Hello, I am trying to make a network graph, using networkx, that has a slider to add edges of specific orders and colors (on top of preexisting, and pre-displayed edges). I have played around with a couple of modes of accomplishing this task, but have inevitably run into varied roadblocks.
Here is the code of one of those attempts, that’s only issue (as of right now), is that the slider itself does not display. I used to the basic plotly tutorial on network graphs and simple sliders to help me along.
from mpi4py import MPI
import time
from array import *
import plotly.graph_objects as go
import networkx as nx
def driverFunc():
nodeChoice = input("How many processes (1 or 8): ")
if nodeChoice == '1':
fPath = "/home/datafilepath..."
dataChoice = input("Which data set would you like to visualize (0-50): ")
fPath += str(dataChoice) + "/"
#initialize networkx graph
inGraph = nx.OrderedGraph()
nodeArr = []
#fill node array
for x in range(1, 101):
nodeArr.append(x)
inGraph.add_nodes_from(nodeArr)
# FUCKFUCKFUCK
inputD = driverDriver(fPath + "G_0")
#add initial input edges
inGraph.add_edges_from(inputD, color='black')
#position
pos = nx.spring_layout(inGraph, k=0.99, iterations=20)
transC = driverDriver(fPath + "dT_0")
#inGraph.add_edges_from(transC, color='')
transFin = driverDriver(fPath + "T_0")
transFinCopy = transFin
#temporarily remove dupilcate edges, networkx might do this automatically
for edge in transFin:
if edge in inputD or edge in transC:
# print(str(edge) + "OUTTA HERE")
transFin.remove(edge)
transC.extend(transFin)
#print(str(transC))
#get x and y positions of edges
edge_x = []
edge_y = []
for edge in inGraph.edges():
edge_x += [pos[edge[0]][0], pos[edge[1]][0], None]
edge_y += [pos[edge[0]][1], pos[edge[1]][1], None]
#x and y positions of nodes
node_x = [pos[k][0] for k in range(1,len(nodeArr))]
node_y = [pos[k][1] for k in range(1,len(nodeArr))]
#initial node and edge traces
node_trace = go.Scatter(
x = node_x, y= node_y,
mode = 'markers',
name = 'net',
marker=dict(symbol = 'circle-dot',
size = 10,
color = '#6959CD',
line = dict(color='rgb(50, 50, 50)', width=0.5)),
text = nodeArr,
hoverinfo = 'text'
)
edge_trace = go.Scatter(x = edge_x, y = edge_y, mode = 'lines',
line = dict(color = 'black', width =1),
hoverinfo = 'none')
data1 = [edge_trace, node_trace]
fig1 = go.Figure(data=data1, layout=go.Layout())
count = 0
#add different colored traces depending on where in the list one is
for edge in transC:
inGraph.add_edge(edge[0], edge[1])
print(str(edge[0])+' '+str(edge[1]))
edge_x += [pos[edge[0]][0], pos[edge[1]][0], None]
edge_y += [pos[edge[0]][1], pos[edge[1]][1], None]
if count+1 > len(deltaTCopy):
fig1.add_trace(
go.Scatter(
x = edge_x[len(edge_x)-1],
y = edge_y[len(edge_y)-1],
visible = False,
line=dict(color='purple', width = 1),
hoverinfo = 'all'
)
)
count+=1
else:
fig1.add_trace(
go.Scatter(
x=edge_x[len(edge_x) - 1],
y=edge_y[len(edge_y) - 1],
visible=False,
line=dict(color='red', width=1),
hoverinfo='all'
)
)
count += 1
steps = []
#slider
for i in range(len(fig1.data)):
step = dict(
method='update',
args=[{'visible':[False]*len(fig1.data)},
{'title':"Slider Step: " + str(i)}],
#layout attribute
)
step["args"][0]["visible"][i] = True #toggle step (i)-th trace to visible
steps.append(step)
sliders = [dict(
active = 10,
currentvalue = {"prefix": "Step: "},
pad={"t": len(transC)},
steps=steps
)]
fig1.update_layout(
sliders = sliders
)
fig1.show()
else:
fPath = "Data\\396\\D_396_Data_8\\"
return 0
I know this is a very slow, gross and unoptimized way of going about things, but I’m going for functionality before I work on optimization, and style.
Much appreciated