When Datapoint is generated, stored information is always DDA params, even in DIA module

[rodvrees]

While DIA-specific params are being parsed from parameter files, generate_datapoint always outputs datapoints with the same set of attributes, which were based on the DDA-parsed params, effectively ignoring a chunk of the other parameters.

ProteoBench/proteobench/datapoint/quant_datapoint.py

Lines 76 to 106 in 213ac84

	def generate_datapoint(
	intermediate: pd.DataFrame, input_format: str, user_input: dict, default_cutoff_min_prec: int = 3
	) -> pd.Series:
	"""Method used to compute metadata for the provided result."""
	current_datetime = datetime.now()
	formatted_datetime = current_datetime.strftime("%Y%m%d_%H%M%S_%f")
	if "comments_for_plotting" not in user_input.keys():
	user_input["comments_for_plotting"] = ""
	user_input = {key: ("" if value is None else value) for key, value in user_input.items()}
	result_datapoint = Datapoint(
	id=input_format + "_" + user_input["software_version"] + "_" + formatted_datetime,
	software_name=input_format,
	software_version=user_input["software_version"],
	search_engine=user_input["search_engine"],
	search_engine_version=user_input["search_engine_version"],
	ident_fdr_psm=user_input["ident_fdr_psm"],
	ident_fdr_peptide=user_input["ident_fdr_peptide"],
	ident_fdr_protein=user_input["ident_fdr_protein"],
	enable_match_between_runs=user_input["enable_match_between_runs"],
	precursor_mass_tolerance=user_input["precursor_mass_tolerance"],
	fragment_mass_tolerance=user_input["fragment_mass_tolerance"],
	enzyme=user_input["enzyme"],
	allowed_miscleavages=user_input["allowed_miscleavages"],
	min_peptide_length=user_input["min_peptide_length"],
	max_peptide_length=user_input["max_peptide_length"],
	intermediate_hash=str(hashlib.sha1(intermediate.to_string().encode("utf-8")).hexdigest()),
	comments=user_input["comments_for_plotting"],
	proteobench_version=proteobench.__version__,
	)

[rodvrees]

https://proteobench.readthedocs.io/en/stable/available-modules/4-DIA-Quantification/#input-data-for-private-visualisation-of-your-benchmark-run-s

For example, the parameters shown here are not the same as for DDA but those for DDA are visualized