def networker_run_compare(cfg, known_results_file, output_dir):
nwk = networker_runner.NetworkerRunner(cfg, output_dir)
nwk.validate()
nwk.run()
# compare this run against existing results
test_geo = nio.read_shp_geograph(os.path.join(output_dir, "edges.shp"),
simplify=False)
known_geo = nio.read_shp_geograph(known_results_file, simplify=False)
# compare sets of edges
test_edges = get_rounded_edge_sets(test_geo, round_precision=8)
known_edges = get_rounded_edge_sets(known_geo, round_precision=8)
assert test_edges == known_edges, \
"edges in test do not match known results"
def networkplanner_run_compare(cfg, known_results_file, output_dir):
nwk_p = networkplanner_runner.NetworkPlannerRunner(cfg, output_dir)
nwk_p.validate()
nwk_p.run()
# compare this run against existing results
test_geo = nio.read_shp_geograph(os.path.join(output_dir,
"networks-proposed.shp"),
simplify=False)
known_geo = nio.read_shp_geograph(known_results_file, simplify=False)
# compare sets of edges
test_edges = get_rounded_edge_sets(test_geo, round_precision=8)
known_edges = get_rounded_edge_sets(known_geo, round_precision=8)
assert test_edges == known_edges, \
"edges in test do not match known results"
def test_dataset_store_to_geograph():
"""
make sure we can go from shp to geograph to dataset_store
"""
data_dir = os.path.join("data", "pop_100")
test_geo = nio.read_shp_geograph(os.path.join(data_dir,
"networks-proposed.shp"),
simplify=False)
dataset = dataset_store.load(os.path.join(data_dir, "dataset.db"))
dataset_geo = networkplanner_runner.dataset_store_to_geograph(dataset)
test_edges = test_geo.get_coord_edge_set()
dataset_edges = dataset_geo.get_coord_edge_set()
assert test_edges == dataset_edges, \
"edges in test do not match dataset results"
def test_dataset_store_to_geograph():
"""
make sure we can go from shp to geograph to dataset_store
"""
data_dir = os.path.join("data", "pop_100")
test_geo = nio.read_shp_geograph(os.path.join(data_dir,
"networks-proposed.shp"),
simplify=False)
dataset = dataset_store.load(os.path.join(data_dir, "dataset.db"))
dataset_geo = networkplanner_runner.dataset_store_to_geograph(dataset)
test_edges = test_geo.get_coord_edge_set()
dataset_edges = dataset_geo.get_coord_edge_set()
assert test_edges == dataset_edges, \
"edges in test do not match dataset results"
def test_line_subgraph_intersection():
"""
Test case where precision and odd geometry issues occur
"""
# initialize network, nodes
existing_net_file = os.path.join("data", "katsina", "existing.shp")
demand_nodes_file = os.path.join("data", "katsina", "metrics.csv")
network = nio.read_shp_geograph(existing_net_file, simplify=False)
network.coords = {
"g-" + str(n): network.coords[n]
for n in network.nodes()
}
new_labels = ["g-" + str(n) for n in network.nodes()]
nx.relabel_nodes(network,
dict(zip(network.nodes(), new_labels)),
copy=False)
nodes = nio.read_csv_geograph(demand_nodes_file, "x", "y")
# populate disjoint set of subgraphs
subgraphs = UnionFind()
# only one connected component, so just add all nodes associated
# with first node
net_nodes = network.nodes()
parent = net_nodes[0]
subgraphs.add_component(parent, budget=0)
for node in net_nodes[1:]:
subgraphs.add_component(node, budget=0)
subgraphs.union(parent, node, 0)
# now find projections onto grid
rtree = network.get_rtree_index()
projected = network.project_onto(nodes, rtree_index=rtree)
projected.remove_nodes_from(network)
assert len(projected.edges()) == 1, "should only be 1 projected edge"
edge = projected.edges()[0]
p1, p2 = projected.coords[edge[0]], projected.coords[edge[1]]
invalid, subgraphs = gm.line_subgraph_intersection(subgraphs, rtree, p1,
p2)
assert not invalid, "edge should intersect network only once"
def test_line_subgraph_intersection():
"""
Test case where precision and odd geometry issues occur
"""
# initialize network, nodes
existing_net_file = os.path.join("data", "katsina", "existing.shp")
demand_nodes_file = os.path.join("data", "katsina", "metrics.csv")
network = nio.read_shp_geograph(existing_net_file, simplify=False)
network.coords = {"g-" + str(n): network.coords[n] for n in network.nodes()}
new_labels = ["g-" + str(n) for n in network.nodes()]
nx.relabel_nodes(network,
dict(zip(network.nodes(), new_labels)),
copy=False)
nodes = nio.read_csv_geograph(demand_nodes_file, "x", "y")
# populate disjoint set of subgraphs
subgraphs = UnionFind()
