import pandas as pd
from d3blocks import D3Blocks

d3 = D3Blocks()
data = {
    'source': ['Alice', 'Alice', 'Bob', 'Charlie', 'Charlie', 'David'],
    'target': ['Bob', 'Charlie', 'Alice', 'David', 'Eve', 'Charlie'],
    'weight': [1, 2, 1, 3, 1, 2]
}
df = pd.DataFrame(data)

d3.d3graph(df, filepath='/tmp/network_demo.html')
    

 
from d3blocks import D3Blocks
import numpy as np

d3 = D3Blocks()
df = d3.import_example('mnist')  # 示例数据集

# 生成随机参数
size = np.random.randint(0, 8, df.shape[0])
opacity = np.random.randint(0, 8, df.shape[0]) / 10
tooltip = df['y'].values.astype(str)
    

 
df

y	cluster_labels	PC1	PC2	tsne_1	tsne_2
0	0	0	-23.998256	361.667670	-25.699284	-52.600788
1	1	5	129.010469	-332.193619	-3.978391	-10.591850
2	2	6	112.689047	-158.580078	-11.380729	12.682563
3	3	7	-269.850189	50.496232	2.136889	43.010288
4	4	2	371.270616	69.399040	5.807659	-38.236446
...	...	...	...	...	...	...
1792	9	7	-234.613707	212.784277	16.879385	36.290092
1793	0	0	99.805264	330.993093	-19.527739	-48.697876
1794	8	6	173.177929	-109.240458	-1.596314	9.206834
1795	9	7	-79.273808	198.656356	15.851237	31.635664
1796	8	6	-6.242530	101.231916	-0.565314	15.440125

 
d3.scatter(
    x=df['PC1'].values, y=df['PC2'].values,
    x1=df['tsne_1'].values, y1=df['tsne_2'].values,
    color=df['y'].values.astype(str), tooltip=tooltip,
    size=size, opacity=opacity, cmap='tab20',
    label_radio=['PCA', 'tSNE'],  # 改为列表类型
    filepath='/tmp/scatter_demo.html'
)

 
import pandas as pd
import matplotlib.pyplot as plt
import networkx as nx

# 创建示例数据
data = {
    'source': ['Alice', 'Alice', 'Bob', 'Charlie', 'Charlie', 'David'],
    'target': ['Bob', 'Charlie', 'Alice', 'David', 'Eve', 'Charlie'],
    'weight': [1, 2, 1, 3, 1, 2]
}
df = pd.DataFrame(data)

 
df
    source	target	weight
 0	Alice	Bob	1
 1	Alice	Charlie	2
 2	Bob	Alice	1
 3	Charlie	David	3
 4	Charlie	Eve	1
 5	David	Charlie	2
 

 
#  conda install pygraphviz

# 创建有向图对象
G = nx.from_pandas_edgelist(df, 'source', 'target', create_using=nx.DiGraph)

# 确定根节点（选择无父节点的节点）
roots = [node for node in G.nodes() if G.in_degree(node) == 0]

# 设置树形布局（根节点在上层）
pos = nx.nx_agraph.graphviz_layout(G, prog='dot', root=roots)

 
# 绘制图形
plt.figure(figsize=(10, 6))
nx.draw(G, pos, with_labels=True, node_size=800, node_color='lightblue', 
        arrows=True, font_size=10, edge_color='gray')
plt.title("Static Tree Structure")
plt.savefig('static_tree.png', dpi=120, bbox_inches='tight')
plt.show()

 
import pandas as pd
from d3blocks import D3Blocks

# Initialize
d3 = D3Blocks(verbose='info', chart='tree', frame=False)

data = {
    'source': ['A', 'A', 'B', 'C', 'C', 'D','E','E','H','H'],
    'target': ['B', 'C', 'F', 'D', 'E', 'H','I','J','L','M'],
    'weight': [100, 100, 2, 3, 3, 4,5,5,6,6]
}
df = pd.DataFrame(data)

# 初始化节点属性
d3.set_node_properties(df)

# 遍历所有节点进行统一设置
for node in d3.node_properties:
    d3.node_properties[node]['size'] = 10
    d3.node_properties[node]['color'] = '#1f77b4'
    d3.node_properties[node]['opacity'] = 0.8
    d3.node_properties[node]['edge_color'] = '#333'

# Set node properties
# d3.set_node_properties(df)
node_size = 25

node_name='M'
d3.node_properties.get(node_name)['size'] = node_size
d3.node_properties.get(node_name)['color'] = '#122178'
d3.node_properties.get(node_name)['tooltip'] = 'good:1000,bad:10<br><img src="img_20250401164847.png">'
d3.node_properties.get(node_name)['edge_color'] = '#00FFFF'
d3.node_properties.get(node_name)['edge_size'] = 5
d3.node_properties.get(node_name)['opacity'] = 0.4

node_name_2='L'
d3.node_properties.get(node_name_2)['size'] = node_size
d3.node_properties.get(node_name_2)['color'] = '#000000'
d3.node_properties.get(node_name_2)['tooltip'] = 'good:1000,bad:10<br><img src="img_20250401164847.png">'
d3.node_properties.get(node_name_2)['edge_color'] = '#00FFFF'
d3.node_properties.get(node_name_2)['edge_size'] = 5
d3.node_properties.get(node_name_2)['opacity'] = 0.4


node_name_3='F'
d3.node_properties.get(node_name_3)['size'] = node_size
d3.node_properties.get(node_name_3)['color'] = '#000000'
d3.node_properties.get(node_name_3)['tooltip'] = 'good:1000,bad:10<br><img src="img_20250401164847.png">'
d3.node_properties.get(node_name_3)['edge_color'] = '#00FFFF'
d3.node_properties.get(node_name_3)['edge_size'] = 5
d3.node_properties.get(node_name_3)['opacity'] = 0.4

# Set edge properties
d3.set_edge_properties(df)

# Show chart
d3.show(hierarchy=[1, 2, 3, 4, 5, 6, 7, 8], filepath=r'/tmp/tree.html',showfig=False)