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config_schemas

Config YAML specification classes.

Avoid adding new imports for algorithms and protocols here. Current imports are for backwards compatibility.

Module​

Submodules​

Functions​

_deserialize_model_ref​

def _deserialize_model_ref(ref: str) ‑> Union[pathlib.Path, str]:

Deserializes a model reference.

If the reference is a path to a file (and that file exists), return a Path instance. Otherwise, returns the str reference unchanged.

_deserialize_path​

def _deserialize_path(    path: Optional[str], context: Optional[dict[str, Any]] = None,) ‑> Optional[pathlib.Path]:

Converts a str into a Path.

If the input is None, the output is None.

If the path to the config file is supplied in the context dict (in the "config_path" key) then any relative paths will be resolved relative to the directory containing the config file. If context is not provided or doesn't contain "config_path", relative paths will be resolved relative to the current working directory.

Arguments

  • path: The path string to deserialize, or None
  • context: Optional context dict that may contain "config_path" key

Returns A Path object, or None if path is None

Classes​

APIKeys​

class APIKeys(access_key_id: str, access_key: str):

API keys for BitfountSession.

Variables​

  • static access_key : str
  • static access_key_id : str

AccessManagerConfig​

class AccessManagerConfig(url: str = 'https://am.hub.bitfount.com'):

Configuration for the access manager.

Variables​

  • static url : str

AggregatorConfig​

class AggregatorConfig(    secure: bool, weights: Optional[dict[str, Union[int, float]]] = None,):

Configuration for the Aggregator.

Variables​

  • static secure : bool
  • static weights : Optional[dict[str, typing.Union[int, float]]]

AlgorithmConfig​

class AlgorithmConfig(name: str, arguments: Optional[Any] = None):

Configuration for the Algorithm.

Subclasses​

Variables​

  • static arguments : Optional[Any]
  • static name : str

BitfountModelReferenceConfig​

class BitfountModelReferenceConfig(    model_ref: Union[Path, str],    model_version: Optional[int] = None,    username: Optional[str] = None,    weights: Optional[str] = None,):

Configuration for BitfountModelReference.

Variables​

  • static model_version : int | None
  • static username : str | None
  • static weights : str | None

CSVReportAlgorithmArgumentsConfig​

class CSVReportAlgorithmArgumentsConfig(    save_path: Optional[Path] = None,    original_cols: Optional[list[str]] = None,    rename_columns: Optional[dict[str, str]] = None,    columns_to_drop: Optional[list[str]] = None,    columns_to_drop_prefix: Optional[list[str]] = None,    columns_to_include: Optional[list[str]] = None,    filter: Optional[list[ColumnFilter]] = None,    sorting_columns: Optional[dict[str, str]] = None,    decimal_places: int = 2,    ophthalmology_args: Optional[OphthalmologyArgsConfig] = None,    trial_name: Optional[str] = None,    aux_cols: Optional[list[str]] = None,    match_patient_visit: Optional[MatchPatientVisit] = None,    matched_csv_path: Optional[Path] = None,    produce_matched_only: bool = True,    produce_trial_notes_csv: bool = False,    csv_extensions: Optional[list[str]] = None,):

Configuration for CSVReportAlgorithm arguments.

Variables​

  • static aux_cols : Optional[list[str]]
  • static columns_to_drop : Optional[list[str]]
  • static columns_to_drop_prefix : Optional[list[str]]
  • static columns_to_include : Optional[list[str]]
  • static csv_extensions : Optional[list[str]]
  • static decimal_places : int
  • static filter : Optional[list[bitfount.federated.algorithms.ophthalmology.trial_inclusion_filters.ColumnFilter]]
  • static original_cols : Optional[list[str]]
  • static produce_matched_only : bool
  • static produce_trial_notes_csv : bool
  • static rename_columns : Optional[dict[str, str]]
  • static sorting_columns : Optional[dict[str, str]]
  • static trial_name : str | None

CSVReportAlgorithmConfig​

class CSVReportAlgorithmConfig(    name: str,    arguments: Optional[CSVReportAlgorithmArgumentsConfig] = CSVReportAlgorithmArgumentsConfig(save_path=None, original_cols=None, rename_columns=None, columns_to_drop=None, columns_to_drop_prefix=None, columns_to_include=None, filter=None, sorting_columns=None, decimal_places=2, ophthalmology_args=None, trial_name=None, aux_cols=None, match_patient_visit=None, matched_csv_path=None, produce_matched_only=True, produce_trial_notes_csv=False, csv_extensions=None),):

Configuration for CSVReportAlgorithm.

Ancestors​

Variables​

  • static name : str

CSVReportGeneratorOphthalmologyAlgorithmArgumentsConfig​

class CSVReportGeneratorOphthalmologyAlgorithmArgumentsConfig(    save_path: Optional[Path] = None,    trial_name: Optional[str] = None,    original_cols: Optional[list[str]] = None,    aux_cols: Optional[list[str]] = [],    rename_columns: Optional[dict[str, str]] = None,    filter: Optional[list[ColumnFilter]] = None,    match_patient_visit: Optional[MatchPatientVisit] = None,    matched_csv_path: Optional[Path] = None,    produce_matched_only: bool = True,    csv_extensions: Optional[list[str]] = None,    produce_trial_notes_csv: bool = False,    sorting_columns: Optional[dict[str, str]] = None,):

Configuration for CSVReportGeneratorOphthalmologyAlgorithm arguments.

Variables​

  • static aux_cols : Optional[list[str]]
  • static csv_extensions : Optional[list[str]]
  • static filter : Optional[list[bitfount.federated.algorithms.ophthalmology.trial_inclusion_filters.ColumnFilter]]
  • static original_cols : Optional[list[str]]
  • static produce_matched_only : bool
  • static produce_trial_notes_csv : bool
  • static rename_columns : Optional[dict[str, str]]
  • static sorting_columns : Optional[dict[str, str]]
  • static trial_name : str | None

CSVReportGeneratorOphthalmologyAlgorithmConfig​

class CSVReportGeneratorOphthalmologyAlgorithmConfig(    name: str,    arguments: Optional[CSVReportGeneratorOphthalmologyAlgorithmArgumentsConfig] = CSVReportGeneratorOphthalmologyAlgorithmArgumentsConfig(save_path=None, trial_name=None, original_cols=None, aux_cols=[], rename_columns=None, filter=None, match_patient_visit=None, matched_csv_path=None, produce_matched_only=True, csv_extensions=None, produce_trial_notes_csv=False, sorting_columns=None),):

Configuration for CSVReportGeneratorOphthalmologyAlgorithm.

Ancestors​

Variables​

  • static name : str

CodeNormalisationAlgorithmArgumentsConfig​

class CodeNormalisationAlgorithmArgumentsConfig():

Configuration for CodeNormalisationAlgorithm arguments.

CodeNormalisationAlgorithmConfig​

class CodeNormalisationAlgorithmConfig(    name: str,    arguments: Optional[CodeNormalisationAlgorithmArgumentsConfig] = CodeNormalisationAlgorithmArgumentsConfig(),):

Configuration for CodeNormalisationAlgorithm.

Ancestors​

Variables​

  • static name : str

DataSplitConfig​

class DataSplitConfig(data_splitter: str = 'percentage', args: _JSONDict = {}):

Configuration for the data splitter.

Variables​

  • static data_splitter : str

DataStructureAssignConfig​

class DataStructureAssignConfig(    target: Optional[Union[str, list[str]]] = None,    image_cols: Optional[list[str]] = None,    image_prefix: Optional[str] = None,):

Configuration for the datastructure assign argument.

Variables​

  • static image_cols : Optional[list[str]]
  • static image_prefix : str | None
  • static target : Union[str, list[str], ForwardRef(None)]

DataStructureConfig​

class DataStructureConfig(    table_config: Optional[DataStructureTableConfig] = None,    assign: DataStructureAssignConfig = DataStructureAssignConfig(target=None, image_cols=None, image_prefix=None),    select: DataStructureSelectConfig = DataStructureSelectConfig(include=None, include_prefix=None, exclude=None),    transform: DataStructureTransformConfig = DataStructureTransformConfig(dataset=None, batch=None, image=None, auto_convert_grayscale_images=True),    data_split: Optional[DataSplitConfig] = None,    schema_requirements: SCHEMA_REQUIREMENTS_TYPES = 'partial',    compatible_datasources: list[str] = ['CSVSource', 'DICOMSource', 'ImageSource', 'InterMineSource', 'NIFTISource', 'DICOMOphthalmologySource', 'HeidelbergSource', 'HeidelbergE2ESource', 'TopconSource'],    filter: Optional[list[TaskFilterConfig]] = None,):

Configuration for the modeller schema and dataset options.

Variables​

  • static compatible_datasources : list[str]
  • static schema_requirements : Union[Literal['empty', 'partial', 'full'], dict[Literal['empty', 'partial', 'full'], Any]]

DataStructureSelectConfig​

class DataStructureSelectConfig(    include: Optional[list[str]] = None,    include_prefix: Optional[str] = None,    exclude: Optional[list[str]] = None,):

Configuration for the datastructure select argument.

Variables​

  • static exclude : Optional[list[str]]
  • static include : Optional[list[str]]
  • static include_prefix : str | None

DataStructureTableConfig​

class DataStructureTableConfig(    table: Union[str, dict[str, str]],    schema_types_override: Optional[Union[SchemaOverrideMapping, Mapping[str, SchemaOverrideMapping]]] = None,):

Configuration for the datastructure table arguments. Deprecated.

Variables​

  • static table : Union[str, dict[str, str]]

DataStructureTransformConfig​

class DataStructureTransformConfig(    dataset: Optional[list[dict[str, _JSONDict]]] = None,    batch: Optional[list[dict[str, _JSONDict]]] = None,    image: Optional[list[dict[str, _JSONDict]]] = None,    auto_convert_grayscale_images: bool = True,):

Configuration for the datastructure transform argument.

