def main():
parser = argparse.ArgumentParser(
description="Calculate Condel score")
parser.add_argument("db_path", metavar="DB_PATH",
help="Functional scores database")
parser.add_argument("weights_path", metavar="WEIGHTS",
help="File containing the scores weights and cutoffs")
parser.add_argument("-p", "--predictors", dest="predictors", metavar="PREDICTORS",
help="Comma separated list of predictors")
parser.add_argument("-u", "--updated-predictor", dest="updated_predictor", metavar="NAME",
help="Updated predictor name")
bglogging.add_logging_arguments(parser)
args = parser.parse_args()
bglogging.initialize(args)
log = bglogging.get_logger("calculate")
log.info("Opening functional scores database ...")
db = FannsSQLiteDb(args.db_path)
db.open()
updated_predictor = args.updated_predictor or "CONDEL"
predictors = set([p["id"] for p in db.predictors()])
if updated_predictor not in predictors:
log.info(" Creating predictor {} ...".format(updated_predictor))
db.add_predictor(updated_predictor, FannsDb.CALCULATED_PREDICTOR_TYPE, source=predictors)
log.info("Loading state ...")
state = load_weights(args.weights_path)
avail_predictors, precision, step, stats = [state[k] for k in ["predictor_names", "precision", "step", "stats"]]
if args.predictors is not None:
predictors = [p for p in [p.strip() for p in args.predictors.split(",")] if p in avail_predictors]
if len(predictors) == 0:
log.error("Unknown predictors: {}".format(args.predictors))
log.error("Available predictor names are: {}".format(", ".join(avail_predictors)))
exit(-1)
else:
predictors = avail_predictors
log.info("Available predictors: {}".format(", ".join(avail_predictors)))
log.info("Selected predictors: {}".format(", ".join(predictors)))
log.info("Calculating ...")
start_time = partial_start_time = time.time()
try:
for num_rows, row in enumerate(db.query_scores(predictors=predictors), start=1):
scores = row["scores"]
condel = wsum = 0
for predictor, score in scores.items():
if score is None:
continue
predictor_stats = stats[predictor]
rmin, rmax, dim, size, cdp, cdn, cutoff = [predictor_stats[k] for k in [
"rmin", "rmax", "dim", "size", "cdp", "cdn", "cutoff"]]
if predictor in PREDICTOR_TRANSFORM:
score = PREDICTOR_TRANSFORM[predictor](score)
r = (score - rmin) / dim
index = int(r * size) if score < rmax else size - 1
if score < cutoff:
w = 1 - cdn[index]
else:
w = 1 - cdp[index]
wsum += w
condel += w * score
#log.info("{}={}, w={} -> {}".format(predictor_name, score, w, score * w))
if wsum != 0:
condel /= wsum
d = {updated_predictor : condel}
db.update_scores(row["id"], d)
#log.info(">>> CONDEL={}".format(condel))
else:
log.warn("wsum = 0, condel={}, scores={}".format(condel, repr(scores)))
partial_time = time.time() - partial_start_time
if partial_time > 5.0:
partial_start_time = time.time()
elapsed_time = time.time() - start_time
log.debug(" {} rows, {:.1f} rows/second".format(hsize(num_rows), num_rows / elapsed_time))
log.info("Commit ...")
db.commit()
except KeyboardInterrupt:
log.warn("Interrupted by Ctrl-C")
db.rollback()
except:
db.rollback()
raise
finally:
db.close()
