Enhance resampling logic in SampleSeries to handle interior zero-dura…

src/impulse_query_engine/model/series/sample_series.py

@@ -1086,6 +1086,10 @@ def resample(self, sample_rate=1.0):
             # last interval of length 0 is a closed interval. Allow resampled series to start and end at last timestamp
             if (stop_index == len(self) - 1) and (self.tstarts[-1] == self.tends[-1]):
                 tstarts = tmp_tstarts[tmp_tstarts <= t_max]
+            # interior zero-duration block (t_min == t_max, not the trailing point-in-time)
+            # leaves tstarts empty; skip to avoid an unmatched tend being appended.
+            if len(tstarts) == 0:
+                continue
             tends = np.append(tstarts[1:], t_max)
             values = self._interp1d()(tstarts)
             new_tstarts.extend(tstarts)

tests/impulse_query_engine/unit/model/series/sample_series_test.py

@@ -878,6 +878,33 @@ def test_resample8():
     nptest.assert_array_equal(exp_values, result.values)
 
 
+def test_resample_with_interior_point_in_time():
+    # Zero-duration sample (tstart == tend) in the middle of the series used
+    # to make the per-block branch extend new_tends without extending
+    # new_tstarts/new_values, tripping the constructor assertion.
+    s1 = SampleSeries([0, 2, 3], [1, 2, 4], [10, 20, 30])
+    result = s1.resample(sample_rate=1.0)
+    exp_tstarts = [0, 3]
+    exp_tends = [1, 4]
+    exp_values = [10, 30]
+    nptest.assert_array_equal(exp_tstarts, result.tstarts)
+    nptest.assert_array_equal(exp_tends, result.tends)
+    nptest.assert_array_equal(exp_values, result.values)
+
+
+def test_resample_with_interior_and_trailing_point_in_time():
+    # Interior point-in-time is skipped; trailing point-in-time is preserved
+    # by the existing special case for the last block.
+    s1 = SampleSeries([0, 2, 3], [1, 2, 3], [10, 20, 30])
+    result = s1.resample(sample_rate=1.0)
+    exp_tstarts = [0, 3]
+    exp_tends = [1, 3]
+    exp_values = [10, 30]
+    nptest.assert_array_equal(exp_tstarts, result.tstarts)
+    nptest.assert_array_equal(exp_tends, result.tends)
+    nptest.assert_array_equal(exp_values, result.values)
+
+
 def test_rolling_average1():
     s1 = SampleSeries([0, 1, 2, 3, 4, 5, 10], [1, 2, 3, 4, 5, 10, 11], [5, 5, 5, 3, 5, 1, 2])
     s1_avg = s1.rolling_average(window_size=3)