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.
AlgorithmConfig
class AlgorithmConfig(name: str, arguments: Optional[Any] = None):
Configuration for the Algorithm.
Subclasses
- CSVReportAlgorithmConfig
- CSVReportGeneratorOphthalmologyAlgorithmConfig
- ETDRSAlgorithmConfig
- FoveaCoordinatesAlgorithmConfig
- GATrialCalculationAlgorithmBronzeConfig
- GATrialCalculationAlgorithmJadeConfig
- GATrialPDFGeneratorAlgorithmAmethystConfig
- GATrialPDFGeneratorAlgorithmJadeConfig
- GenericAlgorithmConfig
- HuggingFaceImageClassificationInferenceAlgorithmConfig
- HuggingFaceImageSegmentationInferenceAlgorithmConfig
- HuggingFacePerplexityEvaluationAlgorithmConfig
- HuggingFaceTextClassificationInferenceAlgorithmConfig
- HuggingFaceTextGenerationInferenceAlgorithmConfig
- ModelAlgorithmConfig
- NextGenPatientQueryAlgorithmConfig
- PrivateSqlQueryAlgorithmConfig
- SqlQueryAlgorithmConfig
- TIMMFineTuningAlgorithmConfig
- TIMMInferenceAlgorithmConfig
- TrialInclusionCriteriaMatchAlgorithmAmethystConfig
- TrialInclusionCriteriaMatchAlgorithmBronzeConfig
- TrialInclusionCriteriaMatchAlgorithmJadeConfig
- bitfount.runners.config_schemas.algorithm_schemas._SimpleCSVAlgorithmAlgorithmConfig
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
filter : Optional[list[ColumnFilter]]
- static
original_cols : Optional[list[str]]
- static
save_path : Optional[pathlib.Path]
CSVReportAlgorithmConfig
class CSVReportAlgorithmConfig( name: str, arguments: Optional[CSVReportAlgorithmArgumentsConfig] = CSVReportAlgorithmArgumentsConfig(save_path=None, original_cols=None, filter=None),):
Configuration for CSVReportAlgorithm.
Ancestors
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
filter : Optional[list[ColumnFilter]]
- static
match_patient_visit : Optional[MatchPatientVisit]
- static
matched_csv_path : Optional[pathlib.Path]
- 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
save_path : Optional[pathlib.Path]
- 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.
Ancestors
Variables
- static
arguments : Optional[CSVReportGeneratorOphthalmologyAlgorithmArgumentsConfig]
- 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[OCTImageMetadataColumns]
- static
slo_image_metadata_columns : Optional[SLOImageMetadataColumns]
- static
slo_mm_height : float
- static
slo_mm_width : float
- static
slo_photo_location_prefixes : Optional[SLOSegmentationLocationPrefix]
- static
threshold : float
ETDRSAlgorithmConfig
class ETDRSAlgorithmConfig(name: str, arguments: Optional[ETDRSAlgorithmArgumentsConfig]):
Configuration for ETDRSAlgorithm.
Ancestors
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
FederatedModelTrainingArgumentsConfig
class FederatedModelTrainingArgumentsConfig( modeller_checkpointing: bool = True, checkpoint_filename: Optional[str] = None,):
Configuration for the FederatedModelTraining algorithm arguments.
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[SLOSegmentationLocationPrefix]
FoveaCoordinatesAlgorithmConfig
class FoveaCoordinatesAlgorithmConfig( name: str, arguments: Optional[FoveaCoordinatesAlgorithmArgumentsConfig] = FoveaCoordinatesAlgorithmArgumentsConfig(bscan_width_col='size_width', location_prefixes=None),):
Configuration for FoveaCoordinatesAlgorithm.
Ancestors
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.
Ancestors
Variables
- static
arguments : Optional[GATrialCalculationAlgorithmBronzeArgumentsConfig]
- 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.
Ancestors
Variables
- static
arguments : Optional[GATrialCalculationAlgorithmJadeArgumentsConfig]
- 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
filter : Optional[list[ColumnFilter]]
- static
pdf_filename_columns : Optional[list[str]]
- static
report_metadata : Optional[ReportMetadata]
- static
save_path : Optional[pathlib.Path]
- 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.
Ancestors
Variables
- static
arguments : Optional[GATrialPDFGeneratorAlgorithmAmethystArgumentsConfig]
- 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
filter : Optional[list[ColumnFilter]]
- static
pdf_filename_columns : Optional[list[str]]
- static
report_metadata : Optional[ReportMetadata]
- static
save_path : Optional[pathlib.Path]
- 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.