Variables​

  • static auto_convert_grayscale_images : bool
  • static batch : Optional[list[dict[str, dict[str, typing.Any]]]]
  • static dataset : Optional[list[dict[str, dict[str, typing.Any]]]]
  • static image : Optional[list[dict[str, dict[str, typing.Any]]]]

DatasourceConfig​

class DatasourceConfig(    datasource: str,    name: str,    data_config: PodDataConfig = PodDataConfig(force_stypes=None, column_descriptions=None, table_descriptions=None, description=None, ignore_cols=None, modifiers=None, datasource_args={}, data_split=None, auto_tidy=False, file_system_filters=None),    datasource_details_config: Optional[PodDetailsConfig] = None,    schema: Optional[Path] = None,):

Datasource configuration for a multi-datasource Pod.

Variables​

  • static datasource : str
  • static name : str

EHRNERProtocolArgumentsConfig​

class EHRNERProtocolArgumentsConfig(aggregator: Optional[AggregatorConfig] = None):

Configuration for EHRNERProtocol arguments.

Variables​

EHRNERProtocolConfig​

class EHRNERProtocolConfig(    name: str,    arguments: Optional[EHRNERProtocolArgumentsConfig] = EHRNERProtocolArgumentsConfig(aggregator=None),):

Configuration for EHRNERProtocol.

Ancestors​

Variables​

  • static name : str

EHRPatientInfoDownloadAlgorithmConfig​

class EHRPatientInfoDownloadAlgorithmConfig(    name: str,    arguments: Optional[EHRPatientInfoDownloadArgumentsConfig] = EHRPatientInfoDownloadArgumentsConfig(),):

Configuration for EHRPatientInfoDownloadAlgorithm.

Ancestors​

Variables​

  • static name : str

EHRPatientQueryAlgorithmConfig​

class EHRPatientQueryAlgorithmConfig(    name: str,    arguments: EHRPatientQueryArgumentsConfig = EHRPatientQueryArgumentsConfig(),):

Configuration for EHRPatientQuery algorithm.

Ancestors​

Variables​

  • static name : str

ETDRSAlgorithmArgumentsConfig​

class ETDRSAlgorithmArgumentsConfig(    laterality: str,    slo_photo_location_prefixes: Optional[SLOSegmentationLocationPrefix] = None,    slo_image_metadata_columns: Optional[SLOImageMetadataColumns] = None,    oct_image_metadata_columns: Optional[OCTImageMetadataColumns] = None,    threshold: float = 0.7,    calculate_on_oct: bool = False,    slo_mm_width: float = 8.8,    slo_mm_height: float = 8.8,):

Configuration for ETDRSAlgorithm arguments.

Variables​

  • static calculate_on_oct : bool
  • static laterality : str
  • static oct_image_metadata_columns : Optional[bitfount.federated.algorithms.ophthalmology.ophth_algo_types.OCTImageMetadataColumns]
  • static slo_image_metadata_columns : Optional[bitfount.federated.algorithms.ophthalmology.ophth_algo_types.SLOImageMetadataColumns]
  • static slo_mm_height : float
  • static slo_mm_width : float
  • static slo_photo_location_prefixes : Optional[bitfount.federated.algorithms.ophthalmology.ophth_algo_types.SLOSegmentationLocationPrefix]
  • static threshold : float

ETDRSAlgorithmConfig​

class ETDRSAlgorithmConfig(name: str, arguments: Optional[ETDRSAlgorithmArgumentsConfig]):

Configuration for ETDRSAlgorithm.

Ancestors​

Variables​

  • static name : str

FederatedAveragingProtocolArgumentsConfig​

class FederatedAveragingProtocolArgumentsConfig(    aggregator: Optional[AggregatorConfig] = None,    steps_between_parameter_updates: Optional[int] = None,    epochs_between_parameter_updates: Optional[int] = None,    auto_eval: bool = True,    secure_aggregation: bool = False,):

Configuration for the FedreatedAveraging Protocol arguments.

Variables​

  • static auto_eval : bool
  • static epochs_between_parameter_updates : int | None
  • static secure_aggregation : bool
  • static steps_between_parameter_updates : int | None

FederatedAveragingProtocolConfig​

class FederatedAveragingProtocolConfig(    name: str,    arguments: Optional[FederatedAveragingProtocolArgumentsConfig] = FederatedAveragingProtocolArgumentsConfig(aggregator=None, steps_between_parameter_updates=None, epochs_between_parameter_updates=None, auto_eval=True, secure_aggregation=False),):

Configuration for the FederatedAveraging Protocol.

Ancestors​

Variables​

  • static name : str

FederatedModelTrainingAlgorithmConfig​

class FederatedModelTrainingAlgorithmConfig(    name: str,    arguments: Optional[FederatedModelTrainingArgumentsConfig] = FederatedModelTrainingArgumentsConfig(modeller_checkpointing=True, checkpoint_filename=None),    model: Optional[ModelConfig] = None,    pretrained_file: Optional[Path] = None,):

Configuration for the FederatedModelTraining algorithm.

Ancestors​

Variables​

  • static name : str

FederatedModelTrainingArgumentsConfig​

class FederatedModelTrainingArgumentsConfig(    modeller_checkpointing: bool = True, checkpoint_filename: Optional[str] = None,):

Configuration for the FederatedModelTraining algorithm arguments.

Variables​

  • static checkpoint_filename : str | None
  • static modeller_checkpointing : bool

FileSystemFilterConfig​

class FileSystemFilterConfig(    file_extension: Optional[SingleOrMulti[str]] = None,    strict_file_extension: bool = False,    file_creation_min_date: Optional[Date] = None,    file_modification_min_date: Optional[Date] = None,    file_creation_max_date: Optional[Date] = None,    file_modification_max_date: Optional[Date] = None,    min_file_size: Optional[float] = None,    max_file_size: Optional[float] = None,):

Filter files based on various criteria.

Arguments

  • file_extension: File extension(s) of the data files. If None, all files will be searched. Can either be a single file extension or a list of file extensions. Case-insensitive. Defaults to None.
  • strict_file_extension: Whether File loading should be strictly done on files with the explicit file extension provided. If set to True will only load those files in the dataset. Otherwise, it will scan the given path for files of the same type as the provided file extension. Only relevant if file_extension is provided. Defaults to False.
  • file_creation_min_date: The oldest possible date to consider for file creation. If None, this filter will not be applied. Defaults to None.
  • file_modification_min_date: The oldest possible date to consider for file modification. If None, this filter will not be applied. Defaults to None.
  • file_creation_max_date: The newest possible date to consider for file creation. If None, this filter will not be applied. Defaults to None.
  • file_modification_max_date: The newest possible date to consider for file modification. If None, this filter will not be applied. Defaults to None.
  • min_file_size: The minimum file size in megabytes to consider. If None, all files will be considered. Defaults to None.
  • max_file_size: The maximum file size in megabytes to consider. If None, all files will be considered. Defaults to None.

Variables​

  • static file_creation_max_date : Optional[Date]
  • static file_creation_min_date : Optional[Date]
  • static file_modification_max_date : Optional[Date]
  • static file_modification_min_date : Optional[Date]
  • static max_file_size : Optional[float]
  • static min_file_size : Optional[float]
  • static strict_file_extension : bool

FoveaCoordinatesAlgorithmArgumentsConfig​

class FoveaCoordinatesAlgorithmArgumentsConfig(    bscan_width_col: str = 'size_width',    location_prefixes: Optional[SLOSegmentationLocationPrefix] = None,):

Configuration for FoveaCoordinatesAlgorithm arguments.

Variables​

  • static bscan_width_col : str
  • static location_prefixes : Optional[bitfount.federated.algorithms.ophthalmology.ophth_algo_types.SLOSegmentationLocationPrefix]

FoveaCoordinatesAlgorithmConfig​

class FoveaCoordinatesAlgorithmConfig(    name: str,    arguments: Optional[FoveaCoordinatesAlgorithmArgumentsConfig] = FoveaCoordinatesAlgorithmArgumentsConfig(bscan_width_col='size_width', location_prefixes=None),):

Configuration for FoveaCoordinatesAlgorithm.

Ancestors​

Variables​

  • static name : str

GAScreeningProtocolAmethystArgumentsConfig​

class GAScreeningProtocolAmethystArgumentsConfig(    aggregator: Optional[AggregatorConfig] = None,    results_notification_email: Optional[bool] = False,    trial_name: Optional[str] = None,    rename_columns: Optional[dict[str, str]] = None,):

Configuration for GAScreeningProtocolAmethyst arguments.

Variables​

  • static rename_columns : Optional[dict[str, str]]
  • static results_notification_email : Optional[bool]
  • static trial_name : str | None

GAScreeningProtocolAmethystConfig​

class GAScreeningProtocolAmethystConfig(    name: str,    arguments: Optional[GAScreeningProtocolAmethystArgumentsConfig] = GAScreeningProtocolAmethystArgumentsConfig(aggregator=None, results_notification_email=False, trial_name=None, rename_columns=None),):

Configuration for GAScreeningProtocolAmethyst.

Ancestors​

Variables​

  • static name : str

GAScreeningProtocolBronzeArgumentsConfig​

class GAScreeningProtocolBronzeArgumentsConfig(    aggregator: Optional[AggregatorConfig] = None,    results_notification_email: Optional[bool] = False,    trial_name: Optional[str] = None,    rename_columns: Optional[dict[str, str]] = None,):

Configuration for GAScreeningProtocolBronze arguments.

Variables​

  • static rename_columns : Optional[dict[str, str]]
  • static results_notification_email : Optional[bool]
  • static trial_name : str | None

GAScreeningProtocolBronzeConfig​

class GAScreeningProtocolBronzeConfig(    name: str,    arguments: Optional[GAScreeningProtocolBronzeArgumentsConfig] = GAScreeningProtocolBronzeArgumentsConfig(aggregator=None, results_notification_email=False, trial_name=None, rename_columns=None),):

Configuration for GAScreeningProtocolBronze.

Ancestors​

Variables​

  • static name : str

GAScreeningProtocolBronzeWithEHRConfig​

class GAScreeningProtocolBronzeWithEHRConfig(    name: str,    arguments: Optional[GAScreeningProtocolBronzeArgumentsConfig] = GAScreeningProtocolBronzeArgumentsConfig(aggregator=None, results_notification_email=False, trial_name=None, rename_columns=None),):

Configuration for GAScreeningProtocolBronzeWithEHR.

