def test_bunny(demand, network):
"""
Test to ensure that the most simple of networks and demand is working.
"""
EXAMPLE_DIR = os.path.join(os.getcwd(), "fasttrips", "Examples",
"Bunny_Hop")
INPUT_NETWORK = os.path.join(EXAMPLE_DIR, "networks", network)
INPUT_DEMAND = os.path.join(EXAMPLE_DIR, "demand", demand)
INPUT_CONFIG = os.path.join(EXAMPLE_DIR, "configs", "base")
OUTPUT_DIR = os.path.join(EXAMPLE_DIR, "output")
Run.run_fasttrips(input_network_dir=INPUT_NETWORK,
input_demand_dir=INPUT_DEMAND,
run_config=os.path.join(INPUT_CONFIG, "config_ft.txt"),
input_functions=os.path.join(INPUT_CONFIG,
'config_ft.py'),
input_weights=os.path.join(INPUT_CONFIG,
"pathweight_ft.txt"),
output_dir=OUTPUT_DIR,
output_folder=demand + "-" + network,
pathfinding_type="stochastic",
capacity=False,
iters=1,
OVERLAP="None",
dispersion=0.5)
def test_post_assignment():
out_folder = "post_assignment_test" # str(uuid.uuid4())
Run.run_fasttrips(input_network_dir=INPUT_NETWORK,
input_demand_dir=INPUT_DEMAND,
run_config=CONFIG_FILE,
input_weights=INPUT_WEIGHTS,
output_dir=OUTPUT_DIR,
output_folder=out_folder,
skim_config_file=SKIMMING_CONFIG,
iters=1)
files_exist(Path(OUTPUT_DIR) / out_folder)
def test_convergence():
'''
This test uses the learning and convergence gap keywords in the config.
'''
Run.run_fasttrips(
input_network_dir=INPUT_NETWORK,
input_demand_dir=INPUT_DEMAND,
run_config=CONFIG_FILE,
input_functions=INPUT_FUNCTIONS,
input_weights=INPUT_WEIGHTS,
output_dir=OUTPUT_DIR,
output_folder=OUTPUT_FOLDER,
capacity=True,
iters=10,
dispersion=0.50,
num_trips=10,
)
def run_convergence():
EXAMPLE_DIR = os.path.join(os.getcwd(), "fasttrips", "Examples",
"Springfield")
INPUT_NETWORK = os.path.join(EXAMPLE_DIR, "networks", "vermont")
INPUT_DEMAND = os.path.join(EXAMPLE_DIR, "demand", "simpson_zorn")
INPUT_CONFIG = os.path.join(EXAMPLE_DIR, "configs", "B")
OUTPUT_DIR = os.path.join(EXAMPLE_DIR, "output")
Run.run_fasttrips(
input_network_dir=INPUT_NETWORK,
input_demand_dir=INPUT_DEMAND,
run_config=CONFIG_FILE,
input_functions=INPUT_FUNCTIONS,
input_weights=INPUT_WEIGHTS,
output_dir=OUTPUT_DIR,
output_folder=OUTPUT_FOLDER,
pathfinding_type="stochastic",
capacity=True,
iters=4,
dispersion=0.50,
num_trips=10,
)
def test_psrc():
"""
Test to ensure that more complex network, PSRC, is working. Also a
useful benchmark for Partridge loader compared to transitfeed.
