本文整理汇总了Python中networkx.draw_networkx_edge_labels方法的典型用法代码示例。如果您正苦于以下问题:Python networkx.draw_networkx_edge_labels方法的具体用法?Python networkx.draw_networkx_edge_labels怎么用?Python networkx.draw_networkx_edge_labels使用的例子?那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类networkx
的用法示例。
在下文中一共展示了networkx.draw_networkx_edge_labels方法的15个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: plot_alerts
# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import draw_networkx_edge_labels [as 别名]
def plot_alerts(_g, _bank_accts, _output_png):
bank_ids = _bank_accts.keys()
cmap = plt.get_cmap("tab10")
pos = nx.nx_agraph.graphviz_layout(_g)
plt.figure(figsize=(12.0, 8.0))
plt.axis('off')
for i, bank_id in enumerate(bank_ids):
color = cmap(i)
members = _bank_accts[bank_id]
nx.draw_networkx_nodes(_g, pos, members, node_size=300, node_color=color, label=bank_id)
nx.draw_networkx_labels(_g, pos, {n: n for n in members}, font_size=10)
edge_labels = nx.get_edge_attributes(_g, "label")
nx.draw_networkx_edges(_g, pos)
nx.draw_networkx_edge_labels(_g, pos, edge_labels, font_size=6)
plt.legend(numpoints=1)
plt.subplots_adjust(left=0, right=1, bottom=0, top=1)
plt.savefig(_output_png, dpi=120)
示例2: plot
# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import draw_networkx_edge_labels [as 别名]
def plot(self, file_path: str):
try:
import matplotlib.pyplot as plt
except ImportError as err:
raise('matplotlib not installed. Failed at: {}', err)
try:
pos = nx.nx_agraph.graphviz_layout(self.directed)
nx.draw(
self.directed,
pos=pos,
node_size=1200,
node_color='lightblue',
linewidths=0.25,
font_size=8,
font_weight='bold',
with_labels=True,
dpi=5000
)
# edge_labels = nx.get_edge_attributes(self.directed, name='attr_dict')
# nx.draw_networkx_edge_labels(self.directed, pos=pos, edge_labels=edge_labels)
plt.savefig(file_path)
except IOError as err:
raise('Could not create plot image: {}', err)
示例3: draw_wstate_tree
# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import draw_networkx_edge_labels [as 别名]
def draw_wstate_tree(svm):
import matplotlib.pyplot as plt
import networkx as nx
from networkx.drawing.nx_agraph import write_dot, graphviz_layout
G = nx.DiGraph()
pending_list = [svm.root_wstate]
while len(pending_list):
root = pending_list.pop()
for trace, children in root.trace_to_children.items():
for c in children:
G.add_edge(repr(root), repr(c), label=trace)
pending_list.append(c)
# pos = nx.spring_layout(G)
pos = graphviz_layout(G, prog='dot')
edge_labels = nx.get_edge_attributes(G, 'label')
nx.draw(G, pos)
nx.draw_networkx_edge_labels(G, pos, edge_labels, font_size=8)
nx.draw_networkx_labels(G, pos, font_size=10)
plt.show()
示例4: print_graph_nx
# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import draw_networkx_edge_labels [as 别名]
def print_graph_nx(vertices, edges, print_dist=False):
import networkx as nx
G=nx.DiGraph()
labels = []
for v in vertices:
G.add_node(v)
for v in vertices:
for e in edges:
G.add_edge(e[0], e[1], weight=int(e[2]))
#labels += [(e[0], e[1]), e[2]]
print("Nodes of graph: ")
print(G.nodes())
print("Edges of graph: ")
print(G.edges())
nx.draw(G, with_labels=True, node_color='y')
#nx.draw_networkx_edge_labels(G,labels)
plt.savefig("simulation_graph.png") # save as png
plt.show()
示例5: draw_graph
# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import draw_networkx_edge_labels [as 别名]
def draw_graph(graph, output):
"""If matplotlib is available, draw the given graph to output file"""
try:
layout = nx.spring_layout(graph)
metrics = {
(src, dst): data['metric']
for src, dst, data in graph.edges_iter(data=True)
}
nx.draw_networkx_edge_labels(graph, layout, edge_labels=metrics)
nx.draw(graph, layout, node_size=20)
nx.draw_networkx_labels(graph, layout,
labels={n: n for n in graph})
if os.path.exists(output):
os.unlink(output)
plt.savefig(output)
plt.close()
log.debug('Graph of %d nodes saved in %s', len(graph), output)
except:
