如何使用更新函数在 Matplotlib 2.0.0 中为 NetworkX 图形设置动画？

Question

我正在尝试弄清楚如何使用 matplotlib 2.0 和其中的 animation 模块为我的 networkx 图表制作动画。我看到 Using NetworkX with matplotlib.ArtistAnimation and Animate graph diffusion with NetworkX 但我无法弄清楚这些更新函数是如何使用伪代码的。

我正在尝试遍历一系列字母（节点），然后绘制从原点 "O" 到当前步骤的路径。查看下面的图会更有意义。我不想渲染它们以在 Python 3.6 之外制作 .mp4。我认为这将是一个很好的资源，可以让人们了解这些更新功能如何运作以及如何将它们应用于可视化网络。

如何使用 update function 为下面的 networkx 图表制作动画？

显然，动画不会出现在具有不同 ax 对象的 matplotlib figure 上，但这只是为了说明帧的布局方式。

import networkx as nx
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import matplotlib.animation as animation


def update_func(num, data, line):
    # https://matplotlib.org/2.0.0/examples/animation/basic_example.html
    line.set_data(data[..., :num])
    return line

# Create Graph
np.random.seed(2)
G = nx.cubical_graph()
G = nx.relabel_nodes(G, {0:"O", 1:"X", 2:"XZ", 3:"Z", 4:"Y", 5:"YZ", 6: "XYZ", 7:"XY"})
pos = nx.spring_layout(G)

# Sequence of letters
sequence_of_letters = "".join(['X', 'Y', 'Z', 'Y', 'Y', 'Z']) #np.random.RandomState(0).choice(list("XYZ"), size=6, replace=True)
idx_colors = sns.cubehelix_palette(5, start=.5, rot=-.75)[::-1]
idx_weights = [3,2,1]

# General graph structure
with plt.style.context("seaborn-white"):
    fig, ax = plt.subplots()
    nx.draw(G, pos=pos, with_labels=True, ax=ax)
    print(ax.get_xlim(), ax.get_ylim())
# (-0.10500000000000001, 1.105) (-0.088398066788676247, 0.93028441715702148)

# Build plot
with plt.style.context("seaborn-white"):
    fig, axes = plt.subplots(ncols=3, nrows=2, figsize=(10,5))
    for i in range(0, len(sequence_of_letters), 3):
        triad = sequence_of_letters[i:i+3]
        for j in range(1,4):
            # Axes index for rows and cols
            idx = i + j - 1
            row_idx, col_idx = {True: (0,idx), False: (1,idx - 3)}[idx < 3]
            ax = axes[row_idx][col_idx]

            # Path in Graph
            path = ["O"] + ["".join(sorted(set(triad[:k + 1]))) for k in range(j)]

           # Background nodes
            nx.draw_networkx_edges(G, pos=pos, ax=ax, edge_color="gray")
            null_nodes = nx.draw_networkx_nodes(G, pos=pos, nodelist=set(G.nodes()) - set(path), node_color="white",  ax=ax)
            null_nodes.set_edgecolor("black")

            # Query nodes
            query_nodes = nx.draw_networkx_nodes(G, pos=pos, nodelist=path, node_color=idx_colors[:len(path)], ax=ax)
            query_nodes.set_edgecolor("white")
            nx.draw_networkx_labels(G, pos=pos, labels=dict(zip(path,path)),  font_color="white", ax=ax)
            edgelist = [path[k:k+2] for k in range(len(path) - 1)]
            nx.draw_networkx_edges(G, pos=pos, edgelist=edgelist, width=idx_weights[:len(path)], ax=ax)

            # Scale plot ax
            ax.set_title("Frame %d:    "%(idx+1) +  " - ".join(path), fontweight="bold")
            ax.set_xlim((-0.10500000000000001, 1.105))
            ax.set_ylim((-0.088398066788676247, 0.93028441715702148))
            ax.set_xticks([])
            ax.set_yticks([])

Answer 1

两个链接问题的答案都提供了关于如何为 networkx 图设置动画的很好的示例。它们比这个问题中的示例代码允许的任何答案都更加规范。

因此，我在这里重点关注如何使用更新函数为问题中的 networkx 图设置动画的问题。

解决方案是将两个for循环中的所有内容都放入一个函数中，该函数至少接受一个索引作为参数。然后可以使用该索引生成图像。

import networkx as nx
import numpy as np
import matplotlib.pyplot as plt
import seaborn.apionly as sns
import matplotlib.animation

# Create Graph
np.random.seed(2)
G = nx.cubical_graph()
G = nx.relabel_nodes(G, {0:"O", 1:"X", 2:"XZ", 3:"Z", 4:"Y", 5:"YZ", 6: "XYZ", 7:"XY"})
pos = nx.spring_layout(G)

# Sequence of letters
sequence_of_letters = "".join(['X', 'Y', 'Z', 'Y', 'Y', 'Z'])
idx_colors = sns.cubehelix_palette(5, start=.5, rot=-.75)[::-1]
idx_weights = [3,2,1]

# Build plot
fig, ax = plt.subplots(figsize=(6,4))


def update(num):
    ax.clear()
    i = num // 3
    j = num % 3 + 1
    triad = sequence_of_letters[i:i+3]
    path = ["O"] + ["".join(sorted(set(triad[:k + 1]))) for k in range(j)]

    # Background nodes
    nx.draw_networkx_edges(G, pos=pos, ax=ax, edge_color="gray")
    null_nodes = nx.draw_networkx_nodes(G, pos=pos, nodelist=set(G.nodes()) - set(path), node_color="white",  ax=ax)
    null_nodes.set_edgecolor("black")

    # Query nodes
    query_nodes = nx.draw_networkx_nodes(G, pos=pos, nodelist=path, node_color=idx_colors[:len(path)], ax=ax)
    query_nodes.set_edgecolor("white")
    nx.draw_networkx_labels(G, pos=pos, labels=dict(zip(path,path)),  font_color="white", ax=ax)
    edgelist = [path[k:k+2] for k in range(len(path) - 1)]
    nx.draw_networkx_edges(G, pos=pos, edgelist=edgelist, width=idx_weights[:len(path)], ax=ax)

    # Scale plot ax
    ax.set_title("Frame %d:    "%(num+1) +  " - ".join(path), fontweight="bold")
    ax.set_xticks([])
    ax.set_yticks([])


ani = matplotlib.animation.FuncAnimation(fig, update, frames=6, interval=1000, repeat=True)
plt.show()

如何使用更新函数在 Matplotlib 2.0.0 中为 NetworkX 图形设置动画？

How to use an update function to animate a NetworkX graph in Matplotlib 2.0.0?

python

animation

graph

matplotlib

networkx