lightcurve class addition

Signed-off-by: cgalelli <[email protected]>

gammapy/maps/axes.py

@@ -2672,53 +2672,13 @@ def group_table(self, edges):
         groups : `~astropy.table.Table`
             Map axis group table.
         """
-        # TODO: try to simplify this code
-        if self.node_type != "edges":
-            raise ValueError("Only edge based map axis can be grouped")
-
-        edges_pix = self.coord_to_pix(edges)
-        edges_pix = np.clip(edges_pix, -0.5, self.nbin - 0.5)
-        edges_idx = np.round(edges_pix + 0.5) - 0.5
-        edges_idx = np.unique(edges_idx)
-        edges_ref = self.pix_to_coord(edges_idx)
-
-        groups = Table()
-        groups[f"{self.name}_min"] = edges_ref[:-1]
-        groups[f"{self.name}_max"] = edges_ref[1:]
-
-        groups["idx_min"] = (edges_idx[:-1] + 0.5).astype(int)
-        groups["idx_max"] = (edges_idx[1:] - 0.5).astype(int)
-
-        if len(groups) == 0:
-            raise ValueError("No overlap between reference and target edges.")
-
-        groups["bin_type"] = "normal   "
-
-        edge_idx_start, edge_ref_start = edges_idx[0], edges_ref[0]
-        if edge_idx_start > 0:
-            underflow = {
-                "bin_type": "underflow",
-                "idx_min": 0,
-                "idx_max": edge_idx_start,
-                f"{self.name}_min": self.pix_to_coord(-0.5),
-                f"{self.name}_max": edge_ref_start,
-            }
-            groups.insert_row(0, vals=underflow)
+        edges = self.reference_time + edges
 
-        edge_idx_end, edge_ref_end = edges_idx[-1], edges_ref[-1]
+        gti = self.to_gti()
 
-        if edge_idx_end < (self.nbin - 0.5):
-            overflow = {
-                "bin_type": "overflow",
-                "idx_min": edge_idx_end + 1,
-                "idx_max": self.nbin - 1,
-                f"{self.name}_min": edge_ref_end,
-                f"{self.name}_max": self.pix_to_coord(self.nbin - 0.5),
-            }
-            groups.add_row(vals=overflow)
+        time_intervals = [(edges[i], edges[i + 1]) for i in range(len(edges) - 1)]
+        groups = gti.group_table(time_intervals)
 
-        group_idx = Column(np.arange(len(groups)))
-        groups.add_column(group_idx, name="group_idx", index=0)
         return groups
 
     def upsample(self):