dssclib

get_dssc_ctrl_data(in_folder, slow_data_pattern, slow_data_aggregators, run_number, slow_data_path)

Obtaining dssc specific slow data like: operating frequency, target gain and encoded gain code from filename, etc.

Source code in /usr/src/app/checkouts/readthedocs.org/user_builds/european-xfel-offline-calibration/envs/latest/lib/python3.8/site-packages/cal_tools/dssclib.py

def get_dssc_ctrl_data(in_folder, slow_data_pattern,
                       slow_data_aggregators, run_number, slow_data_path):
    """Obtaining dssc specific slow data like:
    operating frequency, target gain and encoded gain code from filename, etc.
    """

    # returned dictionaries
    targetGainAll = {}
    encodedGainAll = {}
    operatingFreqAll = {}
    for i in range(16):
        qm = 'Q{}M{}'.format(i // 4 + 1, i % 4 + 1)
        targetGainAll[qm] = None
        encodedGainAll[qm] = None
        operatingFreqAll[qm] = None

    ctrlDataFiles = {}
    for quadrant, aggregator in enumerate(slow_data_aggregators):
        quad_sd_pattern = slow_data_pattern.format("{:04d}".format(run_number),
                                                   "{:02d}".format(aggregator))

        f = os.path.join(in_folder, quad_sd_pattern)
        if os.path.exists(f):
            ctrlDataFiles[quadrant + 1] = f

    if not ctrlDataFiles:
        print("ERROR: no Slow Control Data found!")
        return targetGainAll, encodedGainAll, operatingFreqAll

    daq_format = None

    tGain = {}
    encodedGain = {}
    operatingFreqs = {}
    for quadrant in range(1,5):
        if quadrant in ctrlDataFiles.keys():
            file = ctrlDataFiles[quadrant]
            with h5py.File(file) as h5file:
                iramp_path = f"/RUN/{slow_data_path}{quadrant}/gain/irampFineTrm/value"
                if not daq_format:
                    tGain[quadrant] = 0.0  # 0.0 is default value for TG

                    irampSettings = h5file[iramp_path][0] if iramp_path in h5file else "Various"
                else:
                    epcConfig = h5file[f'/RUN/{slow_data_path}{quadrant}/epcRegisterFilePath/value'][0]\
                        .decode("utf-8")
                    epcConfig = epcConfig[epcConfig.rfind('/') + 1:]

                    print(f"EPC configuration: {epcConfig}")
                    targGain = _extr_gainparam_conffilename(epcConfig)
                    tGain[quadrant] = float(
                        targGain) if targGain is not None else 0.0
                    irampSettings = h5file[iramp_path][0].decode("utf-8")

                gainSettingsMap = {
                    coarseParam: int(
                        h5file[
                            f'/RUN/{slow_data_path}{quadrant}/gain/{coarseParam}/value'
                        ][0]
                    )
                    for coarseParam in ['fcfEnCap', 'csaFbCap', 'csaResistor']
                }

                gainSettingsMap['trimmed'] = np.int64(
                    1) if irampSettings == "Various" else np.int64(0)

                encodedGain[quadrant] = _get_gain_encoded_val(gainSettingsMap)

                opFreq = h5file[f'/RUN/{slow_data_path}{quadrant}/sequencer/cycleLength/value'][0]
                # The Operating Frequency of the detector should be in MHz.
                # Here the karabo operation mode is converted to acquisition rate:
                # 22 corresponds to 4.5 MHz, 44 to 2.25 MHz, etc.
                operatingFreqs[quadrant] = 4.5 * (22.0 / opFreq)
        else:
            print(f"ERROR: no slow data for quadrant {quadrant} is found")

    for varpair in [
        (targetGainAll, tGain),
        (encodedGainAll, encodedGain),
            (operatingFreqAll, operatingFreqs)]:
        for quadrant, value in varpair[1].items():
            for module in range(1, 5):
                qm = f'Q{quadrant}M{module}'
                varpair[0][qm] = value

    return targetGainAll, encodedGainAll, operatingFreqAll

get_pulseid_checksum(fname, h5path, h5path_idx)

generates hash value from pulse pattern (veto defined).

Source code in /usr/src/app/checkouts/readthedocs.org/user_builds/european-xfel-offline-calibration/envs/latest/lib/python3.8/site-packages/cal_tools/dssclib.py

def get_pulseid_checksum(fname, h5path, h5path_idx):
    """generates hash value from pulse pattern (veto defined)."""
    with h5py.File(fname, "r") as infile:
        count = np.squeeze(infile[f"{h5path_idx}/count"])
        first = np.squeeze(infile[f"{h5path_idx}/first"])
        last_index = int(first[count != 0][-1] + count[count != 0][-1])
        first_index = int(first[count != 0][0])
        pulseids = infile[f"{h5path}/pulseId"][first_index:
                                               int(first[count != 0][1])]
        bveto = blake2b(pulseids.data, digest_size=8)
        pulseid_checksum = struct.unpack(
            'd', binascii.unhexlify(bveto.hexdigest()))[0]
        return pulseid_checksum