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csv_report_generation_ophth_algorithm

Algorithm for outputting results to CSV on the pod-side.

Classes​

CSVReportGeneratorAlgorithm​

class CSVReportGeneratorAlgorithm(    save_path: Optional[Union[str, os.PathLike]] = None,    trial_name: Optional[str] = None,    rename_columns: Optional[Mapping[str, str]] = None,    original_cols: Optional[list[str]] = None,    filter: Optional[list[ColumnFilter]] = None,    match_patient_visit: Optional[MatchPatientVisit] = None,    matched_csv_path: Optional[Union[str, os.PathLike]] = None,    produce_matched_only: bool = True,    csv_extensions: Optional[list[str]] = None,    produce_trial_notes_csv: bool = False,    sorting_columns: Optional[dict[str, DFSortType]] = None,    **kwargs: Any,):

Algorithm for generating the CSV results reports.

Ancestors​

Methods​

modeller​

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

Inherited from:

CSVReportGeneratorOphthalmologyAlgorithm.modeller :

Modeller-side of the algorithm.

worker​

def worker(    self,    **kwargs: Any,) ‑> bitfount.federated.algorithms.ophthalmology.csv_report_generation_ophth_algorithm._WorkerSide:

Inherited from:

CSVReportGeneratorOphthalmologyAlgorithm.worker :

Worker-side of the algorithm.

CSVReportGeneratorOphthalmologyAlgorithm​

class CSVReportGeneratorOphthalmologyAlgorithm(    save_path: Optional[Union[str, os.PathLike]] = None,    trial_name: Optional[str] = None,    rename_columns: Optional[Mapping[str, str]] = None,    original_cols: Optional[list[str]] = None,    filter: Optional[list[ColumnFilter]] = None,    match_patient_visit: Optional[MatchPatientVisit] = None,    matched_csv_path: Optional[Union[str, os.PathLike]] = None,    produce_matched_only: bool = True,    csv_extensions: Optional[list[str]] = None,    produce_trial_notes_csv: bool = False,    sorting_columns: Optional[dict[str, DFSortType]] = None,    **kwargs: Any,):

Algorithm for generating the CSV results reports.

Arguments

  • save_path: The folder path where the csv report should be saved.
  • trial_name: The name of the trial for the csv report. If provided, the CSV will be saved as "trial_name"-prescreening-patients-"date".csv. Defaults to None.
  • original_cols: The tabular columns from the datasource to include in the report. If not specified it will include all tabular columns from the datasource.
  • rename_columns: A dictionary of columns to rename. Defaults to None.
  • filter: A list of ColumnFilter instances on which we will filter the data on. Defaults to None. If supplied, columns will be added to the output csv indicating the records that match the specified criteria. If more than one ColumnFilter is given, and additional column will be added to the output csv indicating the datapoints that match all given criteria (as well as the individual matches)
  • match_patient_visit: Used for matching the same patient visit.
  • matched_csv_path: Path to save the matched patients CSV to, if requested. Defaults to save_path (i.e. overwrites the non-matched CSV) if produce_matched_only is True. Otherwise, will create a file based off of the save_path argument.
  • produce_matched_only: If True, only the matched CSV will be generated at the end of the run. If False, both the non-matched and matched CSV will be generated.
  • produce_trial_notes_csv: If True, a CSV file containing the trial notes will be generated at the end of the run. Defaults to False.
  • csv_extensions: List of named CSV extension functions that will be applied to the output CSV just before saving to file.
  • sorting_columns: A dictionary of columns to sort the output CSV by. The keys are column names the values are either 'asc' or 'desc'. Defaults to None.

Ancestors​

Subclasses​

Variables​

  • static fields_dict : ClassVar[T_FIELDS_DICT]

Methods​

modeller​

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

Modeller-side of the algorithm.

worker​

def worker(    self,    **kwargs: Any,) ‑> bitfount.federated.algorithms.ophthalmology.csv_report_generation_ophth_algorithm._WorkerSide:

Worker-side of the algorithm.

MatchPatientVisit​

class MatchPatientVisit(    cols_to_match: list[str],    divergent_col: str,    date_time_col: str,    how: DFMergeType = 'outer',):

Dataclass for matching patient visits.

Allows matching of different scans and results for the same patient visit. Only two records can be matched for the same patient visit.

Arguments

  • cols_to_match: List of columns on which to match.
  • divergent_col: Column containing the divergent strings for the same patient. E.g. the column indicating whether the scan was performed on the left or right eye.
  • date_time_col: The column indicating the date of the patient visit.

Variables​

  • static cols_to_match : list[str]
  • static date_time_col : str
  • static divergent_col : str
  • static how : Literal['inner', 'outer', 'left', 'right']