polaris.analyze.result_kpis.ResultKPIs

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polaris.analyze.result_kpis.ResultKPIs#

class polaris.analyze.result_kpis.ResultKPIs(inputs: PolarisInputs, cache_dir: Path, population_scale_factor: float, include_kpis: Tuple[KPITag, ...], exclude_kpis: Tuple[KPITag, ...] = (KPITag.HIGH_MEMORY, KPITag.BROKEN))#

Bases: object

This class provides an easy way to extract relevant metrics for a single simulation run of POLARIS. The easiest way to generate an instance is via the factory method from_iteration which takes the path to the outputs of a simulation run (or a ConvergenceIteration())

from polaris.analyze.result_kpi import ResultKPIs

kpis = ResultKPIs.from_iteration(ref_project_dir / f"{city}_iteration_2")

Metric comparison plots can then be generated in a notebook using:

results = KpiComparator()
results.add_run(kpis, 'an-arbitrary-label')
results.plot_mode_share()
results.plot_vmt()
results.plot_vmt_by_link_type()

Any number of runs can be added using add_run up to the limit of readability on the generated plots.

__init__(inputs: PolarisInputs, cache_dir: Path, population_scale_factor: float, include_kpis: Tuple[KPITag, ...], exclude_kpis: Tuple[KPITag, ...] = (KPITag.HIGH_MEMORY, KPITag.BROKEN))#

Methods

__init__(inputs, cache_dir, ...[, exclude_kpis])

available_metrics()

cache_all_available_metrics([verbose, ...])

cached_metrics()

close()

from_args(files, iteration_dir[, ...])

from_dir(iteration_dir, **kwargs)

Create a KPI object from a given directory.

from_iteration(iteration, **kwargs)

Create a KPI object from a ConvergenceIteration object.

get_cached_kpi_value(kpi_name[, skip_cache, ...])

get_kpi_value(kpi_name)

has_cached_kpi(kpi_name)

metric_activity_distances()

metric_activity_duration_distribution()

metric_activity_rate_distribution()

metric_activity_start_distribution()

metric_activity_start_time_distributions()

metric_average_vehicle_ownership()

This metric retrieves the average household vehicle ownership from the synthetic population in the output

metric_avo_by_tnc_operator()

metric_calibration_act_gen()

metric_calibration_act_gen_planned()

metric_calibration_boardings()

metric_calibration_destination()

metric_calibration_mode_share()

metric_calibration_mode_share_planned()

metric_calibration_timing()

metric_calibration_timing_planned()

metric_count_validation()

metric_county_to_county_demand()

metric_distance_by_act_type()

metric_escooter_utilization_at_garage()

metric_ev_charging()

metric_ev_consumption()

metric_executed_activity_mode_share_by_income()

metric_executed_modes()

metric_file_sizes()

metric_flow_density_fd()

metric_freight_distance_distribution()

metric_freight_mode_share()

metric_freight_mode_trade_type(**kwargs)

metric_freight_shipping_cost()

metric_freight_trip()

metric_gaps()

metric_garage_access_w_escooters()

metric_mode_shares()

metric_network_gaps_by_hour()

metric_network_gaps_by_link_type()

metric_num_hh()

metric_num_hh_by_hh_size()

metric_num_persons_by_age_band_10()

metric_num_persons_by_age_band_5()

metric_parking_delay_stats()

metric_parking_share()

metric_parking_stats()

metric_parking_utilization()

metric_planned_activity_start_time_distributions()

metric_planned_modes()

metric_planned_rmse_vs_observed()

metric_polaris_exe()

metric_population()

metric_rmse_vs_observed()

metric_road_pricing()

metric_skim_stats()

metric_sov_parking_access_time()

metric_spatial_trips()

metric_summary()

metric_tnc_request_stats()

metric_tnc_stats()

metric_tnc_trip_stats()

metric_traffic_cumulative_gap()

This metric is slow, memory heavy, broken after hdf5 migration and not used very often.

metric_transit_boardings()

metric_transit_experience()

metric_trip_costs()

metric_trip_length_distribution()

metric_tts()

metric_validation_speed()

metric_vehicle_technology(**kwargs)

metric_vmt_vht()

metric_vmt_vht_by_link()

network_gaps_by_x(x)

one_value(conn, query[, default])

