Advanced Usage

import deepvisual as dv
import pandas as pd
import numpy as np
 
# Sample data
df = pd.DataFrame({
    'from': ['A', 'B', 'C', 'D'],
    'to': ['B', 'C', 'D', 'A']
})
 
# Custom positions
custom_positions = {
    'A': (0, 0),
    'B': (1, 1),
    'C': (2, 0),
    'D': (1, -1)
}
 
# Create visualization with custom layout
fig, ax = plt.subplots(figsize=(10, 8))
dv.visualize_doblet_graph(
    df,
    node_positions=custom_positions,
    edge_color="blue",
    node_text_color="black"
)

import deepvisual as dv
import pandas as pd
import matplotlib.pyplot as plt
 
# Create subplots
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(15, 6))
 
# First visualization
df1 = pd.DataFrame({
    'from': ['A', 'B', 'C'],
    'to': ['B', 'C', 'A']
})
dv.visualize_link_doublet(df1, ax=ax1, title='First Graph')
 
# Second visualization
df2 = pd.DataFrame({
    'from': ['X', 'Y', 'Z'],
    'to': ['Y', 'Z', 'X']
})
dv.visualize_link_doublet(df2, ax=ax2, title='Second Graph')
 
plt.tight_layout()
plt.show()

import deepvisual as dv
import pandas as pd
from matplotlib.patches import ArrowStyle
 
# Sample data
df = pd.DataFrame({
    'from': ['Start', 'Process', 'End'],
    'to': ['Process', 'End', 'Start']
})
 
# Custom arrow style
custom_style = ArrowStyle.CurveFilledB(head_length=0.8, head_width=0.6)
 
# Create visualization with custom arrow style
dv.visualize_doblet_graph(
    df,
    arrow_style=custom_style,
    edge_color="red",
    node_text_color="black"
)

import deepvisual as dv
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.widgets import Button
 
# Sample data
df = pd.DataFrame({
    'from': ['A', 'B', 'C'],
    'to': ['B', 'C', 'A']
})
 
# Create figure with button
fig = plt.figure(figsize=(10, 8))
ax = fig.add_subplot(111)
button_ax = fig.add_axes([0.7, 0.05, 0.2, 0.075])
button = Button(button_ax, 'Change Colors')
 
# Initial visualization
viz = dv.visualize_link_doublet(df, ax=ax)
 
# Button click handler
def change_colors(event):
    viz.set_edge_color('green')
    viz.set_node_color('purple')
    fig.canvas.draw()
 
button.on_clicked(change_colors)
plt.show()

import deepvisual as dv
import pandas as pd
import numpy as np
 
# Generate large dataset
n_nodes = 100
nodes = [f'Node_{i}' for i in range(n_nodes)]
df = pd.DataFrame({
    'from': np.random.choice(nodes, 1000),
    'to': np.random.choice(nodes, 1000)
})
 
# Optimize visualization
dv.visualize_doblet_graph(
    df,
    node_text_visible=False,  # Hide node labels for better performance
    edge_color="gray",
    background_color="white",
    figsize=(15, 15)
)

import deepvisual as dv
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.colors import LinearSegmentedColormap
 
# Create custom colormap
colors = ['red', 'yellow', 'green']
cmap = LinearSegmentedColormap.from_list('custom', colors)
 
# Sample data
df = pd.DataFrame({
    'from': ['A', 'B', 'C', 'D'],
    'to': ['B', 'C', 'D', 'A'],
    'weight': [0.2, 0.5, 0.8, 1.0]  # Edge weights
})
 
# Create visualization with custom colormap
dv.visualize_doblet_graph(
    df,
    edge_color=cmap(df['weight']),
    node_text_color="black",
    background_color="white"
)