Netgraph 动画 — 如何显示帧数

Question

我正在尝试将帧号添加到从此处修改的模拟可视化中。有没有简单的方法可以向该动画添加帧编号，以便它显示为绘图标题的一部分？

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 = 10
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].
# They can then be passed directly to matplotlib colormaps (which expect floats on that interval).
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

fig, ax = plt.subplots()
fig.suptitle('Simulation viz @ t=', x= 0.15, y=0.95)
g = Graph(adjacency_matrix, node_labels=NODE_LABELS,
            node_layout = NODE_POS, edge_cmap=cmap, arrows=True, ax=ax)

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()

谢谢你。我将不胜感激任何帮助/建议。

Answer 1

使用 blit (

blit=True

) 进行动画处理时，无法更改图形级别标题，因为 blit 会缓存动画轴之外的所有内容。

最简单的更改是将 blit 设置为 false，然后在动画更新函数中更新图形标题。

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 = 10
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].
# They can then be passed directly to matplotlib colormaps (which expect floats on that interval).
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

fig, ax = plt.subplots()
title = fig.suptitle('Simulation viz @ t=', x= 0.15, y=0.95) # <----
g = Graph(adjacency_matrix, node_labels=NODE_LABELS,
            node_layout = NODE_POS, edge_cmap=cmap, arrows=True, ax=ax)

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)

    title.set_text(f"Simulation viz @ t={ii}") # <----

    return artists

animation = FuncAnimation(fig, update, frames=total_frames, interval=200, blit=False, repeat=False)
plt.show()