def users_with_data_in_experiment_periods(userloads, user_ids): """Return a list of the users with no missing data in two specific, hard-coded periods.""" return users_with_data_in_periods(userloads, user_ids, ul.experiment_periods())
sys.stdout.flush() tempfeeder_nodup.read_all() print "Done reading." tempfeeder_dup.close() tempfeeder_nodup.close() print "Checking for highres meters..." sys.stdout.flush() highres = find_highres_meters(tempfeeder_nodup) print "Narrowing to users with data in experiment periods..." sys.stdout.flush() highres_few_missing = \ users_with_data_in_experiment_periods(tempfeeder_nodup, highres) print "Checking for duplicates." sys.stdout.flush() keepers = check_remove_userload_dupes(tempfeeder_nodup, highres_few_missing) print "Removing manually screened IDs" keepers = remove_manually_screened_ids(keepers) print len(keepers), "candidates for experiment:", keepers path = "keepers.pickle" print "Pickling the keepers to %s." % path with open(path, "w") as f: pickle.dump(keepers, f) path = os.path.join(ul.DATA_DIR, "Experiment timeseries.pdf") print "Plotting all selected timeseries to %s..." % path plot_to_pdf(tempfeeder_nodup, keepers, path, ul.experiment_periods()) print "Storing experiment user IDs to HDF5 file." for path in (tempfeeder_dup.path, tempfeeder_nodup.path): store_user_ids(keepers, path, "cln_pred_exp_ids", "IDs of meters selected for clean+predict experiment early 2012.")
tempfeeder_nodup.read_all() print "Done reading." tempfeeder_dup.close() tempfeeder_nodup.close() print "Checking for highres meters..." sys.stdout.flush() highres = find_highres_meters(tempfeeder_nodup) print "Narrowing to users with data in experiment periods..." sys.stdout.flush() highres_few_missing = \ users_with_data_in_experiment_periods(tempfeeder_nodup, highres) print "Checking for duplicates." sys.stdout.flush() keepers = check_remove_userload_dupes(tempfeeder_nodup, highres_few_missing) print "Removing manually screened IDs" keepers = remove_manually_screened_ids(keepers) print len(keepers), "candidates for experiment:", keepers path = "keepers.pickle" print "Pickling the keepers to %s." % path with open(path, "w") as f: pickle.dump(keepers, f) path = os.path.join(ul.DATA_DIR, "Experiment timeseries.pdf") print "Plotting all selected timeseries to %s..." % path plot_to_pdf(tempfeeder_nodup, keepers, path, ul.experiment_periods()) print "Storing experiment user IDs to HDF5 file." for path in (tempfeeder_dup.path, tempfeeder_nodup.path): store_user_ids( keepers, path, "cln_pred_exp_ids", "IDs of meters selected for clean+predict experiment early 2012.")