Ancestors​

Variables​

  • static name : str

GAScreeningProtocolJadeArgumentsConfig​

class GAScreeningProtocolJadeArgumentsConfig(    aggregator: Optional[AggregatorConfig] = None,    results_notification_email: Optional[bool] = False,    trial_name: Optional[str] = None,    rename_columns: Optional[dict[str, str]] = None,):

Configuration for GAScreeningProtocolJade arguments.

Variables​

  • static rename_columns : Optional[dict[str, str]]
  • static results_notification_email : Optional[bool]
  • static trial_name : str | None

GAScreeningProtocolJadeConfig​

class GAScreeningProtocolJadeConfig(    name: str,    arguments: Optional[GAScreeningProtocolJadeArgumentsConfig] = GAScreeningProtocolJadeArgumentsConfig(aggregator=None, results_notification_email=False, trial_name=None, rename_columns=None),):

Configuration for GAScreeningProtocolJade.

Ancestors​

Variables​

  • static name : str

GATrialCalculationAlgorithmAmethystArgumentsConfig​

class GATrialCalculationAlgorithmAmethystArgumentsConfig(    ga_area_include_segmentations: Optional[list[str]] = None,    ga_area_exclude_segmentations: Optional[list[str]] = None,    extra_segmentations: Optional[list[str]] = None,):

Configuration for GATrialCalculationAlgorithmAmethyst arguments.

GATrialCalculationAlgorithmAmethystConfig​

class GATrialCalculationAlgorithmAmethystConfig(    name: str,    arguments: Optional[GATrialCalculationAlgorithmAmethystArgumentsConfig] = GATrialCalculationAlgorithmAmethystArgumentsConfig(ga_area_include_segmentations=None, ga_area_exclude_segmentations=None, extra_segmentations=None),):

Configuration for GATrialCalculationAlgorithmAmethyst.

Ancestors​

Variables​

  • static name : str

GATrialCalculationAlgorithmBronzeArgumentsConfig​

class GATrialCalculationAlgorithmBronzeArgumentsConfig(    ga_area_include_segmentations: Optional[list[str]] = None,    ga_area_exclude_segmentations: Optional[list[str]] = None,    extra_segmentations: Optional[list[str]] = None,    fovea_landmark_idx: Optional[int] = 2,):

Configuration for GATrialCalculationAlgorithmBronze arguments.

GATrialCalculationAlgorithmBronzeConfig​

class GATrialCalculationAlgorithmBronzeConfig(    name: str,    arguments: Optional[GATrialCalculationAlgorithmBronzeArgumentsConfig] = GATrialCalculationAlgorithmBronzeArgumentsConfig(ga_area_include_segmentations=None, ga_area_exclude_segmentations=None, extra_segmentations=None, fovea_landmark_idx=2),):

Configuration for GATrialCalculationAlgorithmBronze.

Ancestors​

Variables​

  • static name : str

GATrialCalculationAlgorithmCharcoalArgumentsConfig​

class GATrialCalculationAlgorithmCharcoalArgumentsConfig(    ga_area_include_segmentations: Optional[list[str]] = None,    ga_area_exclude_segmentations: Optional[list[str]] = None,    extra_segmentations: Optional[list[str]] = None,):

Configuration for GATrialCalculationAlgorithmCharcoal arguments.

GATrialCalculationAlgorithmCharcoalConfig​

class GATrialCalculationAlgorithmCharcoalConfig(    name: str,    arguments: Optional[GATrialCalculationAlgorithmCharcoalArgumentsConfig] = GATrialCalculationAlgorithmCharcoalArgumentsConfig(ga_area_include_segmentations=None, ga_area_exclude_segmentations=None, extra_segmentations=None),):

Configuration for GATrialCalculationAlgorithmCharcoal.

Ancestors​

Variables​

  • static name : str

GATrialCalculationAlgorithmJadeArgumentsConfig​

class GATrialCalculationAlgorithmJadeArgumentsConfig(    ga_area_include_segmentations: Optional[list[str]] = None,    ga_area_exclude_segmentations: Optional[list[str]] = None,    extra_segmentations: Optional[list[str]] = None,):

Configuration for GATrialCalculationAlgorithmJade arguments.

GATrialCalculationAlgorithmJadeConfig​

class GATrialCalculationAlgorithmJadeConfig(    name: str,    arguments: Optional[GATrialCalculationAlgorithmJadeArgumentsConfig] = GATrialCalculationAlgorithmJadeArgumentsConfig(ga_area_include_segmentations=None, ga_area_exclude_segmentations=None, extra_segmentations=None),):

Configuration for GATrialCalculationAlgorithmJade.

Ancestors​

Variables​

  • static name : str

GATrialPDFGeneratorAlgorithmAmethystArgumentsConfig​

class GATrialPDFGeneratorAlgorithmAmethystArgumentsConfig(    report_metadata: Optional[ReportMetadata] = None,    filename_prefix: Optional[str] = None,    save_path: Optional[Path] = None,    filter: Optional[list[ColumnFilter]] = None,    pdf_filename_columns: Optional[list[str]] = None,    trial_name: Optional[str] = None,):

Configuration for GATrialPDFGeneratorAlgorithmAmethyst arguments.

Variables​

  • static filename_prefix : str | None
  • static filter : Optional[list[bitfount.federated.algorithms.ophthalmology.trial_inclusion_filters.ColumnFilter]]
  • static pdf_filename_columns : Optional[list[str]]
  • static report_metadata : Optional[bitfount.federated.algorithms.ophthalmology.ophth_algo_types.ReportMetadata]
  • static trial_name : str | None

GATrialPDFGeneratorAlgorithmAmethystConfig​

class GATrialPDFGeneratorAlgorithmAmethystConfig(    name: str,    arguments: Optional[GATrialPDFGeneratorAlgorithmAmethystArgumentsConfig] = GATrialPDFGeneratorAlgorithmAmethystArgumentsConfig(report_metadata=None, filename_prefix=None, save_path=None, filter=None, pdf_filename_columns=None, trial_name=None),):

Configuration for GATrialPDFGeneratorAlgorithmAmethyst.

Ancestors​

Variables​

  • static name : str

GATrialPDFGeneratorAlgorithmJadeArgumentsConfig​

class GATrialPDFGeneratorAlgorithmJadeArgumentsConfig(    report_metadata: Optional[ReportMetadata] = None,    filename_prefix: Optional[str] = None,    save_path: Optional[Path] = None,    filter: Optional[list[ColumnFilter]] = None,    pdf_filename_columns: Optional[list[str]] = None,    trial_name: Optional[str] = None,):

Configuration for GATrialPDFGeneratorAlgorithmJade arguments.

Variables​

  • static filename_prefix : str | None
  • static filter : Optional[list[bitfount.federated.algorithms.ophthalmology.trial_inclusion_filters.ColumnFilter]]
  • static pdf_filename_columns : Optional[list[str]]
  • static report_metadata : Optional[bitfount.federated.algorithms.ophthalmology.ophth_algo_types.ReportMetadata]
  • static trial_name : str | None

GATrialPDFGeneratorAlgorithmJadeConfig​

class GATrialPDFGeneratorAlgorithmJadeConfig(    name: str,    arguments: Optional[GATrialPDFGeneratorAlgorithmJadeArgumentsConfig] = GATrialPDFGeneratorAlgorithmJadeArgumentsConfig(report_metadata=None, filename_prefix=None, save_path=None, filter=None, pdf_filename_columns=None, trial_name=None),):

Configuration for GATrialPDFGeneratorAlgorithmJade.

Ancestors​

Variables​

  • static name : str

GenericAlgorithmConfig​

class GenericAlgorithmConfig(name: str, arguments: _JSONDict = {}):

Configuration for unspecified algorithm plugins.

Raises

  • ValueError: if the algorithm name starts with bitfount.

Ancestors​

Variables​

  • static name : str

GenericBiomarkerProtocolGraniteArgumentsConfig​

class GenericBiomarkerProtocolGraniteArgumentsConfig(    aggregator: Optional[AggregatorConfig] = None,    results_notification_email: Optional[bool] = False,    scan_selection: Optional[str] = 'latest',    biomarker_groups: Optional[list[str]] = None,    biomarker_names: Optional[list[str]] = None,):

Configuration for GenericBiomarkerProtocolGranite arguments.

Variables​

  • static biomarker_groups : Optional[list[str]]
  • static biomarker_names : Optional[list[str]]
  • static results_notification_email : Optional[bool]
  • static scan_selection : str | None

GenericBiomarkerProtocolGraniteConfig​

class GenericBiomarkerProtocolGraniteConfig(    name: str,    arguments: Optional[GenericBiomarkerProtocolGraniteArgumentsConfig] = GenericBiomarkerProtocolGraniteArgumentsConfig(aggregator=None, results_notification_email=False, scan_selection='latest', biomarker_groups=None, biomarker_names=None),):

Configuration for GenericBiomarkerProtocolGranite.

Ancestors​

Variables​

  • static name : str

GenericProtocolConfig​

class GenericProtocolConfig(name: str, arguments: _JSONDict = {}):

Configuration for unspecified protocol plugins.

Raises

  • ValueError: if the protocol name starts with bitfount.

Ancestors​

Variables​

  • static name : str

HubConfig​

class HubConfig(url: str = 'https://hub.bitfount.com'):

Configuration for the hub.

Variables​

  • static url : str

HuggingFaceImageClassificationInferenceAlgorithmConfig​

class HuggingFaceImageClassificationInferenceAlgorithmConfig(    name: str,    arguments: Optional[HuggingFaceImageClassificationInferenceArgumentsConfig],):

Configuration for HuggingFaceImageClassificationInference.

