Fix error in ctapipe-process in case telescope event is missing true image

docs/changes/2659.bugfix.rst

@@ -0,0 +1,10 @@
+Fix error in ``ctapipe-process`` when in the middle of a simtel file
+that has true images available, a telescope event is missing the true image.
+This can happen rarely in case a telescope triggered on pure NSB or
+is oversaturated to the point where the true pe didn't fit into memory constraints.
+
+The error was due to the ``DataWriter`` trying to write a ``None`` into an
+already setup table for the true images.
+
+The ``SimTelEventSource`` will now create an invalid true image filled with ``-1``
+for such events.

src/ctapipe/io/simteleventsource.py

@@ -83,6 +83,11 @@
     "MirrorClass",
 ]
 
+# default for MAX_PHOTOELECTRONS in simtel_array is 2_500_000
+# so this should be a safe limit to distinguish "dim image true missing"
+# from "extremely bright true image missing", see issue #2344
+MISSING_IMAGE_BRIGHTNESS_LIMIT = 1_000_000
+
 # Mapping of SimTelArray Calibration trigger types to EventType:
 # from simtelarray: type Dark (0), pedestal (1), in-lid LED (2) or laser/LED (3+) data.
 SIMTEL_TO_CTA_EVENT_TYPE = {
@@ -570,6 +575,7 @@
             self.file_, kind=self.atmosphere_profile_choice
         )
 
+        self._has_true_image = None
         self.log.debug(f"Using gain selector {self.gain_selector}")
 
     def __exit__(self, exc_type, exc_val, exc_tb):
@@ -812,7 +818,7 @@
             self.log.warning(msg)
             warnings.warn(msg)
 
     def _generate_events(self):
         # for events without event_id, we use negative event_ids
         pseudo_event_id = 0
 
@@ -861,6 +867,20 @@
                 impact_distances = np.full(len(self.subarray), np.nan) * u.m
 
             for tel_id, telescope_event in telescope_events.items():
+                if tel_id not in trigger.tels_with_trigger:
+                    # skip additional telescopes that have data but did not
+                    # participate in the subarray trigger decision for this stereo event
+                    # see #2660 for details
+                    self.log.warning(
+                        "Encountered telescope event not present in"
+                        " stereo trigger information, skipping."
+                        " event_id = %d, tel_id = %d, tels_with_trigger: %s",
+                        event_id,
+                        tel_id,
+                        trigger.tels_with_trigger,
+                    )
+                    continue
+
                 adc_samples = telescope_event.get("adc_samples")
                 if adc_samples is None:
                     adc_samples = telescope_event["adc_sums"][:, :, np.newaxis]
@@ -871,6 +891,30 @@
                     .get(tel_id - 1, {})
                     .get("photoelectrons", None)
                 )
+                true_image_sum = true_image_sums[
+                    self.telescope_indices_original[tel_id]
+                ]
+
+                if self._has_true_image is None:
+                    self._has_true_image = true_image is not None
+
+                if self._has_true_image and true_image is None:
+                    if true_image_sum > MISSING_IMAGE_BRIGHTNESS_LIMIT:
+                        self.log.warning(
+                            "Encountered extremely bright telescope event with missing true_image in"
+                            "file that has true images: event_id = %d, tel_id = %d."
+                            "event might be truncated, skipping telescope event",
+                            event_id,
+                            tel_id,
+                        )
+                        continue
+                    else:
+                        self.log.info(
+                            "telescope event event_id = %d, tel_id = %d is missing true image",
+                            event_id,
+                            tel_id,
+                        )
+                        true_image = np.full(n_pixels, -1, dtype=np.int32)
 
                 if data.simulation is not None:
                     if data.simulation.shower is not None:
@@ -887,9 +931,7 @@
                         )
 
                     data.simulation.tel[tel_id] = SimulatedCameraContainer(
-                        true_image_sum=true_image_sums[
-                            self.telescope_indices_original[tel_id]
-                        ],
+                        true_image_sum=true_image_sum,
                         true_image=true_image,
                         impact=impact_container,
                     )

src/ctapipe/io/tableloader.py

@@ -125,7 +125,9 @@ def _join_telescope_events(table1, table2):
 def _merge_table_same_index(table1, table2, index_keys, fallback_join_type="left"):
     """Merge two tables assuming their primary keys are identical"""
     if len(table1) != len(table2):
-        raise ValueError("Tables must have identical length")
+        raise ValueError(
+            f"Tables must have identical length, {len(table1)} != {len(table2)}"
+        )
 
     if len(table1) == 0:
         return table1

src/ctapipe/io/tests/test_datawriter.py

@@ -201,15 +201,16 @@ def test_roundtrip(tmpdir: Path):
 
