Remove expedients plugins because SOM will be default

straxen/contexts.py

@@ -83,12 +83,7 @@
 xnt_common_opts = common_opts.copy()
 xnt_common_opts.update(
     {
-        "register": list(common_opts["register"])
-        + [
-            straxen.PeakletSOMClass,
-            straxen.PeaksSOMClassification,
-            straxen.EventSOMClassification,
-        ],
+        "register": list(common_opts["register"]),
         "register_all": list(common_opts["register_all"])
         + [
             straxen.plugins,

straxen/plugins/events/event_basics_som.py

@@ -29,65 +29,3 @@ def _set_dtype_requirements(self):
     def compute(self, events, peaks):
         result = super().compute(events, peaks)
         return result
-
-
-@export
-class EventSOMClassification(strax.Plugin):
-    """Plugin which propagates S1 SOM infromation to events as long straxen.PeakletClassification is
-    still used."""
-
-    depends_on = ("event_basics", "peak_som_classification")
-    __version__ = "0.0.1"
-
-    provides = "event_som_classification"
-
-    def infer_dtype(self):
-        dtype_peaklets = strax.time_fields + [
-            ("s1_som_sub_type", np.int32, "Main S1 SOM subtype of the peak(let)"),
-            ("s1_som_type", np.int8, "Main S1 SOM type of the peak(let)"),
-            ("s1_loc_x_som", np.int16, "Main S1 x location of the peak(let) in the SOM"),
-            ("s1_loc_y_som", np.int16, "Main S1 y location of the peak(let) in the SOM"),
-            ("alt_s1_som_sub_type", np.int32, "Alt S1 SOM subtype of the peak(let)"),
-            ("alt_s1_som_type", np.int8, "Alt S1 SOM type of the peak(let)"),
-            ("alt_s1_loc_x_som", np.int16, "Alt S1 x location of the peak(let) in the SOM"),
-            ("alt_s1_loc_y_som", np.int16, "Alt S1 y location of the peak(let) in the SOM"),
-        ]
-        return dtype_peaklets
-
-    def propagate_field_to_event(self, peaks, events, events_som):
-        peaks_in_event = strax.split_by_containment(peaks, events)
-        return _propagate_field_to_event(peaks_in_event, events, events_som)
-
-    def compute(self, peaks, events):
-        events_som = np.zeros(len(events), self.dtype)
-        events_som[:] = -1
-        events_som["time"] = events["time"]
-        events_som["endtime"] = events["endtime"]
-
-        events_som = self.propagate_field_to_event(peaks, events, events_som)
-
-        return events_som
-
-
-def _propagate_field_to_event(peaks_in_event, events, events_som):
-
-    for p_in_e, event, event_som in zip(peaks_in_event, events, events_som):
-        main_s1 = p_in_e[event["s1_index"]]
-        _main_s1_exist = event["s1_index"] != -1
-        if _main_s1_exist:
-            assert main_s1["time"] == event["s1_time"]
-            event_som["s1_som_sub_type"] = main_s1["som_sub_type"]
-            event_som["s1_som_type"] = main_s1["som_type"]
-            event_som["s1_loc_x_som"] = main_s1["loc_x_som"]
-            event_som["s1_loc_y_som"] = main_s1["loc_y_som"]
-
-        _alt_s1_exist = event["alt_s1_index"] != -1
-        if _alt_s1_exist:
-            alt_s1 = p_in_e[event["alt_s1_index"]]
-            assert alt_s1["time"] == event["alt_s1_time"], (alt_s1["time"], event["alt_s1_time"])
-            event_som["alt_s1_som_sub_type"] = alt_s1["som_sub_type"]
-            event_som["alt_s1_som_type"] = alt_s1["som_type"]
-            event_som["alt_s1_loc_x_som"] = alt_s1["loc_x_som"]
-            event_som["alt_s1_loc_y_som"] = alt_s1["loc_y_som"]
-
-    return events_som

straxen/plugins/peaklets/peaklet_classification_som.py

@@ -269,17 +269,3 @@ def compute_wf_attributes(data, sample_length, n_samples: int):
         quantiles[i] = cumsum_steps[1:] - cumsum_steps[:-1]
 
     return quantiles
-
-
-@export
-class PeakletSOMClass(PeakletClassificationSOM):
-    """Plugin which allows in addition to the straxen classification the SOM classification."""
-
-    child_plugin = True
-    __version__ = "0.0.1"
-
-    provides = "peaklet_classification_som"
-
-    def compute(self, peaklets):
-        peaklet_classifcation_som = super().compute(peaklets)
-        return peaklet_classifcation_som

straxen/plugins/peaks/peaks_som.py

@@ -38,44 +38,3 @@ def compute(self, peaklets, merged_s2s):
         result["som_sub_type"][_is_merged_s2] = -1
 
         return result
-
-
-@export
-class PeaksSOMClassification(strax.Plugin):
-    """Plugin which propagates S1 SOM infromation to peaks if straxen.PeakClassification is still
-    used."""
-
-    depends_on = ("peak_basics", "peaklet_classification_som")
-    __version__ = "0.0.1"
-
-    provides = "peak_som_classification"
-
-    def infer_dtype(self):
-        dtype_peaklets = strax.time_fields + [
-            ("som_sub_type", np.int32, "SOM subtype of the peak(let)"),
-            ("som_type", np.int8, "SOM type of the peak(let)"),
-            ("loc_x_som", np.int16, "x location of the peak(let) in the SOM"),
-            ("loc_y_som", np.int16, "y location of the peak(let) in the SOM"),
-        ]
-        return dtype_peaklets
-
-    def compute(self, peaklets, peaks):
-        result = np.zeros(len(peaks), self.dtype)
-        result[:] = -1
-        result["time"] = peaks["time"]
-        result["endtime"] = peaks["endtime"]
-
-        # Only select S1 and update their SOM fields:
-        _is_s1_peaks = peaks["type"] == 1
-        _is_s1_som_peaklets = peaklets["straxen_type"] == 1
-        _are_same_s1_peaks = np.all(
-            result[_is_s1_peaks]["time"] == peaklets[_is_s1_som_peaklets]["time"]
-        )
-        assert _are_same_s1_peaks, "S1 peaks and SOM S1 peaklets are not identical?!?"
-
-        # Copy "manually" because only subset of data which does not work
-        # with copy to buffer:
-        for field in ("som_sub_type", "som_type", "loc_x_som", "loc_y_som"):
-            result[field][_is_s1_peaks] = peaklets[field][_is_s1_som_peaklets]
-
-        return result