pass
示例6: draw_graph
# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import draw_networkx_edge_labels [as 别名]
def draw_graph(self):
nx.draw_shell(self.G, with_labels=True, font_weight='bold')
# pos = graphviz_layout(self.G)
# plt.axis('off')
# nx.draw_networkx_nodes(self.G,pos,node_color='g',alpha = 0.8)
# nx.draw_networkx_edges(self.G,pos,edge_color='b',alpha = 0.6)
# nx.draw_networkx_edge_labels(self.G,pos,edge_labels = \
# nx.get_edge_attributes(self.G,'weight'))
# nx.draw_networkx_labels(self.G,pos) # node lables
plt.savefig('graph.png')
示例7: _draw_edge_labels
# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import draw_networkx_edge_labels [as 别名]
def _draw_edge_labels(self, edge_labels, **kwargs):
pos = kwargs.pop('pos', self._pos)
return nx.draw_networkx_edge_labels(self._G, pos, edge_labels=edge_labels, **kwargs)
示例8: draw_and_save_topology
# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import draw_networkx_edge_labels [as 别名]
def draw_and_save_topology(graph: nx.Graph, edge_labels: List[Dict[Tuple[str, str], str]]) -> None:
plt.figure(1, figsize=(12, 12))
pos = nx.spring_layout(graph)
nx.draw_networkx(graph, pos, node_size=1300, node_color='orange')
nx.draw_networkx_edge_labels(graph, pos, edge_labels=edge_labels[0], label_pos=0.8)
nx.draw_networkx_edge_labels(graph, pos, edge_labels=edge_labels[1], label_pos=0.2)
filename = "topology.png"
plt.savefig(filename)
logger.info("The network topology diagram has been saved to %r", filename)
示例9: visualize
# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import draw_networkx_edge_labels [as 别名]
def visualize(self):
# import matplotlib.pyplot as plt
pos = nx.spring_layout(self.graph_state)
edge_labels = {e: self.graph_state.edges[e]['rel'] for e in self.graph_state.edges}
print(edge_labels)
nx.draw_networkx_edge_labels(self.graph_state, pos, edge_labels)
nx.draw(self.graph_state, pos=pos, with_labels=True, node_size=200, font_size=10)
#plt.show()
示例10: _plot_graph
# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import draw_networkx_edge_labels [as 别名]
def _plot_graph(graph, axis, weights=None, display_edge_labels=True):
"""Plot graph using networkx."""
pos = nx.circular_layout(graph)
nx.draw_circular(graph, with_labels=True, node_size=600, alpha=1.0,
ax=axis, node_color='Gainsboro', hold=True, font_size=14,
font_weight='bold')
if display_edge_labels:
edge_labels = nx.get_edge_attributes(graph, weights)
nx.draw_networkx_edge_labels(graph, pos, edge_labels=edge_labels,
font_size=13) # font_weight='bold'
示例11: plot_mute_graph
# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import draw_networkx_edge_labels [as 别名]
def plot_mute_graph():
"""Plot MuTE example network.
Network of 5 AR-processes, which is used as an example the paper
on the MuTE toolbox (Montalto, PLOS ONE, 2014, eq. 14). The
network consists of five autoregressive (AR) processes with model
orders 2 and les and the following (non-linear) couplings:
>>> 0 -> 1, u = 2
>>> 0 -> 2, u = 3
>>> 0 -> 3, u = 2 (non-linear)
>>> 3 -> 4, u = 1
>>> 4 -> 3, u = 1
Returns:
Figure handle
Figure object from the matplotlib package
"""
graph = nx.DiGraph()
graph.add_nodes_from(np.arange(5))
# graph.add_edges_from([(0, 1), (0, 2), (0, 3), (3, 4), (4, 3)])
graph.add_weighted_edges_from([(0, 1, 2), (0, 2, 3), (0, 3, 2), (3, 4, 1),
(4, 3, 1)], weight='delay')
pos = {
0: np.array([1, 1]),
1: np.array([0, 2]),
2: np.array([0, 0]),
3: np.array([2, 1]),
4: np.array([3, 1]),
}
fig = plt.figure()
nx.draw(graph, pos=pos, with_labels=True, node_size=900, alpha=1.0,
node_color='cadetblue', font_weight='bold',
edge_color=['r', 'k', 'r', 'k', 'k'], hold=True)
nx.draw_networkx_edge_labels(graph, pos=pos)
plt.text(2, 0.1, 'non-linear interaction in red')
# see here for an example on how to plot edge labels:
# http://stackoverflow.com/questions/10104700/how-to-set-networkx-edge-labels-offset-to-avoid-label-overlap
return fig
