# write the joined one
join_filename = os.path.join(dir1, "ft_compare_performance.csv")
df_perf_diff.to_csv(join_filename, sep=",", index=False)
FastTripsLogger.info("Wrote joined performance info to %s" % join_filename)
if __name__ == "__main__":
if len(sys.argv) != 3:
print USAGE
print sys.argv
sys.exit(2)
OUTPUT_DIR1 = sys.argv[1]
OUTPUT_DIR2 = sys.argv[2]
fasttrips.setupLogging(os.path.join(OUTPUT_DIR1, "ft_compare_info.log"),
os.path.join(OUTPUT_DIR1, "ft_compare_debug.log"),
logToConsole=True)
pd.set_option('display.width', 300)
for output_file in [
"ft_output_passengerPaths.txt", "ft_output_passengerTimes.txt",
"ft_output_loadProfile.txt"
]:
compare_file(OUTPUT_DIR1, OUTPUT_DIR2, output_file)
compare_pathset(OUTPUT_DIR1, OUTPUT_DIR2)
compare_performance(OUTPUT_DIR1, OUTPUT_DIR2)
elif str(df_diff[col1].dtype) == 'object':
status = "%d/%d objects differ" % (len(df_diff.loc[df_diff[coldiff]==True]), len(df_diff))
elif str(df_diff[col1].dtype)[:3] == 'int':
status = "Values differ by [% 8.2f,% 8.2f] with %d values differing" % (df_diff[coldiff].min(), df_diff[coldiff].max(), len(df_diff.loc[df_diff[coldiff]!=0]))
else:
status = "Values differ by [% 8.2f,% 8.2f] with mean % 8.2f" % (df_diff[coldiff].min(), df_diff[coldiff].max(), df_diff[coldiff].mean())
FastTripsLogger.info(" %-20s %s" % (colname, status))
new_cols.extend([col1, col2, coldiff])
# df_diff = df_diff[new_cols]
if __name__ == "__main__":
if len(sys.argv) != 3:
print USAGE
print sys.argv
sys.exit(2)
OUTPUT_DIR1 = sys.argv[1]
OUTPUT_DIR2 = sys.argv[2]
fasttrips.setupLogging("ft_compare_info.log", "ft_compare_debug.log", logToConsole=True)
pandas.set_option('display.width', 300)
for output_file in ["ft_output_passengerPaths.dat",
"ft_output_passengerTimes.dat",
"ft_output_loadProfile.dat"]:
compare_file(OUTPUT_DIR1, OUTPUT_DIR2, output_file)
df2.drop([fasttrips.Performance.PERFORMANCE_COLUMN_TIME_LABELING, fasttrips.Performance.PERFORMANCE_COLUMN_TIME_ENUMERATING], axis=1, inplace=True)
df_perf_diff = df1.merge(right=df2, how='outer', on=['iteration','trip_list_id_num'], suffixes=('_1','_2'))
# write the joined one
join_filename = os.path.join(dir1, "ft_compare_performance.csv")
df_perf_diff.to_csv(join_filename, sep=",", index=False)
FastTripsLogger.info("Wrote joined performance info to %s" % join_filename)
if __name__ == "__main__":
if len(sys.argv) != 3:
print USAGE
print sys.argv
sys.exit(2)
OUTPUT_DIR1 = sys.argv[1]
OUTPUT_DIR2 = sys.argv[2]
fasttrips.setupLogging(os.path.join(OUTPUT_DIR1, "ft_compare_info.log"),
os.path.join(OUTPUT_DIR1, "ft_compare_debug.log"), logToConsole=True)
pandas.set_option('display.width', 300)
for output_file in ["ft_output_passengerPaths.txt",
"ft_output_passengerTimes.txt",
"ft_output_loadProfile.txt"]:
compare_file(OUTPUT_DIR1, OUTPUT_DIR2, output_file)
compare_pathset(OUTPUT_DIR1, OUTPUT_DIR2)
compare_performance(OUTPUT_DIR1, OUTPUT_DIR2)
print sys.argv
sys.exit(2)
INPUT_DIR, subdir = os.path.split(sys.argv[1])
OUTPUT_DIR = sys.argv[2]
test_pat = re.compile(r"pax(\d+)_(deterministic|stochastic)_iter(\d+)_(cap\d+|nocap)")
if not os.path.exists(OUTPUT_DIR): os.mkdir(OUTPUT_DIR)
pandas.set_option('display.width', 300)
m = test_pat.match(subdir)
print "subdir = [%s]" % subdir
if not os.path.exists(os.path.join(OUTPUT_DIR, subdir)):
os.mkdir(os.path.join(OUTPUT_DIR, subdir))
fasttrips.setupLogging(os.path.join(OUTPUT_DIR,subdir,"ft_info.log"),
os.path.join(OUTPUT_DIR,subdir,"ft_debug.log"),
logToConsole=True)
ft = fasttrips.FastTrips(os.path.join(INPUT_DIR, subdir))
if m.group(2) == "deterministic":
fasttrips.Assignment.ASSIGNMENT_TYPE = fasttrips.Assignment.ASSIGNMENT_TYPE_DET_ASGN
elif m.group(2) == "stochastic":
fasttrips.Assignment.ASSIGNMENT_TYPE = fasttrips.Assignment.ASSIGNMENT_TYPE_STO_ASGN
fasttrips.Assignment.ITERATION_FLAG = int(m.group(3))
if m.group(4) == "nocap":
fasttrips.Assignment.CAPACITY_CONSTRAINT = False
else:
fasttrips.Assignment.CAPACITY_CONSTRAINT = True