Merge pull request perrygeo#193 from giplessis/master

Accessing geometry properties for user-defined stats

docs/manual.rst

@@ -174,6 +174,20 @@ then use it in your ``zonal_stats`` call like so::
     ...             add_stats={'mymean':mymean})
     [{'count': 75, 'mymean': 14.660084635416666}, {'count': 50, 'mymean': 56.605761718750003}]
 
+To have access to geometry properties, a dictionnary can be passed to the user-defined function::
+
+    >>> def mymean_prop(x,prop):
+    ...     return np.ma.mean(x) * prop['id']
+
+then use it in your ``zonal_stats`` call like so::
+
+    >>> zonal_stats("tests/data/polygons.shp",
+    ...             "tests/data/slope.tif",
+    ...             stats="count",
+    ...             add_stats={'mymean_prop':mymean_prop},
+    ...             properties=['id'])
+    [{'count': 75, 'mymean_prop': 14.660084635416666}, {'count': 50, 'mymean_prop': 113.2115234375}]
+
 
 GeoJSON output
 ^^^^^^^^^^^^^^

src/rasterstats/main.py

@@ -112,6 +112,7 @@ def gen_zonal_stats(
         with zonal stats appended as additional properties.
         Use with `prefix` to ensure unique and meaningful property names.
 
+        
     Returns
     -------
     generator of dicts (if geojson_out is False)
@@ -258,7 +259,11 @@ def gen_zonal_stats(
 
             if add_stats is not None:
                 for stat_name, stat_func in add_stats.items():
-                    feature_stats[stat_name] = stat_func(masked)
+                    try:
+                        feature_stats[stat_name] = stat_func(masked, feat['properties'])
+                    except TypeError:
+                        # backwards compatible with single-argument function
+                        feature_stats[stat_name] = stat_func(masked)
 
             if raster_out:
                 feature_stats['mini_raster_array'] = masked

tests/test_zonal.py

@@ -289,6 +289,17 @@ def mymean(x):
         assert stats[i]['mean'] == stats[i]['mymean']
 
 
+def test_add_stats_prop():
+    polygons = os.path.join(DATA, 'polygons.shp')
+
+    def mymean_prop(x, prop):
+        return np.ma.mean(x) * prop['id']
+
+    stats = zonal_stats(polygons, raster, add_stats={'mymean_prop': mymean_prop})
+    for i in range(len(stats)):
+        assert stats[i]['mymean_prop'] == stats[i]['mean'] * (i+1)
+
+
 def test_mini_raster():
     polygons = os.path.join(DATA, 'polygons.shp')
     stats = zonal_stats(polygons, raster, raster_out=True)