straxen.plugins.peaks_he package

Submodules

straxen.plugins.peaks_he.peak_basics_he module

class straxen.plugins.peaks_he.peak_basics_he.PeakBasicsHighEnergy[source]

Bases: PeakBasics

High energy channels: attenuated signals of the top PMT-array Compute the basic peak-properties, thereby dropping structured arrays.

NB: This plugin can therefore be loaded as a pandas DataFrame.

child_ends_with = '_he'
compute(peaks_he)[source]
config: Dict
data_kind: str | immutabledict | dict
depends_on: tuple = 'peaks_he'
deps: Dict
dtype: tuple | dtype | immutabledict | dict
input_buffer: Dict[str, Chunk]
provides: tuple = ('peak_basics_he',)
run_i: int
run_id: str

straxen.plugins.peaks_he.peaks_he module

class straxen.plugins.peaks_he.peaks_he.PeaksHighEnergy[source]

Bases: Peaks

High energy channels: attenuated signals of the top PMT-array Merge peaklets and merged S2s such that we obtain our peaks (replacing all peaklets that were

later re-merged as S2s).

As this step is computationally trivial, never save this plugin.

child_ends_with = '_he'
compute(peaklets_he, merged_s2s_he)[source]
config: Dict
data_kind: str | immutabledict | dict = 'peaks_he'
depends_on: tuple = ('peaklets_he', 'peaklet_classification_he', 'merged_s2s_he')
deps: Dict
dtype: tuple | dtype | immutabledict | dict
infer_dtype()[source]

Return dtype of computed data; used only if no dtype attribute defined.

input_buffer: Dict[str, Chunk]
provides: tuple = ('peaks_he',)
run_i: int
run_id: str

Module contents