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]#