通过csv的权值矩阵直接生产netdrawx的graph

可以使用Python中的pandas和networkx库来实现。

首先，读入csv文件并将其转换为pandas DataFrame：

import pandas as pd

df = pd.read_csv('matrix.csv', index_col=0)

接着，将DataFrame转换为权值字典：

weights = df.to_dict('index')

然后，使用networkx库创建图并添加节点和边：

import networkx as nx

G = nx.Graph()

# 添加节点
for node in df.index:
    G.add_node(node)

# 添加边
for source, targets in weights.items():
    for target, weight in targets.items():
        G.add_edge(source, target, weight=weight)

最后，使用netdrawx库将图渲染为可视化图形：

import netdrawx as ndx

# 渲染图形
ndx.draw(G)

完整代码如下：

import pandas as pd
import networkx as nx
import netdrawx as ndx

# 读入csv文件
df = pd.read_csv('matrix.csv', index_col=0)

# 转换为权值字典
weights = df.to_dict('index')

# 创建图并添加节点和边
G = nx.Graph()

for node in df.index:
    G.add_node(node)

for source, targets in weights.items():
    for target, weight in targets.items():
        G.add_edge(source, target, weight=weight)

# 渲染图形
ndx.draw(G)