Word to Set chosen[wordName] = hndl_Word log.info("WORDSELECT: Predictive Words: Chose {0}".format(chosen.keys())) self._pred_words = chosen.values() return self.pred_words
def select_pred_words_random(self, numWords=None): assert self._resp_word is not None # Add Predictive Words if self._pred_data_tickers is None: self.__add_pred_data_tickers() # Select How Many Words if numWords is None: numWords = geometric(PRED_COUNT_GEOMETRIC_PARAM) + PRED_COUNT_FLOOR log.info('WORDSELECT: Predictive Words: Choosing {0} words'.format(numWords)) # Select Words count = 0 chosen = {} min_date = self.resp_data_min_date if min_date is None: min_ = maxint max_date = self.resp_data_max_date if max_date is None: max_ = -maxint-1 while (len(chosen) < numWords) and (count < numWords*10): count += 1 # Avoid Infinite Loops # Select Words / Create Data Handle ticker = choice(self._resp_data_tickers) hndl_Data = EMF_DataSeries_Handle(self.hndl_DB, ticker=ticker) # Select Words / Create Trans Handle hndl_Trns = EMF_Transformation_Handle(choice(self._pred_trns_ptrns)) # Select Words / Create Trans Handle / Add Parameters to Trans Handle hndl_Trns.parameters = self.__create_random_trns_params() # Select Words / Create Word Handle hndl_Word = EMF_WordSeries_Handle(self.hndl_DB, hndl_Data, hndl_Trns) # Select Words / Ensure Word Validity # Select Words / Ensure Word Validity / Make sure Word Isn't Response Word wordName = str(hndl_Word) if wordName == str(self._resp_word): continue # Select Words / Ensure Word Validity / Make sure Dates Don't Conflict min_challenger = hndl_Word.min_date if min_challenger >= max_date: continue max_challenger = hndl_Word.max_date if max_challenger <= min_date: continue min_date = max(min_date, min_challenger) max_date = min(max_date, max_challenger) # Select Words / Add Word to Set chosen[wordName] = hndl_Word log.info('WORDSELECT: Predictive Words: Chose {0}'.format(wordName)) # TEST: Delete log.info('WORDSELECT:Predictive Words: Chose {0}'.format(chosen.keys())) self._pred_words = chosen.values() return self.pred_words
def select_pred_words_all_tickers(self, trns_ptrn=None, trns_kwargs=None, trns_rndm=False): self._pred_words = [] log.info('WORDSELECT: Predictive Words: Choosing All Data Tickers') if trns_ptrn is None: if trns_rndm: ticker = choice(self._pred_data_tickers) else: trns_ptrn = 'None' if self._pred_data_tickers is None: self.__add_pred_data_tickers() hndl_Trns = EMF_Transformation_Handle(trns_ptrn) if trns_kwargs is None: trns_kwargs = self.pred_trns_kwargs hndl_Trns.parameters = self.__create_random_trns_params(kwargs_list=trns_kwargs) log.info('WORDSELECT: Predictive Words: Chose {0} Transformation'.format(hndl_Trns)) for ticker in self._pred_data_tickers: hndl_Data = EMF_DataSeries_Handle(self.hndl_DB, ticker=ticker) hndl_Word = EMF_WordSeries_Handle(self.hndl_DB, hndl_Data, hndl_Trns) self._pred_words.append(hndl_Word)