def main(argv): l_config = renter_constants.learned_config if len(argv) == 2: # - Convert the raw data to SETI. which = argv[1] if which == '1': l_config = renter_constants.learned_config2 elif which == '2': l_config = renter_constants.learned_config2 l_config.raw_filenames = ['data/from_haoran/clean_*.csv'] elif which == '3' or which =='regression_test': l_config = renter_constants.learned_config2 l_config.raw_filenames = ['data/new_data_set/clean_full_all.csv'] #['data/round1/prices_samples_full_0921212303_all.csv'] if which == 'regression_test': model_cfg.change_dirs('tmp/regression_test', l_config.model_configs) setis = logs_to_seti.generate_seti(l_config.raw_filenames) #setis = setis[0:1000] print 'Generated: %d setis' % len(setis) if _DEBUG: f = open('tmp/cur_run_setis.csv', 'wb') setis_txt = '\n'.join([str(seti) for seti in setis]) f.write(setis_txt) f.close() run_pipeline.run(l_config.model_configs, setis) return { 'setis': setis, 'l_config': l_config }
def testLogsToSeti(): # First three lines are copied from tdg_v0.csv csvs = ['testdata/logs_to_seti_csv0.csv'] # s0. dob: 05/06/1989. gender:f # s1. dob: 05/06/1949. gender:m s0 = seti.create_seti(19.15, bfs=[('has_bite_dog', 'N')], cfs=[('dob', 26.0)]) s1 = seti.create_seti(22.51, bfs=[('has_bite_dog', 'N')], cfs=[('dob', 66.0)]) # Test model gets created and loaded. # Test that we can score one example. setis = logs_to_seti.generate_seti(csvs, for_test=True) wants = [s0, s1] for i in xrange(len(setis)): assertEquals(str(wants[i]), str(setis[i]))