def quick_and_dirty_schedule_qjump_mapping(path_wmata_schedule_data,
analysis_routes):
xwalk_seg_pattern_stop_in = tribble_xwalk_seg_pattern_stop_in()
xwalk_wmata_route_dir_pattern = (wr.read_sched_db_patterns(
path=path_wmata_schedule_data,
analysis_routes=analysis_routes)[['direction', 'route',
'pattern']].drop_duplicates())
xwalk_seg_pattern_stop = (xwalk_seg_pattern_stop_in.merge(
xwalk_wmata_route_dir_pattern,
on=['route', 'direction']).reindex(columns=[
'route', 'pattern', 'direction', 'seg_name_id', 'stop_id',
'approx_time_qjump'
]).assign(approx_time_qjump=lambda df: pd.to_timedelta(
df.approx_time_qjump, unit="s")))
del xwalk_seg_pattern_stop_in
# 2. load segment-pattern crosswalk
# (could be loaded separately or summarized from above)
xwalk_seg_pattern = (xwalk_seg_pattern_stop.drop('stop_id',
1).drop_duplicates())
return xwalk_seg_pattern
import wmatarawnav as wr
executionTime = str(datetime.now() - begin_time).split('.')[0]
print("Run Time Section 1 Import Libraries and Set Global Parameters : {}".
format(executionTime))
print("*" * 100)
# 2 Read, analyze and summarize Schedule data
########################################################################################################################
print(
"Run Section 2: Read, analyze and summarize rawnav, WMATA schedule data..."
)
begin_time = datetime.now()
# Read the Wmata_Schedule data
wmata_schedule_dat = wr.read_sched_db_patterns(path=os.path.join(
path_source_data, "wmata_schedule_data", "Schedule_082719-201718.mdb"),
analysis_routes=analysis_routes)
wmata_schedule_gdf = (gpd.GeoDataFrame(wmata_schedule_dat,
geometry=gpd.points_from_xy(
wmata_schedule_dat.stop_lon,
wmata_schedule_dat.stop_lat),
crs='EPSG:4326').to_crs(epsg=wmata_crs))
# Make Output Directory
path_stop_summary = os.path.join(path_processed_data, "stop_summary.parquet")
if not os.path.isdir(path_stop_summary):
os.mkdir(path_stop_summary)
path_stop_index = os.path.join(path_processed_data, "stop_index.parquet")
if not os.path.isdir(path_stop_index):
"H4",
"EAST",
"irving_fifteenth_sixteenth_stub",
2368,
"H8",
"EAST",
"irving_fifteenth_sixteenth_stub",
2368,
"W47",
"EAST",
"irving_fifteenth_sixteenth_stub",
2368)
xwalk_wmata_route_dir_pattern = (wr.read_sched_db_patterns(
path=os.path.join(path_source_data, "wmata_schedule_data",
"Schedule_082719-201718.mdb"),
analysis_routes=analysis_routes).filter(
items=['direction', 'route', 'pattern']).drop_duplicates())
xwalk_seg_pattern_stop = (xwalk_seg_pattern_stop_in.merge(
xwalk_wmata_route_dir_pattern, on=['route', 'direction']).drop(
'direction',
1).reindex(columns=['route', 'pattern', 'seg_name_id', 'stop_id']))
del xwalk_seg_pattern_stop_in
xwalk_seg_pattern = (xwalk_seg_pattern_stop.drop('stop_id',
1).drop_duplicates())
# 3. load shapes
# Segments