emodpy.emod_task module#
- emodpy.emod_task.dev_mode = False#
Note that these 3 functions could be member functions of EMODTask but Python modules are already pretty good at being ‘static classes’.
- emodpy.emod_task.add_ep4_from_path(task, ep4_path='EP4')[source]#
Add embedded Python scripts from a given path.
- class emodpy.emod_task.EMODTask(command: str | ~idmtools.entities.command_line.CommandLine = <property object>, platform_requirements: ~typing.Set[~idmtools.entities.platform_requirements.PlatformRequirements] = <factory>, _ITask__pre_creation_hooks: ~typing.List[~typing.Callable[[~idmtools.entities.simulation.Simulation | ~idmtools.entities.iworkflow_item.IWorkflowItem, ~idmtools.entities.iplatform.IPlatform], ~typing.NoReturn]] = <factory>, _ITask__post_creation_hooks: ~typing.List[~typing.Callable[[~idmtools.entities.simulation.Simulation | ~idmtools.entities.iworkflow_item.IWorkflowItem, ~idmtools.entities.iplatform.IPlatform], ~typing.NoReturn]] = <factory>, common_assets: ~idmtools.assets.asset_collection.AssetCollection = <factory>, transient_assets: ~idmtools.assets.asset_collection.AssetCollection = <factory>, eradication_path: str | None = None, demographics: ~emodpy.emod_file.DemographicsFiles = <factory>, migrations: ~emodpy.emod_file.MigrationFiles = <factory>, reporters: ~emodpy.reporters.base.Reporters = <factory>, climate: ~emodpy.emod_file.ClimateFiles = <factory>, config: dict = <factory>, config_file_name: str = 'config.json', campaign: ~emodpy.emod_campaign.EMODCampaign = <factory>, simulation_demographics: ~emodpy.emod_file.DemographicsFiles = <factory>, simulation_migrations: ~emodpy.emod_file.MigrationFiles = <factory>, use_embedded_python: bool = True, py_path_list: list = <factory>, is_linux: bool = False, implicit_configs: list = <factory>, sif_filename: str | None = None)[source]#
Bases:
ITaskEMODTask allows easy running and configuration of EMOD Experiments and Simulations
- demographics: DemographicsFiles#
Common Demographics
- migrations: MigrationFiles#
Common Migrations
- climate: ClimateFiles#
Common Climate
- campaign: EMODCampaign#
Campaign configuration
- simulation_demographics: DemographicsFiles#
Simulation level demographics such as overlays
- simulation_migrations: MigrationFiles#
Simulation level migrations
- sif_path = None#
- create_campaign_from_callback(builder, params=None)[source]#
- Parameters:
write_campaign (str) – if not None, the path to write the campaign to
- handle_implicit_configs()[source]#
Execute the implicit config functions created by the demographics builder.
- classmethod from_default2(eradication_path, schema_path, param_custom_cb=None, config_path='config.json', campaign_builder=None, ep4_custom_cb=<function default_ep4_fn>, demog_builder=None, plugin_report=None, serial_pop_files=None, write_default_config=None, ep4_path=None, **kwargs) EMODTask[source]#
Create a task from emod-api Defaults
- Parameters:
eradication_path – Path to Eradication binary.
schema_path – Path to schema.json.
param_custom_cb – Function that sets parameters for config.
campaign_builder – Function that builds the campaign.
ep4_custom_cb – Function that sets EP4 assets. There are 4 options for specificying EP4 scripts: 1) Set ep4_custom_cb=None. This just says “don’t even attempt to use EP4 scripts”. Not the default. 2) All defaults. This uses the built-in ep4 scripts (inside emodpy module) which does some standard pre- and post-processing. You can’t edit these scripts. 3) Set the (new) ep4_path to your local path where your custom scripts are. Leave out ep4_custom_cb so it uses the default function (but with your path). 4) Power mode where you set ep4_custom_cb to your own function which gives you all the power. Probably don’t need this.
demog_builder – Function that builds the demographics configuration and optional migration configuration.
plugin_report – Custom reports file.
serial_pop_files – Input “.dtk” serialized population files.
config_path – Optional filename for the generated config.json, if you don’t like that name.
write_default_config – Set to true if you want to have the default_config.json written locally for inspection.
ep4_path – See ep4_custom_cb section.
