Move set_nan_defaults to be a stand-alone function (#1497)

straxen/plugins/events/event_basics_vanilla.py

@@ -207,19 +207,9 @@ def _get_posrec_dtypes(self):
 
         return posrec_dtpye
 
-    @staticmethod
-    def set_nan_defaults(buffer):
-        """When constructing the dtype, take extra care to set values to np.Nan / -1 (for ints) as 0
-        might have a meaning."""
-        for field in buffer.dtype.names:
-            if np.issubdtype(buffer.dtype[field], np.integer):
-                buffer[field][:] = -1
-            else:
-                buffer[field][:] = np.nan
-
     def compute(self, events, peaks):
         result = np.zeros(len(events), dtype=self.dtype)
-        self.set_nan_defaults(result)
+        strax.set_nan_defaults(result)
 
         split_peaks = strax.split_by_containment(peaks, events)
 

straxen/plugins/events/event_nearest_triggering.py

@@ -1,6 +1,5 @@
 import numpy as np
 import strax
-import straxen
 
 export, __all__ = strax.exporter()
 
@@ -77,7 +76,7 @@ def compute(self, events, peaks):
         split_peaks = strax.split_by_containment(peaks, events)
         result = np.zeros(len(events), self.dtype)
 
-        straxen.EventBasicsVanilla.set_nan_defaults(result)
+        strax.set_nan_defaults(result)
 
         # 1. Assign peaks features to main S1 and main S2 in the event
         for event_i, (event, sp) in enumerate(zip(events, split_peaks)):

straxen/plugins/events/event_shadow.py

@@ -1,8 +1,6 @@
 import numpy as np
 import strax
 
-import straxen
-
 export, __all__ = strax.exporter()
 
 
@@ -108,7 +106,7 @@ def compute(self, events, peaks):
         split_peaks = strax.split_by_containment(peaks, events)
         result = np.zeros(len(events), self.dtype)
 
-        straxen.EventBasicsVanilla.set_nan_defaults(result)
+        strax.set_nan_defaults(result)
 
         # 1. Assign peaks features to main S1 and main S2 in the event
         for event_i, (event, sp) in enumerate(zip(events, split_peaks)):

straxen/plugins/peaks/peak_nearest_triggering.py

@@ -79,7 +79,7 @@ def compute_triggering(self, peaks, current_peak):
         _peaks = _peaks[_is_triggering]
         # init result
         result = np.zeros(len(current_peak), self.dtype)
-        straxen.EventBasicsVanilla.set_nan_defaults(result)
+        strax.set_nan_defaults(result)
 
         # use center_time as the anchor of things
         things = np.zeros(len(_peaks), dtype=strax.time_fields)

straxen/plugins/peaks/peak_per_event.py

@@ -1,6 +1,5 @@
 import numpy as np
 import strax
-import straxen
 
 export, __all__ = strax.exporter()
 
@@ -30,7 +29,7 @@ def compute(self, events, peaks):
         split_peaks = strax.split_by_containment(peaks, events)
         split_peaks_ind = strax.fully_contained_in(peaks, events)
         result = np.zeros(len(peaks), self.dtype)
-        straxen.EventBasicsVanilla.set_nan_defaults(result)
+        strax.set_nan_defaults(result)
 
         # Assign peaks features to main S1 and main S2 in the event
         for event_i, (event, sp) in enumerate(zip(events, split_peaks)):