Added z coordinates to hits dictionary. #2
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peter-madigan
requested changes
Dec 9, 2020
| @@ -557,7 +557,7 @@ def _parse_events_array(self): | |||
| events_dict['q_raw'] = np.array([0.]) | |||
| if len(event) and len(trigs): | |||
| events_dict['ts_start'] = np.array([min(event[0]['timestamp'],trigs[0]['ts'])]) | |||
| events_dict['ts_end'] = np.array([min(event[-1]['timestamp'],trigs[-1]['ts'])]) | |||
| events_dict['ts_end'] = np.array([max(event[-1]['timestamp'],trigs[-1]['ts'])]) | |||
| @@ -588,6 +588,9 @@ def _parse_events_array(self): | |||
| ped = np.array([self.pedestal[unique_id]['pedestal_mv'] for unique_id in hit_uniqueid_str]) | |||
| hits_dict['px'] = xy[:,0] | |||
| hits_dict['py'] = xy[:,1] | |||
| VD = float(str(self.track_fitter.get_parameters('vd')).split(':')[1][:-1]) | |||
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I'm hesitant to apply the drift velocity here, since it then makes it so that a drift velocity must always be required to run the evd script (even if you don't want to do the track reconstruction or the drift velocity is zero). It also is more complicated when you have an external trigger, since the z location should be relative to this timestamp. I figured that it was better to not implement the pz variable in the file and let the analysis do that. Something like this:
hit_ref = f['events'][0]['hit_ref']
ext_trig_ref = f['events'][0]['ext_trig_ref'] if f['events'][0]['n_ext_trigs'] > 0 else None
z_scale = f['tracks'].attrs['z_scale']
if ext_trig_ref is not None:
pz = (f['hits'][hit_ref]['ts'] - f['ext_trigs'][ext_trig_ref][0]['ts']) * z_scale
But... if you're willing to add some logic to this to check for
- are you using a track fitter? -> if not, don't fill pz
- are there external triggers in the event? -> if not, don't fill pz
and then do the timestamp relative to the external trigger then I will merge it in.
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