Skip to main content

algorithm_schemas

Config YAML specification classes related to algorithms.

Classes

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.

Variables

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

CSVReportAlgorithmArgumentsConfig

class CSVReportAlgorithmArgumentsConfig(    save_path: Optional[Path] = None,    original_cols: Optional[list[str]] = None,    filter: Optional[list[ColumnFilter]] = None,):

Configuration for CSVReportAlgorithm arguments.

Variables

  • static original_cols : Optional[list[str]]

CSVReportAlgorithmConfig

class CSVReportAlgorithmConfig(    name: str,    arguments: Optional[CSVReportAlgorithmArgumentsConfig] = CSVReportAlgorithmArgumentsConfig(save_path=None, original_cols=None, filter=None),):

Configuration for CSVReportAlgorithm.

Variables

  • static name : str

CSVReportGeneratorOphthalmologyAlgorithmArgumentsConfig

class CSVReportGeneratorOphthalmologyAlgorithmArgumentsConfig(    save_path: Optional[Path] = None,    trial_name: Optional[str] = None,    original_cols: Optional[list[str]] = None,    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 csv_extensions : Optional[list[str]]
  • 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 : Optional[str]

CSVReportGeneratorOphthalmologyAlgorithmConfig

class CSVReportGeneratorOphthalmologyAlgorithmConfig(    name: str,    arguments: Optional[CSVReportGeneratorOphthalmologyAlgorithmArgumentsConfig] = CSVReportGeneratorOphthalmologyAlgorithmArgumentsConfig(save_path=None, trial_name=None, original_cols=None, 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.

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 slo_mm_height : float
  • static slo_mm_width : float
  • static threshold : float

ETDRSAlgorithmConfig

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

Configuration for ETDRSAlgorithm.

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.

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 : Optional[str]
  • static modeller_checkpointing : 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

FoveaCoordinatesAlgorithmConfig

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

Configuration for FoveaCoordinatesAlgorithm.

Variables

  • static name : str

GATrialCalculationAlgorithmBronzeArgumentsConfig

class GATrialCalculationAlgorithmBronzeArgumentsConfig(    ga_area_include_segmentations: Optional[list[str]] = None,    ga_area_exclude_segmentations: Optional[list[str]] = None,    fovea_landmark_idx: Optional[int] = 1,):

Configuration for GATrialCalculationAlgorithmBronze arguments.

Variables

  • static fovea_landmark_idx : Optional[int]
  • static ga_area_exclude_segmentations : Optional[list[str]]
  • static ga_area_include_segmentations : Optional[list[str]]

GATrialCalculationAlgorithmBronzeConfig

class GATrialCalculationAlgorithmBronzeConfig(    name: str,    arguments: Optional[GATrialCalculationAlgorithmBronzeArgumentsConfig] = GATrialCalculationAlgorithmBronzeArgumentsConfig(ga_area_include_segmentations=None, ga_area_exclude_segmentations=None, fovea_landmark_idx=1),):

Configuration for GATrialCalculationAlgorithmBronze.

Variables

  • static name : str

GATrialCalculationAlgorithmJadeArgumentsConfig

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

Configuration for GATrialCalculationAlgorithmJade arguments.

Variables

  • static ga_area_exclude_segmentations : Optional[list[str]]
  • static ga_area_include_segmentations : Optional[list[str]]

GATrialCalculationAlgorithmJadeConfig

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

Configuration for GATrialCalculationAlgorithmJade.

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 : Optional[str]
  • static pdf_filename_columns : Optional[list[str]]
  • static trial_name : Optional[str]

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.

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 : Optional[str]
  • static pdf_filename_columns : Optional[list[str]]
  • static trial_name : Optional[str]

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.

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.

Variables

  • static name : str

HuggingFaceImageClassificationInferenceAlgorithmConfig

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

Configuration for HuggingFaceImageClassificationInference.

Variables

  • static name : str

HuggingFaceImageClassificationInferenceArgumentsConfig

class HuggingFaceImageClassificationInferenceArgumentsConfig(    model_id: str,    apply_softmax_to_predictions: bool = True,    batch_size: int = 1,    seed: int = 42,    top_k: int = 5,):

Configuration for HuggingFaceImageClassificationInference arguments.

