GbmOnboardTrigger

class gdt.missions.fermi.gbm.trigger.GbmOnboardTrigger(algorithms: dict = {1: TriggerAlgorithm(timescale   16 ms, offset    0 ms, channels [3, 4], threshold 7.50 sigma), 2: TriggerAlgorithm(timescale   32 ms, offset    0 ms, channels [3, 4], threshold 7.50 sigma), 3: TriggerAlgorithm(timescale   32 ms, offset   16 ms, channels [3, 4], threshold 7.50 sigma), 4: TriggerAlgorithm(timescale   64 ms, offset    0 ms, channels [3, 4], threshold 5.00 sigma), 5: TriggerAlgorithm(timescale   64 ms, offset   32 ms, channels [3, 4], threshold 5.00 sigma), 6: TriggerAlgorithm(timescale  128 ms, offset    0 ms, channels [3, 4], threshold 5.00 sigma), 7: TriggerAlgorithm(timescale  128 ms, offset   64 ms, channels [3, 4], threshold 5.00 sigma), 8: TriggerAlgorithm(timescale  256 ms, offset    0 ms, channels [3, 4], threshold 4.00 sigma), 9: TriggerAlgorithm(timescale  256 ms, offset  128 ms, channels [3, 4], threshold 4.00 sigma), 10: TriggerAlgorithm(timescale  512 ms, offset    0 ms, channels [3, 4], threshold 4.00 sigma), 11: TriggerAlgorithm(timescale  512 ms, offset  256 ms, channels [3, 4], threshold 4.00 sigma), 12: TriggerAlgorithm(timescale 1024 ms, offset    0 ms, channels [3, 4], threshold 4.50 sigma), 13: TriggerAlgorithm(timescale 1024 ms, offset  512 ms, channels [3, 4], threshold 4.50 sigma), 14: TriggerAlgorithm(timescale 2048 ms, offset    0 ms, channels [3, 4], threshold 4.50 sigma), 15: TriggerAlgorithm(timescale 2048 ms, offset 1024 ms, channels [3, 4], threshold 4.50 sigma), 16: TriggerAlgorithm(timescale 4096 ms, offset    0 ms, channels [3, 4], threshold 4.50 sigma), 17: TriggerAlgorithm(timescale 4096 ms, offset 2048 ms, channels [3, 4], threshold 4.50 sigma), 22: TriggerAlgorithm(timescale   16 ms, offset    0 ms, channels [2, 2], threshold 8.00 sigma), 23: TriggerAlgorithm(timescale   32 ms, offset    0 ms, channels [2, 2], threshold 8.00 sigma), 24: TriggerAlgorithm(timescale   32 ms, offset   16 ms, channels [2, 2], threshold 8.00 sigma), 25: TriggerAlgorithm(timescale   64 ms, offset    0 ms, channels [2, 2], threshold 5.50 sigma), 26: TriggerAlgorithm(timescale   64 ms, offset   32 ms, channels [2, 2], threshold 5.50 sigma), 43: TriggerAlgorithm(timescale   16 ms, offset    0 ms, channels [5, 7], threshold 8.00 sigma), 50: TriggerAlgorithm(timescale   16 ms, offset    0 ms, channels [4, 7], threshold 8.00 sigma)}, background_window: int = 17024, background_offset: int = 4096, resolution: int = 16, channel_edges: list = None, det_names: list = None, n: int = 2, verbose: bool = True)

Bases: SlidingWindowMethod

Class for applying GBM’s on-board trigger algorithm

Methods Summary

prepare_data(ttes[, time_range])

Method to prepare TTE data into a PHAII format for use with trigger algorithms.

Methods Documentation

prepare_data(ttes: list, time_range: list = None)

Method to prepare TTE data into a PHAII format for use with trigger algorithms. During preparation, TTE files are sorted according to detector name and we check that there is one file for each NaI detector.

Parameters:

ttes (list) – List of GbmTte objects

Returns:

(list)