Add data_start to temporary dtype for events_nv (#1447)

straxen/plugins/events_nv/event_waveform_nv.py

@@ -44,15 +44,13 @@ def setup(self):
         self.to_pe[self.channel_range[0] :] = to_pe[:]
 
     def compute(self, events_nv, records_nv, start, end):
-        events = events_nv
-        events_waveform = np.zeros(len(events), self.dtype)
+        events_waveform = np.zeros(len(events_nv), self.dtype)
 
         # Compute shape like properties:
         _tmp_events = np.zeros(len(events_nv), dtype=_temp_event_data_type())
         strax.copy_to_buffer(events_nv, _tmp_events, "_temp_nv_evts_wf_cpy")
         _tmp_events["length"] = (events_nv["endtime"] - events_nv["time"]) // 2
         _tmp_events["dt"] = 2
-        print(records_nv)
         strax.simple_summed_waveform(records_nv, _tmp_events, self.to_pe)
         strax.compute_widths(_tmp_events)
 
@@ -79,11 +77,7 @@ def veto_event_waveform_dtype(
     return dtype
 
 
-def _temp_event_data_type(
-    n_samples_wf: int = 150,
-    n_pmts: int = 120,
-    n_widths: int = 11,
-) -> list:
+def _temp_event_data_type(n_samples_wf: int = 150, n_widths: int = 11) -> list:
     """Temp.
 
     data type which adds field required to use some of the functions used to compute the shape of
@@ -101,6 +95,11 @@ def _temp_event_data_type(
             np.float32,
             n_samples_wf,
         ),
+        (
+            ("Dummy first waveform data in PE/sample (not PE/ns!)", "data_start"),
+            np.float32,
+            n_samples_wf,
+        ),
         (("Peak widths in range of central area fraction [ns]", "width"), np.float32, n_widths),
         (
             ("Peak widths: time between nth and 5th area decile [ns]", "area_decile_from_midpoint"),