Variables

  • static apply_softmax_to_predictions : bool
  • static batch_size : int
  • static model_id : str
  • static seed : int
  • static top_k : int

HuggingFaceImageSegmentationInferenceAlgorithmConfig

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

Configuration for HuggingFaceImageSegmentationInference.

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,):

Configuration for HuggingFaceImageSegmentationInference arguments.

Variables

  • 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 : Optional[str]
  • static seed : int
  • static subtask : Optional[str]
  • static threshold : float

HuggingFacePerplexityEvaluationAlgorithmConfig

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

Configuration for the HuggingFacePerplexityEvaluation algorithm.

Variables

  • static name : str

HuggingFacePerplexityEvaluationArgumentsConfig

class HuggingFacePerplexityEvaluationArgumentsConfig(    model_id: str, stride: int = 512, seed: int = 42,):

Configuration for the HuggingFacePerplexityEvaluation algorithm arguments.

Variables

  • static model_id : str
  • static seed : int
  • static stride : int

HuggingFaceTextClassificationInferenceAlgorithmConfig

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

Configuration for HuggingFaceTextClassificationInference.

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,):

Configuration for HuggingFaceTextClassificationInference arguments.

Variables

  • static batch_size : int
  • static function_to_apply : Optional[str]
  • static model_id : str
  • static seed : int
  • static top_k : int

HuggingFaceTextGenerationInferenceAlgorithmConfig

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

Configuration for the HuggingFaceTextGenerationInference algorithm.

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',):

Configuration for the HuggingFaceTextGenerationInference algorithm arguments.

Variables

  • static device : Optional[str]
  • static early_stopping : bool
  • static eos_token_id : Optional[int]
  • 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 : Optional[int]
  • static prompt_format : Optional[str]
  • static repetition_penalty : float
  • static seed : int
  • static torch_dtype : str

ModelAlgorithmConfig

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

Configuration for the Model algorithms.

Variables

ModelEvaluationAlgorithmConfig

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

Configuration for the ModelEvaluation algorithm.

Variables

  • static name : str

ModelEvaluationArgumentsConfig

class ModelEvaluationArgumentsConfig():

Configuration for the ModelEvaluation algorithm arguments.

ModelInferenceAlgorithmConfig

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

Configuration for the ModelInference algorithm.

Variables

  • static name : str

ModelInferenceArgumentsConfig

class ModelInferenceArgumentsConfig(class_outputs: Optional[list[str]] = None):

Configuration for the ModelInference algorithm arguments.

Variables

  • static class_outputs : Optional[list[str]]

ModelTrainingAndEvaluationAlgorithmConfig

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

Configuration for the ModelTrainingAndEvaluation algorithm.

Variables

  • static name : str

ModelTrainingAndEvaluationArgumentsConfig

class ModelTrainingAndEvaluationArgumentsConfig():

Configuration for the ModelTrainingAndEvaluation algorithm arguments.

NextGenPatientQueryAlgorithmConfig

class NextGenPatientQueryAlgorithmConfig(    name: str, arguments: Optional[NextGenPatientQueryArgumentsConfig],):

Configuration for NextGenPatientQuery algorithm.

Variables

  • static name : str

NextGenPatientQueryArgumentsConfig

class NextGenPatientQueryArgumentsConfig(    icd10_codes: list[str],    cpt4_codes: list[str],    fhir_url: str = 'https://fhir.nextgen.com/nge/prod/fhir-api-r4/fhir/R4',    enterprise_url: str = 'https://nativeapi.nextgen.com/nge/prod/nge-api/api',    smart_on_fhir_url: Optional[str] = None,    smart_on_fhir_resource_server_url: Optional[str] = None,):

Configuration for NextGenPatientQuery algorithm arguments.

Variables

  • static cpt4_codes : list[str]
  • static enterprise_url : str
  • static fhir_url : str
  • static icd10_codes : list[str]
  • static smart_on_fhir_resource_server_url : Optional[str]
  • static smart_on_fhir_url : Optional[str]

PrivateSqlQueryAlgorithmConfig

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

Configuration for the PrivateSqlQuery algorithm.

Variables

  • static name : str

PrivateSqlQueryArgumentsConfig

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

Configuration for the PrivateSqlQuery algorithm arguments.

