def trip_to_geojson(trip, tl):
"""
Trips are the main focus of our current visualization, so they are most complex.
Each trip is represented as a feature collection with the following features:
- two features for the start and end places
- features for each stop in the trip
- features for each section in the trip
:param trip: the trip object to be converted
:param tl: the timeline used to retrieve related objects
:return: the geojson version of the trip
"""
feature_array = []
curr_start_place = tl.get_object(trip.data.start_place)
curr_end_place = tl.get_object(trip.data.end_place)
start_place_geojson = place_to_geojson(curr_start_place)
start_place_geojson["properties"]["feature_type"] = "start_place"
feature_array.append(start_place_geojson)
end_place_geojson = place_to_geojson(curr_end_place)
end_place_geojson["properties"]["feature_type"] = "end_place"
feature_array.append(end_place_geojson)
trip_tl = esdt.get_cleaned_timeline_for_trip(trip.user_id, trip.get_id())
stops = trip_tl.places
for stop in stops:
feature_array.append(stop_to_geojson(stop))
for i, section in enumerate(trip_tl.trips):
section_gj = section_to_geojson(section, tl)
feature_array.append(section_gj)
trip_geojson = gj.FeatureCollection(features=feature_array,
properties=trip.data)
trip_geojson.id = str(trip.get_id())
feature_array.extend(
geojson_incidents_in_range(trip.user_id, curr_start_place.data.exit_ts,
curr_end_place.data.enter_ts))
if trip.metadata.key == esda.CLEANED_UNTRACKED_KEY:
# trip_geojson.properties["feature_type"] = "untracked"
# Since the "untracked" type is not correctly handled on the phone, we just
# skip these trips until
# https://github.com/e-mission/e-mission-phone/issues/118
# is fixed
# TODO: Once it is fixed, re-introduce the first line in this block
# and remove the None check in get_geojson_for_timeline
return None
else:
trip_geojson.properties["feature_type"] = "trip"
return trip_geojson
def trip_to_geojson(trip, tl):
"""
Trips are the main focus of our current visualization, so they are most complex.
Each trip is represented as a feature collection with the following features:
- two features for the start and end places
- features for each stop in the trip
- features for each section in the trip
:param trip: the trip object to be converted
:param tl: the timeline used to retrieve related objects
:return: the geojson version of the trip
"""
feature_array = []
curr_start_place = tl.get_object(trip.data.start_place)
curr_end_place = tl.get_object(trip.data.end_place)
start_place_geojson = place_to_geojson(curr_start_place)
start_place_geojson["properties"]["feature_type"] = "start_place"
feature_array.append(start_place_geojson)
end_place_geojson = place_to_geojson(curr_end_place)
end_place_geojson["properties"]["feature_type"] = "end_place"
feature_array.append(end_place_geojson)
trip_tl = esdt.get_cleaned_timeline_for_trip(trip.user_id, trip.get_id())
stops = trip_tl.places
for stop in stops:
feature_array.append(stop_to_geojson(stop))
for i, section in enumerate(trip_tl.trips):
section_gj = section_to_geojson(section, tl)
feature_array.append(section_gj)
trip_geojson = gj.FeatureCollection(features=feature_array, properties=trip.data)
trip_geojson.id = str(trip.get_id())
feature_array.extend(geojson_incidents_in_range(trip.user_id,
curr_start_place.data.exit_ts,
curr_end_place.data.enter_ts))
if trip.metadata.key == esda.CLEANED_UNTRACKED_KEY:
# trip_geojson.properties["feature_type"] = "untracked"
# Since the "untracked" type is not correctly handled on the phone, we just
# skip these trips until
# https://github.com/e-mission/e-mission-phone/issues/118
# is fixed
# TODO: Once it is fixed, re-introduce the first line in this block
# and remove the None check in get_geojson_for_timeline
return None
else:
trip_geojson.properties["feature_type"] = "trip"
return trip_geojson
def trip_to_geojson(trip, tl):
"""
Trips are the main focus of our current visualization, so they are most complex.
Each trip is represented as a feature collection with the following features:
- two features for the start and end places
- features for each stop in the trip
- features for each section in the trip
:param trip: the trip object to be converted
:param tl: the timeline used to retrieve related objects
:return: the geojson version of the trip
"""
feature_array = []
curr_start_place = tl.get_object(trip.data.start_place)
curr_end_place = tl.get_object(trip.data.end_place)
start_place_geojson = place_to_geojson(curr_start_place)
start_place_geojson["properties"]["feature_type"] = "start_place"
feature_array.append(start_place_geojson)
end_place_geojson = place_to_geojson(curr_end_place)
end_place_geojson["properties"]["feature_type"] = "end_place"
feature_array.append(end_place_geojson)
trip_tl = esdt.get_cleaned_timeline_for_trip(trip.user_id, trip.get_id())
stops = trip_tl.places
for stop in stops:
feature_array.append(stop_to_geojson(stop))
for i, section in enumerate(trip_tl.trips):
# TODO: figure out whether we should do this at the model.
# The first section starts with the start of the trip. But the trip itself starts at the first
# point where we exit the geofence, not at the start place. That is because we don't really know when
# we left the start place. We can fix this in the model through interpolation. For now, we assume that the
# gap between the real departure time and the time that the trip starts is small, and just combine it here.
section_gj = section_to_geojson(section, tl)
feature_array.append(section_gj)
trip_geojson = gj.FeatureCollection(features=feature_array,
properties=trip.data)
trip_geojson.id = str(trip.get_id())
trip_geojson.properties["feature_type"] = "trip"
return trip_geojson
def trip_to_geojson(trip, tl):
"""
Trips are the main focus of our current visualization, so they are most complex.
Each trip is represented as a feature collection with the following features:
- two features for the start and end places
- features for each stop in the trip
- features for each section in the trip
:param trip: the trip object to be converted
:param tl: the timeline used to retrieve related objects
:return: the geojson version of the trip
"""
feature_array = []
curr_start_place = tl.get_object(trip.data.start_place)
curr_end_place = tl.get_object(trip.data.end_place)
start_place_geojson = place_to_geojson(curr_start_place)
start_place_geojson["properties"]["feature_type"] = "start_place"
feature_array.append(start_place_geojson)
end_place_geojson = place_to_geojson(curr_end_place)
end_place_geojson["properties"]["feature_type"] = "end_place"
feature_array.append(end_place_geojson)
trip_tl = esdt.get_cleaned_timeline_for_trip(trip.user_id, trip.get_id())
stops = trip_tl.places
for stop in stops:
feature_array.append(stop_to_geojson(stop))
for i, section in enumerate(trip_tl.trips):
# TODO: figure out whether we should do this at the model.
# The first section starts with the start of the trip. But the trip itself starts at the first
# point where we exit the geofence, not at the start place. That is because we don't really know when
# we left the start place. We can fix this in the model through interpolation. For now, we assume that the
# gap between the real departure time and the time that the trip starts is small, and just combine it here.
section_gj = section_to_geojson(section, tl)
feature_array.append(section_gj)
trip_geojson = gj.FeatureCollection(features=feature_array, properties=trip.data)
trip_geojson.id = str(trip.get_id())
trip_geojson.properties["feature_type"] = "trip"
return trip_geojson