- Returns:
EMODTask
- classmethod from_files(eradication_path=None, config_path=None, campaign_path=None, demographics_paths=None, ep4_path=None, custom_reports_path=None, asset_path=None, **kwargs)[source]#
Load custom EMOD files when creating
EMODTask.- Parameters:
asset_path – If an asset path is passed, the climate, dlls, and migrations will be searched there
eradication_path – The eradication.exe path.
config_path – The custom configuration file.
campaign_path – The custom campaign file.
demographics_paths – The custom demographics files (single file or a list).
custom_reports_path – Custom reports file
Returns: An initialized experiment
- load_files(config_path=None, campaign_path=None, custom_reports_path=None, demographics_paths=None, asset_path=None) NoReturn[source]#
Load files in the experiment/base_simulation.
- Parameters:
asset_path – Path to find assets
config_path – Configuration file path
campaign_path – Campaign file path
demographics_paths – Demographics file path
custom_reports_path – Path for the custom reports file
- pre_creation(parent: Simulation | IWorkflowItem, platform: IPlatform)[source]#
Call before a task is executed. This ensures our configuration is properly done
- add_py_path(path_to_add) NoReturn[source]#
Add path to list of python paths prepended to sys.path in embedded interpreter
Returns:
- gather_common_assets() AssetCollection[source]#
Gather Experiment Level Assets Returns:
- gather_transient_assets() AssetCollection[source]#
Gather assets that are per simulation Returns:
- copy_simulation(base_simulation: Simulation) Simulation[source]#
Called when making copies of a simulation.
Here we deep copy parts of the simulation to ensure we don’t accidentally update objects :param base_simulation: Base Simulation
Returns:
- set_parameter(name: str, value: any) dict[source]#
Set a value in the EMOD config.json file. This will be deprecated in the future in favour of emod_api.config.
- Parameters:
name – Name of parameter to set
value – Value to set
- Returns:
Tags to set
- static set_parameter_sweep_callback(simulation: Simulation, param: str, value: Any) Dict[str, Any][source]#
Convenience callback for sweeps
- Parameters:
simulation – Simulation we are updating
param – Parameter
value – Value
- Returns:
Tags to set on simulation
- classmethod set_parameter_partial(parameter: str)[source]#
Convenience callback for sweeps
- Parameters:
parameter – Parameter to set
Returns:
- get_parameter(name: str, default: Any | None = None)[source]#
Get a parameter in the simulation.
- Parameters:
name – The name of the parameter.
default – Optional, the default value.
- Returns:
The value of the parameter.
- update_parameters(params)[source]#
Bulk update the configuration parameter values. This will be deprecated in the future in favour of emod_api.config.
- Parameters:
params – A dictionary with new values.
- Returns:
None
- reload_from_simulation(simulation: Simulation)[source]#
Optional hook that is called when loading simulations from a platform.
- classmethod get_file_from_comps(exp_id, filename)[source]#
Get file or files from COMPS. Retrieve all files named <filename> in experiment <exp_id> and put them in a local directory called exp_id. On linux, this is under “latest_experiment”. This function will eventually be added to pyCOMPS.
- classmethod cache_experiment_metadata_in_sql(exp_id, optional_data_files=None)[source]#
Create local sqlite database of experiment metadata, plus optional data from post-proc file. Tags will be column names.
- Parameters:
exp_id – ID of experiment.
optional_data_files – List of filenames (not path) of downloaded files containing single value post-processed on server.
- Returns:
None.
- class emodpy.emod_task.EMODTaskSpecification[source]#
Bases:
TaskSpecification- get(configuration: dict) EMODTask[source]#
Return an EMODTask object using provided configuration :param configuration: Configuration for Task
- Returns:
EMODTask for configuration