type=float,
metavar="x",
default=10,
dest="tail_length",
help="Maximum length/width for " "tails Default %(default)f",
)
args = parser.parse_args()
logging.basicConfig()
log.setLevel(logging.INFO)
# Get generator of clustered nodes
# We keep these in OSRM units for now.
clustered_nodes = itertools.groupby(
topotools.read_clusters(args.input, args.bbox, scale=False), operator.attrgetter("clust")
)
# keep a list of nodes we orphan
orphans = []
good_nodes = []
for clustidx, nodes in clustered_nodes:
node_list = list(nodes)
points = np.array([(x.lon, x.lat) for x in node_list], dtype=float)
if len(node_list) < 20:
log.info("Cluster has less than 20 nodes, orphaning")
orphans.extend(node_list)
continue
log.setLevel(logging.INFO)
with open(args.hulls, 'r') as inputfd:
features = geojson.load(inputfd)
cluster_features = {}
for feature in features['features']:
cluster_id = feature['properties']['clust']
cluster_features[cluster_id] = asShape(feature['geometry'])
log.info("Loaded %i hulls", len(cluster_features))
# Get generator of clustered nodes
# We keep these in OSRM units for now.
clustered_node_iters = itertools.groupby(
topotools.read_clusters(args.input, args.bbox, scale=False),
operator.attrgetter('clust')
)
# Get the ID, the hull (if it exists), and the nodes for each cluster
clustered_nodes = (
(clust, cluster_features.get(clust), list(nodes))
for clust, nodes in clustered_node_iters
)
def find_edge_nodes(fargs):
""" Find nodes are near the edge of the hull"""
cluster, cluster_hull, nodes = fargs
# There is no hull for this community, it's been deleted.
if cluster_hull is None:
log.error("Missing hull, keeping all nodes in cluster %i",
parser.add_argument('--AND', dest="and_shapes", nargs='+', type=str,
default=[], metavar='file.shp',
help='List of .shp files to '
'AND the output shapes with')
parser.add_argument('--seed', default=1, type=int, help='random seed')
args = parser.parse_args()
logging.basicConfig()
log.setLevel(logging.INFO)
random.seed(args.seed)
clustered_nodes = itertools.groupby(
topotools.read_clusters(args.input, args.bbox),
operator.attrgetter('clust')
)
pruned_nodes = []
for clustidx, nodes in clustered_nodes:
log.info("Pruning interior of cluster %i", clustidx)
draw = None
if args.drawprune and clustidx in args.drawprune:
draw = 'prune_%i.png' % clustidx
pruned = topotools.voronoi_prune_region(nodes, 25, draw=draw)
pruned_nodes.extend(pruned)
pruned_nodes.sort(key=operator.attrgetter('clust'))
