Exemplo n.º 1
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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"
Exemplo n.º 2
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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"
Exemplo n.º 3
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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"
Exemplo n.º 4
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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"
Exemplo n.º 5
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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"
Exemplo n.º 6
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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"
Exemplo n.º 7
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# 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?
Exemplo n.º 8
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        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)
Exemplo n.º 9
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                    "-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)
Exemplo n.º 10
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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)