peaklets_he.py

import numpy as np
import strax
import straxen
from straxen.plugins.peaklets.peaklets import Peaklets
from straxen.plugins.defaults import HE_PREAMBLE

export, __all__ = strax.exporter()


@export
class PeakletsHighEnergy(Peaklets):
    __doc__ = HE_PREAMBLE + (Peaklets.__doc__ or "")
    depends_on = "records_he"
    provides = "peaklets_he"
    data_kind = "peaklets_he"
    __version__ = "0.1.0"
    child_plugin = True
    save_when = strax.SaveWhen.TARGET

    n_he_pmts = straxen.URLConfig(
        track=False, default=752, infer_type=False, help="Maximum channel of the he channels"
    )

    he_channel_offset = straxen.URLConfig(
        track=False, default=500, infer_type=False, help="Minimum channel number of the he channels"
    )

    le_to_he_amplification = straxen.URLConfig(
        default=20,
        track=True,
        infer_type=False,
        help="Difference in amplification between low energy and high energy channels",
    )

    peak_min_pmts_he = straxen.URLConfig(
        default=2,
        infer_type=False,
        child_option=True,
        parent_option_name="peak_min_pmts",
        track=True,
        help="Minimum number of contributing PMTs needed to define a peak",
    )

    saturation_correction_on_he = straxen.URLConfig(
        default=False,
        infer_type=False,
        child_option=True,
        parent_option_name="saturation_correction_on",
        track=True,
        help="On off switch for saturation correction for High Energy channels",
    )

    hit_min_amplitude_he = straxen.URLConfig(
        default="cmt://hit_thresholds_he?version=ONLINE&run_id=plugin.run_id",
        track=True,
        infer_type=False,
        help=(
            "Minimum hit amplitude in ADC counts above baseline. "
            "Specify as a tuple of length n_tpc_pmts, or a number,"
            'or a string like "pmt_commissioning_initial" which means calling'
            "hitfinder_thresholds.py"
            "or a tuple like (correction=str, version=str, nT=boolean),"
            "which means we are using cmt."
        ),
    )

    # We cannot, we only have the top array, so should not.
    sum_waveform_top_array = False

    @property
    def n_tpc_pmts(self):
        # Have to hack the url config to avoid nasty numba errors for the main Peaklets plugin
        return self.n_he_pmts

    def infer_dtype(self):
        return strax.peak_dtype(n_channels=self.n_he_pmts, digitize_top=self.sum_waveform_top_array)

    def setup(self):
        self.to_pe = self.gain_model
        buffer_pmts = np.zeros(self.he_channel_offset)
        self.to_pe = np.concatenate((buffer_pmts, self.to_pe))
        self.to_pe *= self.le_to_he_amplification
        self.hit_thresholds = self.hit_min_amplitude_he
        self.channel_range = self.channel_map["he"]

    def compute(self, records_he, start, end):
        result = super().compute(records_he, start, end)
        return result["peaklets"]