`.tsp._anal`: add (unused) `detect_vlm_gaps()`

piker/tsp/_anal.py

@@ -616,6 +616,18 @@ def detect_price_gaps(
     # ])
     ...
 
+# TODO: probably just use the null_segs impl above?
+def detect_vlm_gaps(
+    df: pl.DataFrame,
+    col: str = 'volume',
+
+) -> pl.DataFrame:
+
+    vnull: pl.DataFrame = w_dts.filter(
+        pl.col(col) == 0
+    )
+    return vnull
+
 
 def dedupe(
     src_df: pl.DataFrame,
@@ -626,7 +638,6 @@ def dedupe(
 
 ) -> tuple[
     pl.DataFrame,  # with dts
-    pl.DataFrame,  # gaps
     pl.DataFrame,  # with deduplicated dts (aka gap/repeat removal)
     int,  # len diff between input and deduped
 ]:
@@ -639,19 +650,22 @@ def dedupe(
     '''
     wdts: pl.DataFrame = with_dts(src_df)
 
-    # maybe sort on any time field
-    if sort:
-        wdts = wdts.sort(by='time')
-        # TODO: detect out-of-order segments which were corrected!
-        # -[ ] report in log msg
-        # -[ ] possibly return segment sections which were moved?
+    deduped = wdts
 
     # remove duplicated datetime samples/sections
     deduped: pl.DataFrame = wdts.unique(
-        subset=['dt'],
+        # subset=['dt'],
+        subset=['time'],
         maintain_order=True,
     )
 
+    # maybe sort on any time field
+    if sort:
+        deduped = deduped.sort(by='time')
+        # TODO: detect out-of-order segments which were corrected!
+        # -[ ] report in log msg
+        # -[ ] possibly return segment sections which were moved?
+
     diff: int = (
         wdts.height
         -