     # make sure it is readable by the event source and matches the images
 
-    for event in EventSource(output_path):
-        for tel_id, dl1 in event.dl1.tel.items():
-            original_image = events[event.count].dl1.tel[tel_id].image
-            read_image = dl1.image
-            assert np.allclose(original_image, read_image, atol=0.1)
-
-            original_peaktime = events[event.count].dl1.tel[tel_id].peak_time
-            read_peaktime = dl1.peak_time
-            assert np.allclose(original_peaktime, read_peaktime, atol=0.01)
+    with EventSource(output_path) as source:
+        for event in source:
+            for tel_id, dl1 in event.dl1.tel.items():
+                original_image = events[event.count].dl1.tel[tel_id].image
+                read_image = dl1.image
+                assert np.allclose(original_image, read_image, atol=0.1)
+
+                original_peaktime = events[event.count].dl1.tel[tel_id].peak_time
+                read_peaktime = dl1.peak_time
+                assert np.allclose(original_peaktime, read_peaktime, atol=0.01)
 
 
 def test_dl1writer_no_events(tmpdir: Path):

src/ctapipe/io/tests/test_hdf5.py

@@ -988,19 +988,19 @@ class Container1(Container):
 
     # But when explicitly giving the prefixes, this works and order
     # should not be important
-    reader = HDF5TableReader(path)
-    generator = reader.read(
-        "/values",
-        [Container1, Container1],
-        prefixes=["bar", "foo"],
-    )
+    with HDF5TableReader(path) as reader:
+        generator = reader.read(
+            "/values",
+            [Container1, Container1],
+            prefixes=["bar", "foo"],
+        )
 
-    for value in (1, 2, 3):
-        c1, c2 = next(generator)
-        assert c1.value == 5 * value
-        assert c1.prefix == "bar"
-        assert c2.value == value
-        assert c2.prefix == "foo"
+        for value in (1, 2, 3):
+            c1, c2 = next(generator)
+            assert c1.value == 5 * value
+            assert c1.prefix == "bar"
+            assert c2.value == value
+            assert c2.prefix == "foo"
 
 
 @pytest.mark.parametrize("input_type", (str, Path, tables.File))

src/ctapipe/io/tests/test_simteleventsource.py

@@ -653,3 +653,38 @@ def test_provenance(provenance, prod5_gamma_simtel_path):
     assert len(inputs) == 1
     assert inputs[0]["url"] == str(prod5_gamma_simtel_path)
     assert inputs[0]["reference_meta"] is None
+
+
+def test_prod6_issues():
+    """Test behavior of source on file from prod6, see issues #2344 and #2660"""
+    input_url = "dataset://prod6_issues.simtel.zst"
+
+    events_checked_trigger = set()
+    events_checked_image = set()
+
+    # events with two telescope events but only one in stereo trigger in simtel
+    strange_trigger_events = {
+        1548602: 3,
+        2247909: 32,
+        3974908: 2,
+        4839806: 1,
+    }
+    missing_true_images = {1664106: 32}
+
+    with SimTelEventSource(input_url) as source:
+        for e in source:
+            event_id = e.index.event_id
+            if event_id in strange_trigger_events:
+                expected_tel_id = strange_trigger_events[event_id]
+                np.testing.assert_equal(e.trigger.tels_with_trigger, [expected_tel_id])
+                assert e.trigger.tel.keys() == {expected_tel_id}
+                assert e.r1.tel.keys() == {expected_tel_id}
+                events_checked_trigger.add(event_id)
+
+            if event_id in missing_true_images:
+                tel_id = missing_true_images[event_id]
+                np.testing.assert_equal(e.simulation.tel[tel_id].true_image, -1)
+                events_checked_image.add(event_id)
+
+    assert strange_trigger_events.keys() == events_checked_trigger
+    assert missing_true_images.keys() == events_checked_image

src/ctapipe/tools/tests/test_process.py

@@ -535,3 +535,36 @@ def test_on_old_file(input_url, args, tmp_path):
         np.testing.assert_array_equal(
             finite_reco, events["HillasReconstructor_is_valid"]
         )
+
+
+def test_prod6_issues(tmp_path):
+    """Test behavior of source on file from prod6, see issues #2344 and #2660"""
+    input_url = "dataset://prod6_issues.simtel.zst"
+    output_path = tmp_path / "test.dl1.h5"
+
+    run_tool(
+        ProcessorTool(),
+        argv=[
+            f"--input={input_url}",
+            f"--output={output_path}",
+            "--write-images",
+            "--write-showers",
+            "--overwrite",
+        ],
+        cwd=tmp_path,
+        raises=True,
+    )
+
+    with TableLoader(output_path) as loader:
+        tel_events = loader.read_telescope_events()
+        subarray_events = loader.read_subarray_events()
+
+        trigger_counts = np.count_nonzero(subarray_events["tels_with_trigger"], axis=0)
+        _, tel_event_counts = np.unique(tel_events["tel_id"], return_counts=True)
+
+        mask = trigger_counts > 0
+        np.testing.assert_equal(trigger_counts[mask], tel_event_counts)
+
+        images = loader.read_telescope_events([32], true_images=True)
+        images.add_index("event_id")
+        np.testing.assert_array_equal(images.loc[1664106]["true_image"], -1)