CODEWITHSUNDEEP
pythonnetwork-programmingnetworkx
DPM
DPM

Reputation: 935

nx.draw() plots edges as bi-directional even tho they are uni-directional

So consider a Lattice where every edge is bi-directional. Now I have some code that removes some edges in order to reduce the percentage of edges that are bi-directional and increase the percentage of uni-directional edges:

import networkx as nx
import matplotlib.pyplot as plt
import numpy as np
from random import shuffle

G = nx.grid_2d_graph(20,20, periodic=True)
G = nx.relabel.convert_node_labels_to_integers(G)
G2 = nx.DiGraph(G)
nx.set_edge_attributes(G2, values = 1, name = 'weight')
edge_list = list(G2.edges())
shuffle(edge_list)

remove_list = []
seen = []

for (u,v) in edge_list:
    seen.append((u,v))
    if (v,u) in edge_list:
        if (v,u) not in seen:
            sample = rd.sample([(u,v), (v,u)],1)[0]
            if len(remove_list)< 0.8*(len(edge_list)/2):
                remove_list.append(sample)
            else:
                break

G2.remove_edges_from(remove_list)

Now I saved the edges that are uni-directional in a list:

H = [(u,v) for (u,v) in G2.edges if (v,u) not in G2.edges]

H[:10]

[(0, 20),
 (0, 1),
 (0, 380),
 (1, 2),
 (2, 22),
 (2, 382),
 (3, 4),
 (5, 4),
 (5, 25),
 (5, 6)]

What I want to do now is plot this Lattice:

edge_color = ['red' if (u,v) in H else 'black' for (u,v) in G2.edges] ## uni-directional edges will be red and bi-directional ones will be black

pos = {(x,y):(y,-x) for x,y in product(range(size), range(size))}
pos1 = {i: value for i, value in zip(range(size**2), pos.values())}## assign the nodes to their positions

plt.figure(figsize=(40, 40)) 
nx.draw(G2,node_size=3000,node_color='lightgreen', with_labels=True, pos=pos1, width=5, edge_color = edge_color)

The problem with this is that in the plot I have red edges that are bi-directional which is wrongenter image description here

enter image description here

Let's compare the output of H[:10] with the plot:

As you can see the edge (0,1) is painted correctly but has two arrows indicating its a bi-directional one even tho it isn't. Another example is the edge (1,21) which is a bi-directional one and is painted red. Can someone help me fix this?

Upvotes: 3

Views: 270

Answers (2)

willcrack
willcrack

Reputation: 1852

G = nx.grid_2d_graph(20,20, periodic=True)

From the nx.grid_2d_graph docs:

periodic (bool or iterable) – If periodic is True, both dimensions are periodic. If False, none are periodic. If periodic is iterable, it should yield 2 bool values indicating whether the 1st and 2nd axes, respectively, are periodic.

I didn't know what a periodic grid lattice was, so I did a little research(Google), and found this:

From Matarazzo, U., Tsur, D., & Ziv-Ukelson, M. (2014). Efficient all path score computations on grid graphs. Theoretical Computer Science, 525, 138-149.:

A periodic grid graph is an infinite graph obtained by concatenating horizontally an infinite number of a (finite) grid graph.

Conclusion

This is still pretty mysterious to me, but you can see in the results that you obtained, that edges seem somehow overlapping(like there was more than one graph being drawn...).
So, it seems like you are obtaining some unexpected results due to this "periodicity" feature. Removing periodic=True and returning this value back to default,False, solves the issue:

G = nx.grid_2d_graph(20,20)

result

Upvotes: 2

GIOVANNI QUINONES VALDEZ
GIOVANNI QUINONES VALDEZ

Reputation: 257

One problem is that your are using G2.edges as a list which is not. So saying (u,v) in G2.edges is not checking for item membership making your H list wrong. So you can just do:

H = [(u,v) for (u,v) in G2.edges if (v,u) not in list(G2.edges)]

I am not sure if this completely solves your problem, but at least solves that one issue.

Upvotes: 0

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