# only one connected component, so just add all nodes associated
# with first node
net_nodes = network.nodes()
parent = net_nodes[0]
subgraphs.add_component(parent, budget=0)
for node in net_nodes[1:]:
subgraphs.add_component(node, budget=0)
subgraphs.union(parent, node, 0)
# now find projections onto grid
rtree = network.get_rtree_index()
projected = network.project_onto(nodes, rtree_index=rtree)
projected.remove_nodes_from(network)
assert len(projected.edges()) == 1, "should only be 1 projected edge"
edge = projected.edges()[0]
p1, p2 = projected.coords[edge[0]], projected.coords[edge[1]]
invalid, subgraphs = gm.line_subgraph_intersection(subgraphs,
rtree,
p1, p2)
assert not invalid, "edge should intersect network only once"
# setup log
logger = logging.getLogger('networker')
logger.info("networker %s (Python %s)" %
(networker.__version__, '.'.join(map(str, sys.version_info[:3]))))
parser = argparse.ArgumentParser(description="Clean network and report it")
parser.add_argument("network_filename", help="network to be cleaned")
parser.add_argument("--output_directory", "-o", \
default=".", \
help="directory where network output files will be written")
args = parser.parse_args()
net = nio.read_shp_geograph(args.network_filename, simplify=False)
num_found = 0
for zero_len_edge in net.find_zero_len_edges():
node0 = zero_len_edge[0]
node1 = zero_len_edge[1]
num_found += 1
logger.warn("found zero length edge ({},{}), with coords ({},{})".\
format(node0, node1, net.coords[node0], net.coords[node1]))
net.remove_edge(node0, node1)
logger.info("found {} total zero length edges".format(num_found))
#TODO: Additional checks?
dest="spherical_accuracy", action="store_true", default=False,
help="connect nodes to edges as though on a sphere (ignored unprojected inputs)")
parser.add_argument("--output_directory", "-o", \
default=".", \
help="directory where all output files will be written")
args = parser.parse_args()
nodes = nio.read_csv_geograph(args.node_filename,
args.x_column,
args.y_column)
net = None
if len(args.network_filename) > 5 and args.network_filename[-5:] == '.json':
net = nio.read_json_geograph(args.network_filename)
else:
net = nio.read_shp_geograph(args.network_filename, simplify=False)
# relabel nodes/coords so that merge can work
prefix = "net-"
nx.relabel_nodes(net,
{n: prefix + str(n) for n in net.nodes()}, copy=False)
net.coords = {prefix + str(n): c for n, c in
net.coords.items()}
def project_helper(use_rtree, spherical_accuracy):
if use_rtree:
logger.info("building rtree...")
rtree = net.get_rtree_index()
logger.info("projecting nodes...")
return net.project_onto(nodes, rtree_index=rtree,
spherical_accuracy=spherical_accuracy)
"-n",
type=int,
default=100,
help="size of nodes in pixels")
parser.add_argument("--output_file", "-o", \
default="network.png", \
help="file to write image to")
args = parser.parse_args()
nets = []
for net_file in args.network_files:
if len(net_file) > 5 and net_file[-5:] == '.json':
nets.append(nio.read_json_geograph(net_file))
else:
nets.append(nio.read_shp_geograph(net_file, simplify=False))
# do the rendering and save to file
import matplotlib
matplotlib.use('Agg')
from matplotlib import pyplot as plt
plt.figure(figsize=(8, 8))
for net in nets:
utils.draw_geograph(net, node_size=args.node_size)
# don't render axes
cur_axes = plt.gca()
cur_axes.set_frame_on(False)
cur_axes.axes.get_xaxis().set_visible(False)
cur_axes.axes.get_yaxis().set_visible(False)
parser.add_argument("network_files", metavar="NETWORK_FILE", type=str,
nargs="+", help="network to be rendered (.shp OR .json)")
parser.add_argument("--node_size", "-n", type=int, default=100,
help="size of nodes in pixels")
parser.add_argument("--output_file", "-o", \
default="network.png", \
help="file to write image to")
args = parser.parse_args()
nets = []
for net_file in args.network_files:
if len(net_file) > 5 and net_file[-5:] == '.json':
nets.append(nio.read_json_geograph(net_file))
else:
nets.append(nio.read_shp_geograph(net_file, simplify=False))
# do the rendering and save to file
import matplotlib
matplotlib.use('Agg')
from matplotlib import pyplot as plt
plt.figure(figsize=(8,8))
for net in nets:
utils.draw_geograph(net, node_size=args.node_size)
# don't render axes
cur_axes = plt.gca()
cur_axes.set_frame_on(False)
cur_axes.axes.get_xaxis().set_visible(False)
cur_axes.axes.get_yaxis().set_visible(False)