3D network visualisations using plotly

#Install needed packages !pip install networkx !pip install plotly==4.9.0

#Import the required packages import networkx as nx import plotly.graph_objects as go import pandas as pd %matplotlib inline

#Let's import the ZKC graph: ZKC_graph = nx.karate_club_graph() #Let's keep track of which nodes represent John A and Mr Hi Mr_Hi = 0 John_A = 33 #remember the number of nodes since this will come in useful later Num_nodes = 34 #get the club labels - i.e. which club each individual ended up joining club_labels = list(nx.get_node_attributes(ZKC_graph,'club').values())

#communities from last time - one list for each community community_0 = [8, 14, 15, 18, 20, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33] community_1 = [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 16, 17, 19, 21] #label for each node corresponds to community 0 or community 1 community_label = [1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 0, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]

#Let's opt for a spring layout spring_pos = nx.spring_layout(ZKC_graph, seed=2)

#draw the network nx.draw_networkx_nodes(ZKC_graph, spring_pos, nodelist=community_0, node_color='g', alpha=0.4) nx.draw_networkx_nodes(ZKC_graph, spring_pos, nodelist=community_1, node_color='m', alpha=0.4) #let's highlight Mr Hi (solid purple) and John A (solid green) nx.draw_networkx_nodes(ZKC_graph, spring_pos, nodelist=[John_A], node_color='g', alpha=1) nx.draw_networkx_nodes(ZKC_graph, spring_pos, nodelist=[Mr_Hi], node_color='m', alpha=1) nx.draw_networkx_edges(ZKC_graph, spring_pos,stlye='dashed',width = 0.5)

#As before we use networkx to determine node positions. We want to do the same spring layout but in 3D spring_3D = nx.spring_layout(ZKC_graph,dim=3, seed=18) #an example node coordinate spring_3D[4]

#we need to seperate the X,Y,Z coordinates for Plotly x_nodes = [spring_3D[i][0] for i in range(Num_nodes)]# x-coordinates of nodes y_nodes = [spring_3D[i][1] for i in range(Num_nodes)]# y-coordinates z_nodes = [spring_3D[i][2] for i in range(Num_nodes)]# z-coordinates

#We also need a list of edges to include in the plot edge_list = ZKC_graph.edges() edge_list

#we need to create lists that contain the starting and ending coordinates of each edge. x_edges=[] y_edges=[] z_edges=[] #need to fill these with all of the coordiates for edge in edge_list: #format: [beginning,ending,None] x_coords = [spring_3D[edge[0]][0],spring_3D[edge[1]][0],None] x_edges += x_coords y_coords = [spring_3D[edge[0]][1],spring_3D[edge[1]][1],None] y_edges += y_coords z_coords = [spring_3D[edge[0]][2],spring_3D[edge[1]][2],None] z_edges += z_coords

#create a trace for the edges trace_edges = go.Scatter3d(x=x_edges, y=y_edges, z=z_edges, mode='lines', line=dict(color='black', width=2), hoverinfo='none')

#create a trace for the nodes trace_nodes = go.Scatter3d(x=x_nodes, y=y_nodes, z=z_nodes, mode='markers', marker=dict(symbol='circle', size=10, color=community_label, #color the nodes according to their community colorscale=['lightgreen','magenta'], #either green or mageneta line=dict(color='black', width=0.5)), text=club_labels, hoverinfo='text')

trace_MrHi = go.Scatter3d(x=[x_nodes[Mr_Hi]], y=[y_nodes[Mr_Hi]], z=[z_nodes[Mr_Hi]], mode='markers', name='Mr_Hi', marker=dict(symbol='circle', size=10, color='darkmagenta', line=dict(color='black', width=0.5) ), text = ['Mr_Hi'], hoverinfo = 'text')

trace_JohnA = go.Scatter3d(x=[x_nodes[John_A]], y=[y_nodes[John_A]], z=[z_nodes[John_A]], mode='markers', name='John_A', marker=dict(symbol='circle', size=10, color='green', line=dict(color='black', width=0.5) ), text = ['Officer'], hoverinfo = 'text')

#we need to set the axis for the plot axis = dict(showbackground=False, showline=False, zeroline=False, showgrid=False, showticklabels=False, title='')

#also need to create the layout for our plot layout = go.Layout(title="Two Predicted Factions of Zachary's Karate Club", width=650, height=625, showlegend=False, scene=dict(xaxis=dict(axis), yaxis=dict(axis), zaxis=dict(axis), ), margin=dict(t=100), hovermode='closest')

#Include the traces we want to plot and create a figure data = [trace_edges, trace_nodes, trace_MrHi, trace_JohnA] fig = go.Figure(data=data, layout=layout) fig.show()