def match_tile_to_point_generator()

in analysis/webservice/algorithms_spark/MatchupDoms.py [0:0]

• 42 lines of code
• 10 McCabe index (conditional complexity)

def match_tile_to_point_generator(tile_service, tile_id, m_tree, edge_results, search_domain_bounding_wkt,
                                  search_parameter, radius_tolerance, aeqd_proj):
    from nexustiles.model.nexusmodel import NexusPoint
    from webservice.algorithms_spark.MatchupDoms import DomsPoint  # Must import DomsPoint or Spark complains

    # Load tile
    try:
        the_time = datetime.now()
        tile = tile_service.mask_tiles_to_polygon(wkt.loads(search_domain_bounding_wkt),
                                                  tile_service.find_tile_by_id(tile_id))[0]
        print("%s Time to load tile %s" % (str(datetime.now() - the_time), tile_id))
    except IndexError:
        # This should only happen if all measurements in a tile become masked after applying the bounding polygon
        print('Tile is empty after masking spatially. Skipping this tile.')
        return

    # Convert valid tile lat,lon tuples to UTM tuples
    the_time = datetime.now()
    # 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
         aslice in valid_indices])

    print("%s Time to convert primary points for tile %s" % (str(datetime.now() - the_time), tile_id))

    a_time = datetime.now()
    p_tree = spatial.cKDTree(primary_points, leafsize=30)
    print("%s Time to build primary tree" % (str(datetime.now() - a_time)))

    a_time = datetime.now()
    matched_indexes = p_tree.query_ball_tree(m_tree, radius_tolerance)
    print("%s Time to query primary tree for tile %s" % (str(datetime.now() - a_time), tile_id))
    for i, point_matches in enumerate(matched_indexes):
        if len(point_matches) > 0:
            if tile.is_multi:
                data_vals = [tile_data[tuple(valid_indices[i])] for tile_data in tile.data]
            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]],
                depth=None,
                time=tile.times[valid_indices[i][0]],
                index=valid_indices[i],
                data_vals=data_vals
            )

            p_doms_point = DomsPoint.from_nexus_point(p_nexus_point, tile=tile)
            for m_point_index in point_matches:
                m_doms_point = DomsPoint.from_edge_point(edge_results[m_point_index])
                yield p_doms_point, m_doms_point