More robust slicing for lag-calc

eqcorrscan/core/match_filter/detection.py

@@ -406,11 +406,19 @@ def extract_stream(self, stream, length, prepick, all_vert=False,
                 pick.sort(key=lambda p: p.time)
             pick = pick[0]
             cut_start = pick.time - prepick
-            cut_end = cut_start + length
-            _st = _st.slice(starttime=cut_start, endtime=cut_end).copy()
-            # Minimum length check
+            # Find nearest sample to avoid trimming to too-short length - see #573
             for tr in _st:
-                if abs((tr.stats.endtime - tr.stats.starttime) -
+                sample_offset = (cut_start - tr.stats.starttime) / tr.stats.delta
+                sample_offset //= 1
+                # If the sample offset is not a whole number, always take the sample
+                # before that requested
+                _tr_cut_start = tr.stats.starttime + (sample_offset * tr.stats.delta)
+                _tr_cut_end = _tr_cut_start + length
+                Logger.info(f"Trimming {tr.id} between {_tr_cut_end} and {_tr_cut_end}.")
+                _tr = tr.slice(_tr_cut_start, _tr_cut_end).copy()
+                Logger.debug(f"Length: {(_tr.stats.endtime - _tr.stats.starttime)}")
+                Logger.debug(f"Requested length: {length}")
+                if abs((_tr.stats.endtime - _tr.stats.starttime) -
                        length) < tr.stats.delta:
                     cut_stream += tr
                 else:

eqcorrscan/tests/lag_calc_test.py

@@ -26,14 +26,14 @@ class SyntheticTests(unittest.TestCase):
     def setUpClass(cls):
         np.random.seed(999)
         print("Setting up class")
-        np.random.seed(999)
         samp_rate = 50
         t_length = .75
         # Make some synthetic templates
         templates, data, seeds = generate_synth_data(
             nsta=5, ntemplates=5, nseeds=10, samp_rate=samp_rate,
             t_length=t_length, max_amp=10, max_lag=15, phaseout="both",
             jitter=0, noise=False, same_phase=True)
+        print("Made synthetic data")
         # Rename channels
         channel_mapper = {"SYN_Z": "HHZ", "SYN_H": "HHN"}
         for tr in data:
@@ -44,6 +44,7 @@ def setUpClass(cls):
         party = Party()
         t = 0
         data_start = data[0].stats.starttime
+        print("Making party")
         for template, template_seeds in zip(templates, seeds):
             template_name = "template_{0}".format(t)
             detections = []
@@ -68,6 +69,8 @@ def setUpClass(cls):
             family = Family(template=_template, detections=detections)
             party += family
             t += 1
+            print(f"Made template {template_name}")
+        print("Made party")
         cls.party = party
         cls.data = data
         cls.t_length = t_length