NuRadioReco.modules.RNO_G.stationHitFilter module
Hit Filter Module (RNO-G specific, can be upgraded to more general use in the future) The main purpose is to reject thermal events in data.
- class NuRadioReco.modules.RNO_G.stationHitFilter.stationHitFilter(complete_time_check=False, complete_hit_check=False, time_window=10.0, threshold_multiplier=6.5, select_trigger=None)[source]
Bases:
objectPasses event through “hit filter”. Looks for temporal coincidence in multiple channel pairs.
Currently this module is designed specifically for the deep components of an RNO-G station and uses only the deep in-ice channels. The module checks for temporal coincidences in multiple channel pairs (uses only antennas at ~100 depth; i.e., not the shallow v-pols). Adjacent channels are put into groups: G0: (0,1,2,3); G1: (9,10); G2: (23,22); G3: (8,4). To determine the timing and amplitude of a “hit” in every channel, the Hilbert Transform is applied to the waveform and the maximum is found. The time of the maximum is then used to check for coincidences in each group. This “time checker” requires at least 1 coincident pair in G0 (PA), and another coincident pair in any other group (including G0 - with an additional requirement that channel pairs need to be connected). When the time check fails, by default, a “hit checker” will see if there’s any in-ice channel that has a high hit (maximum > threshold_multiplier * noise_RMS) and whenever there’s a high hit the event passes the module.
- Parameters:
- complete_time_check: bool (default: False)
If False, time checker will stop early whenever criteria are satisfied. If True, time checker will run through all channel groups no matter what.
- complete_hit_check: bool (default: False)
If False, only run the hit checker when the time checker fails. If True, always run the hit checker.
- time_window: float (default: 10.0*units.ns)
Coincidence window for two adjacent channels.
- threshold_multiplier: float (default: 6.5)
High hit threshold multiplier, where a hit threshold is the multiplier times the noise RMS.
- select_trigger: str (default: None)
Select a specific trigger type to run this filter on. If None, all triggers will be evaluated. If you select a specific trigger, events with other triggers will be treated as if they have passed the module (but not counted).
Methods
See if the input event will survive the Hit Filter or not.
begin([log_level])Set up logging info.
run(evt, station[, det, noise_RMS_all])Runs the Hit Filter.
set_up(set_of_traces, set_of_times, noise_RMS)Set things up before passing to the Hit Filter.
end
- begin(log_level=20)[source]
Set up logging info.
- Parameters:
- log_level: enum
Set verbosity level of logger (default: logging.INFO)
- set_up(set_of_traces, set_of_times, noise_RMS)[source]
Set things up before passing to the Hit Filter.
This setup function calculates the noise RMS, sets the high hit threshold for each channel, gets the Hilbert envelope, and finds the time when the maximum happens (hit). IMPORTANT: If you use this function by yourself, make sure your inputs come from all 15 in-ice channels in order only, rather than all 24 channels.
- Parameters:
- set_of_traces: 2-D array of floats
A set of input trace arrays of all 15 in-ice channels
- set_of_times: 2-D array of floats
A set of input times arrays of all 15 in-ice channels
- noise_RMS: 1-D array of floats
A set of input noise RMS values of all 15 in-ice channels
- apply_hit_filter()[source]
See if the input event will survive the Hit Filter or not.
After the setup, it first checks with the time checker, if event passed the time checker then it passes the Hit Filter; if event failed the time checker, then checks with the hit checker to find a high hit.
- Returns:
- self._passed_hit_filter: bool
Event passed the Hit Filter or not
- run(evt, station, det=None, noise_RMS_all=None)[source]
Runs the Hit Filter.
- Parameters:
- evt: `NuRadioReco.framework.event.Event`
Using the event object to get the trigger type
- station: `NuRadioReco.framework.station.Station`
The station to use the Hit Filter on
- det: Detector object | None
Detector object (not used in this method, included to have the same signature as other NuRadio classes)
- noise_RMS_all: 1-D numpy array (default: None)
Noise RMS values of all 24 channels, if not given the Hit Filter will calculate them for the 15 in-ice channels
- Returns:
- self.is_passed_hit_filter(): bool
Event passed the Hit Filter or not
- get_threshold_multiplier()[source]
- Returns:
- self._threshold_multiplier: float
High hit threshold multiplier (default: 6.5)
- get_in_ice_channels()[source]
- Returns:
- self._in_ice_channels: 1-D list of ints
In-ice channel IDs in a list: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 21, 22, 23]
- get_in_ice_channel_groups()[source]
- Returns:
- self._in_ice_channel_groups: Several 1-D lists of ints in a tuple
In-ice channel groups in a tuple: ([0, 1, 2, 3], [9, 10], [23, 22], [8, 4])
- get_channel_pairs_in_PA()[source]
- Returns:
- self._channel_pairs_in_PA: Several 1-D lists of ints in a tuple
Channel pairs of the PA in a tuple: ([0, 1], [0, 2], [0, 3], [1, 2], [1, 3], [2, 3])
- get_envelope_max_time_index()[source]
- Returns:
- self._envelope_max_time_index: 1-D numpy array of ints
Hit time index of each channel
- get_envelope_max_time()[source]
- Returns:
- self._envelope_max_time: 1-D numpy array of floats
Hit time of each channel
- get_in_ice_channels_noise_RMS()[source]
- Returns:
- self._noise_RMS: 1-D numpy array of floats
Noise RMS values for channels
- get_envelope_traces()[source]
- Returns:
- self._envelope_traces: 2-D numpy array of floats
Arrays of envelope traces for channels
- get_hit_thresholds()[source]
- Returns:
- self._hit_thresholds: 1-D numpy array of floats
Hit threshold of each channel
- is_passed_hit_filter()[source]
- Returns:
- self._passed_hit_filter: bool
See if event passed the Hit Filter
- is_passed_time_checker()[source]
- Returns:
- self._passed_time_checker: bool
See if event passed the time checker
- is_passed_hit_checker()[source]
- Returns:
- self._passed_hit_checker: bool
See if event passed the hit checker
- is_over_hit_threshold()[source]
- Returns:
- self._is_over_hit_threshold: 1-D numpy array of bools
See if there’s a high hit in each channel
- is_in_time_window()[source]
- Returns:
- self._is_in_time_window: 2-D list of bools
See if a channel pair is coincident in the group
- is_wanted_trigger_type()[source]
- Returns:
- self.__is_wanted_trigger_type: bool
When we want to select only events with low threshold triggers.
- is_in_time_window_PA()[source]
- Returns:
- dict: dictionary of bools
See if channel pairs are coincident or not in Group 0 (PA) In the dictionary, there are 6 pairs: (0,1), (0,2), (0,3), (1,2), (1,3), (2,3) To see if a pair is coincident one can do, for example: is_in_time_window_PA[(0,1)], then it will be True or False