Ancestors​

Variables​

  • static name : str

HuggingFaceImageClassificationInferenceArgumentsConfig​

class HuggingFaceImageClassificationInferenceArgumentsConfig(    model_id: str,    model_input_format: str = 'torch_tensor',    apply_softmax_to_predictions: bool = True,    batch_size: int = 1,    seed: int = 42,    top_k: int = 5,    subfolder: Optional[str] = None,    postprocessors: Optional[list[dict[str, Any]]] = None,    access_token: Optional[str] = None,):

Configuration for HuggingFaceImageClassificationInference arguments.

Variables​

  • static access_token : str | None
  • static apply_softmax_to_predictions : bool
  • static batch_size : int
  • static model_id : str
  • static model_input_format : str
  • static postprocessors : Optional[list[dict[str, typing.Any]]]
  • static seed : int
  • static subfolder : str | None
  • static top_k : int

HuggingFaceImageSegmentationInferenceAlgorithmConfig​

class HuggingFaceImageSegmentationInferenceAlgorithmConfig(    name: str, arguments: Optional[HuggingFaceImageSegmentationInferenceArgumentsConfig],):

Configuration for HuggingFaceImageSegmentationInference.

Ancestors​

Variables​

  • static name : str

HuggingFaceImageSegmentationInferenceArgumentsConfig​

class HuggingFaceImageSegmentationInferenceArgumentsConfig(    model_id: str,    alpha: float = 0.3,    batch_size: int = 1,    dataframe_output: bool = False,    mask_threshold: float = 0.5,    overlap_mask_area_threshold: float = 0.5,    seed: int = 42,    save_path: Optional[str] = None,    subtask: Optional[str] = None,    threshold: float = 0.9,    access_token: Optional[str] = None,):

Configuration for HuggingFaceImageSegmentationInference arguments.

Variables​

  • static access_token : str | None
  • static alpha : float
  • static batch_size : int
  • static dataframe_output : bool
  • static mask_threshold : float
  • static model_id : str
  • static overlap_mask_area_threshold : float
  • static save_path : str | None
  • static seed : int
  • static subtask : str | None
  • static threshold : float

HuggingFaceNERInferenceAlgorithmConfig​

class HuggingFaceNERInferenceAlgorithmConfig(    name: str, arguments: Optional[HuggingFaceNERInferenceArgumentsConfig] = None,):

Configuration for HuggingFaceNERInference algorithm.

Ancestors​

Variables​

  • static name : str

HuggingFaceNERInferenceArgumentsConfig​

class HuggingFaceNERInferenceArgumentsConfig(    model_id: Optional[str] = 'OpenMed/OpenMed-NER-PathologyDetect-PubMed-v2-109M',    batch_size: Optional[int] = 16,    aggregation_strategy: Optional[str] = 'simple',    seed: Optional[int] = 42,    postprocessors: Optional[list[dict[str, Any]]] = None,    access_token: Optional[str] = None,):

Configuration for HuggingFaceNERInference algorithm arguments.

Variables​

  • static access_token : str | None
  • static aggregation_strategy : str | None
  • static batch_size : int | None
  • static model_id : str | None
  • static postprocessors : Optional[list[dict[str, typing.Any]]]
  • static seed : int | None

HuggingFacePerplexityEvaluationAlgorithmConfig​

class HuggingFacePerplexityEvaluationAlgorithmConfig(    name: str, arguments: Optional[HuggingFacePerplexityEvaluationArgumentsConfig],):

Configuration for the HuggingFacePerplexityEvaluation algorithm.

Ancestors​

Variables​

  • static name : str

HuggingFacePerplexityEvaluationArgumentsConfig​

class HuggingFacePerplexityEvaluationArgumentsConfig(    model_id: str, stride: int = 512, seed: int = 42, access_token: Optional[str] = None,):

Configuration for the HuggingFacePerplexityEvaluation algorithm arguments.

Variables​

  • static access_token : str | None
  • static model_id : str
  • static seed : int
  • static stride : int

HuggingFaceTextClassificationInferenceAlgorithmConfig​

class HuggingFaceTextClassificationInferenceAlgorithmConfig(    name: str, arguments: Optional[HuggingFaceTextClassificationInferenceArgumentsConfig],):

Configuration for HuggingFaceTextClassificationInference.

Ancestors​

Variables​

  • static name : str

HuggingFaceTextClassificationInferenceArgumentsConfig​

class HuggingFaceTextClassificationInferenceArgumentsConfig(    model_id: str,    batch_size: int = 1,    function_to_apply: Optional[str] = None,    seed: int = 42,    top_k: int = 5,    access_token: Optional[str] = None,):

Configuration for HuggingFaceTextClassificationInference arguments.

Variables​

  • static access_token : str | None
  • static batch_size : int
  • static function_to_apply : str | None
  • static model_id : str
  • static seed : int
  • static top_k : int

HuggingFaceTextGenerationInferenceAlgorithmConfig​

class HuggingFaceTextGenerationInferenceAlgorithmConfig(    name: str, arguments: Optional[HuggingFaceTextGenerationInferenceArgumentsConfig],):

Configuration for the HuggingFaceTextGenerationInference algorithm.

Ancestors​

Variables​

  • static name : str

HuggingFaceTextGenerationInferenceArgumentsConfig​

class HuggingFaceTextGenerationInferenceArgumentsConfig(    model_id: str,    prompt_format: Optional[str] = None,    max_length: int = 50,    num_return_sequences: int = 1,    seed: int = 42,    min_new_tokens: int = 1,    repetition_penalty: float = 1.0,    num_beams: int = 1,    early_stopping: bool = True,    pad_token_id: Optional[int] = None,    eos_token_id: Optional[int] = None,    device: Optional[str] = None,    torch_dtype: str = 'float32',    access_token: Optional[str] = None,):

Configuration for the HuggingFaceTextGenerationInference algorithm arguments.

Variables​

  • static access_token : str | None
  • static device : str | None
  • static early_stopping : bool
  • static eos_token_id : int | None
  • static max_length : int
  • static min_new_tokens : int
  • static model_id : str
  • static num_beams : int
  • static num_return_sequences : int
  • static pad_token_id : int | None
  • static prompt_format : str | None
  • static repetition_penalty : float
  • static seed : int
  • static torch_dtype : str

InferenceAndCSVReportArgumentsConfig​

class InferenceAndCSVReportArgumentsConfig(aggregator: Optional[AggregatorConfig] = None):

Configuration for InferenceAndCSVReport arguments.

Variables​

InferenceAndCSVReportConfig​

class InferenceAndCSVReportConfig(    name: str,    arguments: Optional[InferenceAndCSVReportArgumentsConfig] = InferenceAndCSVReportArgumentsConfig(aggregator=None),):

Configuration for InferenceAndCSVReport.

Ancestors​

Variables​

  • static name : str

InferenceAndCSVReportWithAggregateReportingArgumentsConfig​

class InferenceAndCSVReportWithAggregateReportingArgumentsConfig(    aggregator: Optional[AggregatorConfig] = None,):

Configuration for InferenceAndCSVReportWithAggregateReporting arguments.

Variables​

InferenceAndCSVReportWithAggregateReportingConfig​

class InferenceAndCSVReportWithAggregateReportingConfig(    name: str,    arguments: Optional[InferenceAndCSVReportWithAggregateReportingArgumentsConfig] = InferenceAndCSVReportWithAggregateReportingArgumentsConfig(aggregator=None),):

Configuration for InferenceAndCSVReportWithAggregateReporting.

Ancestors​

Variables​

  • static name : str

InferenceAndReturnCSVReportArgumentsConfig​

class InferenceAndReturnCSVReportArgumentsConfig(    aggregator: Optional[AggregatorConfig] = None,):

Configuration for InferenceAndReturnCSVReport arguments.

Variables​

InferenceAndReturnCSVReportConfig​

class InferenceAndReturnCSVReportConfig(    name: str,    arguments: Optional[InferenceAndReturnCSVReportArgumentsConfig] = InferenceAndReturnCSVReportArgumentsConfig(aggregator=None),):

Configuration for InferenceAndReturnCSVReport.

Ancestors​

Variables​

  • static name : str

InstrumentedInferenceAndCSVReportArgumentsConfig​

class InstrumentedInferenceAndCSVReportArgumentsConfig(    aggregator: Optional[AggregatorConfig] = None,):

Configuration for InstrumentedInferenceAndCSVReport arguments.

Variables​

InstrumentedInferenceAndCSVReportConfig​

class InstrumentedInferenceAndCSVReportConfig(    name: str,    arguments: Optional[InstrumentedInferenceAndCSVReportArgumentsConfig] = InstrumentedInferenceAndCSVReportArgumentsConfig(aggregator=None),):

Configuration for InstrumentedInferenceAndCSVReport.

Ancestors​

Variables​

  • static name : str

LongitudinalAlgorithmArgumentsConfig​

class LongitudinalAlgorithmArgumentsConfig():

Configuration for LongitudinalAlgorithm arguments.

LongitudinalAlgorithmConfig​

class LongitudinalAlgorithmConfig(    name: str,    arguments: Optional[LongitudinalAlgorithmArgumentsConfig] = LongitudinalAlgorithmArgumentsConfig(),):

Configuration for LongitudinalAlgorithm.

Ancestors​

Variables​

  • static name : str

ModelAlgorithmConfig​

class ModelAlgorithmConfig(    name: str,    arguments: Optional[Any] = None,    model: Optional[ModelConfig] = None,    pretrained_file: Optional[Path] = None,):

Configuration for the Model algorithms.

Ancestors​

Subclasses​

Variables​

ModelConfig​

class ModelConfig(    name: Optional[str] = None,    structure: Optional[ModelStructureConfig] = None,    bitfount_model: Optional[BitfountModelReferenceConfig] = None,    hyperparameters: _JSONDict = {},    logger_config: Optional[LoggerConfig] = None,    dp_config: Optional[DPModellerConfig] = None,):

Configuration for the model.

Variables​

  • static hyperparameters : dict[str, typing.Any]
  • static name : str | None

ModelEvaluationAlgorithmConfig​

class ModelEvaluationAlgorithmConfig(    name: str,    arguments: Optional[ModelEvaluationArgumentsConfig] = ModelEvaluationArgumentsConfig(),    model: Optional[ModelConfig] = None,    pretrained_file: Optional[Path] = None,):

Configuration for the ModelEvaluation algorithm.

