aequilibrae.distribution package

Submodules

aequilibrae.distribution.gravity_application module

Algorithms to apply synthetic gravity models with power, exponential and gamma functions

The procedures implemented in this code are some of those suggested in Modelling Transport, 4th Edition, Ortuzar and Willumsen, Wiley 2011

class aequilibrae.distribution.gravity_application.GravityApplication(**kwargs)

Bases: object

” Model is an instance of SyntheticGravityModel class Impedance is an instance of AequilibraEMatrix Row and Column vectors are instances of AequilibraeData

apply()
apply_function()
check_data()
check_parameters()
get_parameters()

aequilibrae.distribution.gravity_calibration module

Algorithms to calibrate synthetic gravity models with power and exponential functions

The procedures implemented in this code are some of those suggested in Modelling Transport, 4th Edition, Ortuzar and Willumsen, Wiley 2011

class aequilibrae.distribution.gravity_calibration.GravityCalibration(**kwargs)

Bases: object

” where function is: ‘EXPO’ or ‘POWER’. ‘GAMMA’ and ‘FRICTION FACTORS’ to be implemented at a later time parameters are: ‘max trip length’

apply_gravity()
assemble_model(b1)
calibrate()
check_inputs()
get_parameters()

aequilibrae.distribution.ipf module

Iterative Proportional Fitting (Fratar)

class aequilibrae.distribution.ipf.Ipf(**kwargs)

Bases: object

check_data()
check_parameters()
factor(marginals, targets)
fit()
get_parameters(model)
tot_columns(matrix)
tot_rows(matrix)

aequilibrae.distribution.synthetic_gravity_model module

Simple class object to represent synthetic gravity models

class aequilibrae.distribution.synthetic_gravity_model.SyntheticGravityModel

Bases: object

load(file_name)
save(file_name)

Module contents