def run(route, prd, **kwargs):
"""
:type route: pyticas.ttypes.Route
:type prd: pyticas.ttypes.Period
:return:
"""
critical_density = kwargs.get(
'moe_critical_density',
get_system_config_info().moe_critical_density)
lane_capacity = kwargs.get('moe_lane_capacity',
get_system_config_info().moe_lane_capacity)
# load_data total flow data
tq_results = total_flow.run(route, prd)
tq_results = moe_helper.add_virtual_rnodes(tq_results, route)
# load_data density data
ks_results = density.run(route, prd)
ks_results = moe_helper.add_virtual_rnodes(ks_results, route)
# copy results to save LVMT values
lvmt_results = [res.clone() for res in ks_results]
# calculate LVMT
lvmt_data = _calculate_uvmt(tq_results, ks_results, prd.interval,
critical_density, lane_capacity, **kwargs)
for ridx, res in enumerate(lvmt_results):
res.data = lvmt_data[ridx]
return lvmt_results
def run(route, prd, **kwargs):
"""
:type route: pyticas.ttypes.Route
:type prd: pyticas.ttypes.Period
:return:
"""
critical_density = kwargs.get('critical_k', DEFAULT_CRITICAL_DENSITY)
lane_capacity = kwargs.get('lan_capacity', DEFAULT_LANE_CAPACITY)
# load_data total flow data
tq_results = total_flow.run(route, prd)
tq_results = moe_helper.add_virtual_rnodes(tq_results, route)
# load_data density data
ks_results = density.run(route, prd)
ks_results = moe_helper.add_virtual_rnodes(ks_results, route)
# copy results to save LVMT values
lvmt_results = [res.clone() for res in ks_results]
# calculate LVMT
lvmt_data = _calculate_lvmt(tq_results, ks_results, prd.interval,
critical_density, lane_capacity, **kwargs)
for ridx, res in enumerate(lvmt_results):
res.data = lvmt_data[ridx]
return lvmt_results
def run(route, prd, **kwargs):
"""
:type route: pyticas.ttypes.Route
:type prd: pyticas.ttypes.Period
:return:
"""
# load_data speed data
moe_congestion_threshold_speed = kwargs.pop("moe_congestion_threshold_speed",
get_system_config_info().moe_congestion_threshold_speed)
us = moe_helper.get_speed(route.get_stations(), prd, **kwargs)
us_results = moe_helper.add_virtual_rnodes(us, route)
us_data = [res.data for res in us_results]
us_data = spatial_avg.imputation(us_data)
# make empty whole_data for congested miles by copying speed whole_data and reseting data
cmh_results = [res.clone() for res in us_results]
for ridx, res in enumerate(cmh_results):
cmh_results[ridx].data = [0] * len(prd.get_timeline())
cmh_results[ridx].prd = prd
# calculate CMH
cm_data = _calculate_cmh(us_data, prd.interval, moe_congestion_threshold_speed, **kwargs)
for ridx, res in enumerate(cmh_results):
res.data = cm_data[ridx]
return cmh_results
def add_virtual_rnodes(results, route, **kwargs):
"""
:type results: list[RNodeData]
:type route: pyticas.ttypes.Route
:rtype: list[RNodeData]
"""
return moe_helper.add_virtual_rnodes(results, route, **kwargs)
def run(route, prd, **kwargs):
"""
:type route: pyticas.ttypes.Route
:type prd: pyticas.ttypes.Period
:return:
"""
rnode_list = route.get_stations()
# load_data vmt data
vmt_results = vmt.run(route, prd)
vmt_data = [res.data for res in vmt_results]
# load_data speed data
us_results = speed.run(route, prd)
us_results = moe_helper.add_virtual_rnodes(us_results, route)
us_data = [res.data for res in us_results]
# copy results to save VMT values
vht_results = [res.clone() for res in us_results]
# calculate VMT
vht_data = _calculate_vht(vmt_data, us_data, prd.interval, **kwargs)
for ridx, res in enumerate(vht_results):
res.data = vht_data[ridx]
return vht_results
def run(route, prd, **kwargs):
"""
:type route: pyticas.ttypes.Route
:type prd: pyticas.ttypes.Period
:return:
"""
# load_data speed data
us = moe_helper.get_speed(route.get_stations(), prd, **kwargs)
us_results = moe_helper.add_virtual_rnodes(us, route)
us_data = [res.data for res in us_results]
us_data = spatial_avg.imputation(us_data)
# make empty whole_data for STT by copying speed whole_data and reseting data
stt_results = [res.clone() for res in us_results]
for ridx, res in enumerate(stt_results):
stt_results[ridx].data = [0] * len(prd.get_timeline())
stt_results[ridx].prd = prd
# calculate STT
cm_data = _calculate_stt(us_data, prd.interval, **kwargs)
for ridx, res in enumerate(stt_results):
res.data = cm_data[ridx]
return stt_results
def run(route, prd, **kwargs):
"""
:type route: pyticas.ttypes.Route
:type prd: pyticas.ttypes.Period
:return:
"""
# load_data total flow data
tq_results = total_flow.run(route, prd)
tq_results = moe_helper.add_virtual_rnodes(tq_results, route)
tq_data = [res.data for res in tq_results]
