def prepare_reference(reference_params: dict, location: str, paired: bool):
ParameterValidator.assert_keys(list(reference_params.keys()), ["format", "params"], location,
"reference")
seq_import_params = reference_params["params"] if "params" in reference_params else {}
assert os.path.isfile(seq_import_params["path"]), f"{location}: the file {seq_import_params['path']} does not exist. " \
f"Specify the correct path under reference."
if "is_repertoire" in seq_import_params:
assert seq_import_params["is_repertoire"] == False, f"{location}: is_repertoire must be False for SequenceImport"
else:
seq_import_params["is_repertoire"] = False
if "paired" in seq_import_params:
assert seq_import_params["paired"] == paired, f"{location}: paired must be {paired} for SequenceImport"
else:
seq_import_params["paired"] = paired
format_str = reference_params["format"]
import_class = ReflectionHandler.get_class_by_name("{}Import".format(format_str))
default_params = DefaultParamsLoader.load(EnvironmentSettings.default_params_path / "datasets",
DefaultParamsLoader.convert_to_snake_case(format_str))
params = {**default_params, **seq_import_params}
processed_params = DatasetImportParams.build_object(**params)
receptors = ImportHelper.import_items(import_class, reference_params["params"]["path"], processed_params)
return receptors
def make_reports_docs(path: Path):
filename = "reports.rst"
file_path = path / filename
with file_path.open("w") as file:
pass
for report_type_class in [
DataReport, EncodingReport, MLReport, TrainMLModelReport,
MultiDatasetReport
]:
with file_path.open("a") as file:
doc_format = DocumentationFormat(
cls=report_type_class,
cls_name=f"**{report_type_class.get_title()}**",
level_heading=DocumentationFormat.LEVELS[1])
write_class_docs(doc_format, file)
subdir = DefaultParamsLoader.convert_to_snake_case(
report_type_class.__name__) + "s"
classes = ReflectionHandler.all_nonabstract_subclasses(
report_type_class, "", f"reports/{subdir}/")
make_docs(path, classes, filename, "", "a")