GravityModelRunResults#

class caf.distribute.gravity_model.core.GravityModelRunResults(cost_distribution, cost_convergence, value_distribution, target_cost_distribution=None, cost_function=None, cost_params=None)#

Bases: GravityModelResults

A collection of results from a run of the Gravity Model.

Parameters:

  • cost_distribution (caf.toolkit.cost_utils.CostDistribution) – The achieved cost distribution of the run.

  • cost_convergence (float) – The achieved cost convergence value of the run. If target_cost_distribution is not set, then this should be 0. This will be the same as calculating the convergence of cost_distribution and target_cost_distribution.

  • value_distribution (numpy.ndarray) – The achieved distribution of the given values (usually trip values between different places).

  • target_cost_distribution (caf.toolkit.cost_utils.CostDistribution | None) – If set, this will be the cost distribution the gravity model was aiming for during its run.

  • cost_function (caf.distribute.cost_functions.CostFunction | None) – If set, this will be the cost function used in the gravity model run.

  • cost_params (dict[str, Any] | None) – If set, the cost parameters used with the cost_function to achieve the results.

Attributes Summary

cost_function

cost_params

summary

Summary of the GM run parameters as a series.

target_cost_distribution

Attributes Documentation

cost_function: CostFunction | None = None#
cost_params: dict[str, Any] | None = None#
summary#

Summary of the GM run parameters as a series.

Outputs the gravity model parameters used to generate the distribution.

Returns:

a summary of the run

Return type:

pd.DataFrame

target_cost_distribution: CostDistribution | None = None#