Skip to main content

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]] = 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 objects to filter the data by.
  • save_path: The folder path where the pdf report should be saved.
  • 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

Variables

  • static fields_dict : ClassVar[T_FIELDS_DICT]

Methods


modeller

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

Modeller-side of the algorithm.

PDFGeneratorRunProtocol

class PDFGeneratorRunProtocol(*args, **kwargs):

Protocol defining the run method for PDF generators.

Methods


run

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

Generate PDF reports for the GA model results.