def readEventsFile(file, types):
"""Reads a MATSim events file
Parameters:
file (string): the path of the events file
types (string): the event types to consider
"""
return matsim.event_reader(file, types=types)
def count(persons, f):
counts = Counter({k: 0 for k in persons})
for ev in event_reader(p + f, types=["actstart"]):
if ev["actType"] == "leisure":
counts[ev["person"]] += 1
return counts
def read_events(f, act=None, lookup=True):
data = []
for ev in event_reader(f, types=["episimContact"]):
# Lookup maxgroup size of container
if lookup and ev["container"] in container.index:
ev["maxGroupSize"] = container.loc[ev["container"]].maxGroupSize
if not act or any(x in ev["actType"] for x in act):
data.append(ev)
return pd.DataFrame(data).astype(dtype={"duration": "float", "groupSize": "int",
"type": "str", "actType": "str", "container": "str"})
outfile = "drt-vehicles.json"
print("reading network", sys.argv[1])
network = matsim.read_network(sys.argv[1])
# Build link x/y lookup -- use 'to_node' (endpoint) of link
nodes = network.nodes >> mutate(to_node=X.node_id)
links = network.links >> inner_join(nodes, by="to_node") >> select(
X.link_id, X.x, X.y)
link_coords = {}
for link in links.values:
link_coords[link[0]] = (float(link[1]), float(link[2]))
print("reading events", sys.argv[2])
events = matsim.event_reader(sys.argv[2], types="actstart,actend")
# lookups by person's health status, coords, and timepoints
agents = {}
act_ends = {}
cur_location = {}
for event in events:
# only interested in DRT vehicle events
if event["actType"] != "DrtBusStop":
continue
person_id = event["person"]
time = int(event["time"])
print(len(facilities), "facilities found")
for day in [9]: # range(1, 2):
print(f"Processing day {day}")
# outfile hard-coded for now
fTrips = "trips.json"
fInfections = f"{day:03d}-infections.json"
magic_seconds = (day) * 86400
# trips are identical across all days; so only read them once.
whichEvents = "episimPersonStatus,actstart,actend"
events = matsim.event_reader(f"day_{day:03d}.xml.gz", types=whichEvents)
# lookups by person's health status, coords, and timepoints
agents = {}
infected_people = set()
act_ends = {}
cur_location = {}
facility_missing = 0
facility_found = 0
for event in events:
person_id = event["person"]
if person_id.startswith("freight"):
continue
x0=X.x, y0=X.y, to_node=X.to_node_x) >> inner_join(nodes, by="to_node")
>> select(X.link_id, X.x0, X.y0, X.x_y, X.y_y))
link_coords = {}
for link in links.values:
link_coords[link[0]] = (
float(link[1]),
float(link[2]),
float(link[3]),
float(link[4]),
)
print("reading events:", p_events)
events = matsim.event_reader(
p_events,
types=
"entered link,left link,vehicle enters traffic,vehicle leaves traffic,PersonEntersVehicle,PersonLeavesVehicle,DrtRequest submitted,PassengersRequest scheduled",
)
# lookups by person's health status, coords, and timepoints
agents = {}
drt_requests = {}
drt_request_list = []
for event in events:
# only interested in (1) DRT requests and (2) DRT vehicle events
if event["type"] == "DrtRequest submitted":
coord = link_coords[event["fromLink"]]
x, y = (0.5 * (coord[0] + coord[2]), 0.5 * (coord[1] + coord[3]))
lat, lon = coord_transformer.transform(x, y)
coord_from = [round(lon, 5), round(lat, 5)]
scenario_path = get_scenario_path(data_path, scenario_name)
vis_path = scenario_path + '/vis'
output_path = vis_path + '/custom'
try:
os.mkdir(output_path)
except FileExistsError:
pass
# read shp files
shp_files_path = vis_path + '/genet_standard_output/shp_files'
network_path = shp_files_path + '/network_links.shp'
network = gpd.read_file(network_path)
# stream through events
events = matsim.event_reader(scenario_path +
'/output/output_events.xml.gz',
types='entered link')
link_counts = defaultdict(int)
for event in tqdm(events):
if event['type'] == 'entered link':
link_counts[event['link']] += 1
link_counts = pd.DataFrame.from_dict(link_counts,
orient='index',
columns=['count'
]).rename_axis('link_id')
# merge data
network_counts = network.rename(columns={
'id': 'link_id'
}).merge(link_counts, on='link_id')
sample_rate = 10
# disease status numeric codes
disease_code = {
"susceptible": 0,
"infectedButNotContagious": 1,
"contagious": 2,
}
#outfile hard-coded for now
outfile = '00' + str(day) + '-infections.json'
# magic_seconds = 691100 # day 8
magic_seconds = day * 86400 # 345600 # 691200 # 345600
events = matsim.event_reader("day_00" + str(day) + ".xml.gz",
types="episimPersonStatus,actstart,actend")
# lookups by person's health status, coords, and timepoints
agents = {}
infected_people = set()
act_ends = {}
cur_location = {}
for event in events:
person_id = event["person"]
if person_id.startswith("freight"):
continue
time = int(event["time"] - magic_seconds)
if time < 0: