smif.cli package

A command line interface to the system of systems framework

This command line interface implements a number of methods.

• setup creates an example project with the recommended folder structure

• run performs a simulation of an individual sector model, or the whole system

  of systems model

• validate performs a validation check of the configuration file
• app runs the graphical user interface, opening in a web browser

Folder structure

When configuring a project for the CLI, the folder structure below should be used. In this example, there is one system-of-systems model, combining a water supply and an energy demand model:

/config
    project.yaml
    /sector_models
        energy_demand.yml
        water_supply.yml
    /sos_models
        energy_water.yml
    /model_runs
        run_to_2050.yml
        short_test_run.yml
        ...
/data
    /initial_conditions
        reservoirs.yml
    /interval_definitions
        annual_intervals.csv
    /interventions
        water_supply.yml
    /narratives
        high_tech_dsm.yml
    /region_definitions
        /oxfordshire
            regions.geojson
        /uk_nations_shp
            regions.shp
    /scenarios
        population.csv
        raininess.csv
    /water_supply
        /initial_system
/models
    energy_demand.py
    water_supply.py
/planning
    expected_to_2020.yaml
    national_infrastructure_pipeline.yml

The sector model implementations can be installed independently of the model run configuration. The paths to python wrapper classes (implementing SectorModel) should be specified in each sector_model/*.yml configuration.

The project.yaml file specifies the metadata shared by all elements of the project; sos_models specify the combinations of sector_models and scenarios while individual model_runs specify the scenario, strategy and narrative combinations to be used in each run of the models.

Submodules:

• smif.cli.log module

Data:

USE_WIN32	bool(x) -> bool
before_step	Prepare a single model to run (call once before calling smif step)
confirm	Prompts for a yes or no response from the user
csv2parquet	Convert CSV to Parquet - assuming the CSV can be parsed as a dataframe
decide	Run a decision step for a model run
list_available_results	List the available results for a specified model run.
list_missing_results	List the missing results for a specified model run.
list_model_runs	List the model runs defined in the config, optionally indicating whether complete results exist.
main	Parse args and run
parse_arguments	Parse command line arguments
prepare_convert
prepare_model_runs	Generate multiple model runs according to a model run file referencing a scenario with multiple variants.
prepare_scenario	Update scenario configuration file to include multiple scenario variants.
run	Run the model runs as requested.
run_app	Run the client/server application
setup_project_folder	Setup a sample project
step	Run a single model for a single timestep

Reference

smif.cli.before_step(args)

Prepare a single model to run (call once before calling smif step)

Parameters:args –

smif.cli.confirm(prompt=None, response=False)

Prompts for a yes or no response from the user

Parameters:

• prompt (str, default=None) –
• response (bool, default=False) –

Returns:

True for yes and False for no.

Return type:

bool

Notes

response should be set to the default value assumed by the caller when user simply types ENTER.

Examples

>>> confirm(prompt='Create Directory?', response=True)
Create Directory? [y]|n:
True
>>> confirm(prompt='Create Directory?', response=False)
Create Directory? [n]|y:
False
>>> confirm(prompt='Create Directory?', response=False)
Create Directory? [n]|y: y
True

smif.cli.csv2parquet(args)

Convert CSV to Parquet - assuming the CSV can be parsed as a dataframe

smif.cli.decide(args)

Run a decision step for a model run

Parameters:args –

smif.cli.list_available_results(args)

List the available results for a specified model run.

smif.cli.list_missing_results(args)

List the missing results for a specified model run.

smif.cli.list_model_runs(args)

List the model runs defined in the config, optionally indicating whether complete results exist.

smif.cli.main(arguments=None)

Parse args and run

smif.cli.parse_arguments()

Parse command line arguments

Returns: Return type:argparse.ArgumentParser

smif.cli.prepare_convert(args)

smif.cli.prepare_model_runs(args)

Generate multiple model runs according to a model run file referencing a scenario with multiple variants.

smif.cli.prepare_scenario(args)

Update scenario configuration file to include multiple scenario variants.

The initial scenario configuration file is overwritten.

smif.cli.run(args)

Run the model runs as requested. Check if results exist and asks user for permission to overwrite

Parameters:args –

smif.cli.run_app(args)

Run the client/server application

Parameters:args –

smif.cli.setup_project_folder(args)

Setup a sample project

smif.cli.step(args)

Run a single model for a single timestep

Parameters:args –