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readtype=args.readtype,
names=args.names,
barcoded=args.barcoded,
combine="track")
datadf, settings = filter_and_transform_data(datadf, vars(args))
if args.raw:
datadf.to_csv(settings["path"] + "NanoComp-data.tsv.gz",
sep="\t",
index=False,
compression="gzip")
if args.store:
pickle.dump(
obj=datadf,
file=open(settings["path"] + "NanoComp-data.pickle", 'wb'))
if args.split_runs:
utils.change_identifiers(datadf, split_dict)
if args.barcoded:
datadf["dataset"] = datadf["barcode"]
identifiers = list(datadf["dataset"].unique())
write_stats(
datadfs=[datadf[datadf["dataset"] == i] for i in identifiers],
outputfile=settings["path"] + "NanoStats.txt",
names=identifiers)
if args.plot != 'false':
plots = make_plots(datadf, settings)
make_report(plots, settings["path"])
logging.info("Succesfully processed all input.")
except Exception as e:
logging.error(e, exc_info=True)
raise