Merge pull request #182 from jacanchaplais/feature/lhe-classmethod-177

Added classmethod to read LHE event data #177

graphicle/base.py

@@ -45,6 +45,35 @@
 DataType = ty.TypeVar("DataType")
 
 
+class LheEventInterface(ty.Protocol):
+    """Interface for a generic Les Houches event.
+
+    :group: base
+
+    .. versionadded:: 0.4.0
+    """
+
+    @property
+    def pdg(self) -> IntVector:
+        ...
+
+    @property
+    def pmu(self) -> AnyVector:
+        ...
+
+    @property
+    def color(self) -> AnyVector:
+        ...
+
+    @property
+    def helicity(self) -> HalfIntVector:
+        ...
+
+    @property
+    def status(self) -> HalfIntVector:
+        ...
+
+
 class EventInterface(ty.Protocol):
     """Defines the interface for a generic event object expected by
     graphicle's routines. Attributes are stored as numpy arrays, with

graphicle/data.py

@@ -2296,6 +2296,36 @@ def copy(self) -> "ParticleSet":
         """Copies the underlying data into a new ParticleSet instance."""
         return _composite_copy(self)
 
+    @classmethod
+    def from_lhe_event(cls, event: base.LheEventInterface) -> "ParticleSet":
+        """Creates a ParticleSet instance directly from a data structure
+        holding LHE data. This is useful when you want to study the hard
+        process, without needing to shower or hadronize.
+
+        .. versionadded:: 0.4.0
+
+        Parameters
+        ----------
+        event : LheEventInterface
+            A data structure with attributes "pdg", "pmu", "color",
+            "helicity", and "status". These attributes provide access to
+            numpy arrays, which hold the underlying Les Houches event
+            data.
+
+        Returns
+        -------
+        ParticleSet
+            A composite object, wrapping the data provided in Graphicle
+            objects, and providing a unified interface to them.
+        """
+        props = ("pdg", "pmu", "color", "helicity", "status")
+        pcls = cls.from_numpy(**{name: getattr(event, name) for name in props})
+        pcls.final = MaskArray(np.zeros(len(pcls), dtype=np.bool_))
+        status_map = {-1: -21, 1: -23, -2: -22, 2: -22, 3: -22, -9: -12}
+        for old_code, new_code in status_map.items():
+            pcls.status.data[pcls.status.data == old_code] = new_code
+        return pcls
+
     @classmethod
     def from_numpy(
         cls,