def plot_network(graph, title):
plt.axis('off')
pos = graphviz_layout(graph)
nx.draw_networkx(graph, pos=pos, with_labels=False, **dzcnapy.small_attrs)
depth = max(nx.get_node_attributes(graph, 'generation').values()) + 1
colors = get_colors(depth)
color = [colors[graph.node[n]["generation"]] for n in graph]
dzcnapy.small_attrs["node_color"] = color
patchList = []
for index in range(depth):
data_key = mpatches.Patch(color=colors[index],
label='Generation {}'.format(index))
patchList.append(data_key)
plt.legend(handles=patchList)
dzcnapy.set_extent(pos, plt)
dzcnapy.plot(title, [15, 15], save=True)
G4 = nx.star_graph(20)
G5 = nx.complete_graph(20)
G2 = nx.balanced_tree(2, 5)
G3 = nx.grid_2d_graph(5, 4)
names = ("Linear (path)", "Ring (Cycle)", "Balanced Tree", "Mesh (Grid)",
"Star", "Complete")
graphs = G0, G1, G2, G3, G4, G5
layouts = (graphviz_layout, ) * len(graphs)
for i, (g, name, layout) in enumerate(zip(graphs, names, layouts)):
ax = plt.subplot(3, 2, i + 1)
pos = layout(g)
nx.draw_networkx_edges(g, pos, alpha=0.5, ax=ax, **dzcnapy.small_attrs)
nx.draw_networkx_nodes(g, pos, ax=ax, **dzcnapy.small_attrs)
dzcnapy.set_extent(pos, ax, name)
dzcnapy.plot("synthetic3")
#Generate and draw random networks
G0 = nx.erdors_renyi_graph(50, 0.05)
G1 = nx.connected_watts_strogatz_graph(50, 4, 0.05)
G2 = nx.barabasi_albert_graph(50, 4)
G3 = nx.powerlaw_cluster_graph(50, 4, 0.05)
names = ("Erdos-Renvi (p=0.05)", "Watts-Strogatz (k=4, p=0.5)",
"Barabasi-Albert (k=4)", "Holme-Kim (k=4, p=0.5)")
graphs = G0, G1, G2, G3
layouts = (nx.circular_layout, nx.circular_layout, graphviz_layout,
graphviz_layout)
import networkx as nx, community, csv
import matplotlib.style as style, matplotlib.pyplot as plt
from networkx.drawing.nx_agraph import graphviz_layout
import dzcnapy_plotlib as dzcnapy
F = nx.DiGraph()
F.add_node("C")
F.add_edges_from([("B", "b0"), ("b0", "b1"), ("b1", "B")])
F.add_edges_from([("A", "a0"), ("a0", "a1"), ("a1", "a2"), ("a1", "a3"), ("a3", "A")])
pos = graphviz_layout(F)
nx.draw_networkx(F, pos, **dzcnapy.attrs)
dzcnapy.set_extent(pos, plt)
dzcnapy.plot("abcNwtwork")
G = nx.Graph(
(("Alpha", "Bravo"), ("Bravo", "Charlie"), ("Charlie", "Delta"),
("Charlie", "Echo"), ("Charlie", "Foxtrot"), ("Delta", "Echo"),
("Delta", "Foxtrot"), ("Echo", "Foxtrot"), ("Echo", "Golf"),
("Echo", "Hotel"), ("Foxtrot", "Golf"), ("Foxtrot", "Hotel"),
("Delta", "Hotel"), ("Golf", "Hotel"), ("Delta", "India"),
("Charlie", "India"), ("India", "Juliet"), ("Golf", "Kilo"),
("Alpha", "Kilo"), ("Bravo", "Lima")))
pos = graphviz_layout(G)
core = nx.k_core(G)
crust = nx.k_crust(G)
corona3 = nx.k_corona(G, k=3).nodes()
nx.draw_networkx(G, pos, nodelist=core, **dzcnapy.attrs)
nx.draw_networkx_edges(G, pos, core.edges(), **dzcnapy.tick_attrs)
nx.draw_networkx_edges(G, pos, crust.edges(), **dzcnapy.tick_attrs)
nx.draw_networkx_nodes(G, pos, crust, node_shape='v', **dzcnapy.attrs)
def slice_network(G, T, copy=True):
"""
Remove all edges with weight<T from G or its copy.
"""
F = G.copy() if copy else G
F.remove_edges_from(
(n1, n2) for n1, n2, w in F.edges(data="weight") if w < T)
return F
# Draw different degrees of slicing for a random graph
ergraph = nx.erdos_renyi_graph(100, 0.1)
nx.set_edge_attributes(ergraph, "weight", {(n1, n2): random.random()
for n1, n2 in ergraph.edges()})
pos = graphviz_layout(ergraph)
for i, threshold in enumerate([0, 0.7, 0.8, 0.9, 0.95, 1.0]):
ax = plt.subplot(3, 2, i + 1)
slice_network(ergraph, threshold, copy=False)
nx.draw_networkx_edges(ergraph,
pos,
alpha=0.65,
ax=ax,
**dzcnapy.small_attrs)
nx.draw_networkx_nodes(ergraph, pos, ax=ax, **dzcnapy.small_attrs)
dzcnapy.set_extent(pos, ax, "Threshold={}".format(threshold))
dzcnapy.plot("slicing")
