SDAP-441 - Implement SDAP-440 changes to match_spark

CHANGELOG.md

@@ -24,6 +24,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - SDAP-482: Updated Saildrone in situ endpoint in config file
 - SDAP-485: Improved behavior for retrying failed Cassandra inserts when saving matchup results.
 - SDAP-487: Improved result fetch speed for large matchup results by tweaking `doms.doms_data` schema to support querying by primary value id.
+- SDAP-440: Rolled out L2 change to the following algorithms:
+  - SDAP-441: `/match_spark`
 ### Deprecated
 ### Removed
 - SDAP-465: Removed `climatology` directory. 

analysis/webservice/algorithms_spark/Matchup.py

@@ -826,9 +826,9 @@ def tile_to_edge_points(tile):
             data = [tile.data[tuple(idx)]]
 
         edge_point = {
-            'latitude': tile.latitudes[idx[1]],
-            'longitude': tile.longitudes[idx[2]],
-            'time': datetime.utcfromtimestamp(tile.times[idx[0]]).strftime('%Y-%m-%dT%H:%M:%SZ'),
+            'latitude': tile.latitudes[tuple(idx)[-2:]],
+            'longitude': tile.longitudes[tuple(idx)[-2:]],
+            'time': datetime.utcfromtimestamp(tile.times[tuple(idx)[-2:]]).strftime('%Y-%m-%dT%H:%M:%SZ'),
             'source': tile.dataset,
             'platform': 'orbiting satellite',
             'device': None,
@@ -847,7 +847,7 @@ def match_satellite_to_insitu(tile_ids, primary_b, secondary_b, parameter_b, tt_
     if len(tile_ids) == 0:
         return []
 
-    tile_service = tile_service_factory()
+    tile_service = tile_service_factory(desired_projection='swath')
 
     # Determine the spatial temporal extents of this partition of tiles
     tiles_bbox = tile_service.get_bounding_box(tile_ids)
@@ -937,8 +937,8 @@ def match_satellite_to_insitu(tile_ids, primary_b, secondary_b, parameter_b, tt_
             valid_indices = tile.get_indices()
 
             primary_points = np.array([aeqd_proj(
-                tile.longitudes[aslice[2]],
-                tile.latitudes[aslice[1]]
+                tile.longitudes[tuple(aslice)[-2:]],
+                tile.latitudes[tuple(aslice)[-2:]]
             ) for aslice in valid_indices])
             matchup_points.extend(primary_points)
             edge_results.extend(tile_to_edge_points(tile))
@@ -984,7 +984,7 @@ def match_tile_to_point_generator(tile_service, tile_id, m_tree, edge_results, s
     # Get list of indices of valid values
     valid_indices = tile.get_indices()
     primary_points = np.array(
-        [aeqd_proj(tile.longitudes[aslice[2]], tile.latitudes[aslice[1]]) for
+        [aeqd_proj(tile.longitudes[tuple(aslice)[-2:]], tile.latitudes[tuple(aslice)[-2:]]) for
          aslice in valid_indices])
 
     print("%s Time to convert primary points for tile %s" % (str(datetime.now() - the_time), tile_id))
@@ -1003,10 +1003,10 @@ def match_tile_to_point_generator(tile_service, tile_id, m_tree, edge_results, s
             else:
                 data_vals = tile.data[tuple(valid_indices[i])]
             p_nexus_point = NexusPoint(
-                latitude=tile.latitudes[valid_indices[i][1]],
-                longitude=tile.longitudes[valid_indices[i][2]],
+                latitude=tile.latitudes[tuple(valid_indices[i])[-2:]],
+                longitude=tile.longitudes[tuple(valid_indices[i])[-2:]],
                 depth=None,
-                time=tile.times[valid_indices[i][0]],
+                time=tile.times[tuple(valid_indices[i])[-2:]],
                 index=valid_indices[i],
                 data_vals=data_vals
             )