Ancestors​

Variables​

  • static name : str

ModelEvaluationArgumentsConfig​

class ModelEvaluationArgumentsConfig():

Configuration for the ModelEvaluation algorithm arguments.

ModelInferenceAlgorithmConfig​

class ModelInferenceAlgorithmConfig(    name: str,    arguments: ModelInferenceArgumentsConfig = ModelInferenceArgumentsConfig(class_outputs=None, postprocessors=None),    model: Optional[ModelConfig] = None,    pretrained_file: Optional[Path] = None,):

Configuration for the ModelInference algorithm.

Ancestors​

Variables​

  • static name : str

ModelInferenceArgumentsConfig​

class ModelInferenceArgumentsConfig(    class_outputs: Optional[list[str]] = None,    postprocessors: Optional[list[dict[str, Any]]] = None,):

Configuration for the ModelInference algorithm arguments.

Variables​

  • static class_outputs : Optional[list[str]]
  • static postprocessors : Optional[list[dict[str, typing.Any]]]

ModelStructureConfig​

class ModelStructureConfig(name: str, arguments: _JSONDict = {}):

Configuration for the ModelStructure.

Variables​

  • static name : str

ModelTrainingAndEvaluationAlgorithmConfig​

class ModelTrainingAndEvaluationAlgorithmConfig(    name: str,    arguments: Optional[ModelTrainingAndEvaluationArgumentsConfig] = ModelTrainingAndEvaluationArgumentsConfig(),    model: Optional[ModelConfig] = None,    pretrained_file: Optional[Path] = None,):

Configuration for the ModelTrainingAndEvaluation algorithm.

Ancestors​

Variables​

  • static name : str

ModelTrainingAndEvaluationArgumentsConfig​

class ModelTrainingAndEvaluationArgumentsConfig():

Configuration for the ModelTrainingAndEvaluation algorithm arguments.

ModellerConfig​

class ModellerConfig(    pods: PodsConfig,    task: TaskConfig,    secrets: Optional[APIKeys | RefreshableJWT | dict[SecretsUse, APIKeys | RefreshableJWT]] = None,    modeller: ModellerUserConfig = ModellerUserConfig(username='_default', identity_verification_method='oidc-device-code', private_key_file=None),    hub: HubConfig = HubConfig(url='https://hub.bitfount.com'),    message_service: MessageServiceConfig = MessageServiceConfig(url='messaging.bitfount.com', port=443, tls=True, use_local_storage=False),    version: Optional[str] = None,    project_id: Optional[str] = None,    run_on_new_data_only: bool = False,    batched_execution: Optional[bool] = None,    test_run: bool = False,    force_rerun_failed_files: bool = True,    enable_anonymized_tracker_upload: bool = False,    requires_ehr_connection: bool = False,    supports_mps: Optional[bool] = None,    task_run_metadata: Optional[_JSONDict] = None,):

Full configuration for the modeller.

Subclasses​

Variables​

  • static batched_execution : Optional[bool]
  • static enable_anonymized_tracker_upload : bool
  • static force_rerun_failed_files : bool
  • static project_id : str | None
  • static requires_ehr_connection : bool
  • static run_on_new_data_only : bool
  • static supports_mps : Optional[bool]
  • static task_run_metadata : Optional[dict[str, typing.Any]]
  • static test_run : bool
  • static version : str | None

ModellerUserConfig​

class ModellerUserConfig(    username: str = '_default',    identity_verification_method: str = 'oidc-device-code',    private_key_file: Optional[Path] = None,):

Configuration for the modeller.

Arguments

  • username: The username of the modeller. This can be picked up automatically from the session but can be overridden here.
  • identity_verification_method: The method to use for identity verification. Accepts one of the values in IDENTITY_VERIFICATION_METHODS, i.e. one of key-based, oidc-auth-code or oidc-device-code.
  • private_key_file: The path to the private key file for key-based identity verification.

Variables​

  • static identity_verification_method : str
  • static username : str

NextGenSearchProtocolArgumentsConfig​

class NextGenSearchProtocolArgumentsConfig(    rename_columns: Optional[dict[str, str]] = None,):

Configuration for NextGenSearchProtocol arguments.

Variables​

  • static rename_columns : Optional[dict[str, str]]

NextGenSearchProtocolConfig​

class NextGenSearchProtocolConfig(    name: str,    arguments: Optional[NextGenSearchProtocolArgumentsConfig] = NextGenSearchProtocolArgumentsConfig(rename_columns=None),):

Configuration for NextGenSearchProtocol.

Ancestors​

Variables​

  • static name : str

PathConfig​

class PathConfig(path: Path):

Configuration for the path.

Variables​

PatientTrialMatchingProtocolArgumentsConfig​

class PatientTrialMatchingProtocolArgumentsConfig(    aggregator: Optional[AggregatorConfig] = None,    trials_connection_string: Optional[str] = None,    trials_database_url: Optional[str] = None,):

Configuration for PatientTrialMatchingProtocol arguments.

Variables​

  • static trials_connection_string : str | None
  • static trials_database_url : str | None

PatientTrialMatchingProtocolConfig​

class PatientTrialMatchingProtocolConfig(    name: str,    arguments: Optional[PatientTrialMatchingProtocolArgumentsConfig] = PatientTrialMatchingProtocolArgumentsConfig(aggregator=None, trials_connection_string=None, trials_database_url=None),):

Configuration for PatientTrialMatchingProtocol.

Ancestors​

Variables​

  • static name : str

PodConfig​

class PodConfig(    name: str,    secrets: Optional[APIKeys | RefreshableJWT | dict[SecretsUse, APIKeys | RefreshableJWT]] = None,    datasources: Optional[list[DatasourceConfig]] = None,    access_manager: AccessManagerConfig = AccessManagerConfig(url='https://am.hub.bitfount.com'),    hub: HubConfig = HubConfig(url='https://hub.bitfount.com'),    message_service: MessageServiceConfig = MessageServiceConfig(url='messaging.bitfount.com', port=443, tls=True, use_local_storage=False),    differential_privacy: Optional[DPPodConfig] = None,    approved_pods: Optional[list[str]] = None,    username: str = '_default',    update_schema: bool = False,    pod_db: Union[bool, PodDbConfig] = False,    show_datapoints_with_results_in_db: bool = True,    version: Optional[str] = None,    ehr_config: Optional[EHRConfig] = None,    config_reload_file_poll_interval_seconds: Optional[float] = None,    cluster_id: Optional[str] = None,):

Full configuration for the pod.

Raises

  • ValueError: If a username is not provided alongside API keys.

Variables​

  • static approved_pods : Optional[list[str]]
  • static cluster_id : str | None
  • static config_reload_file_poll_interval_seconds : Optional[float]
  • static name : str
  • static show_datapoints_with_results_in_db : bool
  • static update_schema : bool
  • static username : str
  • static version : str | None
  • pod_id : str - The pod ID of the pod specified.

PodDataConfig​

class PodDataConfig(    force_stypes: Optional[dict] = None,    column_descriptions: Optional[Union[Mapping[str, Mapping[str, str]], Mapping[str, str]]] = None,    table_descriptions: Optional[Mapping[str, str]] = None,    description: Optional[str] = None,    ignore_cols: Optional[Union[list[str], Mapping[str, list[str]]]] = None,    modifiers: Optional[dict[str, DataPathModifiers]] = None,    datasource_args: _JSONDict = {},    data_split: Optional[DataSplitConfig] = None,    auto_tidy: bool = False,    file_system_filters: Optional[FileSystemFilterConfig] = None,):

Configuration for the Schema, BaseSource and Pod.

Arguments

  • force_stypes: The semantic types to force for the data. Can either be:
  • A mapping from pod name to type-to-column mapping (e.g. {"pod_name": {"categorical": ["col1", "col2"]}}).
  • A direct mapping from type to column names (e.g. {"categorical": ["col1", "col2"]}).
  • ignore_cols: The columns to ignore. This is passed to the data source.
  • modifiers: The modifiers to apply to the data. This is passed to the BaseSource.
  • datasource_args: Key-value pairs of arguments to pass to the data source constructor.
  • data_split: The data split configuration. This is passed to the data source.
  • auto_tidy: Whether to automatically tidy the data. This is used by the Pod and will result in removal of NaNs and normalisation of numeric values. Defaults to False.
  • file_system_filters: Filter files based on various criteria for datasources that are FileSystemIterable. Defaults to None.

Variables​

  • static auto_tidy : bool
  • static datasource_args : dict[str, typing.Any]
  • static description : str | None
  • static force_stypes : Optional[dict]

PodDbConfig​

class PodDbConfig(path: Path):

Configuration of the Pod DB.

Variables​

PodDetailsConfig​

class PodDetailsConfig(display_name: str, description: str = ''):

Configuration for the pod details.

Arguments

  • display_name: The display name of the pod.
  • description: The description of the pod.

Variables​

  • static description : str
  • static display_name : str

PodsConfig​

class PodsConfig(identifiers: list[str]):

Configuration for the pods to use for the modeller.

Variables​

  • static identifiers : list[str]

PrivateSqlQueryAlgorithmConfig​

class PrivateSqlQueryAlgorithmConfig(    name: str, arguments: PrivateSqlQueryArgumentsConfig,):

Configuration for the PrivateSqlQuery algorithm.

Ancestors​

Variables​

  • static name : str

PrivateSqlQueryArgumentsConfig​

class PrivateSqlQueryArgumentsConfig(    epsilon: float,    delta: float,    query: Optional[str] = None,    column_ranges: Optional[dict[str, PrivateSqlQueryColumnArgumentsConfig]] = None,    table: Optional[str] = None,    db_schema: Optional[str] = None,    aggregate_columns: Optional[list[str]] = None,    group_by_columns: Optional[list[str]] = None,    aggregation_func: Optional[str] = None,):

Configuration for the PrivateSqlQuery algorithm arguments.

