plotting time-series data over a network

Hi @marcomusy

I am trying to plot time series data related to nodes of a graph

import networkx as nx
from vedo import *

G = nx.gnm_random_graph(n=10, m=15, seed=1)
nxpos = nx.spring_layout(G)
nxpts = [nxpos[pt] for pt in sorted(nxpos)]

nx_lines = []
for i, j in G.edges():
    p1 = nxpos[i].tolist() + [0]  # add z-coord
    p2 = nxpos[j].tolist() + [0]
    nx_lines.append([p1, p2])

nx_pts = Points(nxpts, r=12)
nx_edg = Lines(nx_lines).lw(2)

# node values
values = [[100, .80, .10, .79, .70, .60, .75, .78, .65, .90],[1, .80, .10, .79, .70, .60, .75, .78, .65, .10],[1000, .30, .10, .79, .70, .60, .75, .78, .65, .90]]
time = [0, 0.1, 0.2] # in seconds
for val,t in zip(values, time):
    nx_pts.pointColors(val, cmap='YlGn', vmin=min(val), vmax=max(val)).addScalarBar()
    show(nx_pts, nx_edg, nx_pts.labels('id'), interactive=True, bg='black', title=f'{t} seconds')

I intend to create multiple frames with time stamp displayed in each frame. I couldn’t achieve this using the above code. Suggestions on how to visualize the data over time will be highly appreciated.

[DeepaMahm]

Please check if by chance pycharm installed vtk9.0.1 instead of vtk8.1.2, because that might be causing issues.

I’ve checked the version and it’s vtk8.1.2. I could see the correct images in the interactive mode, the problem is while the images are saved. first 2 images are black

EDIT: I’ve installed vtk9.0.1 now and finally, I’m able to view the correct images.

[marcomusy]

Hi, try the following:

import networkx as nx
from vedo import *

G = nx.gnm_random_graph(n=10, m=15, seed=1)
nxpos = nx.spring_layout(G)

nxpts = [nxpos[pt] for pt in sorted(nxpos)]
nx_lines = [ (nxpts[i], nxpts[j]) for i, j in G.edges() ]

nx_pts = Points(nxpts, r=12)
nx_edg = Lines(nx_lines).lw(2)

# node values
values = [[1, .80, .10, .79, .70, .60, .75, .78, .65, .90],
          [3, .80, .10, .79, .70, .60, .75, .78, .65, .10],
          [1, .30, .10, .79, .70, .60, .75, .78, .65, .90]]
time = [0.0, 0.1, 0.2] # in seconds
for val,t in zip(values, time):
    nx_pts.cmap('YlGn', val, vmin=0.1, vmax=3)
    if t==0:
        nx_pts.addScalarBar()
 
    # make a plot title
    x0, x1 = nx_pts.xbounds()
    y0, y1 = nx_pts.ybounds()
    t = Text('My μ-Graph at time='+str(t)+' seconds',
             font='BPmonoItalics', justify='center', s=.07, c='lb')
    t.pos((x0+x1)/2, y1*1.4)
    show(nx_pts, nx_edg, nx_pts.labels('id',c='w'), t,
         interactive=True, bg='black')