changed the spatial aggregation for globvapour and snow area extent p…

…rovider to use the cython aggregator.

src/cablab/providers/globvapour.py

@@ -4,7 +4,7 @@
 import netCDF4
 from cablab import BaseCubeSourceProvider
 from cablab.util import NetCDFDatasetCache, aggregate_images
-from skimage.transform import resize
+import cablab.resize as resize
 
 VAR_NAME = 'tcwv_res'
 
@@ -51,17 +51,19 @@ def compute_variable_images_from_sources(self, index_to_weight):
             i = next(iter(new_indices))
             file, time_index = self._get_file_and_time_index(i)
             dataset = self.dataset_cache.get_dataset(file)
-            globvapour = resize(dataset.variables[VAR_NAME][time_index, :, :], (720, 1440), preserve_range=True,
-                                order=3)
+            globvapour = dataset.variables[VAR_NAME]
+            _, lat_size, lon_size = globvapour.shape
+            globvapour = resize.resize(lon_size, lat_size, globvapour[time_index, :, :], 1440, 720, order=3)
         else:
             images = [None] * len(new_indices)
             weights = [None] * len(new_indices)
             j = 0
             for i in new_indices:
                 file, time_index = self._get_file_and_time_index(i)
                 dataset = self.dataset_cache.get_dataset(file)
-                variable = resize(dataset.variables[VAR_NAME][time_index, :, :], (720, 1440), preserve_range=True,
-                                  order=3)
+                variable = dataset.variables[VAR_NAME]
+                _, lat_size, lon_size = variable.shape
+                variable = resize.resize(lon_size, lat_size, variable[time_index, :, :], 1440, 720, order=3)
                 images[j] = variable
                 weights[j] = index_to_weight[i]
                 j += 1
@@ -86,9 +88,9 @@ def _init_source_time_ranges(self):
         dir_names = os.listdir(self.dir_path)
 
         for dir_name in dir_names:
-            file_names = os.listdir(os.path.join(self.dir_path,dir_name))
+            file_names = os.listdir(os.path.join(self.dir_path, dir_name))
             for file_name in file_names:
-                file = os.path.join(self.dir_path,dir_name,file_name)
+                file = os.path.join(self.dir_path, dir_name, file_name)
                 dataset = self.dataset_cache.get_dataset(file)
                 time = dataset.variables['time']
                 dates1 = netCDF4.num2date(time[:], 'days since 1970-01-01 00:00:00', calendar='gregorian')
@@ -103,4 +105,4 @@ def _init_source_time_ranges(self):
     @staticmethod
     def _last_day_of_month(any_day):
         next_month = any_day.replace(day=28) + timedelta(days=4)
-        return next_month - timedelta(days=next_month.day)
+        return next_month - timedelta(days=next_month.day)

src/cablab/providers/snow_area_extent.py

@@ -7,6 +7,7 @@
 from cablab import BaseCubeSourceProvider
 from cablab.util import NetCDFDatasetCache
 from skimage.measure import block_reduce
+import cablab.resize as resize
 
 VAR_NAME = 'MFSC'
 
@@ -56,7 +57,7 @@ def compute_variable_images_from_sources(self, index_to_weight):
             snow_area_extent.filled(numpy.nan)
         else:
             weight_sum = 0.0
-            snow_area_extent_sum = numpy.zeros((18000, 36000), dtype=numpy.float32)
+            snow_area_extent_sum = numpy.zeros((18000, 36000), dtype=numpy.float64)
             for i in new_indices:
                 weight = index_to_weight[i]
                 file, time_index = self._get_file_and_time_index(i)
@@ -75,12 +76,8 @@ def compute_variable_images_from_sources(self, index_to_weight):
             raise ValueError('illegal downscale factor, '
                              'the downscale factor has to be an integer value.')
 
-        print(snow_area_extent[snow_area_extent == numpy.nan])
-
-        snow_area_extent = block_reduce(snow_area_extent, (latitude_downscale_factor, longitude_downscale_factor),
-                                        func=numpy.ma.mean)
-
-        print(snow_area_extent[snow_area_extent == numpy.nan])
+        snow_area_extent = resize.resize(lon_size, lat_size, snow_area_extent, self.cube_config.grid_width,
+                                         self.cube_config.grid_height)
 
         return {VAR_NAME: snow_area_extent}
 

test/providers/test_snow_area_extent.py

@@ -46,7 +46,7 @@ def test_temporal_coverage(self):
     def test_get_images(self):
         provider = SnowAreaExtentProvider(CubeConfig(), SOURCE_DIR)
         provider.prepare()
-        images = provider.compute_variable_images(datetime(2005, 1, 1), datetime(2005, 1, 9))
+        images = provider.compute_variable_images(datetime(2003, 1, 1), datetime(2003, 2, 11))
         self.assertIsNotNone(images)
         self.assertTrue('MFSC' in images)
         image = images['MFSC']
@@ -57,7 +57,7 @@ def test_get_images(self):
     def test_get_images_from_single_time_period(self):
         provider = SnowAreaExtentProvider(CubeConfig(), SOURCE_DIR)
         provider.prepare()
-        images = provider.compute_variable_images(datetime(2003, 1, 1), datetime(2003, 1, 9))
+        images = provider.compute_variable_images(datetime(2003, 1, 1), datetime(2003, 1, 31))
         self.assertIsNotNone(images)
         self.assertTrue('MFSC' in images)
         image = images['MFSC']