I. #8 reclassify check for crop_prod_perc

Adding a test as well

src/natcap/invest/crop_production_percentile.py

@@ -321,11 +321,17 @@ def execute(args):
                 _COARSE_YIELD_PERCENTILE_FILE_PATTERN % (
                     crop_name, yield_percentile_id, file_suffix))
             create_coarse_yield_percentile_task = task_graph.add_task(
-                func=pygeoprocessing.reclassify_raster,
+                func=utils._reclassify_raster_op,
                 args=((clipped_climate_bin_raster_path, 1),
                       bin_to_percentile_yield,
                       coarse_yield_percentile_raster_path, gdal.GDT_Float32,
                       _NODATA_YIELD),
+                kwargs={'values_required': True,
+                        'error_details': {
+                            'raster_name': f'{crop_name} Climate Bin',
+                            'column_name': 'climate_bin',
+                            'table_name': (
+                                f'Climate {crop_name} Percentile Yield')}},
                 target_path_list=[coarse_yield_percentile_raster_path],
                 dependent_task_list=[crop_climate_bin_task],
                 task_name='create_coarse_yield_percentile_%s_%s' % (

tests/test_crop_production.py

@@ -157,6 +157,54 @@ class CropProductionTests(unittest.TestCase):
         with self.assertRaises(ValueError):
             crop_production_percentile.execute(args)
 
+    def test_crop_production_percentile_missing_climate_bin(self):
+        """Crop Production: test crop percentile with a missing climate bin."""
+        from natcap.invest import crop_production_percentile
+
+        args = {
+            'workspace_dir': self.workspace_dir,
+            'results_suffix': '',
+            'landcover_raster_path': os.path.join(
+                SAMPLE_DATA_PATH, 'landcover.tif'),
+            'landcover_to_crop_table_path': os.path.join(
+                SAMPLE_DATA_PATH, 'landcover_to_crop_table.csv'),
+            'aggregate_polygon_path': os.path.join(
+                SAMPLE_DATA_PATH, 'aggregate_shape.shp'),
+            'model_data_path': MODEL_DATA_PATH,
+            'n_workers': '-1'
+        }
+
+        # copy model data directory to a temp location so that hard coded
+        # data paths can be altered for this test.
+        tmp_copy_model_data_path = os.path.join(
+            self.workspace_dir, 'tmp_model_data')
+
+        shutil.copytree(MODEL_DATA_PATH, tmp_copy_model_data_path)
+
+        # remove a row from the wheat percentile yield table so that a wheat
+        # climate bin value is missing
+        climate_bin_wheat_table_path = os.path.join(
+           MODEL_DATA_PATH, 'climate_percentile_yield_tables',
+           'wheat_percentile_yield_table.csv')
+
+        bad_climate_bin_wheat_table_path = os.path.join(
+           tmp_copy_model_data_path, 'climate_percentile_yield_tables',
+           'wheat_percentile_yield_table.csv')
+
+        os.remove(bad_climate_bin_wheat_table_path)
+
+        table_df = pandas.read_csv(climate_bin_wheat_table_path)
+        table_df = table_df[table_df['climate_bin'] != 40]
+        table_df.to_csv(bad_climate_bin_wheat_table_path)
+        table_df = None
+
+        args['model_data_path'] = tmp_copy_model_data_path
+        with self.assertRaises(ValueError) as context:
+            crop_production_percentile.execute(args)
+        self.assertTrue(
+            "The missing values found in the wheat Climate Bin raster but not"
+            " the table are: [40]" in str(context.exception))
+
     def test_crop_production_regression_bad_crop(self):
         """Crop Production: test crop regression with a bad crop name."""
         from natcap.invest import crop_production_regression