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carpediem
Asked: 2025-04-28 15:12:53 +0800 CST

带有两个动画子图的 Matplotlib 图形：如何同时更新两者

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我正在尝试使用 matplotlib 和 pyplot 绘制一个包含两个子图的图表来可视化模拟结果。两个图表都应该包含动画：一个使用 NetGraph 库（它是一个包含节点的图表，用于显示网络流量），另一个绘制另外两个变量的线图（为了简单起见，这里使用 sin(x) 和 cos(x)，它们都应该在每个时间段更新——就像图表一样）。我有一个更新函数可以更新图表，但我不确定如何同时更新线图。欢迎大家提出任何建议。

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()
python

1 个回答

  1. Best Answer

    你的脚本似乎没有包含 sin/cos 函数的实现和绘图功能。我添加了它们并运行了脚本，它显示了两个图。试试这个

    import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
from netgraph import Graph

# Simulate a dynamic network
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)

# Normalize the weights
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)

# Prepare figure
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)

# Initialize Graph
g = Graph(adjacency_matrix, node_labels=NODE_LABELS,
          node_layout=NODE_POS, edge_cmap=cmap, arrows=True, ax=ax1)

# Prepare x-axis values for sin and cos
x = np.linspace(0, 2*np.pi, 100)

# Initialize two line plots (empty initially)
line_sin, = ax2.plot([], [], label='sin(x)')
line_cos, = ax2.plot([], [], label='cos(x)')
ax2.set_xlim(0, 2*np.pi)
ax2.set_ylim(-1.5, 1.5)
ax2.legend()

# Define update function
def update(ii):
    artists = []

    # Update the graph (netgraph)
    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)

    # Update the line plots
    y_sin = np.sin(x + ii * 0.2)  # phase shift over time
    y_cos = np.cos(x + ii * 0.2)
    line_sin.set_data(x, y_sin)
    line_cos.set_data(x, y_cos)
    artists.append(line_sin)
    artists.append(line_cos)

    return artists

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