Variables​

  • static aggregate_columns : Optional[list[str]]
  • static aggregation_func : str | None
  • static db_schema : str | None
  • static delta : float
  • static epsilon : float
  • static group_by_columns : Optional[list[str]]
  • static query : str | None
  • static table : str | None

PrivateSqlQueryColumnArgumentsConfig​

class PrivateSqlQueryColumnArgumentsConfig(    lower: Optional[int] = None, upper: Optional[int] = None,):

Configuration for the PrivateSqlQuery algorithm column arguments.

Variables​

  • static lower : int | None
  • static upper : int | None

ProtocolConfig​

class ProtocolConfig(name: str, arguments: Optional[Any] = None):

Configuration for the Protocol.

Subclasses​

Variables​

  • static arguments : Optional[Any]
  • static name : str

RecordFilterAlgorithmArgumentsConfig​

class RecordFilterAlgorithmArgumentsConfig(    strategies: list[FilterStrategy], filter_args_list: list[dict[str, Any]],):

Configuration for RecordFilter algorithm arguments.

Variables​

  • static filter_args_list : list[dict[str, typing.Any]]

RecordFilterAlgorithmConfig​

class RecordFilterAlgorithmConfig(    name: str, arguments: Optional[RecordFilterAlgorithmArgumentsConfig],):

Configuration for RecordFilter algorithm.

Ancestors​

Variables​

  • static name : str

ReduceCSVAlgorithmCharcoalArgumentsConfig​

class ReduceCSVAlgorithmCharcoalArgumentsConfig(    save_path: Optional[Path] = None,    eligible_only: bool = True,    delete_intermediate: Optional[bool] = None,):

Configuration for ReduceCSVAlgorithmCharcoal arguments.

Variables​

  • static delete_intermediate : Optional[bool]
  • static eligible_only : bool

ReduceCSVAlgorithmCharcoalConfig​

class ReduceCSVAlgorithmCharcoalConfig(    name: str,    arguments: Optional[ReduceCSVAlgorithmCharcoalArgumentsConfig] = ReduceCSVAlgorithmCharcoalArgumentsConfig(save_path=None, eligible_only=True, delete_intermediate=None),):

Configuration for ReduceCSVAlgorithmCharcoal.

Ancestors​

Variables​

  • static name : str

ResultsOnlyProtocolArgumentsConfig​

class ResultsOnlyProtocolArgumentsConfig(    aggregator: Optional[AggregatorConfig] = None,    secure_aggregation: bool = False,    save_location: Optional[list[SaveLocation]] = [<SaveLocation.Modeller: 'Modeller'>],    save_path: Optional[Path] = None,):

Configuration for the ResultsOnly Protocol arguments.

Variables​

  • static secure_aggregation : bool

ResultsOnlyProtocolConfig​

class ResultsOnlyProtocolConfig(    name: str,    arguments: Optional[ResultsOnlyProtocolArgumentsConfig] = ResultsOnlyProtocolArgumentsConfig(aggregator=None, secure_aggregation=False, save_location=[<SaveLocation.Modeller: 'Modeller'>], save_path=None),):

Configuration for the ResultsOnly Protocol.

Ancestors​

Variables​

  • static name : str

RetinalDiseaseProtocolCobaltArgumentsConfig​

class RetinalDiseaseProtocolCobaltArgumentsConfig(    aggregator: Optional[AggregatorConfig] = None,):

Configuration for RetinalDiseaseProtocolCobalt arguments.

Variables​

RetinalDiseaseProtocolCobaltConfig​

class RetinalDiseaseProtocolCobaltConfig(    name: str,    arguments: Optional[RetinalDiseaseProtocolCobaltArgumentsConfig] = RetinalDiseaseProtocolCobaltArgumentsConfig(aggregator=None),):

Configuration for RetinalDiseaseProtocolCobalt.

Ancestors​

Variables​

  • static name : str

SqlQueryAlgorithmConfig​

class SqlQueryAlgorithmConfig(name: str, arguments: SqlQueryArgumentsConfig):

Configuration for the SqlQuery algorithm.

Ancestors​

Variables​

  • static name : str

SqlQueryArgumentsConfig​

class SqlQueryArgumentsConfig(query: str, table: Optional[str] = None):

Configuration for the SqlQuery algorithm arguments.

Variables​

  • static query : str
  • static table : str | None

TIMMFederatedTrainingAlgorithmConfig​

class TIMMFederatedTrainingAlgorithmConfig(    name: str, arguments: Optional[TIMMFederatedTrainingArgumentsConfig],):

Configuration for TIMMFederatedTraining algorithm.

Ancestors​

Variables​

  • static name : str

TIMMFederatedTrainingArgumentsConfig​

class TIMMFederatedTrainingArgumentsConfig(    model_id: str,    args: Optional[TemplatedTimmTrainingConfig] = None,    labels: Optional[list[str]] = None,    pretrained_file: Optional[str] = None,    lora_rank: Optional[Union[int, str]] = None,):

Configuration for TIMMFederatedTraining algorithm arguments.

Variables​

  • static labels : Optional[list[str]]
  • static lora_rank : Union[int, str, ForwardRef(None)]
  • static model_id : str
  • static pretrained_file : str | None

TIMMFineTuningAlgorithmConfig​

class TIMMFineTuningAlgorithmConfig(    name: str, arguments: Optional[TIMMFineTuningArgumentsConfig],):

Configuration for TIMMFineTuning algorithm.

Ancestors​

Variables​

  • static name : str

TIMMFineTuningArgumentsConfig​

class TIMMFineTuningArgumentsConfig(    model_id: str,    args: Optional[TemplatedTimmTrainingConfig] = None,    batch_transformations: Optional[dict[str, list[Union[str, _JSONDict]]]] = None,    labels: Optional[list[str]] = None,    return_weights: bool = False,    save_path: Optional[Path] = None,):

Configuration for TIMMFineTuning algorithm arguments.

Variables​

  • static labels : Optional[list[str]]
  • static model_id : str
  • static return_weights : bool

TIMMInferenceAlgorithmConfig​

class TIMMInferenceAlgorithmConfig(    name: str, arguments: Optional[TIMMInferenceArgumentsConfig],):

Configuration for TIMMInference algorithm.

Ancestors​

Variables​

  • static name : str

TIMMInferenceArgumentsConfig​

class TIMMInferenceArgumentsConfig(    model_id: str,    num_classes: Optional[int] = None,    checkpoint_path: Optional[Path] = None,    class_outputs: Optional[list[str]] = None,    batch_transformations: Optional[list[Union[str, _JSONDict]]] = None,    hf_checkpoint_repo_id: Optional[str] = None,    hf_checkpoint_filename: Optional[str] = None,    postprocessors: Optional[list[dict[str, Any]]] = None,):

Configuration for TIMMInference algorithm arguments.

Variables​

  • static class_outputs : Optional[list[str]]
  • static hf_checkpoint_filename : str | None
  • static hf_checkpoint_repo_id : str | None
  • static model_id : str
  • static num_classes : int | None
  • static postprocessors : Optional[list[dict[str, typing.Any]]]

TaskConfig​

class TaskConfig(    protocol: Union[ProtocolConfig._get_subclasses()],    algorithm: Union[Union[AlgorithmConfig._get_subclasses()], list[Union[AlgorithmConfig._get_subclasses()]]],    data_structure: DataStructureConfig,    aggregator: Optional[AggregatorConfig] = None,    transformation_file: Optional[Path] = None,    primary_results_path: Optional[str] = None,):

Configuration for the task.

Arguments

  • protocol: The protocol configuration for the task.
  • algorithm: The algorithm(s) to run for this task.
  • data_structure: The data structure configuration.
  • aggregator: Optional aggregator configuration.
  • transformation_file: Optional path to a transformation file.
  • primary_results_path: Optional path for primary results.

Variables​

  • static primary_results_path : str | None

TaskFilterConfig​

class TaskFilterConfig(    filter_type: str, value: Union[Date, DateTD, int, float, bool, list[str], str],):

Configuration for a single task-level filter.

Arguments

  • filter_type: The type of filter (kebab-case string matching TaskFilterType).
  • value: The filter value. Can be a templated string (e.g., "{{ variable }}")

or an actual value. Type depends on filter_type:

  • file-creation-min-date, file-creation-max-date, file-modification-min-date, file-modification-max-date, min-dob, max-dob, scan-acquisition-min-date, scan-acquisition-max-date: dict with year (required), month (optional), day (optional)
  • min-file-size, max-file-size: float (MB)
  • min-frames, max-frames: int
  • check-required-fields: bool to enable required field checking
  • required-field-names: list[str] of field names to check
  • modality: str, either "OCT" or "SLO"
  • series-description: str
  • inferred-scan-type: str

Variables​

  • static filter_type : str
  • static value : Union[Date, DateTD, int, float, bool, list[str], str]

TemplatedModellerConfig​

class TemplatedModellerConfig(    pods: PodsConfig,    task: TaskConfig,    secrets: Optional[APIKeys | RefreshableJWT | dict[SecretsUse, APIKeys | RefreshableJWT]] = None,    modeller: ModellerUserConfig = ModellerUserConfig(username='_default', identity_verification_method='oidc-device-code', private_key_file=None),    hub: HubConfig = HubConfig(url='https://hub.bitfount.com'),    message_service: MessageServiceConfig = MessageServiceConfig(url='messaging.bitfount.com', port=443, tls=True, use_local_storage=False),    version: Optional[str] = None,    project_id: Optional[str] = None,    run_on_new_data_only: bool = False,    batched_execution: Optional[bool] = None,    test_run: bool = False,    force_rerun_failed_files: bool = True,    enable_anonymized_tracker_upload: bool = False,    requires_ehr_connection: bool = False,    supports_mps: Optional[bool] = None,    task_run_metadata: Optional[_JSONDict] = None,    template: Optional[dict[str, TemplateVariablesEntryString | TemplateVariablesEntryNumber | TemplateVariablesEntryNestedArray | TemplateVariablesEntryArray | TemplateVariablesEntryObject | TemplateVariablesEntryObjectArray | TemplateVariablesEntryFilePath | TemplateVariablesEntryModelSlug | TemplateVariablesEntrySchemaColumnName | TemplateVariablesEntrySchemaColumnNameArray | TemplateVariablesEntryBool | TemplateVariablesEntryTaskFilters]] = None,):

Schema for task templates.

