fix tests

Author: dcherian

flox/core.py

@@ -639,7 +639,9 @@ def rechunk_for_cohorts(
         return array.rechunk({axis: newchunks})
 
 
-def rechunk_for_blockwise(array: DaskArray, axis: T_Axis, labels: np.ndarray) -> DaskArray:
+def rechunk_for_blockwise(
+    array: DaskArray, axis: T_Axis, labels: np.ndarray, *, force: bool = True
+) -> DaskArray:
     """
     Rechunks array so that group boundaries line up with chunk boundaries, allowing
     embarrassingly parallel group reductions.
@@ -672,11 +674,16 @@ def rechunk_for_blockwise(array: DaskArray, axis: T_Axis, labels: np.ndarray) ->
         return array
 
     Δn = abs(len(newchunks) - len(chunks))
-    if (Δn / len(chunks) < BLOCKWISE_RECHUNK_NUM_CHUNKS_THRESHOLD) and (
-        abs(max(newchunks) - max(chunks)) / max(chunks) < BLOCKWISE_RECHUNK_CHUNK_SIZE_THRESHOLD
+    if force or (
+        (Δn / len(chunks) < BLOCKWISE_RECHUNK_NUM_CHUNKS_THRESHOLD)
+        and (
+            abs(max(newchunks) - max(chunks)) / max(chunks) < BLOCKWISE_RECHUNK_CHUNK_SIZE_THRESHOLD
+        )
     ):
         # Less than 25% change in number of chunks, let's do it
         return array.rechunk({axis: newchunks})
+    else:
+        return array
 
 
 def reindex_(
@@ -2496,7 +2503,7 @@ def groupby_reduce(
     ):
         # Let's try rechunking for sorted 1D by.
         (single_axis,) = axis_
-        array = rechunk_for_blockwise(array, single_axis, by_)
+        array = rechunk_for_blockwise(array, single_axis, by_, force=False)
 
     if _is_first_last_reduction(func):
         if has_dask and nax != 1: