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v1

biomarker_tabulation step v1.

Module​

Submodules​

Functions​

task_fn​

def task_fn(    datasource: BaseSource,    config: BiomarkerTabulationConfig,    ga_metrics: CacheAccessor,    fluid_metrics: CacheAccessor,    cst_metrics: CacheAccessor,    gcc_metrics: CacheAccessor,    filenames: list[str],) ‑> BiomarkerTabulationResult:

Merge, derive and filter the four metric caches into a csv_report_df.

Arguments

  • datasource: The datasource (unused directly; the cache rows are already keyed by the datasource filenames).
  • config: Selection config (biomarker_groups / biomarker_names).
  • ga_metrics: Cache accessor for the background ga_calculation step.
  • fluid_metrics: Cache accessor for the background fluid_calculation step.
  • cst_metrics: Cache accessor for the background cst_calculation step.
  • gcc_metrics: Cache accessor for the background gcc_calculation step.
  • filenames: The selected filenames; every one is guaranteed a row (as an all-NA row when a calculation skipped/failed the file), mirroring the v8 protocol's _fill_missing_metrics backfill.

Returns BiomarkerTabulationResult carrying the tabulated csv_report_df with TECHNICAL column names plus the filename column.

Classes​

Config​

class Config(**data: Any):

Config selecting which biomarker columns land in the CSV report.

The filter operates on the TECHNICAL (internal) column names; display renaming happens downstream in the csv_report step. There is deliberately no rename_columns field here.

Arguments

  • biomarker_groups: Biomarker group names to include (empty ⇒ all groups).
  • biomarker_names: Individual technical column names to include (empty ⇒ none beyond the selected groups).

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Variables​

  • static biomarker_groups : list[str]
  • static biomarker_names : list[str]
  • static model_config

Result​

class Result(**data: Any):

Container for the tabulated biomarker csv_report_df.

The DataFrame keeps TECHNICAL column names plus the filename column, so the downstream csv_report step can merge it onto freshly-read source data and apply display renaming.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Variables​

  • static model_config