Add configurations (cat_2019, cat_2020, fr_2019)

S4A.py

@@ -16,7 +16,6 @@
 from itertools import product
 import numpy as np
 import xarray as xr
-import dask
 import netCDF4
 import datasets
 from pathlib import Path
@@ -88,8 +87,9 @@ class S4A(datasets.GeneratorBasedBuilder):
 
     BUILDER_CONFIGS = [
         datasets.BuilderConfig(name="complete", version=VERSION, description="All Sen4AgriNet data."),
-        datasets.BuilderConfig(name="tiny", version=VERSION, description="Just three samples for testing."),
         datasets.BuilderConfig(name="cat_2019", version=VERSION, description="Sen4AgriNet data for Catalonia 2019."),
+        datasets.BuilderConfig(name="cat_2020", version=VERSION, description="Sen4AgriNet data for Catalonia 2020."),
+        datasets.BuilderConfig(name="fr_2019", version=VERSION, description="Sen4AgriNet data for France 2019."),
     ]
 
     DEFAULT_CONFIG_NAME = "complete"
@@ -141,27 +141,36 @@ class S4A(datasets.GeneratorBasedBuilder):
                         downloaded_paths = dl_manager.download(_URL + f'/{year}' + f'/{tile}' + f'/{year}_{tile}_patch_{str(x_i).zfill(2)}_{str(y_i).zfill(2)}.nc')
                         root_paths.append(downloaded_paths)
 
-            return [
-                datasets.SplitGenerator(
-                    name='complete',
-                    # These kwargs will be passed to _generate_examples
-                    gen_kwargs={
-                        "root_paths": root_paths,
-                    },
-                ),
-            ]
-        elif self.config.name == 'tiny':
-            selected_files = ['2019_31TCF_patch_00_11.nc', '2019_31UCP_patch_01_19.nc', '2020_31TDG_patch_11_17.nc']
+        elif self.config.name == 'cat_2019':
+            year = '2019'
+            for tile in CAT_TILES:
+                x, y = PATCH_IDX[year][tile]
+                for x_i in range(x + 1):
+                    for y_i in range(y + 1):
+                        downloaded_paths = dl_manager.download(_URL + f'/{year}' + f'/{tile}' + f'/{year}_{tile}_patch_{str(x_i).zfill(2)}_{str(y_i).zfill(2)}.nc')
+                        root_paths.append(downloaded_paths)
 
-            for file in selected_files:
-                year, tile = file.split('_')[:2]
+        elif self.config.name == 'cat_2020':
+            year = '2020'
+            for tile in CAT_TILES:
+                x, y = PATCH_IDX[year][tile]
+                for x_i in range(x + 1):
+                    for y_i in range(y + 1):
+                        downloaded_paths = dl_manager.download(_URL + f'/{year}' + f'/{tile}' + f'/{year}_{tile}_patch_{str(x_i).zfill(2)}_{str(y_i).zfill(2)}.nc')
+                        root_paths.append(downloaded_paths):
 
-                downloaded_paths = dl_manager.download(_URL + f'/{year}' + f'/{tile}' + f'/{file}')
-                root_paths.append(downloaded_paths)
+        elif self.config.name == 'fr_2019':
+            year = '2019'
+            for tile in FR_TILES:
+                x, y = PATCH_IDX[year][tile]
+                for x_i in range(x + 1):
+                    for y_i in range(y + 1):
+                        downloaded_paths = dl_manager.download(_URL + f'/{year}' + f'/{tile}' + f'/{year}_{tile}_patch_{str(x_i).zfill(2)}_{str(y_i).zfill(2)}.nc')
+                        root_paths.append(downloaded_paths):
 
-            return [
+        return [
                 datasets.SplitGenerator(
-                    name='tiny',
+                    name='self.config.name',
                     # These kwargs will be passed to _generate_examples
                     gen_kwargs={
                         "root_paths": root_paths,
@@ -173,20 +182,20 @@ class S4A(datasets.GeneratorBasedBuilder):
     # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
     def _generate_examples(self, root_paths):
         for file in root_paths:
-            data = xr.open_dataset(file, chunks=-1, engine='netcdf4')
+            netcdf = netCDF4.Dataset(file)
 
             res = {
-                "patch_full_name": data.patch_full_name,
-                "patch_year": data.patch_year,
-                "patch_name": data.patch_name,
-                "patch_country_code": data.patch_country_code,
-                "patch_tile": data.patch_tile
+                "patch_full_name": netcdf.patch_full_name,
+                "patch_year": netcdf.patch_year,
+                "patch_name": netcdf.patch_name,
+                "patch_country_code": netcdf.patch_country_code,
+                "patch_tile": netcdf.patch_tile
             }
 
             time_recorded = False
 
             for variable in ['B01', 'B02', 'B03', 'B04', 'B05', 'B06', 'B07', 'B08', 'B09', 'B10', 'B11', 'B12', 'B8A', 'labels', 'parcels']:
-                v = xr.open_dataset(file, chunks=-1, engine='netcdf4', group=variable)
+                v = xr.open_dataset(xr.backends.NetCDF4DataStore(netcdf[variable]))
                 if not time_recorded:
                     res['timestamp'] = (v.time.values.astype(np.int64) // 10 ** 9).tolist()
                     time_recorded = True