File size: 1,914 Bytes
2dd33e7
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
#!/usr/bin/env python3
"""
Plot a single sample from the KdV-Burgers dataset.
"""

import numpy as np
import matplotlib.pyplot as plt
from burgers_dataset import KdvBurgersDataset

def plot_kdv_burgers_sample(sample, save_path="sample_plot.png"):
    """Plot a single sample from the KdV-Burgers dataset"""
    fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12, 5))
    
    # Extract data using descriptive naming
    spatial_coordinates = sample['spatial_coordinates']
    u_initial = sample['u_initial']
    u_trajectory = sample['u_trajectory']
    time_coordinates = sample['time_coordinates']
    
    # Plot initial condition
    ax1.plot(spatial_coordinates, u_initial, 'b-', linewidth=2)
    ax1.set_xlabel('x')
    ax1.set_ylabel('u(x, t=0)')
    ax1.set_title('Initial Condition')
    ax1.grid(True, alpha=0.3)
    ax1.set_xlim(0, spatial_coordinates[-1])
    
    # Plot space-time evolution
    im = ax2.pcolormesh(
        spatial_coordinates,
        time_coordinates,
        u_trajectory,
        cmap="RdBu_r",
        shading="gouraud",
        rasterized=True,
    )
    ax2.set_xlim(0, spatial_coordinates[-1])
    ax2.set_ylim(0, time_coordinates[-1])
    ax2.set_xlabel('x')
    ax2.set_ylabel('t')
    ax2.set_title("KdV-Burgers Evolution")
    
    # Add colorbar
    plt.colorbar(im, ax=ax2, label='u(x,t)')
    
    plt.tight_layout()
    plt.savefig(save_path, dpi=200, bbox_inches='tight')
    plt.close()
    
    print(f"Sample visualization saved to {save_path}")

if __name__ == "__main__":
    # Set random seed for reproducibility
    np.random.seed(42)
    
    # Create dataset
    dataset = KdvBurgersDataset()
    
    # Generate a single sample
    sample = next(iter(dataset))
    
    print("Sample keys:", list(sample.keys()))
    for key, value in sample.items():
        print(f"{key}: shape {value.shape}")
    
    # Plot the sample
    plot_kdv_burgers_sample(sample)