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ga_trial_pdf_algorithm_base

Base class and implementations for GA Trial PDF algorithms.

Classes​

BaseGATrialPDFGeneratorAlgorithm​

class BaseGATrialPDFGeneratorAlgorithm(    *,    datastructure: DataStructure,    report_metadata: ReportMetadata,    filter: Optional[list[ColumnFilter | MethodFilter]] = None,    save_path: Optional[Union[str, os.PathLike]] = None,    filename_prefix: Optional[str] = None,    pdf_filename_columns: Optional[list[str]] = None,    total_ga_area_lower_bound: float = 2.5,    total_ga_area_upper_bound: float = 17.5,    trial_name: Optional[str] = None,    **kwargs: Any,):

Base algorithm factory for GA Trial PDF report generation.

Arguments

  • datastructure: The data structure to use for the algorithm.
  • report_metadata: A ReportMetadata for the pdf report metadata fields.
  • filter: A list of ColumnFilter or MethodFilter objects for eligibility.
  • filename_prefix: The prefix for the pdf filename. Defaults to None.
  • pdf_filename_columns: The columns from the datasource that should be used for the pdf filename. If not provided, the filename will be saved as "Patient_index_i.pdf" where i is the index in the filtered datasource. Defaults to None.
  • total_ga_area_lower_bound: The lower bound for the total GA area. Defaults to 2.5.
  • total_ga_area_upper_bound: The upper bound for the total GA area. Defaults to 17.5.

Ancestors​

Subclasses​

Variables​

  • static fields_dict : ClassVar[T_FIELDS_DICT]

Methods​

modeller​

def modeller(    self, *, context: ProtocolContext, **kwargs: Any,) ‑> NoResultsModellerAlgorithm:

Inherited from:

BaseNonModelAlgorithmFactory.modeller :

Modeller-side of the algorithm.

worker​

def worker(self, *, context: ProtocolContext, **kwargs: Any) ‑> ~T_WorkerSide:

Inherited from:

BaseNonModelAlgorithmFactory.worker :

Worker-side of the algorithm.

PDFGeneratorRunProtocol​

class PDFGeneratorRunProtocol(*args, **kwargs):

Protocol defining the run method for PDF generators.

Ancestors​

Methods​

run​

def run(    self,    *,    results_df: pd.DataFrame,    ga_dict: Any,    task_id: str,    filenames: Optional[list[str]] = None,    **kwargs: Any,) ‑> pandas.core.frame.DataFrame:

Generate PDF reports for the GA model results.