Carrier-level Summaries¶

This page provides an overview of the carrier-level summary visualizations available in PassengerSim.

One Simulation Run¶

The results from a simulation run are stored in a SimulationTables instance, which is returned from Simulation.run or can be loaded from a stored database of results. This object has a number of methods to generate visualizations for the results of the simulation.

Out[1]:

PosixPath('saved-output/simple-sim.20250221-122545.pkl.lz4')

In [2]:

from passengersim import SimulationTables

summary = SimulationTables.from_pickle("saved-output/simple-sim")

from passengersim import SimulationTables summary = SimulationTables.from_pickle("saved-output/simple-sim")

Revenues¶

SimulationTables.fig_carrier_revenues

Display the average revenues by carrier.

In [3]:

summary.fig_carrier_revenues()

summary.fig_carrier_revenues()

Out[3]:

Mileage¶

SimulationTables.fig_carrier_mileage

Display the available seat miles (ASM) and average revenue passenger miles (RPM) by carrier.

In [4]:

summary.fig_carrier_mileage()

summary.fig_carrier_mileage()

Out[4]:

Load Factors¶

SimulationTables.fig_carrier_load_factors

Display the average system load factors by carrier. The system load factor is calculated based on ASM and RPM figures for the carrier, which weights larger capacity vehicles and longer distance legs more heavily, to reflect their larger relative importance in evaluating carrier performance.

In [5]:

summary.fig_carrier_load_factors()

summary.fig_carrier_load_factors()

Out[5]:

Alternatively, this function can also display the average leg load factor, which considers the fraction of capacity sold on each leg, and weights all legs uniformly.

In [6]:

summary.fig_carrier_load_factors(load_measure="avg_leg_lf")

summary.fig_carrier_load_factors(load_measure="avg_leg_lf")

Out[6]:

Load Factor Distributions¶

SimulationTables.fig_leg_load_factor_distribution

Display the distribution of leg load factors. This can be done for all carriers individually (by_carrier=True, or omitted as this is the default), or across carriers in aggregate (by_carrier=False), for a specific carrier (by_carrier='AL1').

In [7]:

summary.fig_leg_load_factor_distribution()

summary.fig_leg_load_factor_distribution()

Out[7]:

Local Passenger Percentages¶

Display the percentage of local passengers by carrier. By default, this is the percentage of bookings that are local (i.e. flying on only a single leg). Alternatively, this method accepts a load_measure argument that can be set to 'leg_pax', which will report the percentage of leg passengers who are local -- the numerator of this ratio is the same, but the denominator is larger (assuming there are any connecting passengers in the network).

In [8]:

summary.fig_carrier_local_share()

summary.fig_carrier_local_share()

Out[8]:

In [9]:

summary.fig_carrier_local_share("leg_pax")

summary.fig_carrier_local_share("leg_pax")

Out[9]:

Yields¶

SimulationTables.fig_carrier_yields

Display the average yield (revenue per passenger mile) by carrier.

In [10]:

summary.fig_carrier_yields()

summary.fig_carrier_yields()

Out[10]:

Fare Class Mix¶

SimulationTables.fig_fare_class_mix

Display the fare class mix by carrier.

In [11]:

summary.fig_fare_class_mix()

summary.fig_fare_class_mix()

Out[11]:

Contrasting Multiple Runs¶

Similar figures are available contrasting the results of multiple runs, by bundling multiple SimulationTables objects in a Contrast instance.

In [12]:

from passengersim.contrast import Contrast

comps = Contrast(
    Simple=summary,
    Untruncated=SimulationTables.from_pickle("saved-output/untruncated-sim"),
)

from passengersim.contrast import Contrast comps = Contrast( Simple=summary, Untruncated=SimulationTables.from_pickle("saved-output/untruncated-sim"), )

Revenues¶

Contrast.fig_carrier_revenues.

Display the average revenues by carrier.

In [13]:

comps.fig_carrier_revenues()

comps.fig_carrier_revenues()

Out[13]:

Load Factors¶

Contrast.fig_carrier_load_factors.

Display the average system load factors by carrier. The system load factor is calculated based on ASM and RPM figures for the carrier, which weights larger capacity vehicles and longer distance legs more heavily, to reflect their larger relative importance in evaluating carrier performance.

In [14]:

comps.fig_carrier_load_factors()

comps.fig_carrier_load_factors()

Out[14]:

In [15]:

comps.fig_carrier_load_factors(load_measure="avg_leg_lf")

comps.fig_carrier_load_factors(load_measure="avg_leg_lf")

Out[15]:

Yields¶

Contrast.fig_carrier_yields.

Display the average yield (revenue per passenger mile) by carrier.

In [16]:

comps.fig_carrier_yields()

comps.fig_carrier_yields()

Out[16]:

Fare Class Mix¶

Contrast.fig_fare_class_mix.

Display the fare class mix by carrier.

In [17]:

comps.fig_fare_class_mix()

comps.fig_fare_class_mix()

Out[17]: