I'm trying to vizualize simulation results with a figure containing 2 subplots using matplotlib pyplot. Both should contain animation: one uses netgraph library (it's a graph with nodes showing flows of the network) and the other should plot a line graph of another 2 variables (to keep it simple here lets use: sin(x) & cos(x) where both should be updated at each time period--just like the graph). I have an update function to update the graph, but I'm unsure, how to update the line plot at the same time. I would appreciate any suggestions. import numpy as np import matplotlib.pyplot as plt from matplotlib.animation import FuncAnimation from netgraph import Graph # Simulate a dynamic network with total_frames = 21 total_nodes = 5 NODE_LABELS = {0: 'A', 1: 'B', 2: 'C', 3: 'D', 4: 'E'} NODE_POS = {0: (0.0, 0.5), 1: (0.65, 0.25), 2: (0.7, 0.5), 3: (0.5, 0.75), 4: (0.25, 0.25)} adjacency_matrix = np.random.rand(total_nodes, total_nodes) < 0.25 weight_matrix = np.random.randn(total_frames, total_nodes, total_nodes) # Normalise the weights, such that they are on the interval [0, 1]. vmin, vmax = -2, 2 weight_matrix[weight_matrix<vmin] = vmin weight_matrix[weight_matrix>vmax] = vmax weight_matrix -= vmin weight_matrix /= vmax - vmin cmap = plt.cm.RdGy def annotate_axes(fig): for i, ax in enumerate(fig.axes): ax.tick_params(labelbottom=False, labelleft=False) fig = plt.figure(figsize=(11, 6)) ax1 = plt.subplot2grid((6, 11), (0, 0), rowspan=6, colspan=5) ax2 = plt.subplot2grid((6, 11), (1, 6), rowspan=2, colspan=5) annotate_axes(fig) title1 = ax1.set_title('Simulation viz', x=0.25, y=1.25) title2 = ax2.set_title('Flow @t', x=0.15, y=1.25) g = Graph(adjacency_matrix, node_labels=NODE_LABELS, node_layout = NODE_POS, edge_cmap=cmap, arrows=True, ax=ax1) def update(ii): artists = [] for jj, kk in zip(*np.where(adjacency_matrix)): w = weight_matrix[ii, jj, kk] artist = g.edge_artists[(jj, kk)] artist.set_facecolor(cmap(w)) artist.update_width(0.03 * np.abs(w-0.5)) artists.append(artist) return artists animation = FuncAnimation(fig, update, frames=total_frames, interval=200, blit=True, repeat=False) plt.show() Continue reading...