Using the proportion in urban nature area. RE:#1180

src/natcap/invest/urban_nature_access.py

@@ -942,7 +942,7 @@ def execute(args):
     if args['search_radius_mode'] == RADIUS_OPT_UNIFORM:
         search_radii = set([float(args['search_radius'])])
     elif args['search_radius_mode'] == RADIUS_OPT_URBAN_NATURE:
-        urban_nature_attrs = attr_table[attr_table['urban_nature'] == 1]
+        urban_nature_attrs = attr_table[attr_table['urban_nature'] > 0]
         try:
             search_radii = set(urban_nature_attrs['search_radius_m'].unique())
         except KeyError as missing_key:
@@ -1805,13 +1805,16 @@ def _reclassify_urban_nature_area(
     """Reclassify LULC pixels into the urban nature area they represent.
 
     After execution, urban nature pixels will have values representing the
-    pixel's area, while pixels that are not urban nature will have a pixel
-    value of 0.  Nodata values will propagate to the output raster.
+    pixel's area of urban nature (pixel area * proportion of urban nature),
+    while pixels that are not urban nature will have a pixel value of 0.
+    Nodata values will propagate to the output raster.
 
     Args:
         lulc_raster_path (string): The path to a land-use/land-cover raster.
         lulc_attribute_table (string): The path to a CSV table representing
             LULC attributes.  Must have "lucode" and "urban_nature" columns.
+            The "urban_nature" column represents a proportion 0-1 of how much
+            of the pixel's area represents urban nature.
         target_raster_path (string): Where the reclassified urban nature raster
             should be written.
         only_these_urban_nature_codes=None (iterable or None): If ``None``, all
@@ -1833,13 +1836,15 @@ def _reclassify_urban_nature_area(
         valid_urban_nature_codes = set(only_these_urban_nature_codes)
     else:
         valid_urban_nature_codes = set(
-            lulc_attribute_df[lulc_attribute_df['urban_nature'] == 1].index)
+            lulc_attribute_df[lulc_attribute_df['urban_nature'] > 0].index)
 
     urban_nature_area_map = {}
-    for lucode in lulc_attribute_df.index:
+    for row in lulc_attribute_df[['urban_nature']].itertuples():
+        lucode = row.Index
+        urban_nature_proportion = row.urban_nature
         urban_nature_area = 0
         if lucode in valid_urban_nature_codes:
-            urban_nature_area = squared_pixel_area
+            urban_nature_area = squared_pixel_area * urban_nature_proportion
         urban_nature_area_map[lucode] = urban_nature_area
 
     lulc_raster_info = pygeoprocessing.get_raster_info(lulc_raster_path)

tests/test_urban_nature_access.py

@@ -85,7 +85,8 @@ def _build_model_args(workspace):
             6,0,100
             7,1,100
             8,0,100
-            9,1,100"""))
+            9,1,100
+            """))
 
     admin_geom = [
         shapely.geometry.box(
@@ -960,6 +961,18 @@ class UNATests(unittest.TestCase):
         """UNA: Run the model with urban nature proportion."""
         from natcap.invest import urban_nature_access
 
+        args = _build_model_args(self.workspace_dir)
+        args['search_radius_mode'] = urban_nature_access.RADIUS_OPT_UNIFORM
+        args['search_radius'] = 1000
+        with open(args['lulc_attribute_table'], 'a') as attr_table:
+            attr_table.write("10,0.5,100\n")
+
+        # make sure our inputs validate
+        validation_results = urban_nature_access.validate(args)
+        self.assertEqual(validation_results, [])
+
+        urban_nature_access.execute(args)
+
     def test_validate(self):
         """UNA: Basic test for validation."""
         from natcap.invest import urban_nature_access