diff --git a/idq/batch.py b/idq/batch.py index 5a6de9aeefbe2461be4bdeebac9b73cf79bb88db..5d994980075d73535346845df60e565e7e71af70 100644 --- a/idq/batch.py +++ b/idq/batch.py @@ -700,7 +700,7 @@ def calibrate( config_path, data_id=None, preferred=False, - use_training_set=False, + use_training_set=True, ): """ calibrate the classifier predictions based on historical data diff --git a/idq/calibration.py b/idq/calibration.py index 028d63dd5cec67e71641eb044ff3ccd4e5051a58..3ec4b1488d35ee417ffc9190ced0a2e92d27951a 100644 --- a/idq/calibration.py +++ b/idq/calibration.py @@ -30,8 +30,8 @@ DEFAULT_MAXB = 1e0 DEFAULT_TOL = 1e-4 DEFAULT_DLOGLIKE = 1 -DEFAULT_GLITCH_B = 1 / 24. -DEFAULT_CLEAN_B = 1 / 12. +DEFAULT_GLITCH_B = 1 / 24.0 +DEFAULT_CLEAN_B = 1 / 12.0 DEFAULT_RATE_ESTIMATION = "livetime" diff --git a/idq/reports.py b/idq/reports.py index a4cca4b294fbb1d45fea5d5015dbc16db35aec55..9ec97326b14360d9e79fec75d8884c0330c77f70 100644 --- a/idq/reports.py +++ b/idq/reports.py @@ -272,33 +272,36 @@ class Report(object): "found %d timeseries for %s" % (len(series[nickname]), nickname) ) + model_hashes = { + s.model_id for nickname in nicknames for s in series[nickname] + } + data_start = min(names.hash2start_end(hash_)[0] for hash_ in model_hashes) + # find calibration maps logger.info( "finding calibration maps within [%.3f, %.3f) based on timeseries" - % (self.start, self.end) + % (data_start, self.end) ) - calib_starts = {} for nickname in nicknames: calibration_ids = {s.calibration_id for s in series[nickname]} unique_ids = {names.hash2id(calib_id) for calib_id in calibration_ids} calibmaps[nickname] = find_calibration_maps( - self.config, self.start, self.end, nickname, hashes=calibration_ids + self.config, data_start, self.end, nickname, hashes=calibration_ids ) logger.info( "found %d calibration maps out of %d requested for %s" % (len(calibmaps[nickname]), len(unique_ids), nickname) ) - calib_starts[nickname] = min( - map_.start for map_ in calibmaps[nickname].values() - ) # find models - logger.info("finding models based on calibration map metadata") + logger.info( + "finding models within [%.3f, %.3f) based on timeseries" + % (data_start, self.end) + ) for nickname in nicknames: model_ids = {s.model_id for s in series[nickname]} - start_time = calib_starts[nickname] models[nickname] = find_models( - self.config, start_time, self.end, nickname, hashes=model_ids + self.config, data_start, self.end, nickname, hashes=model_ids ) logger.info( "found %d models out of %d requested for %s"