"""
Run.run_fasttrips(
input_network_dir=INPUT_NETWORK,
input_demand_dir=INPUT_DEMAND,
run_config=CONFIG_FILE,
input_weights=INPUT_WEIGHTS,
input_functions=INPUT_FUNCTIONS,
output_dir=OUTPUT_DIR,
output_folder="test_psrc",
max_stop_process_count=2,
pf_iters=2,
overlap_variable="None",
pathfinding_type="stochastic",
capacity=True,
iters=1,
OVERLAP="None",
dispersion=1.0,
num_trips=5,
)
def test_max_stop_process_count(stop_process_count, passengers_arrived):
r = Run.run_fasttrips(
input_network_dir=INPUT_NETWORK,
input_demand_dir=INPUT_DEMAND,
run_config=CONFIG_FILE,
input_weights=INPUT_WEIGHTS,
output_dir=OUTPUT_DIR,
output_folder="test_dispers_%4.2d" % stop_process_count,
overlap_variable="None",
pf_iters=2,
pathfinding_type="stochastic",
max_stop_process_count=stop_process_count,
iters=1,
num_trips=test_size,
dispersion=0.50)
assert passengers_arrived == r["passengers_arrived"]
def test_assignment_type(assignment_type):
OUTPUT_FOLDER = "assignment_type_%s" % (assignment_type)
r = Run.run_fasttrips(input_network_dir=INPUT_NETWORK,
input_demand_dir=INPUT_DEMAND,
run_config=CONFIG_FILE,
input_weights=INPUT_WEIGHTS,
output_dir=OUTPUT_DIR,
output_folder=OUTPUT_FOLDER,
overlap_variable="None",
pf_iters=2,
max_stop_process_count=2,
pathfinding_type=assignment_type,
iters=1,
dispersion=0.50,
num_trips=5)
assert r["passengers_arrived"] > 0
def test_user_classes():
r = Run.run_fasttrips(input_network_dir=INPUT_NETWORK,
input_demand_dir=INPUT_DEMAND,
run_config=CONFIG_FILE,
input_weights=INPUT_WEIGHTS,
input_functions=INPUT_FUNCTIONS,
output_dir=OUTPUT_DIR,
output_folder="test_userclasses",
max_stop_process_count=2,
pf_iters=2,
overlap_variable="None",
pathfinding_type="stochastic",
iters=1,
dispersion=0.50,
num_trips=5,
number_of_processes=1)
assert r["passengers_arrived"] > 0
def test_dispersion(dispersion_rate, utils_conversion_factor, passengers_arrived):
r = Run.run_fasttrips(
input_network_dir=INPUT_NETWORK,
input_demand_dir=INPUT_DEMAND,
run_config=os.path.join(INPUT_CONFIG, "config_ft.txt"),
input_weights=os.path.join(INPUT_CONFIG, "pathweight_ft.txt"),
output_dir=OUTPUT_DIR,
output_folder="test_dispers_%4.2f" % dispersion_rate,
max_stop_process_count=2,
utils_conversion_factor=utils_conversion_factor,
pf_iters=2,
overlap_variable="None",
pathfinding_type="stochastic",
iters=1,
dispersion=dispersion_rate,
num_trips=test_size)
assert passengers_arrived == r["passengers_arrived"]
def test_feedback(feedback_iters, capacity_const):
r = Run.run_fasttrips(input_network_dir=INPUT_NETWORK,
input_demand_dir=INPUT_DEMAND,
run_config=CONFIG_FILE,
input_weights=INPUT_WEIGHTS,
output_dir=OUTPUT_DIR,
output_folder="test_feedback_iters-%d_capConst-%s" %
(feedback_iters, capacity_const),
max_stop_process_count=2,
pf_iters=2,
overlap_variable="None",
utils_conversion_factor=10,
pathfinding_type="stochastic",
capacity=capacity_const,
iters=feedback_iters,
num_trips=5,
dispersion=0.50)
assert r["passengers_arrived"] > 0
def test_overlap(overlap_var, split_links):
r = Run.run_fasttrips(input_network_dir=INPUT_NETWORK,
input_demand_dir=INPUT_DEMAND,
run_config=CONFIG_FILE,
input_weights=INPUT_WEIGHTS,
output_dir=OUTPUT_DIR,
output_folder="test_overlap_var-%s_split-%s" %
(overlap_var, split_links),
max_stop_process_count=2,
pf_iters=2,
pathfinding_type="stochastic",
overlap_variable=overlap_var,
overlap_split_transit=split_links,
iters=1,
dispersion=0.50,
num_trips=5)
assert r["passengers_arrived"] > 0
def test_fares(ignore_PF_fares, ignore_EN_fares):
r = Run.run_fasttrips(input_network_dir=INPUT_NETWORK,
