GMCalibParams#

class caf.distribute.gravity_model.multi_area.GMCalibParams(furness_jac=False, diff_step=1e-08, ftol=0.0001, xtol=0.0001, furness_tol=1e-06, grav_max_iters=100, failure_tol=0, default_retry=True)#

Bases: object

Parameters required for the multi tld gravity mode calibrate method.

All of the arguements have defaults, i.e. you can create the default object with no arguements. HOWEVER, read the parameter section below, it is important to understand the impact and implications of the parameters you use. If they don’t make sense, go pester your nearest Demand Modelling expert.

Parameters:

  • furness_jac (bool, optional) – Whether to Furness within the Jacobian function. Not furnessing within the Jacobian does not represent knock on effects to other areas of altering parameters for a given area. If you expect these effects to be significant this should be set to True, but otherwise the process runs quicker with it set to False. Default False.

  • diff_step (float, optional) – Copied from scipy.optimize.least_squares documentation, where it is passed to: Determines the relative step size for the finite difference approximation of the Jacobian. The actual step is computed as x * diff_step. If None (default), then diff_step is taken to be a conventional “optimal” power of machine epsilon for the finite difference scheme used, default 1e-8

  • ftol (float, optional) – The tolerance to pass to scipy.optimize.least_squares. The search will stop once this tolerance has been met. This is the tolerance for termination by the change of the cost function, default 1e-4

  • xtol (float, optional) – The tolerance to pass to scipy.optimize.least_squares. The search will stop once this tolerance has been met. This is the tolerance for termination by the change of the independent variables. Default 1e-4

  • furness_tol (float, optional) – Target Root Mean Square Error that is aimed for with each furness iteration, once condition is met furness with terminate, returning that iterations results. Default 1e-6

  • grav_max_iters (int, optional) – The maximum number of calibration iterations to complete before termination if the ftol has not been met. Default 100

  • failure_tol (float, optional) – If, after initial calibration using init_params, the achieved convergence is less than this value, calibration will be run again with the default parameters from self.cost_function. Default 0

  • default_retry (bool, optional:) – If, after running with init_params, the achieved convergence is less than failure_tol, calibration will be run again with the default parameters of self.cost_function. This argument is ignored if the default parameters are given as `init_params. Default True

Attributes Summary

default_retry

diff_step

failure_tol

ftol

furness_jac

furness_tol

grav_max_iters

xtol

Attributes Documentation

default_retry: bool = True#
diff_step: float = 1e-08#
failure_tol: float = 0#
ftol: float = 0.0001#
furness_jac: bool = False#
furness_tol: float = 1e-06#
grav_max_iters: int = 100#
xtol: float = 0.0001#