Ancestors
Variables
- static
arguments : Optional[GATrialPDFGeneratorAlgorithmJadeArgumentsConfig]
- static
name : str
GenericAlgorithmConfig
class GenericAlgorithmConfig(name: str, arguments: _JSONDict = {}):
Configuration for unspecified algorithm plugins.
Raises
ValueError
: if the algorithm name starts withbitfount.
Ancestors
HuggingFaceImageClassificationInferenceAlgorithmConfig
class HuggingFaceImageClassificationInferenceAlgorithmConfig( name: str, arguments: Optional[HuggingFaceImageClassificationInferenceArgumentsConfig],):
Configuration for HuggingFaceImageClassificationInference.
Ancestors
Variables
- static
arguments : Optional[HuggingFaceImageClassificationInferenceArgumentsConfig]
- 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.
Ancestors
Variables
- static
arguments : Optional[HuggingFaceImageSegmentationInferenceArgumentsConfig]
- 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.
Ancestors
Variables
- static
arguments : Optional[HuggingFacePerplexityEvaluationArgumentsConfig]
- static
name : str
HuggingFacePerplexityEvaluationArgumentsConfig
class HuggingFacePerplexityEvaluationArgumentsConfig( model_id: str, stride: int = 512, seed: int = 42,):
Configuration for the HuggingFacePerplexityEvaluation algorithm arguments.
HuggingFaceTextClassificationInferenceAlgorithmConfig
class HuggingFaceTextClassificationInferenceAlgorithmConfig( name: str, arguments: Optional[HuggingFaceTextClassificationInferenceArgumentsConfig],):
Configuration for HuggingFaceTextClassificationInference.
Ancestors
Variables
- static
arguments : Optional[HuggingFaceTextClassificationInferenceArgumentsConfig]
- 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.
Ancestors
Variables
- static
arguments : Optional[HuggingFaceTextGenerationInferenceArgumentsConfig]
- 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.
Ancestors
Subclasses
ModelEvaluationAlgorithmConfig
class ModelEvaluationAlgorithmConfig( name: str, arguments: Optional[ModelEvaluationArgumentsConfig], model: Optional[ModelConfig] = None, pretrained_file: Optional[Path] = None,):
Configuration for the ModelEvaluation algorithm.
Ancestors
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.
Ancestors
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.
Ancestors
ModelTrainingAndEvaluationArgumentsConfig
class ModelTrainingAndEvaluationArgumentsConfig():
Configuration for the ModelTrainingAndEvaluation algorithm arguments.
NextGenPatientQueryAlgorithmConfig
class NextGenPatientQueryAlgorithmConfig( name: str, arguments: Optional[NextGenPatientQueryArgumentsConfig],):
Configuration for NextGenPatientQuery algorithm.
Ancestors
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.
Ancestors
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
column_ranges : Union[dict[str, PrivateSqlQueryColumnArgumentsConfig], dict[str, dict[str, PrivateSqlQueryColumnArgumentsConfig]]]
- 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.
SqlQueryAlgorithmConfig
class SqlQueryAlgorithmConfig(name: str, arguments: SqlQueryArgumentsConfig):
Configuration for the SqlQuery algorithm.
Ancestors
SqlQueryArgumentsConfig
class SqlQueryArgumentsConfig(query: str, table: Optional[str] = None):
Configuration for the SqlQuery algorithm arguments.
TIMMFineTuningAlgorithmConfig
class TIMMFineTuningAlgorithmConfig( name: str, arguments: Optional[TIMMFineTuningArgumentsConfig],):
Configuration for TIMMFineTuning algorithm.
Ancestors
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
args : Optional[TIMMTrainingConfig]
- static
batch_transformations : Optional[dict[str, list[typing.Union[str, dict[str, typing.Any]]]]]
- static
labels : Optional[list[str]]
- static
model_id : str
- static
return_weights : bool
- static
save_path : Optional[pathlib.Path]
TIMMInferenceAlgorithmConfig
class TIMMInferenceAlgorithmConfig( name: str, arguments: Optional[TIMMInferenceArgumentsConfig],):
Configuration for TIMMInference algorithm.
Ancestors
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
batch_transformations : Optional[list[typing.Union[str, dict[str, typing.Any]]]]
- static
checkpoint_path : Optional[pathlib.Path]
- 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.
Ancestors
Variables
- static
arguments : Optional[TrialInclusionCriteriaMatchAlgorithmAmethystArgumentsConfig]
- 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.
Ancestors
Variables
- static
arguments : Optional[TrialInclusionCriteriaMatchAlgorithmBronzeArgumentsConfig]
- 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
arguments : Optional[TrialInclusionCriteriaMatchAlgorithmJadeArgumentsConfig]
- static
name : str