Spaces:
Sleeping
Sleeping
File size: 1,414 Bytes
33d7314 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 | from __future__ import annotations
from pathlib import Path
import pandas as pd
from .common import PubTimePreparedData, resolve_source, source_label
from . import cancer_analysis, covid_analysis, cvd_analysis
PREPARERS = {
"cancer": cancer_analysis.prepare,
"covid": covid_analysis.prepare,
"cvd": cvd_analysis.prepare,
}
def prepare_from_archive(domain: str, project_root: Path) -> tuple[PubTimePreparedData, str, str]:
source_path = resolve_source(project_root)
return prepare_from_source(domain, source_path, source_label(source_path, project_root))
def prepare_from_source(domain: str, source_path: Path, label: str | None = None) -> tuple[PubTimePreparedData, str, str]:
preparer = PREPARERS.get(domain)
if preparer is None:
empty = PubTimePreparedData(
domain=domain,
raw_rows=0,
analytic_rows=0,
survival_rows=0,
predictors=tuple(),
high_missing_predictors=tuple(),
missing_percentages={},
survival_df=pd.DataFrame(),
scaled_survival_df=pd.DataFrame(),
cox_model_status={"status": "unavailable", "reason": "Unknown domain."},
)
return empty, label or str(source_path), "directory" if source_path.is_dir() else "zip"
return preparer(source_path), label or str(source_path), "directory" if source_path.is_dir() else "zip"
|