Variables

  • static db_schema : Optional[str]
  • static delta : float
  • static epsilon : float
  • static query : str
  • static table : Optional[str]

PrivateSqlQueryColumnArgumentsConfig

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

Configuration for the PrivateSqlQuery algorithm column arguments.

Variables

  • static lower : Optional[int]
  • static upper : Optional[int]

SqlQueryAlgorithmConfig

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

Configuration for the SqlQuery algorithm.

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 : Optional[str]

TIMMFineTuningAlgorithmConfig

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

Configuration for TIMMFineTuning algorithm.

Variables

  • static name : str

TIMMFineTuningArgumentsConfig

class TIMMFineTuningArgumentsConfig(    model_id: str,    args: Optional[TIMMTrainingConfig] = 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.

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,):

Configuration for TIMMInference algorithm arguments.

Variables

  • static class_outputs : Optional[list[str]]
  • static model_id : str
  • static num_classes : Optional[int]

TrialInclusionCriteriaMatchAlgorithmAmethystArgumentsConfig

class TrialInclusionCriteriaMatchAlgorithmAmethystArgumentsConfig(    cnv_threshold: float = 0.5,    largest_ga_lesion_lower_bound: float = 1.26,    total_ga_area_lower_bound: float = 2.5,    total_ga_area_upper_bound: float = 17.5,):

Configuration for TrialInclusionCriteriaMatchAlgorithmAmethyst arguments.

Variables

  • static cnv_threshold : float
  • static largest_ga_lesion_lower_bound : float
  • static total_ga_area_lower_bound : float
  • static total_ga_area_upper_bound : float

TrialInclusionCriteriaMatchAlgorithmAmethystConfig

class TrialInclusionCriteriaMatchAlgorithmAmethystConfig(    name: str,    arguments: Optional[TrialInclusionCriteriaMatchAlgorithmAmethystArgumentsConfig] = TrialInclusionCriteriaMatchAlgorithmAmethystArgumentsConfig(cnv_threshold=0.5, largest_ga_lesion_lower_bound=1.26, total_ga_area_lower_bound=2.5, total_ga_area_upper_bound=17.5),):

Configuration for TrialInclusionCriteriaMatchAlgorithmAmethyst.

Variables

  • static name : str

TrialInclusionCriteriaMatchAlgorithmBronzeArgumentsConfig

class TrialInclusionCriteriaMatchAlgorithmBronzeArgumentsConfig(    cnv_threshold: float = 0.5,    largest_ga_lesion_lower_bound: float = 1.26,    total_ga_area_lower_bound: float = 2.5,    total_ga_area_upper_bound: float = 17.5,    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 cnv_threshold : float
  • static distance_from_fovea_lower_bound : float
  • static distance_from_fovea_upper_bound : float
  • static exclude_foveal_ga : bool
  • static largest_ga_lesion_lower_bound : float
  • static total_ga_area_lower_bound : float
  • static total_ga_area_upper_bound : float

TrialInclusionCriteriaMatchAlgorithmBronzeConfig

class TrialInclusionCriteriaMatchAlgorithmBronzeConfig(    name: str,    arguments: Optional[TrialInclusionCriteriaMatchAlgorithmBronzeArgumentsConfig] = TrialInclusionCriteriaMatchAlgorithmBronzeArgumentsConfig(cnv_threshold=0.5, largest_ga_lesion_lower_bound=1.26, total_ga_area_lower_bound=2.5, total_ga_area_upper_bound=17.5, distance_from_fovea_lower_bound=0.0, distance_from_fovea_upper_bound=inf, exclude_foveal_ga=False),):

Configuration for TrialInclusionCriteriaMatchAlgorithmBronze.

Variables

  • static name : str

TrialInclusionCriteriaMatchAlgorithmJadeArgumentsConfig

class TrialInclusionCriteriaMatchAlgorithmJadeArgumentsConfig():

Configuration for TrialInclusionCriteriaMatchAlgorithmJade arguments.

TrialInclusionCriteriaMatchAlgorithmJadeConfig

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

Configuration for TrialInclusionCriteriaMatchAlgorithmJade.

Variables

  • static name : str