Struct sim::analytics::Analytics

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pub struct Analytics {
Show 16 fields
    pub road_thruput: TimeSeriesCount<RoadID>,
    pub intersection_thruput: TimeSeriesCount<IntersectionID>,
    pub traffic_signal_thruput: TimeSeriesCount<CompressedMovementID>,
    pub demand: BTreeMap<MovementID, usize>,
    pub bus_arrivals: Vec<(Time, CarID, TransitRouteID, TransitStopID)>,
    pub passengers_boarding: BTreeMap<TransitStopID, Vec<(Time, TransitRouteID, Duration)>>,
    pub passengers_alighting: BTreeMap<TransitStopID, Vec<(Time, TransitRouteID)>>,
    pub started_trips: BTreeMap<TripID, Time>,
    pub finished_trips: Vec<(Time, TripID, TripMode, Option<Duration>)>,
    pub problems_per_trip: BTreeMap<TripID, Vec<(Time, Problem)>>,
    pub trip_log: Vec<(Time, TripID, Option<PathRequest>, TripPhaseType)>,
    pub intersection_delays: BTreeMap<IntersectionID, Vec<(u8, Time, Duration, AgentType)>>,
    pub parking_lane_changes: BTreeMap<LaneID, Vec<(Time, bool)>>,
    pub parking_lot_changes: BTreeMap<ParkingLotID, Vec<(Time, bool)>>,
    pub(crate) alerts: Vec<(Time, AlertLocation, String)>,
    record_anything: bool,

}
Expand description

As a simulation runs, different pieces emit Events. The Analytics object listens to these, organizing and storing some information from them. The UI queries Analytics to draw time-series and display statistics.

For all maps whose weekday scenario fully runs, the game’s release includes some “prebaked results.” These are just serialized Analytics after running the simulation on a map without any edits for the full day. This is the basis of A/B testing – the player can edit the map, start running the simulation, and compare the live Analytics to the prebaked baseline Analytics.

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§road_thruput: TimeSeriesCount<RoadID>§intersection_thruput: TimeSeriesCount<IntersectionID>§traffic_signal_thruput: TimeSeriesCount<CompressedMovementID>§demand: BTreeMap<MovementID, usize>

Most fields in Analytics are cumulative over time, but this is just for the current moment in time.

§bus_arrivals: Vec<(Time, CarID, TransitRouteID, TransitStopID)>§passengers_boarding: BTreeMap<TransitStopID, Vec<(Time, TransitRouteID, Duration)>>

For each passenger boarding, how long did they wait at the stop?

§passengers_alighting: BTreeMap<TransitStopID, Vec<(Time, TransitRouteID)>>§started_trips: BTreeMap<TripID, Time>§finished_trips: Vec<(Time, TripID, TripMode, Option<Duration>)>

Finish time, ID, mode, trip duration if successful (or None if cancelled)

§problems_per_trip: BTreeMap<TripID, Vec<(Time, Problem)>>

Record different problems that each trip encounters.

§trip_log: Vec<(Time, TripID, Option<PathRequest>, TripPhaseType)>§intersection_delays: BTreeMap<IntersectionID, Vec<(u8, Time, Duration, AgentType)>>

Only for traffic signals. The u8 is the movement index from a CompressedMovementID.

§parking_lane_changes: BTreeMap<LaneID, Vec<(Time, bool)>>

Per parking lane or lot, when does a spot become filled (true) or free (false)

§parking_lot_changes: BTreeMap<ParkingLotID, Vec<(Time, bool)>>§alerts: Vec<(Time, AlertLocation, String)>§record_anything: bool

For benchmarking, we may want to disable collecting data.

Implementations§

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impl Analytics

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pub fn new(record_anything: bool) -> Analytics

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pub fn event(&mut self, ev: Event, time: Time, map: &Map)

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pub fn record_demand(&mut self, path: &Path, map: &Map)

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pub fn finished_trip_time(&self, trip: TripID) -> Option<Duration>

Ignores the current time. Returns None for cancelled trips.

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pub fn both_finished_trips( &self, now: Time, before: &Analytics ) -> Vec<(TripID, Duration, Duration, TripMode)>

Returns pairs of trip times for finished trips in both worlds. (ID, before, after, mode)

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pub fn get_trip_phases(&self, trip: TripID, map: &Map) -> Vec<TripPhase>

If calling on prebaked Analytics, be careful to pass in an unedited map, to match how the simulation was originally run. Otherwise the paths may be nonsense.

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pub fn get_all_trip_phases(&self) -> BTreeMap<TripID, Vec<TripPhase>>

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pub fn active_agents(&self, now: Time) -> Vec<(Time, usize)>

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pub fn parking_lane_availability( &self, now: Time, l: LaneID, capacity: usize ) -> Vec<(Time, usize)>

Returns the free spots over time

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pub fn parking_lot_availability( &self, now: Time, pl: ParkingLotID, capacity: usize ) -> Vec<(Time, usize)>

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fn parking_spot_availability( now: Time, changes: &[(Time, bool)], capacity: usize ) -> Vec<(Time, usize)>

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pub fn problems_per_intersection( &self, now: Time, id: IntersectionID ) -> Vec<(ProblemType, Vec<(Time, usize)>)>

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pub fn problems_per_lane( &self, now: Time, id: LaneID ) -> Vec<(ProblemType, Vec<(Time, usize)>)>

Trait Implementations§

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impl Clone for Analytics

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fn clone(&self) -> Analytics

Returns a copy of the value. Read more
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fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source. Read more
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impl Default for Analytics

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fn default() -> Analytics

Returns the “default value” for a type. Read more
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impl<'de> Deserialize<'de> for Analytics

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fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>
where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer. Read more
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impl Serialize for Analytics

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fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>
where __S: Serializer,

Serialize this value into the given Serde serializer. Read more

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