Merge pull request #1513 from phargogh/bugfix/1512-una-over-and-under…

…supply-sums-missing

Fix issue with over- and under-supply values missing from UNA administrative vector

HISTORY.rst

@@ -45,6 +45,13 @@ Unreleased Changes
     * Fixed an issue where Urban Nature Access would crash if an administrative
       boundary geometry did not overlap any people in the population raster.
       https://github.com/natcap/invest/issues/1503
+    * Fixed an issue where the output administrative units vector's
+      ``Pund_adm`` and ``Povr_adm`` fields representing undersupplied and
+      oversupplied populations, respectively, had values of 0 when running the
+      model with search radii defined per population group.  The output
+      administrative units vector now has the correct values for these fields,
+      consistent with the user's guide chapter.
+      https://github.com/natcap/invest/issues/1512
 
 3.14.1 (2023-12-18)
 -------------------

src/natcap/invest/urban_nature_access.py

@@ -360,15 +360,23 @@
                             "about": (
                                 "The total population within the "
                                 "administrative unit that is undersupplied "
-                                "with urban nature.")
+                                "with urban nature. If aggregating by "
+                                "population groups, this will be the sum "
+                                "of undersupplied populations across all "
+                                "population groups within this administrative "
+                                "unit.")
                         },
                         "Povr_adm": {
                             "type": "number",
                             "units": u.people,
                             "about": (
                                 "The total population within the "
                                 "administrative unit that is oversupplied "
-                                "with urban nature.")
+                                "with urban nature. If aggregating by "
+                                "population groups, this will be the sum "
+                                "of oversupplied populations across all "
+                                "population groups within this administrative "
+                                "unit.")
                         },
                         "SUP_DEMadm_cap_[POP_GROUP]": {
                             "type": "number",
@@ -1978,14 +1986,18 @@ def _get_zonal_stats(raster_path):
                 feature_id]['sum']
             group_sup_dem_in_region = urban_nature_sup_dem_stats[
                 feature_id]['sum']
+            group_oversupply_in_region = oversupply_stats[feature_id]['sum']
+            group_undersupply_in_region = undersupply_stats[feature_id]['sum']
             stats_by_feature[feature_id][f'SUP_DEMadm_cap_{groupname}'] = (
                 group_sup_dem_in_region / group_population_in_region)
             stats_by_feature[feature_id][f'Pund_adm_{groupname}'] = (
-                undersupply_stats[feature_id]['sum'])
+                group_undersupply_in_region)
             stats_by_feature[feature_id][f'Povr_adm_{groupname}'] = (
-                oversupply_stats[feature_id]['sum'])
+                group_oversupply_in_region)
             sums['supply-demand'][feature_id] += group_sup_dem_in_region
             sums['population'][feature_id] += group_population_in_region
+            sums['oversupply'][feature_id] += group_oversupply_in_region
+            sums['undersupply'][feature_id] += group_undersupply_in_region
 
     for feature_id in feature_ids:
         stats_by_feature[feature_id]['SUP_DEMadm_cap'] = (

tests/test_urban_nature_access.py

@@ -569,10 +569,10 @@ def test_radii_by_pop_group(self):
             'pop_female': attributes[0]['pop_female'],
             'pop_male': attributes[0]['pop_male'],
             'adm_unit_id': 0,
-            'Pund_adm': 0,
+            'Pund_adm': 3991.8271484375,
             'Pund_adm_female': 2235.423095703125,
             'Pund_adm_male': 1756.404052734375,
-            'Povr_adm': 0,
+            'Povr_adm': 1084.1727294921875,
             'Povr_adm_female': 607.13671875,
             'Povr_adm_male': 477.0360107421875,
             'SUP_DEMadm_cap': -17.907799109781322,
@@ -645,10 +645,10 @@ def test_radii_by_pop_group_exponential_kernal(self):
             'pop_female': attributes[0]['pop_female'],
             'pop_male': attributes[0]['pop_male'],
             'adm_unit_id': 0,
-            'Pund_adm': 0,
+            'Pund_adm': 4801.7900390625,
             'Pund_adm_female': 2689.00244140625,
             'Pund_adm_male': 2112.78759765625,
-            'Povr_adm': 0,
+            'Povr_adm': 274.2098693847656,
             'Povr_adm_female': 153.55752563476562,
             'Povr_adm_male': 120.65234375,
             'SUP_DEMadm_cap': -17.907799109781322,