Add support for grid_height/grid_width as separate values

queries.yaml

@@ -976,10 +976,36 @@ post_process:
     params:
       source_layer: places
       start_zoom: 8
-      end_zoom: 12
+      end_zoom: 9
+      items_matching: { kind: locality }
+      max_items: 1
+      grid_width: 3
+      sorting_keys:
+        - { sort_key: 'min_zoom', reverse: False }
+        - { sort_key: 'collision_rank', reverse: False }
+        - { sort_key: 'population', reverse: True }
+        - { sort_key: 'id', reverse: True }
+  - fn: vectordatasource.transform.keep_n_features_gridded
+    params:
+      source_layer: places
+      start_zoom: 9
+      end_zoom: 11
+      items_matching: { kind: locality }
+      max_items: 1
+      grid_width: 6
+      sorting_keys:
+        - { sort_key: 'min_zoom', reverse: False }
+        - { sort_key: 'collision_rank', reverse: False }
+        - { sort_key: 'population', reverse: True }
+        - { sort_key: 'id', reverse: True }
+  - fn: vectordatasource.transform.keep_n_features_gridded
+    params:
+      source_layer: places
+      start_zoom: 11
+      end_zoom: 13
       items_matching: { kind: locality }
       max_items: 1
-      grid_size: 16
+      grid_width: 12
       sorting_keys:
         - { sort_key: 'min_zoom', reverse: False }
         - { sort_key: 'collision_rank', reverse: False }

test/test_transform.py

@@ -424,7 +424,7 @@ def test_not_points(self):
                 source_layer="test_layer",
                 items_matching=dict(foo="bar"),
                 max_items=1,
-                grid_size=2,
+                grid_width=2,
                 sorting_keys=[
                     {"sort_key": "foo"},
                 ],
@@ -461,7 +461,7 @@ def test_points_keep_1(self):
                 source_layer="test_layer",
                 items_matching=dict(foo="bar"),
                 max_items=1,
-                grid_size=2,
+                grid_width=2,
                 sorting_keys=[
                     {"sort_key": "foo"},
                 ],
@@ -499,7 +499,7 @@ def test_points_keep_1_multisort_second(self):
                 source_layer="test_layer",
                 items_matching=dict(foo="bar"),
                 max_items=1,
-                grid_size=2,
+                grid_width=2,
                 sorting_keys=[
                     {"sort_key": "min_zoom"},
                     {"sort_key": "population", "reverse": True},
@@ -538,7 +538,7 @@ def test_points_keep_1_multisort_minzoom(self):
                 source_layer="test_layer",
                 items_matching=dict(foo="bar"),
                 max_items=1,
-                grid_size=2,
+                grid_width=2,
                 sorting_keys=[
                     {"sort_key": "min_zoom"},
                     {"sort_key": "population", "reverse": True},
@@ -581,7 +581,7 @@ def test_points_keep_1_different_buckets(self):
                 source_layer="test_layer",
                 items_matching=dict(foo="bar"),
                 max_items=1,
-                grid_size=2,
+                grid_width=2,
                 sorting_keys=[
                     {"sort_key": "population", "reverse": True},
                 ],
@@ -625,7 +625,7 @@ def test_points_keep_more_than_in_one_bucket(self):
                 source_layer="test_layer",
                 items_matching=dict(foo="bar"),
                 max_items=5,
-                grid_size=2,
+                grid_width=2,
                 sorting_keys=[
                     {"sort_key": "min_zoom", "reverse": True},
                     {"sort_key": "population"},
@@ -667,7 +667,7 @@ def test_fail_on_non_integer_reverse_sort_key(self):
                 source_layer="test_layer",
                 items_matching=dict(foo="bar"),
                 max_items=5,
-                grid_size=2,
+                grid_width=2,
                 sorting_keys=[
                     {"sort_key": "population", "reverse": True},
                 ],

vectordatasource/transform.py

@@ -3120,9 +3120,10 @@ def keep_n_features_gridded(ctx):
     pairs in `items_matching` into a grid, then keep the
     first `max_items` features in each grid cell.
 
-    The grid is created by dividing the width and height
-    of the tile into `grid_size` buckets (so you end up
-    with grid_size*grid_size buckets total).
+    The grid is created by dividing the tile into buckets.
+    You can specify the `grid_width` and `grid_height` to
+    get grid_width*grid_height buckets or just `grid_width`
+    to get grid_width*grid_width buckets.
 
     NOTE: This only works with point features and will
     pass through non-point features untouched.
@@ -3139,15 +3140,17 @@ def keep_n_features_gridded(ctx):
     end_zoom = ctx.params.get('end_zoom')
     items_matching = ctx.params.get('items_matching')
     max_items = ctx.params.get('max_items')
-    grid_size = ctx.params.get('grid_size')
+    grid_width = ctx.params.get('grid_width')
+    # if grid_height is not specified, use grid_width for grid_height
+    grid_height = ctx.params.get('grid_height') or grid_width
     sorting_keys = ctx.params.get('sorting_keys')
 
     # leaving items_matching, grid_size, or max_items as None (or zero)
     # would mean that this filter would do nothing, so assume
     # that this is really a configuration error.
     assert items_matching, 'keep_n_features_gridded: missing or empty item match dict'
     assert max_items, 'keep_n_features_gridded: missing or zero max number of items'
-    assert grid_size, 'keep_n_features_gridded: missing or zero grid size'
+    assert grid_width, 'keep_n_features_gridded: missing or zero grid width'
     assert sorting_keys, 'keep_n_features_gridded: missing sorting keys'
     assert isinstance(sorting_keys, list), 'keep_n_features_gridded: sorting keys should be a list'
 
@@ -3166,8 +3169,8 @@ def keep_n_features_gridded(ctx):
         return None
 
     minx, miny, maxx, maxy = ctx.unpadded_bounds
-    bucket_width = (maxx - minx) / grid_size
-    bucket_height = (maxy - miny) / grid_size
+    bucket_width = (maxx - minx) / grid_width
+    bucket_height = (maxy - miny) / grid_height
 
     # Sort the features into buckets
     buckets = defaultdict(list)