Module: hybrid_vector_model.route_choice_model

Created on 21.06.2018

@author: Samuel

Classes:

RouteChoiceModel(**printerArgs)

classdocs

class RouteChoiceModel(**printerArgs)[source]

Bases: vemomoto_core.tools.hrprint.HierarchichalPrinter

classdocs

Attributes:

NOISEBOUND

VARIABLE_LABELS

fitted

prepared

Methods:

fit([guess, improveGuess, disp])

Fits the route choice model.

get_confidence_intervals([fileName, show])

get_nLL_funtions()

set_fitting_data(dayData, shiftData, …)

NOISEBOUND = 0.05
VARIABLE_LABELS = ['P(drive randomly)', 'route choice exponent', 'P(observable if driving randomly)']
fit(guess=None, improveGuess=False, disp=True)[source]

Fits the route choice model.

Parameters
  • guess (float[]) – Guess for the maximum likelihood estimate.

  • improveGuess (bool) – If True, guess will be used as initial guess for the model fit. Otherwise, it will be used as the maximum likelihood estimate.

  • disp (bool) – Whether partial results shall be printed.

property fitted
get_confidence_intervals(fileName=None, show=True, **optim_args)[source]
get_nLL_funtions()[source]
property prepared
set_fitting_data(dayData, shiftData, inspectedRoutes, routeLengths, trafficModel, complianceRate, properDataRate)[source]