Add CutList

strax/plugins/cut_plugin.py

@@ -2,6 +2,7 @@
 import numpy as np
 import strax
 from .plugin import Plugin, SaveWhen
+from .merge_only_plugin import MergeOnlyPlugin
 
 export, __all__ = strax.exporter()
 
@@ -65,3 +66,69 @@ def compute(self, **kwargs):
     def cut_by(self, **kwargs):
         # This should be provided by the user making a CutPlugin
         raise NotImplementedError()
+
+
+@export
+class CutList(MergeOnlyPlugin):
+    """Base class that merges all existing cuts into a single array which can be loaded by the
+    analysts."""
+
+    __version__ = "0.0.0"
+
+    save_when = SaveWhen.TARGET
+    cuts = ()
+    # need to declare depends_on here to satisfy strax
+    # https://github.com/AxFoundation/strax/blob/df18c9cef38ea1cee9737d56b1bea078ebb246a9/strax/plugin.py#L99
+    depends_on = ()
+    _depends_on = ()
+
+    def infer_dtype(self):
+        dtype = super().infer_dtype()
+        dtype += [
+            (
+                (
+                    f"Boolean AND of all cuts in {self.accumulated_cuts_string}",
+                    self.accumulated_cuts_string,
+                ),
+                np.bool_,
+            )
+        ]
+        return dtype
+
+    def compute(self, **kwargs):
+        cuts = super().compute(**kwargs)
+        cuts_joint = np.zeros(len(cuts), self.dtype)
+        strax.copy_to_buffer(
+            cuts, cuts_joint, f"_copy_cuts_{strax.deterministic_hash(self.depends_on)}"
+        )
+        cuts_joint[self.accumulated_cuts_string] = get_accumulated_bool(cuts)
+        return cuts_joint
+
+    @property  # type: ignore
+    def depends_on(self):  # noqa
+        if not len(self._depends_on):
+            deps = []
+            for c in self.cuts:
+                deps.extend(strax.to_str_tuple(c.provides))
+            self._depends_on = tuple(deps)
+        return self._depends_on
+
+    @depends_on.setter
+    def depends_on(self, str_or_tuple):
+        self._depends_on = strax.to_str_tuple(str_or_tuple)
+
+
+@export
+def get_accumulated_bool(array):
+    """Computes accumulated boolean over all cuts.
+
+    :param array: Array containing merged cuts.
+
+    """
+    fields = array.dtype.names
+    fields = np.array([f for f in fields if f not in ("time", "endtime")])
+
+    res = np.ones(len(array), np.bool_)
+    for field in fields:
+        res &= array[field]
+    return res