return tq_results, tq_data
def run(route, prd, **kwargs):
"""
:type route: pyticas.ttypes.Route
:type prd: pyticas.ttypes.Period
:return:
"""
# load_data total flow data
ks_results = density.run(route, prd)
ks_results = moe_helper.add_virtual_rnodes(ks_results, route)
ks_data = [res.data for res in ks_results]
return ks_results, ks_data
def run(route, prd, **kwargs):
"""
:type route: pyticas.ttypes.Route
:type prd: pyticas.ttypes.Period
:return:
"""
rnode_list = route.get_stations()
# load_data total flow data
tq = moe_helper.get_total_flow(rnode_list, prd, **kwargs)
tq_results = moe_helper.add_virtual_rnodes(tq, route)
lane_data = [res.lanes for res in tq_results]
return lane_data
def run(route, prd, **kwargs):
"""
:type route: pyticas.ttypes.Route
:type prd: pyticas.ttypes.Period
:return:
"""
rnode_list = route.get_stations()
# load_data total flow data
us = moe_helper.get_speed(rnode_list, prd, **kwargs)
us_results = moe_helper.add_virtual_rnodes(us, route)
us_data = [res.data for res in us_results]
us_data = spatial_avg.imputation(us_data)
return us, us_results, us_data
def run(route, prd, **kwargs):
"""
:type route: pyticas.ttypes.Route
:type prd: pyticas.ttypes.Period
:return:
"""
ext_hour = kwargs.get('ext_hour', DEFAULT_END_HOUR_EXTENSION)
now = datetime.datetime.now()
ext_prd = prd.clone().extend_end_hour(ext_hour)
if ext_prd.end_date > datetime.datetime.now():
ext_prd.end_date = now
n_origin_data = len(prd.get_timeline())
# load_data speed data (load_data more data than given period)
us = moe_helper.get_speed(route.get_stations(), ext_prd, **kwargs)
us_results = moe_helper.add_virtual_rnodes(us, route)
us_data = [res.data for res in us_results]
us_data = spatial_avg.imputation(us_data)
# make empty whole_data for travel time by copying speed whole_data and reseting data
tt_results = [res.clone() for res in us_results]
for idx, res in enumerate(tt_results):
tt_results[idx].traffic_type = TrafficType.travel_time
for ridx, res in enumerate(tt_results):
tt_results[ridx].data = [-1] * n_origin_data
tt_results[ridx].prd = prd
# calculate travel time by increasing time index
for tidx in range(n_origin_data):
partial_data = [pd[tidx:] for pd in us_data]
tts = _calculate_tt(partial_data, prd.interval, **kwargs)
for ridx, tt_data in enumerate(tt_results):
tt_results[ridx].data[tidx] = tts[ridx]
return tt_results
def run(route, prd, **kwargs):
"""
:type route: pyticas.ttypes.Route
:type prd: pyticas.ttypes.Period
:return:
"""
rnode_list = route.get_stations()
# load_data total flow data
tq = moe_helper.get_total_flow(rnode_list, prd, **kwargs)
tq_results = moe_helper.add_virtual_rnodes(tq, route)
tq_data = [res.data for res in tq_results]
# copy whole_data to save VMT values
n_data = len(prd.get_timeline())
vmt_results = [res.clone() for res in tq_results]
# calculate VMT
vmt_data = _calculate_vmt(tq_data, prd.interval, **kwargs)
for ridx, res in enumerate(vmt_results):
res.data = vmt_data[ridx]
return vmt_results
def run(route, prd, **kwargs):
"""
:type route: pyticas.ttypes.Route
:type prd: pyticas.ttypes.Period
:return:
"""
# load_data vmt data
vmt_results = vmt.run(route, prd)
# load_data speed data
us_results = speed.run(route, prd)
us_results = moe_helper.add_virtual_rnodes(us_results, route)
# copy whole_data to save VMT values
dvh_results = [res.clone() for res in vmt_results]
# calculate VHT
dvh_data = _calculate_dvh(vmt_results, us_results, prd.interval, **kwargs)
for ridx, res in enumerate(dvh_results):
res.data = dvh_data[ridx]
return dvh_results
if __name__ == '__main__':
import os
from pyticas.infra import Infra
from pyticas import route
from pyticas import period
from pyticas.moe import writer
data_path = os.path.abspath(os.path.join(os.path.dirname(__file__), '../../../../../data'))
Infra.initialize(data_path)
infra = Infra.load_infra()
r = route.load_route_by_name('Route I-494 WB')
prd1 = period.create_period_from_string('2016-05-17 06:00:00', '2016-05-17 09:00:00', 300)
prd2 = period.create_period_from_string('2016-05-18 06:00:00', '2016-05-18 09:00:00', 300)
res1 = run(r, prd1)
res2 = run(r, prd2)
res = [res1, res2]
writer.write_cm(os.path.join(infra.get_path('moe', create=True), 'cm.xlsx'), r, res)
from pyticas.moe.mods import speed
ures1 = speed.run(r, prd1)
ures2 = speed.run(r, prd2)
ures1 = moe_helper.add_virtual_rnodes(ures1, r)
ures2 = moe_helper.add_virtual_rnodes(ures2, r)
ures = [ures1, ures2]
writer.write(os.path.join(infra.get_path('moe', create=True), 'u.xlsx'), r, ures)
