piglot.solver.multi_case_solver.MultiCaseSolver

class MultiCaseSolver(cases: List[Case], parameters: ParameterSet, output_dir: str, tmp_dir: str, verbosity: str, parallel: int = 1)[source]

Base class for solvers with multiple cases.

Methods

`get_case_class`	Get the case class to use for this solver.
`get_case_params`	Get the parameters for a given hash.
`get_case_results`	Get the results for all cases for a given hash.
`get_current_response`	Get the responses from a given output field for all cases.
`get_output_fields`	Get all output fields.
`get_output_response`	Get the responses from all output fields for a given case.
`prepare`	Prepare data for the optimisation.
`read`	Read the solver from the configuration dictionary.
`solve`	Solve all cases for the given set of parameter values.

abstract classmethod get_case_class() → Type[Case][source]

Get the case class to use for this solver.

Returns

get_case_params(param_hash: str) → Dict[str, float][source]

Get the parameters for a given hash.

get_case_results(param_hash: str) → List[CaseResult][source]

Get the results for all cases for a given hash.

get_current_response() → Dict[str, OutputResult]

Get the responses from a given output field for all cases.

get_output_fields() → List[str][source]

Get all output fields.

get_output_response(param_hash: str) → Dict[str, OutputResult][source]

Get the responses from all output fields for a given case.

classmethod read(config: Dict[str, Any], parameters: ParameterSet, output_dir: str) → T[source]

Read the solver from the configuration dictionary.

solve(values: ndarray, concurrent: bool) → Dict[str, OutputResult][source]

Solve all cases for the given set of parameter values.

valuesarray: Current parameters to evaluate.
concurrentbool: Whether this run may be concurrent to another one (so use unique file names).