input_demand_dir=INPUT_DEMAND,
run_config=CONFIG_FILE,
input_weights=INPUT_WEIGHTS,
output_dir=OUTPUT_DIR,
output_folder="test_ignore_fares_PF-%s_EN-%s" %
(ignore_PF_fares, ignore_EN_fares),
pathfinding_type="stochastic",
max_stop_process_count=2,
pf_iters=2,
overlap_variable="None",
iters=1,
dispersion=0.50,
num_trips=5,
transfer_fare_ignore_pathfinding=ignore_PF_fares,
transfer_fare_ignore_pathenum=ignore_EN_fares)
assert r["passengers_arrived"] > 0
def test_overlap(overlap_var, split_links):
if overlap_var == "time" and sys.version_info > (3, 0):
pytest.xfail("python and pandas updates make time division fail for now Issue #172")
r = Run.run_fasttrips(
input_network_dir=INPUT_NETWORK,
input_demand_dir=INPUT_DEMAND,
run_config=CONFIG_FILE,
input_weights=INPUT_WEIGHTS,
output_dir=OUTPUT_DIR,
output_folder="test_overlap_var-%s_split-%s" % (overlap_var, split_links),
max_stop_process_count=2,
pf_iters=2,
pathfinding_type="stochastic",
overlap_variable=overlap_var,
overlap_split_transit=split_links,
iters=1,
dispersion=0.50,
num_trips=5)
assert r["passengers_arrived"] > 0
import os
from fasttrips import Run
# DIRECTORY LOCATIONS
EXAMPLE_DIR = os.path.abspath(os.path.dirname(__file__))
INPUT_NETWORK = os.path.join(EXAMPLE_DIR, 'networks', 'vermont')
INPUT_DEMAND = os.path.join(EXAMPLE_DIR, 'demand', 'general')
INPUT_CONFIG = os.path.join(EXAMPLE_DIR, 'configs', 'A')
OUTPUT_DIR = os.path.join(EXAMPLE_DIR, 'output')
OUTPUT_FOLDER = "general_run"
# INPUT FILE LOCATIONS
CONFIG_FILE = os.path.join(INPUT_CONFIG, 'config_ft.txt')
INPUT_WEIGHTS = os.path.join(INPUT_CONFIG, 'pathweight_ft.txt')
print("Running Fast-Trips in %s" % (EXAMPLE_DIR.split(os.sep)[-1:]))
Run.run_fasttrips(input_network_dir=INPUT_NETWORK,
input_demand_dir=INPUT_DEMAND,
run_config=CONFIG_FILE,
input_weights=INPUT_WEIGHTS,
output_dir=OUTPUT_DIR,
output_folder=OUTPUT_FOLDER,
pathfinding_type="stochastic",
overlap_variable="count",
overlap_split_transit=True,
iters=3,
dispersion=0.50)
import os
from fasttrips import Run
network = "psrc_1_1"
demand = "psrc_1_1"
config = "base"
out_folder = "seattle_base"
ex_dir = os.path.abspath(os.path.dirname(__file__))
print
"Running Fast-Trips in %s" % (ex_dir.split(os.sep)[-1:])
Run.run_fasttrips(
input_network_dir=os.path.join(ex_dir, "networks", network),
input_demand_dir=os.path.join(ex_dir, "demand", demand),
run_config=os.path.join(ex_dir, "configs", config, "config_ft.txt"),
input_weights=os.path.join(ex_dir, "configs", config, "pathweight_ft.txt"),
input_functions=os.path.join(ex_dir, "configs", config, 'config_ft.py'),
output_dir=os.path.join(ex_dir, "output"),
output_folder=out_folder,
pathfinding_type="stochastic",
overlap_variable="count",
overlap_split_transit=True,
iters=1,
dispersion=0.50)
import os
from fasttrips import Run
EXAMPLES_DIR = os.path.join(os.path.dirname(os.getcwd()),"fasttrips","Examples","test_scenario")
Run.run_fasttrips(
input_network_dir = os.path.join(EXAMPLES_DIR,"network"),
input_demand_dir = os.path.join(EXAMPLES_DIR,"demand_reg"),
run_config = os.path.join(EXAMPLES_DIR,"demand_reg","config_ft.txt"),
input_weights = os.path.join(EXAMPLES_DIR,"demand_reg","pathweight_ft.txt"),
output_dir = os.path.join(EXAMPLES_DIR,"output"),
output_folder = "example",
pathfinding_type = "stochastic",
overlap_variable = "count",
overlap_split_transit = True,
iters = 1,
dispersion = 0.50)
def test_pat_before_and_after():
"""
Test to ensure that some of the pathfinder trips are returned before preferred departure
or after preferred arrival.