Ancestors​

TrialInclusionCriteriaMatchAlgorithmAmethystArgumentsConfig​

class TrialInclusionCriteriaMatchAlgorithmAmethystArgumentsConfig(    cnv_threshold: float = 0.5,    largest_ga_lesion_lower_bound: float = 1.26,    largest_ga_lesion_upper_bound: Optional[float] = None,    total_ga_area_lower_bound: float = 2.5,    total_ga_area_upper_bound: float = 17.5,    patient_age_lower_bound: Optional[int] = None,    patient_age_upper_bound: Optional[int] = None,):

Configuration for TrialInclusionCriteriaMatchAlgorithmAmethyst arguments.

TrialInclusionCriteriaMatchAlgorithmAmethystConfig​

class TrialInclusionCriteriaMatchAlgorithmAmethystConfig(    name: str,    arguments: Optional[TrialInclusionCriteriaMatchAlgorithmAmethystArgumentsConfig] = TrialInclusionCriteriaMatchAlgorithmAmethystArgumentsConfig(cnv_threshold=0.5, largest_ga_lesion_lower_bound=1.26, largest_ga_lesion_upper_bound=None, total_ga_area_lower_bound=2.5, total_ga_area_upper_bound=17.5, patient_age_lower_bound=None, patient_age_upper_bound=None),):

Configuration for TrialInclusionCriteriaMatchAlgorithmAmethyst.

Ancestors​

Variables​

  • static name : str

TrialInclusionCriteriaMatchAlgorithmBronzeArgumentsConfig​

class TrialInclusionCriteriaMatchAlgorithmBronzeArgumentsConfig(    conditions_inclusion_study_eye_codes: Optional[list[str]] = None,    conditions_exclusion_study_eye_codes: Optional[list[str]] = None,    conditions_exclusion_codes: Optional[list[str]] = None,    procedures_exclusion_study_eye_codes: Optional[list[str]] = None,    procedures_exclusion_codes: Optional[list[str]] = None,    eligible_on_inclusion_codes_lat_unknown: bool = True,    eligible_on_exclusion_codes_lat_unknown: bool = True,    code_exclusion_time_windows: Optional[dict[str, dict[str, int]]] = None,    procedures_exclusion_class_count: Optional[dict[str, Any]] = None,    cnv_threshold: float = 0.5,    largest_ga_lesion_lower_bound: float = 1.26,    largest_ga_lesion_upper_bound: Optional[float] = None,    total_ga_area_lower_bound: float = 2.5,    total_ga_area_upper_bound: float = 17.5,    patient_age_lower_bound: Optional[int] = None,    patient_age_upper_bound: Optional[int] = None,    conditions_inclusion_codes: Optional[list[str]] = None,    distance_from_fovea_lower_bound: float = 0.0,    distance_from_fovea_upper_bound: float = inf,    exclude_foveal_ga: bool = False,):

Configuration for TrialInclusionCriteriaMatchAlgorithmBronze arguments.

Variables​

  • static conditions_inclusion_codes : Optional[list[str]]
  • static distance_from_fovea_lower_bound : float
  • static distance_from_fovea_upper_bound : float
  • static exclude_foveal_ga : bool

TrialInclusionCriteriaMatchAlgorithmBronzeConfig​

class TrialInclusionCriteriaMatchAlgorithmBronzeConfig(    name: str,    arguments: Optional[TrialInclusionCriteriaMatchAlgorithmBronzeArgumentsConfig] = TrialInclusionCriteriaMatchAlgorithmBronzeArgumentsConfig(conditions_inclusion_study_eye_codes=None, conditions_exclusion_study_eye_codes=None, conditions_exclusion_codes=None, procedures_exclusion_study_eye_codes=None, procedures_exclusion_codes=None, eligible_on_inclusion_codes_lat_unknown=True, eligible_on_exclusion_codes_lat_unknown=True, code_exclusion_time_windows=None, procedures_exclusion_class_count=None, cnv_threshold=0.5, largest_ga_lesion_lower_bound=1.26, largest_ga_lesion_upper_bound=None, total_ga_area_lower_bound=2.5, total_ga_area_upper_bound=17.5, patient_age_lower_bound=None, patient_age_upper_bound=None, conditions_inclusion_codes=None, distance_from_fovea_lower_bound=0.0, distance_from_fovea_upper_bound=inf, exclude_foveal_ga=False),):

Configuration for TrialInclusionCriteriaMatchAlgorithmBronze.

Ancestors​

Variables​

  • static name : str

TrialInclusionCriteriaMatchAlgorithmCharcoalArgumentsConfig​

class TrialInclusionCriteriaMatchAlgorithmCharcoalArgumentsConfig(    conditions_inclusion_study_eye_codes: Optional[list[str]] = None,    conditions_exclusion_study_eye_codes: Optional[list[str]] = None,    conditions_exclusion_codes: Optional[list[str]] = None,    procedures_exclusion_study_eye_codes: Optional[list[str]] = None,    procedures_exclusion_codes: Optional[list[str]] = None,    eligible_on_inclusion_codes_lat_unknown: bool = True,    eligible_on_exclusion_codes_lat_unknown: bool = True,    code_exclusion_time_windows: Optional[dict[str, dict[str, int]]] = None,    procedures_exclusion_class_count: Optional[dict[str, Any]] = None,    cnv_threshold: float = 0.5,    largest_ga_lesion_lower_bound: float = 1.26,    largest_ga_lesion_upper_bound: Optional[float] = None,    total_ga_area_lower_bound: float = 2.5,    total_ga_area_upper_bound: float = 17.5,    patient_age_lower_bound: Optional[int] = None,    patient_age_upper_bound: Optional[int] = None,    conditions_inclusion_codes: Optional[list[str]] = None,    hypertransmission_threshold: Optional[float] = None,    neurosensory_retina_atrophy_threshold: Optional[float] = None,    drusen_threshold: Optional[float] = None,    diffuse_edema_threshold: Optional[float] = None,    diffuse_edema_typical_width_micrometers: Optional[float] = None,    epiretinal_fibrosis_threshold: Optional[float] = None,    epiretinal_fibrosis_typical_width_micrometers: Optional[float] = None,    hard_exudates_threshold: Optional[float] = None,    intraretinal_cystoid_fluid_threshold: Optional[float] = None,    intraretinal_cystoid_fluid_typical_width_micrometers: Optional[float] = None,    serous_rpe_detachment_threshold: Optional[float] = None,    subretinal_fluid_threshold: Optional[float] = None,    subretinal_fluid_typical_width_micrometers: Optional[float] = None,    subretinal_hyperreflective_material__shrm__threshold: Optional[float] = None,    subretinal_hyperreflective_material_typical_width_micrometers: Optional[float] = None,    diabetic_macular_edema_threshold: Optional[float] = None,    diabetic_macular_edema_typical_width_micrometers: Optional[float] = None,    wet_amd_threshold: Optional[float] = None,    require_imaging_inclusion: bool = True,):

Configuration for TrialInclusionCriteriaMatchAlgorithmCharcoal arguments.

Variables​

  • static conditions_inclusion_codes : Optional[list[str]]
  • static diabetic_macular_edema_threshold : Optional[float]
  • static diabetic_macular_edema_typical_width_micrometers : Optional[float]
  • static diffuse_edema_threshold : Optional[float]
  • static diffuse_edema_typical_width_micrometers : Optional[float]
  • static drusen_threshold : Optional[float]
  • static epiretinal_fibrosis_threshold : Optional[float]
  • static epiretinal_fibrosis_typical_width_micrometers : Optional[float]
  • static hard_exudates_threshold : Optional[float]
  • static hypertransmission_threshold : Optional[float]
  • static intraretinal_cystoid_fluid_threshold : Optional[float]
  • static intraretinal_cystoid_fluid_typical_width_micrometers : Optional[float]
  • static neurosensory_retina_atrophy_threshold : Optional[float]
  • static require_imaging_inclusion : bool
  • static serous_rpe_detachment_threshold : Optional[float]
  • static subretinal_fluid_threshold : Optional[float]
  • static subretinal_fluid_typical_width_micrometers : Optional[float]
  • static subretinal_hyperreflective_material__shrm__threshold : Optional[float]
  • static subretinal_hyperreflective_material_typical_width_micrometers : Optional[float]
  • static wet_amd_threshold : Optional[float]

TrialInclusionCriteriaMatchAlgorithmCharcoalConfig​

class TrialInclusionCriteriaMatchAlgorithmCharcoalConfig(    name: str,    arguments: Optional[TrialInclusionCriteriaMatchAlgorithmCharcoalArgumentsConfig] = TrialInclusionCriteriaMatchAlgorithmCharcoalArgumentsConfig(conditions_inclusion_study_eye_codes=None, conditions_exclusion_study_eye_codes=None, conditions_exclusion_codes=None, procedures_exclusion_study_eye_codes=None, procedures_exclusion_codes=None, eligible_on_inclusion_codes_lat_unknown=True, eligible_on_exclusion_codes_lat_unknown=True, code_exclusion_time_windows=None, procedures_exclusion_class_count=None, cnv_threshold=0.5, largest_ga_lesion_lower_bound=1.26, largest_ga_lesion_upper_bound=None, total_ga_area_lower_bound=2.5, total_ga_area_upper_bound=17.5, patient_age_lower_bound=None, patient_age_upper_bound=None, conditions_inclusion_codes=None, hypertransmission_threshold=None, neurosensory_retina_atrophy_threshold=None, drusen_threshold=None, diffuse_edema_threshold=None, diffuse_edema_typical_width_micrometers=None, epiretinal_fibrosis_threshold=None, epiretinal_fibrosis_typical_width_micrometers=None, hard_exudates_threshold=None, intraretinal_cystoid_fluid_threshold=None, intraretinal_cystoid_fluid_typical_width_micrometers=None, serous_rpe_detachment_threshold=None, subretinal_fluid_threshold=None, subretinal_fluid_typical_width_micrometers=None, subretinal_hyperreflective_material__shrm__threshold=None, subretinal_hyperreflective_material_typical_width_micrometers=None, diabetic_macular_edema_threshold=None, diabetic_macular_edema_typical_width_micrometers=None, wet_amd_threshold=None, require_imaging_inclusion=True),):

Configuration for TrialInclusionCriteriaMatchAlgorithmCharcoal.

