High-level analysis modules

Functions that are used to run different types of analysis on the restoration of interdependent networks

Running methods

runutils.batch_run(params, fail_sce_param)

Batch run different methods for a given list of damage scenarios, given global parameters.

Parameters

  • params (dict) – DESCRIPTION.

  • fail_sce_param (dict) – DESCRIPTION.

Returns

Return type

None. Writes to file

runutils.run_method(fail_sce_param, v_r, layers, method, judgment_type=None, res_alloc_type=None, valuation_type=None, output_dir='..', misc=None)

This function runs a given method for different numbers of resources, and a given judge, auction, and valuation type in the case of JC.

Parameters

  • fail_sce_param (dict) – information about damage scenarios.

  • v_r (float, list of float, or list of lists of floats) – number of resources, if this is a list of floats, each float is interpreted as a different total number of resources, and indp is run given the total number of resources. It only works when auction_type != None. If this is a list of lists of floats, each list is interpreted as fixed upper bounds on the number of resources each layer can use (same for all time step)..

  • layers (TYPE) – DESCRIPTION.

  • method (TYPE) – DESCRIPTION.

  • judgment_type (str, optional) – Type of Judgments in Judgment Call Method. The default is None.

  • res_alloc_type (str, optional) – Type of resource allocation method for resource allocation. The default is None.

  • valuation_type (str, optional) – Type of valuation in auction. The default is None.

  • output_dir (str, optional) – DESCRIPTION. The default is ‘..’.

Returns

Return type

None. Writes to file

Running methods for a toy example

runutils.run_sample_problems()
runutils.run_indp_sample(layers)
runutils.run_tdindp_sample(layers)
runutils.run_jc_sample(layers, judge_types, auction_type, valuation_type)
runutils.run_game_sample(layers, judge_types, auction_type, valuation_type, game_type='NORMALGAME', signals=None, beliefs=None, reduced_act=None)
runutils.run_mh_sample(layers)