示例12: showTask
# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import draw_networkx_edge_labels [as 别名]
def showTask(task, root="ROOT()", filename="task.dot"):
import matplotlib.pyplot as plt
g = nx.DiGraph()
nodes = [root]
visited = set()
nodelist = []
print(root)
print(task.nodeSummary())
while len(nodes) > 0:
node = nodes.pop()
visited.add(node)
children = task.children[node]
print("NODE =", node, "CHILDREN =")
weights = task.weights[node]
if len(weights) > 0:
for child, wt in zip(children, weights):
print("\t",child,"weight =", wt)
g.add_edge(node, child, weight=int(wt))
nodelist.append(child)
if child not in visited:
print("\t\tadding", child)
nodes.append(child)
elif len(children) > 0:
raise RuntimeError('weights not initialized')
pos = nx.nx_agraph.graphviz_layout(g, prog="dot")
nx.draw_networkx_edges(g, pos, width=1.0, alpha=1., arrows=False)
nx.draw(g, pos, prog='dot', node_size=1000, nodelist=nodelist,
width=1.0, alpha=1., arrows=True, with_labels=True,)
labels = nx.get_edge_attributes(g,'weight')
nx.draw_networkx_edge_labels(g,pos,edge_labels=labels)
#a = nx.nx_agraph.to_agraph(g)
#a.draw('ex.png', prog='dot')
plt.axis('off')
plt.show()
示例13: plot_graph
# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import draw_networkx_edge_labels [as 别名]
def plot_graph(G, out_file=None, node_size=1500, font_size=10,
node_and_labels=None, edge_and_labels=None):
"""
plot a graph
"""
pos = nx.get_node_attributes(G, 'pos')
if not pos:
pos = nx.spring_layout(G)
nx.draw_networkx(G, pos, node_size=node_size,
node_color='w',
edge_color='k',
labels = node_and_labels,
font_size=font_size,
font_color='r',
arrows=True,
with_labels=True)
plt.axis('off')
if edge_and_labels:
nx.draw_networkx_edge_labels(G, pos,
edge_labels=edge_and_labels,
font_color='r',
label_pos=0.4,
alpha=0.0)
if out_file:
plt.savefig(out_file, bbox_inches='tight')
plt.show()
示例14: plot
# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import draw_networkx_edge_labels [as 别名]
def plot(self, density=1.0):
"""Plots a network diagram from (triple) nodes and edges in the KB.
:param float density: Probability (0-1) that a given edge will be plotted, \
useful to thin out dense graphs for visualization."""
edgelist = [e for e in self.G.edges(data=True) if random.random() < density]
newg = nx.DiGraph(edgelist)
pos = nx.spring_layout(newg)
plt.figure(1,figsize=(12,12))
nx.draw_networkx_nodes(newg, pos, node_size=200)
nx.draw_networkx_edges(newg, pos, edgelist=edgelist, width=1, font_size=8)
nx.draw_networkx_labels(newg, pos, font_size=10, font_family='sans-serif')
nx.draw_networkx_edge_labels(newg, pos)
plt.axis('off')
plt.show()
示例15: _build_graph
# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import draw_networkx_edge_labels [as 别名]
def _build_graph(show=False):
"""Load word dependencies into graph using networkx. Enables easy traversal of dependencies for parsing particular patterns.
One graph is created for each sentence.
Args:
show (bool): If set to True, labeled visualization of network will be opened via matplotlib for each sentence
Returns:
None: Global variable G is set from within function
"""
global G
G = nx.Graph()
node_labels, edge_labels = {}, {}
for idx, dep in enumerate(A.deps):
types = ["dependent", "governor"]
# nodes, labels
for x in types:
G.add_node(str(dep[x]), word=dep[x + "Gloss"], pos=A.lookup[dep[x]]["pos"])
node_labels[str(dep[x])] = dep[x + "Gloss"] + " : " + A.lookup[dep[x]]["pos"]
# edges, labels
G.add_edge(str(dep[types[0]]), str(dep[types[1]]), dep=dep["dep"])
edge_labels[(str(dep[types[0]]), str(dep[types[1]]))] = dep["dep"]
if show == True:
pos = nx.spring_layout(G)
nx.draw_networkx(G, pos=pos, labels=node_labels, node_color="white", alpha=.5)
nx.draw_networkx_edge_labels(G, pos=pos, edge_labels=edge_labels)
plt.show()
#########################################
# Dependency / POS parsing functions
#########################################