Remove per-row index level across components

docs/changelog.md

@@ -22,6 +22,8 @@ Changed:
   instead of zeros as a fill value for runs with a varying number of pulses
   (!347).
 - [imshow2()][extra.utils.imshow2] will now add a colorbar automatically (!351).
+- [DelayLineDetector][extra.components.DelayLineDetector] now longer attaches an index level for each row in [hits()][extra.components.DelayLineDetector.hits] and [signals()][extra.components.DelayLineDetector.signals] (!362).
+- [AdqRawChannel][extra.components.AdqRawChannel] now longer attaches an index level for each row in [train_edges()][extra.components.AdqRawChannel.train_edges] and [pulse_edges()][extra.components.AdqRawChannel.pulse_edges] (!362).
 
 ## [2025.1]
 

src/extra/components/adq.py

@@ -447,9 +447,9 @@ def _shape_edges(self, edges, amplitudes, index):
         from . import DelayLineDetector
 
         edges = DelayLineDetector._build_reduced_pd(
-            None, edges, index, entry_level='edgeIndex')
+            None, edges, index)
         amplitudes = DelayLineDetector._build_reduced_pd(
-            None, amplitudes, index, entry_level='edgeIndex')
+            None, amplitudes, index)
 
         return pd.DataFrame({'edge': edges, 'amplitude': amplitudes})
 

src/extra/components/dld.py

@@ -185,8 +185,14 @@ def _build_reduced_pd(self, data, index, entry_level=None, mask_func=None):
         if entry_level is not None:
             index_df[entry_level] = np.flatnonzero(finite_mask) % num_rows
 
-        return pd_cls(np.ascontiguousarray(raw[finite_mask]),
-                      pd.MultiIndex.from_frame(index_df))
+        if len(index_df.columns) > 1:
+            # Multiple index columns, create a MultiIndex again.
+            index = pd.MultiIndex.from_frame(index_df)
+        else:
+            # If only a single column is left, build a simple index.
+            index = pd.Index(index_df[next(iter(index_df.columns))])
+
+        return pd_cls(np.ascontiguousarray(raw[finite_mask]), index)
 
     @staticmethod
     def insert_aligned_columns(df, columns):
@@ -229,8 +235,7 @@ def insert_aligned_columns(df, columns):
             if shared_index[:2] == df.index.names[:2]:
                 # Same pulse dimensions as the dataframe.
                 if num_per_pulse is None:
-                    num_per_pulse = df.groupby(
-                        level=df.index.names[:-1]).size()
+                    num_per_pulse = df.groupby(level=df.index.names).size()
 
                 align = num_per_pulse
 
@@ -386,8 +391,7 @@ def signals(self, pulse_dim='pulseId', extra_columns={}, max_method=None):
 
         df = self._build_reduced_pd(
             (kd := self._instrument_src['rec.signals']).ndarray(),
-            self._align_pulse_index(kd, pulse_dim), 'signalIndex',
-            mask_func)
+            self._align_pulse_index(kd, pulse_dim), None, mask_func)
 
         if extra_columns:
             self.insert_aligned_columns(df, extra_columns)
@@ -427,8 +431,7 @@ def hits(self, pulse_dim='pulseId', extra_columns={}, max_method=None):
 
         df = self._build_reduced_pd(
             (kd := self._instrument_src['rec.hits']).ndarray(),
-            self._align_pulse_index(kd, pulse_dim), 'hitIndex',
-            mask_func)
+            self._align_pulse_index(kd, pulse_dim), None, mask_func)
 
         if extra_columns:
             self.insert_aligned_columns(df, extra_columns)

tests/test_components_adq.py

@@ -277,7 +277,7 @@ def test_train_edges(mock_sqs_remi_run):
 
     assert isinstance(df, pd.DataFrame)
     np.testing.assert_array_equal(df.columns, ['edge', 'amplitude'])
-    np.testing.assert_array_equal(df.index.names, ['trainId', 'edgeIndex'])
+    np.testing.assert_array_equal(df.index.name, 'trainId')
     assert len(df) == 100
 
     np.testing.assert_allclose(df['edge'], 8944.0)
@@ -311,7 +311,7 @@ def test_pulse_edges(mock_sqs_remi_run):
     assert isinstance(df, pd.DataFrame)
     np.testing.assert_array_equal(df.columns, ['edge', 'amplitude'])
     np.testing.assert_array_equal(
-        df.index.names, ['trainId', 'pulseId', 'edgeIndex'])
+        df.index.names, ['trainId', 'pulseId'])
     assert len(df) == 40
 
     np.testing.assert_array_equal(

tests/test_components_dld.py

@@ -70,8 +70,7 @@ def test_dld_df(mock_sqs_remi_run, key, pulse_dim):
     df = getattr(dld, f'{key}s')(pulse_dim)
 
     assert (df.columns == list(dtype.names)).all()
-    assert df.index.names == [
-        'trainId', pulse_dim, 'fel', 'ppl', f'{key}Index']
+    assert df.index.names == ['trainId', pulse_dim, 'fel', 'ppl']
 
     # Check counts per pulse, should be a repeating pattern of 1-4.
     np.testing.assert_equal(