python networkx: do networkx's centrality algorithms use a weighted adjacency matrix?
Date : March 29 2020, 07:55 AM
it should still fix some issue Both of those algorithms as implemented in NetworkX will use edge weights if specified with the edge attribute 'weight' (for each edge). If you do not specify a weight on the edge the numeric value 1 will be used. This is very unclear from the documentation. I've opened an issue at https://github.com/networkx/networkx/issues/920 so the developers fix this.

Python: List of tuples: compare all tuples and retrive tuples where the elements of tuples are not equal to any other tu
Tag : python , By : Hitesh Prajapati
Date : March 29 2020, 07:55 AM
I hope this helps . You can compare all tuples using a double loop, and use list comprehension for scalability: i = 0
while i < len(z):
j = i+1
while j < len(z):
if any([z[i][n]==z[j][n] for n in range(len(z[0]))]):
del z[j] # Shift all values, so no need to update j
else:
j += 1
i += 1

Python NetworkX error: module 'networkx.drawing' has no attribute 'graphviz_layout'
Date : March 29 2020, 07:55 AM
Any of those help The answer is courtesy @Bonlenfum and code from https://networkx.github.io/documentation/networkx1.10/examples/drawing/simple_path.htmlHere's the code that worked: >>> import networkx as nx
>>> import matplotlib.pyplot as plt
>>> G=nx.Graph()
>>> G.add_node(1)
>>> G.add_nodes_from([2,3])
>>> nx.draw(G)
>>> plt.savefig("simple_path.png")
>>> plt.show()
try:
import matplotlib.pyplot as plt
except:
raise
def graph_draw(graph):
nx.draw(graph,
node_size = [16 * graph.degree(n) for n in graph],
node_color = [graph.depth[n] for n in graph],
with_labels = False)

Plotting degree distribution of networkx.DiGraph using networkx.degree_histogram and matplotlib
Date : March 29 2020, 07:55 AM
I think the issue was by ths following , One way of printing the (in plus out)degree histogram with test code: import matplotlib.pyplot as plt
import networkx as nx
def plot_degree_dist(G):
degrees = [G.degree(n) for n in G.nodes()]
plt.hist(degrees)
plt.show()
plot_degree_dist(nx.gnp_random_graph(100, 0.5, directed=True))

Missing edges when using add_edges_from with networkx python
Tag : python , By : user135518
Date : March 29 2020, 07:55 AM
will help you This is due to the fact that your mydict variable contains both (x,y) and (y,x). If you build a networkx.Graph (instead of a networkx.DiGraph) then (x,y) is considered to be the same of (y,x). Example: import networkx as nx
mydict = {(3,4): 5, (4,3): 6, (1,2): 6}
g = nx.Graph()
di_g = nx.DiGraph()
g.add_edges_from(mydict)
di_g.add_edges_from(mydict)
print(g.edges) # [(3, 4), (1, 2)]
print(di_g.edges) # [(3, 4), (4, 3), (1, 2)]

