<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def collapse(l, raw):
 """ LiPD Version 1.3 Main function to initiate time series to LiPD conversion Each object has a: "paleoNumber" or "chronNumber" "tableNumber" "modelNumber" "time_id" "mode" - chronData or paleoData "tableType" - "meas" "ens" "summ" :param list l: Time series :return dict _master: LiPD data, sorted by dataset name """

    logger_ts.info("enter collapse")
    # LiPD data (in progress), sorted dataset name
    _master = {}
    _dsn = ""

    try:
        # Determine if we're collapsing a paleo or chron time series
        _pc = l[0]["mode"]

        # Loop the time series
        for entry in l:
            # Get notable keys
            dsn = entry['dataSetName']
            _dsn = dsn
            _current = entry

            # Since root items are the same in each column of the same dataset, we only need these steps the first time.
            if dsn not in _master:
                logger_ts.info("collapsing: {}".format(dsn))
                print("collapsing: {}".format(dsn))
                _master, _current = _collapse_root(_master, _current, dsn, _pc)
                try:
                    _master[dsn]["paleoData"] = raw[dsn]["paleoData"]
                    if "chronData" in raw[dsn]:
                        _master[dsn]["chronData"] = raw[dsn]["chronData"]
                except KeyError as e:
                    print("collapse: Could not collapse an object the dataset: {}, {}".format(dsn, e))

            # Collapse pc, calibration, and interpretation
            _master = _collapse_pc(_master, _current, dsn, _pc)

        # The result combined into a single dataset. Remove the extra layer on the data.
        if len(_master) == 1:
            _master = _master[_dsn]
            print("Created LiPD data: 1 dataset")
        else:
            print("Created LiPD data: {} datasets".format(len(_master)))

    except Exception as e:
        print("Error: Unable to collapse time series, {}".format(e))
        logger_ts.error("collapse: Exception: {}".format(e))

    logger_ts.info("exit collapse")
    return _master