analysis/webservice/algorithms_spark/Matchup.py [761:804]:
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            'device': None,
            'fileurl': tile.granule,
            'variables': tile.variables,
            'var_values': data
        }
        edge_points.append(edge_point)
    return edge_points


def match_satellite_to_insitu(tile_ids, primary_b, secondary_b, parameter_b, tt_b, rt_b, platforms_b,
                              bounding_wkt_b, depth_min_b, depth_max_b, tile_service_factory):
    the_time = datetime.now()
    tile_ids = list(tile_ids)
    if len(tile_ids) == 0:
        return []

    tile_service = tile_service_factory()

    # Determine the spatial temporal extents of this partition of tiles
    tiles_bbox = tile_service.get_bounding_box(tile_ids)
    tiles_min_time = tile_service.get_min_time(tile_ids)
    tiles_max_time = tile_service.get_max_time(tile_ids)

    # Increase spatial extents by the radius tolerance
    matchup_min_lon, matchup_min_lat = add_meters_to_lon_lat(tiles_bbox.bounds[0], tiles_bbox.bounds[1],
                                                             -1 * rt_b.value)
    matchup_max_lon, matchup_max_lat = add_meters_to_lon_lat(tiles_bbox.bounds[2], tiles_bbox.bounds[3], rt_b.value)

    # Don't go outside of the search domain
    search_min_x, search_min_y, search_max_x, search_max_y = wkt.loads(bounding_wkt_b.value).bounds
    matchup_min_lon = max(matchup_min_lon, search_min_x)
    matchup_min_lat = max(matchup_min_lat, search_min_y)
    matchup_max_lon = min(matchup_max_lon, search_max_x)
    matchup_max_lat = min(matchup_max_lat, search_max_y)

    # Find the centroid of the matchup bounding box and initialize the projections
    matchup_center = box(matchup_min_lon, matchup_min_lat, matchup_max_lon, matchup_max_lat).centroid.coords[0]
    aeqd_proj = pyproj.Proj(proj='aeqd', lon_0=matchup_center[0], lat_0=matchup_center[1])

    # Increase temporal extents by the time tolerance
    matchup_min_time = tiles_min_time - tt_b.value
    matchup_max_time = tiles_max_time + tt_b.value
    print("%s Time to determine spatial-temporal extents for partition %s to %s" % (
        str(datetime.now() - the_time), tile_ids[0], tile_ids[-1]))
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analysis/webservice/algorithms_spark/MatchupDoms.py [606:649]:
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            'device': None,
            'fileurl': tile.granule,
            'variables': tile.variables,
            'var_values': data
        }
        edge_points.append(edge_point)
    return edge_points


def match_satellite_to_insitu(tile_ids, primary_b, secondary_b, parameter_b, tt_b, rt_b, platforms_b,
                              bounding_wkt_b, depth_min_b, depth_max_b, tile_service_factory):
    the_time = datetime.now()
    tile_ids = list(tile_ids)
    if len(tile_ids) == 0:
        return []

    tile_service = tile_service_factory()

    # Determine the spatial temporal extents of this partition of tiles
    tiles_bbox = tile_service.get_bounding_box(tile_ids)
    tiles_min_time = tile_service.get_min_time(tile_ids)
    tiles_max_time = tile_service.get_max_time(tile_ids)

    # Increase spatial extents by the radius tolerance
    matchup_min_lon, matchup_min_lat = add_meters_to_lon_lat(tiles_bbox.bounds[0], tiles_bbox.bounds[1],
                                                             -1 * rt_b.value)
    matchup_max_lon, matchup_max_lat = add_meters_to_lon_lat(tiles_bbox.bounds[2], tiles_bbox.bounds[3], rt_b.value)

    # Don't go outside of the search domain
    search_min_x, search_min_y, search_max_x, search_max_y = wkt.loads(bounding_wkt_b.value).bounds
    matchup_min_lon = max(matchup_min_lon, search_min_x)
    matchup_min_lat = max(matchup_min_lat, search_min_y)
    matchup_max_lon = min(matchup_max_lon, search_max_x)
    matchup_max_lat = min(matchup_max_lat, search_max_y)

    # Find the centroid of the matchup bounding box and initialize the projections
    matchup_center = box(matchup_min_lon, matchup_min_lat, matchup_max_lon, matchup_max_lat).centroid.coords[0]
    aeqd_proj = pyproj.Proj(proj='aeqd', lon_0=matchup_center[0], lat_0=matchup_center[1])

    # Increase temporal extents by the time tolerance
    matchup_min_time = tiles_min_time - tt_b.value
    matchup_max_time = tiles_max_time + tt_b.value
    print("%s Time to determine spatial-temporal extents for partition %s to %s" % (
        str(datetime.now() - the_time), tile_ids[0], tile_ids[-1]))
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