Attributes

result_time_step

result_time_step = 3600#
__init__(inputs: PolarisInputs, cache_dir: Path, population_scale_factor: float, include_kpis: Tuple[KPITag, ...], exclude_kpis: Tuple[KPITag, ...] = (KPITag.HIGH_MEMORY, KPITag.BROKEN))#
classmethod from_iteration(iteration: ConvergenceIteration, **kwargs)#

Create a KPI object from a ConvergenceIteration object.

classmethod from_dir(iteration_dir: Path, **kwargs)#

Create a KPI object from a given directory.

classmethod from_args(files: PolarisInputs, iteration_dir: Path, cache_name: str = 'kpi.cache', clear_cache=False, exit_if_no_cache=False, population_scale_factor=None, include_kpis: Tuple[KPITag, ...] = (KPITag.SYSTEM, KPITag.POPULATION, KPITag.ACTIVITIES, KPITag.TRIPS, KPITag.TNC, KPITag.TRAFFIC, KPITag.TRANSIT, KPITag.VEHICLES, KPITag.CALIBRATION, KPITag.VALIDATION, KPITag.CONVERGENCE, KPITag.GLOBAL, KPITag.PARKING, KPITag.FREIGHT), exclude_kpis: Tuple[KPITag, ...] = (KPITag.HIGH_MEMORY, KPITag.BROKEN))#
cache_all_available_metrics(verbose=False, metrics_to_cache=None, skip_cache=False)#
classmethod available_metrics()#
close()#
get_kpi_value(kpi_name)#
get_cached_kpi_value(kpi_name, skip_cache=False, force_cache=False)#
has_cached_kpi(kpi_name)#
cached_metrics()#
metric_summary()#
metric_file_sizes()#
metric_polaris_exe()#
metric_gaps()#
static one_value(conn, query, default=0)#
metric_population()#
metric_num_persons_by_age_band_5()#
metric_num_persons_by_age_band_10()#
metric_num_hh()#
metric_num_hh_by_hh_size()#
metric_tts()#
metric_distance_by_act_type()#
metric_planned_modes()#
metric_executed_modes()#
metric_mode_shares()#
metric_executed_activity_mode_share_by_income()#
metric_activity_start_distribution()#
metric_activity_rate_distribution()#
metric_activity_duration_distribution()#
metric_vmt_vht()#
metric_ev_charging()#
metric_ev_consumption()#
metric_flow_density_fd()#
metric_activity_distances()#
metric_vehicle_technology(**kwargs)#
metric_tnc_request_stats()#
metric_tnc_trip_stats()#
metric_tnc_stats()#
metric_avo_by_tnc_operator()#
metric_road_pricing()#
metric_transit_boardings()#
metric_transit_experience()#
network_gaps_by_x(x)#
metric_network_gaps_by_hour()#
metric_skim_stats()#
metric_count_validation()#
metric_rmse_vs_observed()#
metric_planned_rmse_vs_observed()#
metric_calibration_act_gen()#
metric_calibration_act_gen_planned()#
metric_calibration_mode_share()#
metric_calibration_mode_share_planned()#
metric_calibration_timing()#
metric_calibration_timing_planned()#
metric_calibration_destination()#
metric_calibration_boardings()#
metric_validation_speed()#
metric_trip_length_distribution()#
metric_trip_costs()#
metric_activity_start_time_distributions()#
metric_planned_activity_start_time_distributions()#
metric_county_to_county_demand()#
metric_average_vehicle_ownership()#

This metric retrieves the average household vehicle ownership from the synthetic population in the output

metric_traffic_cumulative_gap()#

This metric is slow, memory heavy, broken after hdf5 migration and not used very often. Renaming it to m_etric to remove it from auto-running.

metric_spatial_trips()#
metric_sov_parking_access_time()#
metric_parking_share()#
metric_escooter_utilization_at_garage()#
metric_parking_utilization()#
metric_garage_access_w_escooters()#
metric_parking_stats()#
metric_parking_delay_stats()#
metric_freight_mode_share()#
metric_freight_shipping_cost()#
metric_freight_mode_trade_type(**kwargs)#
metric_freight_trip()#
metric_freight_distance_distribution()#
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