"""
OUTPUT_FOLDER = 'pat_scenario'
r = Run.run_fasttrips(input_network_dir=INPUT_NETWORK,
input_demand_dir=INPUT_DEMAND,
run_config=CONFIG_FILE,
input_weights=INPUT_WEIGHTS,
output_dir=OUTPUT_DIR,
output_folder=OUTPUT_FOLDER,
pathfinding_type="stochastic",
overlap_variable="count",
iters=1,
dispersion=0.50)
links = pd.read_csv(os.path.join(OUTPUT_DIR, OUTPUT_FOLDER,
'pathset_links.csv'),
usecols=[
'person_trip_id', 'pathnum', 'linkmode', 'linknum',
'new_A_time', 'new_B_time'
],
parse_dates=['new_A_time', 'new_B_time'],
infer_datetime_format=True)
trips = pd.read_csv(os.path.join(INPUT_DEMAND, 'trip_list.txt'),
usecols=[
'person_trip_id', 'departure_time', 'arrival_time',
'time_target'
])
departure_link = links.loc[links.groupby(['person_trip_id',
'pathnum'])['linknum'].idxmin()]
# The C++ Pathfinder doesn't seem to respect the last egress leg from a preferred time perspective
arrival_link = links.loc[links[links.linkmode == 'transit'].groupby(
['person_trip_id', 'pathnum'])['linknum'].idxmax()]
network_date = links['new_A_time'].dt.date.unique()[0]
trips['arrival_time'] = trips['arrival_time'].apply(
lambda x: parse_date(network_date, x))
trips['departure_time'] = trips['departure_time'].apply(
lambda x: parse_date(network_date, x))
arrival_trips = trips[trips['time_target'] == 'arrival']
departure_trips = trips[trips['time_target'] == 'departure']
departures = pd.merge(departure_trips[['person_trip_id',
'departure_time']],
departure_link[['person_trip_id', 'new_A_time']],
on=['person_trip_id'])
arrivals = pd.merge(arrival_trips[['person_trip_id', 'arrival_time']],
arrival_link[['person_trip_id', 'new_B_time']],
on=['person_trip_id'])
early_departure = departures[
departures['new_A_time'] < departures['departure_time']]
size = early_departure.shape[0]
assert size > 0
confirm_size = early_departure[(
(early_departure['departure_time'] - early_departure['new_A_time']) /
np.timedelta64(1, 'm')) <= 10].shape[0]
assert size == confirm_size
late_arrivals = arrivals[arrivals['new_B_time'] > arrivals['arrival_time']]
size = late_arrivals.shape[0]
assert size > 0
confirm_size = \
late_arrivals[((late_arrivals['new_B_time'] - late_arrivals['arrival_time']) / np.timedelta64(1, 'm')) <= 10].shape[
0]
assert size == confirm_size
print "Input Level: %s" % (inp)
print "out folder %s\n" % (output_folder)
else:
if os.path.exists(output_folder):
print "Path exists [%s] -- skipping" % output_folder
else:
from fasttrips import Run
Run.run_fasttrips(
input_network_dir=network_inputs,
input_demand_dir=demand_inputs,
run_config=run_config,
input_weights=pathweights,
output_dir=base_dir,
iters=1,
output_folder=output_folder,
number_of_processes=proc,
dispersion=levels[lev]["disp"],
overlap_split_transit=levels[lev]["overlap_split"],
overlap_variable=levels[lev]["overlap"],
max_stop_process_count=levels[lev]["max_revisit"],
time_window=levels[lev]["dt"],
transfer_fare_ignore_pathfinding=levels[lev]
["transfer_fare_ignore_pathfinding"],
transfer_fare_ignore_pathenum=levels[lev]
["transfer_fare_ignore_pathenum"],
)
if args.norun:
print "TOTAL RUNS: %d" % (run_count)
