diff --git a/funcs.smk b/funcs.smk index ab0e0c5..9f38713 100644 --- a/funcs.smk +++ b/funcs.smk @@ -16,7 +16,7 @@ def process_miscellaneous_plates(misc_plates_d): for plate, plate_dict in misc_plates_d.items(): misc_plates[plate] = {} if not req_keys.issubset(plate_dict): - raise ValueError(f"miscellaneous_plate {plate} lacks {req_keys =}") + raise ValueError(f"miscellaneous_plate {plate} lacks {req_keys=}") misc_plates[plate]["viral_library"] = plate_dict["viral_library"] misc_plates[plate]["neut_standard_set"] = plate_dict["neut_standard_set"] samples = pd.read_csv(plate_dict["samples_csv"]) @@ -58,20 +58,20 @@ def process_plate(plate, plate_params): "curvefit_qc", } if not req_plate_params.issubset(plate_params): - raise ValueError(f"{plate =} {plate_params =} lacks {req_plate_params =}") + raise ValueError(f"{plate=} {plate_params=} lacks {req_plate_params=}") if plate_params["viral_library"] not in viral_libraries: raise ValueError( - f"{plate =} {plate_params['viral_library'] =} not in {viral_libraries =}" + f"{plate=} {plate_params['viral_library']=} not in {viral_libraries=}" ) if plate_params["neut_standard_set"] not in neut_standard_sets: raise ValueError( - f"{plate =} {plate_params['neut_standard_set'] =} not in {neut_standard_sets =}" + f"{plate=} {plate_params['neut_standard_set']=} not in {neut_standard_sets=}" ) plate_d = copy.deepcopy(plate_params) plate_d["group"] = str(plate_d["group"]) plate_d["date"] = str(plate_d["date"]) if not re.fullmatch(r"\d{4}\-\d{2}\-\d{2}", str(plate_d["date"])): - raise ValueError(f"{plate =} {plate_d['date'] =} not in YYYY-MM-DD format") + raise ValueError(f"{plate=} {plate_d['date']=} not in YYYY-MM-DD format") # get default barcode parser params, update if specified per plate plate_d["illumina_barcode_parser_params"] = copy.deepcopy( @@ -86,10 +86,10 @@ def process_plate(plate, plate_params): req_sample_cols = ["well", "serum", "dilution_factor", "replicate", "fastq"] samples_df = pd.read_csv(plate_params["samples_csv"], comment="#") if not set(req_sample_cols).issubset(samples_df.columns): - raise ValueError(f"{plate =} {samples_df.columns =} lacks {req_sample_cols =}") + raise ValueError(f"{plate=} {samples_df.columns=} lacks {req_sample_cols=}") if samples_df["serum"].isnull().any(): - raise ValueError(f"{plate =} 'samples_csv' has null values in 'serum' column") + raise ValueError(f"{plate=} 'samples_csv' has null values in 'serum' column") # try to turn columns of ints and NAs into Int64 to avoid ints appearing as flaots for col in ["replicate", "dilution_factor"]: @@ -155,17 +155,17 @@ def process_plate(plate, plate_params): .drop(columns="duplicates") ) if len(dup_rows): - raise ValueError(f"{plate =} has duplicated serum / replicates:\n{dup_rows}") + raise ValueError(f"{plate=} has duplicated serum / replicates:\n{dup_rows}") # make sure dilution_factor is valid if not ( (samples_df["dilution_factor"] >= 1) | (samples_df["serum"] == "none") ).all(): - raise ValueError(f"{plate =} has dilution factors not >= 1 for non-none serum") + raise ValueError(f"{plate=} has dilution factors not >= 1 for non-none serum") # make sure there is at least one "none" sample if "none" not in set(samples_df["serum"]): - raise ValueError(f"{plate =} has no samples with serum set to 'none'") + raise ValueError(f"{plate=} has no samples with serum set to 'none'") # make sure fastqs are unique dup_fastqs = ( @@ -176,7 +176,7 @@ def process_plate(plate, plate_params): .drop(columns="duplicates") ) if len(dup_fastqs): - raise ValueError(f"{plate =} has duplicate FASTQs:\n{dup_fastqs}") + raise ValueError(f"{plate=} has duplicate FASTQs:\n{dup_fastqs}") plate_d["samples"] = samples_df diff --git a/seqneut-pipeline.smk b/seqneut-pipeline.smk index 4e8703c..e21c1fe 100644 --- a/seqneut-pipeline.smk +++ b/seqneut-pipeline.smk @@ -39,7 +39,7 @@ plates = { groups = sorted(set(plate_params["group"] for plate_params in plates.values())) groups_cannot_contain = ["|", "_"] # wildcard problems if group contains these if any(s in group for s in groups_cannot_contain for group in groups): - raise ValueError(f"found {groups_cannot_contain =} character in {groups =}") + raise ValueError(f"found {groups_cannot_contain=} character in {groups=}") wildcard_constraints: @@ -47,7 +47,7 @@ wildcard_constraints: if not set(config["sera_override_defaults"]).issubset(groups): - raise ValueError(f"{config['sera_override_defaults'] =} keyed by invalid groups") + raise ValueError(f"{config['sera_override_defaults']=} keyed by invalid groups") samples = pd.concat(