Ancestors​

Variables​

  • static name : str

TrialInclusionCriteriaMatchAlgorithmEHRArgumentsConfig​

class TrialInclusionCriteriaMatchAlgorithmEHRArgumentsConfig(    conditions_inclusion_study_eye_codes: Optional[list[str]] = None,    conditions_exclusion_study_eye_codes: Optional[list[str]] = None,    conditions_exclusion_codes: Optional[list[str]] = None,    procedures_exclusion_study_eye_codes: Optional[list[str]] = None,    procedures_exclusion_codes: Optional[list[str]] = None,    eligible_on_inclusion_codes_lat_unknown: bool = True,    eligible_on_exclusion_codes_lat_unknown: bool = True,    code_exclusion_time_windows: Optional[dict[str, dict[str, int]]] = None,    procedures_exclusion_class_count: Optional[dict[str, Any]] = None,    patient_age_lower_bound: Optional[int] = None,    patient_age_upper_bound: Optional[int] = None,    conditions_inclusion_codes: Optional[Union[list[str], list[list[str]]]] = None,    conditions_flag_codes: Optional[list[str]] = None,    medications_exclusion_class_count: Optional[dict[str, Any]] = None,):

Configuration for TrialInclusionCriteriaMatchAlgorithmEHR arguments.

Variables​

  • static conditions_flag_codes : Optional[list[str]]
  • static conditions_inclusion_codes : Union[list[str], list[list[str]], ForwardRef(None)]
  • static medications_exclusion_class_count : Optional[dict[str, typing.Any]]
  • static patient_age_lower_bound : int | None
  • static patient_age_upper_bound : int | None

TrialInclusionCriteriaMatchAlgorithmEHRConfig​

class TrialInclusionCriteriaMatchAlgorithmEHRConfig(    name: str,    arguments: Optional[TrialInclusionCriteriaMatchAlgorithmEHRArgumentsConfig] = TrialInclusionCriteriaMatchAlgorithmEHRArgumentsConfig(conditions_inclusion_study_eye_codes=None, conditions_exclusion_study_eye_codes=None, conditions_exclusion_codes=None, procedures_exclusion_study_eye_codes=None, procedures_exclusion_codes=None, eligible_on_inclusion_codes_lat_unknown=True, eligible_on_exclusion_codes_lat_unknown=True, code_exclusion_time_windows=None, procedures_exclusion_class_count=None, patient_age_lower_bound=None, patient_age_upper_bound=None, conditions_inclusion_codes=None, conditions_flag_codes=None, medications_exclusion_class_count=None),):

Configuration for TrialInclusionCriteriaMatchAlgorithmEHR.

Ancestors​

Variables​

  • static name : str

TrialInclusionCriteriaMatchAlgorithmGlaucomaCharcoalArgumentsConfig​

class TrialInclusionCriteriaMatchAlgorithmGlaucomaCharcoalArgumentsConfig(    conditions_inclusion_study_eye_codes: Optional[list[str]] = None,    conditions_exclusion_study_eye_codes: Optional[list[str]] = None,    conditions_exclusion_codes: Optional[list[str]] = None,    procedures_exclusion_study_eye_codes: Optional[list[str]] = None,    procedures_exclusion_codes: Optional[list[str]] = None,    eligible_on_inclusion_codes_lat_unknown: bool = True,    eligible_on_exclusion_codes_lat_unknown: bool = True,    code_exclusion_time_windows: Optional[dict[str, dict[str, int]]] = None,    procedures_exclusion_class_count: Optional[dict[str, Any]] = None,    patient_age_lower_bound: Optional[int] = None,    conditions_inclusion_codes: Optional[Union[list[str], list[list[str]]]] = None,):

Configuration for TrialInclusionCriteriaMatchAlgorithmGlaucomaCharcoal arguments.

Variables​

  • static conditions_inclusion_codes : Union[list[str], list[list[str]], ForwardRef(None)]
  • static patient_age_lower_bound : int | None

TrialInclusionCriteriaMatchAlgorithmGlaucomaCharcoalConfig​

class TrialInclusionCriteriaMatchAlgorithmGlaucomaCharcoalConfig(    name: str,    arguments: Optional[TrialInclusionCriteriaMatchAlgorithmGlaucomaCharcoalArgumentsConfig] = TrialInclusionCriteriaMatchAlgorithmGlaucomaCharcoalArgumentsConfig(conditions_inclusion_study_eye_codes=None, conditions_exclusion_study_eye_codes=None, conditions_exclusion_codes=None, procedures_exclusion_study_eye_codes=None, procedures_exclusion_codes=None, eligible_on_inclusion_codes_lat_unknown=True, eligible_on_exclusion_codes_lat_unknown=True, code_exclusion_time_windows=None, procedures_exclusion_class_count=None, patient_age_lower_bound=None, conditions_inclusion_codes=None),):

Configuration for TrialInclusionCriteriaMatchAlgorithmGlaucomaCharcoal.

Ancestors​

Variables​

  • static name : str

TrialInclusionCriteriaMatchAlgorithmJadeArgumentsConfig​

class TrialInclusionCriteriaMatchAlgorithmJadeArgumentsConfig():

Configuration for TrialInclusionCriteriaMatchAlgorithmJade arguments.

TrialInclusionCriteriaMatchAlgorithmJadeConfig​

class TrialInclusionCriteriaMatchAlgorithmJadeConfig(    name: str,    arguments: Optional[TrialInclusionCriteriaMatchAlgorithmJadeArgumentsConfig] = TrialInclusionCriteriaMatchAlgorithmJadeArgumentsConfig(),):

Configuration for TrialInclusionCriteriaMatchAlgorithmJade.

Ancestors​

Variables​

  • static name : str

TrialInclusionCriteriaMatchAlgorithmSapphireArgumentsConfig​

class TrialInclusionCriteriaMatchAlgorithmSapphireArgumentsConfig(    cnv_threshold: float = 0.5,    largest_ga_lesion_lower_bound: float = 1.26,    largest_ga_lesion_upper_bound: Optional[float] = None,    total_ga_area_lower_bound: float = 2.5,    total_ga_area_upper_bound: float = 17.5,    patient_age_lower_bound: Optional[int] = None,    patient_age_upper_bound: Optional[int] = None,):

Configuration for TrialInclusionCriteriaMatchAlgorithmSapphire arguments.

TrialInclusionCriteriaMatchAlgorithmSapphireConfig​

class TrialInclusionCriteriaMatchAlgorithmSapphireConfig(    name: str,    arguments: Optional[TrialInclusionCriteriaMatchAlgorithmSapphireArgumentsConfig] = TrialInclusionCriteriaMatchAlgorithmSapphireArgumentsConfig(cnv_threshold=0.5, largest_ga_lesion_lower_bound=1.26, largest_ga_lesion_upper_bound=None, total_ga_area_lower_bound=2.5, total_ga_area_upper_bound=17.5, patient_age_lower_bound=None, patient_age_upper_bound=None),):

Configuration for TrialInclusionCriteriaMatchAlgorithmSapphire.

Ancestors​

Variables​

  • static name : str

TrialMatchingAlgorithmArgumentsConfig​

class TrialMatchingAlgorithmArgumentsConfig(    top_n: int = 5, max_distance_km: Optional[float] = None, default_country: str = 'us',):

Configuration for TrialMatchingAlgorithm arguments.

Variables​

  • static default_country : str
  • static max_distance_km : Optional[float]
  • static top_n : int

TrialMatchingAlgorithmConfig​

class TrialMatchingAlgorithmConfig(    name: str,    arguments: TrialMatchingAlgorithmArgumentsConfig = TrialMatchingAlgorithmArgumentsConfig(top_n=5, max_distance_km=None, default_country='us'),):

Configuration for TrialMatchingAlgorithm.

Ancestors​

Variables​

  • static name : str

WetAMDScreeningProtocolSapphireArgumentsConfig​

class WetAMDScreeningProtocolSapphireArgumentsConfig(    aggregator: Optional[AggregatorConfig] = None,    results_notification_email: Optional[bool] = False,    trial_name: Optional[str] = None,    rename_columns: Optional[dict[str, str]] = None,    batch_grouping: Optional[TemplatedGroupingConfig] = None,):

Configuration for WetAMDScreeningProtocolSapphire arguments.

Variables​

  • static rename_columns : Optional[dict[str, str]]
  • static results_notification_email : Optional[bool]
  • static trial_name : str | None

WetAMDScreeningProtocolSapphireConfig​

class WetAMDScreeningProtocolSapphireConfig(    name: str,    arguments: Optional[WetAMDScreeningProtocolSapphireArgumentsConfig] = WetAMDScreeningProtocolSapphireArgumentsConfig(aggregator=None, results_notification_email=False, trial_name=None, rename_columns=None, batch_grouping=None),):

Configuration for WetAMDScreeningProtocolSapphire.

Ancestors​

Variables​

  • static name : str

_SimpleCSVAlgorithmAlgorithmConfig​

class _SimpleCSVAlgorithmAlgorithmConfig(    name: str,    arguments: Optional[_SimpleCSVAlgorithmArgumentsConfig] = _SimpleCSVAlgorithmArgumentsConfig(save_path=None),):

Configuration for _SimpleCSVAlgorithm.

Ancestors​

Variables​

  • static arguments : Optional[bitfount.runners.config_schemas.algorithm_schemas._SimpleCSVAlgorithmArgumentsConfig]
  • static name : str

_SimpleCSVAlgorithmArgumentsConfig​

class _SimpleCSVAlgorithmArgumentsConfig(save_path: Optional[Path] = None):

Configuration for _SimpleCSVAlgorithm arguments.

Variables​