Merge pull request graphnet-team#837 from astrojarred/astrojarred/issue836

Add MAGIC Telescope detector class

Author: astrojarred

data/geometry_tables/magic/magic.parquet

@@ -41,3 +41,4 @@
 ICECUBE_GEOMETRY_TABLE_DIR = os.path.join(GEOMETRY_TABLE_DIR, "icecube")
 PROMETHEUS_GEOMETRY_TABLE_DIR = os.path.join(GEOMETRY_TABLE_DIR, "prometheus")
 LIQUIDO_GEOMETRY_TABLE_DIR = os.path.join(GEOMETRY_TABLE_DIR, "liquid-o")
+MAGIC_GEOMETRY_TABLE_DIR = os.path.join(GEOMETRY_TABLE_DIR, "magic")

src/graphnet/constants.py

@@ -4,3 +4,4 @@
 from .detector import Detector
 from .liquido import LiquidO_v1
 from .prometheus import ORCA150
+from .magic import MAGIC

src/graphnet/models/detector/__init__.py

@@ -0,0 +1,61 @@
+"""MAGIC-specific `Detector` class(es)."""
+
+from typing import Dict, Callable, Any
+import torch
+import os
+
+from graphnet.models.detector.detector import Detector
+from graphnet.constants import MAGIC_GEOMETRY_TABLE_DIR
+
+
+class MAGIC(Detector):
+    """`Detector` class for MAGIC telescopes."""
+
+    geometry_table_path = os.path.join(
+        MAGIC_GEOMETRY_TABLE_DIR, "magic.parquet"
+    )
+
+    # By default, treat the telescope ID as a spatial-like z-coordinate
+    xyz = ["x_cam", "y_cam", "tel_id"]
+
+    def __init__(self, use_charge_epsilon: bool = True, **kwargs: Any) -> None:
+        """Construct detector for the MAGIC telescopes.
+
+        Args:
+            use_charge_epsilon: Whether to add a small epsilon value to charge
+                before taking log10 to avoid log(0). Defaults to True (uses
+                1e-6). Set to False if data is guaranteed to have zero-padding.
+        """
+        super().__init__(**kwargs)
+        self._charge_epsilon = 1e-6 if use_charge_epsilon else 0.0
+
+    def feature_map(self) -> Dict[str, Callable]:
+        """Map standardization functions to each dimension.
+
+        Note: tel_id can take the integer values 0 or 1, where:
+            - 0 corresponds to MAGIC-I
+            - 1 corresponds to MAGIC-II
+        """
+        feature_map = {
+            "x_cam": self._xy,
+            "y_cam": self._xy,
+            "tel_id": self._identity,
+            "time": self._time,
+            "charge": self._charge,
+            "telescope_phi": self._identity,
+            "telescope_theta": self._identity,
+        }
+        return feature_map
+
+    def _xy(self, x: torch.tensor) -> torch.tensor:
+        return x / 28.5
+
+    def _time(self, x: torch.tensor) -> torch.tensor:
+        """Scale time based on the average time of arrival."""
+        t_min = -30
+        t_max = 60
+        return (x - t_min) / (t_max - t_min)
+
+    def _charge(self, x: torch.tensor) -> torch.tensor:
+        """Add a small epsilon to avoid log(0)."""
+        return torch.log10(x + self._charge_epsilon)