PyGraphviz (几何图形可视化工具) 简单入门

import pygraphviz as pgv

G = pgv.AGraph(directed=True, strict=False, nodesep=0, ranksep=1.2, rankdir="TB",
               splines="none", concentrate=True, bgcolor="write",
               compound=True, normalize=False, encoding='UTF-8')

G.add_node(name, label=None, fontname="Times-Roman", fontsize=14,
           shape="ellipse", style="rounded", color="black", fontcolor="black",
           pos="x,y(!)", fixedsize=False, width=1, height=1)

G.add_nodes_from(names, **attr) # 批量添加点，参数同上  

G.add_edge(origin, target, color="black", style="solid", penwidth=1,
           label="", fontname="Times-Roman", fontsize=14, fontcolor="black",
           arrowsize=1, arrowhead="normal", arrowtail="normal", dir="forward")

G.add_nodes_from([[origin_1, target_1],
                  [origin_2, target_2],...], **attr)  # 批量添加线，参数同上

G.layout()
G.draw(file_name, prog="neato")

import pygraphviz as pgv

G = pgv.AGraph(directed=True, strict=False, ranksep=0.2, splines="spline", concentrate=True)

# 设置节点标签
nodeA = "Police\nIntelligence"
nodeB = "Police Station"
nodeC = "Criminal Action"
nodeD = "Incidents"
nodeE = "Police Dockets"
nodeF = "Control Room\nAwareness"
nodeG = "Patroller Information"
nodeH = "Patroller Awareness"

# 添加节点
G.add_nodes_from([nodeA, nodeB, nodeC, nodeD, nodeE, nodeF, nodeG, nodeH],
                 color="#ffffff", fontname="times bold italic")

# 添加边
G.add_edges_from([[nodeA, nodeB], [nodeA, nodeF], [nodeB, nodeC], [nodeC, nodeD],
                  [nodeC, nodeG], [nodeD, nodeE], [nodeD, nodeG], [nodeE, nodeA],
                  [nodeF, nodeA], [nodeF, nodeG], [nodeF, nodeH], [nodeG, nodeF],
                  [nodeH, nodeG]], color="#7F01FF", arrowsize=0.8)

# 导出图形
G.layout()
G.draw("因果关系图.png", prog="dot")

import pygraphviz as pgv

G = pgv.AGraph(directed=True, rankdir="TB")

# 设置节点标签
Root = "道路交通流畅"
negative_1 = "平均延误时间"
negative_2 = "负荷度"
negative_3 = "小区位置"
negative_4 = "相对延误率"
negative_5 = "房屋密度"
negative_6 = "人口密度"
negative_7 = "总延误率"
negative_8 = "排队率"
negative_9 = "行驶时间"
positive_1 = "通行能力"
positive_2 = "公路层级"
positive_3 = "路网结构"
positive_4 = "行驶速度"
positive_5 = "路网长度"
positive_6 = "小区面积"
positive_7 = "内部道路密度"
positive_8 = "路网密度"

# 添加节点
G.add_node(Root, style="filled", shape="box3d", color="#feb64d")
for negative in [eval(_) for _ in dir() if _.startswith("negative")]:
    G.add_node(negative, style="filled", shape="ellipse", color="#CFDBF6")

for positive in [eval(_) for _ in dir() if _.startswith("positive")]:
    G.add_node(positive, style="filled", shape="ellipse", color="#B4E7B7")

# 添加边
G.add_edges_from([[Root, negative_1], [Root, negative_6], [Root, negative_8], [Root, negative_9],
                  [negative_1, negative_2], [negative_1, negative_7], [negative_2, negative_3],
                  [negative_2, negative_7], [negative_3, negative_4], [negative_8, negative_9],
                  [positive_2, negative_5], [positive_3, negative_4], [positive_4, negative_5]],
                 color="#B4DBFF", style="dashed", penwidth=1.5)

G.add_edges_from([[Root, positive_1], [Root, positive_8], [negative_5, negative_4],
                  [negative_6, positive_4], [negative_5, positive_4], [negative_9, positive_5],
                  [positive_1, positive_2], [positive_2, positive_3], [positive_6, positive_5],
                  [positive_7, positive_6], [positive_8, positive_7]],
                 color="#B4E7B7", style="dashed", penwidth=1.5)

# 导出图形
G.layout()
G.draw("因子相关性图.png", prog="dot")

import pygraphviz as pgv

G = pgv.AGraph(directed=True, rankdir="LR")

# 设置层数、每层节点数
network_structure = input("输入神经网络每层节点数，如：[10, 7, 5, 4, 2, 1]\n")
all_nodes = [[f"layer{layer_index}node{node_index}" for node_index in range(layer_nodes_num)] for
             layer_index, layer_nodes_num in enumerate(eval(network_structure))]

# 添加输入层节点
for node_index, node in enumerate(all_nodes[0]):
    G.add_node(node, label="", shape="circle", style="bold", color="#60acfc", pos=f"0,{0.6 * node_index}!")

# 添加输入层文本
G.add_node(f"Input_Layer", shape="none", label=f"Input_Layer({len(all_nodes[0])})",
           pos=f"{0},{(node_index + 1) * 0.6}!")

# 添加中间层、输出层节点
for layer_index, layer in enumerate(all_nodes[1:]):
    color = "#5bc49f" if layer_index == len(all_nodes[1:]) - 1 else "#ff7c7c"

    for node_index, node in enumerate(layer):
        x = 1.5 * (layer_index + 1)
        y = - 0.3 * (len(all_nodes[layer_index + 1]) - len(all_nodes[0])) + 0.6 * node_index
        G.add_node(node, label="", shape="circle", style="bold", color=color, pos=f"{x},{y}!")

    # 添加中间层、输出层文本
    text = f"Output_Layer({len(all_nodes[-1])})" if layer_index == len(all_nodes[1:]) - 1 else f"Layer_{layer_index + 1}({len(layer)})"
    G.add_node(f"Layer_{layer_index + 1})", shape="none", label=text,
               pos=f"{x},{y + 0.4}!")

# 添加线
for layer_index in range(all_nodes.__len__() - 1):
    for start in all_nodes[layer_index]:
        for end in all_nodes[layer_index + 1]:
            G.add_edge(start, end)

# 导出图形
G.layout()
G.draw("神经网络.png")

# 运行代码，输入 [5, 10, 15, 15, 15, 10, 5, 1]