Padding

This notebooks shows how to pad a signal under various boudary conditions.

In [1]:

import torch
from bounds import  pad
import matplotlib.pyplot as plt

import torch from bounds import pad import matplotlib.pyplot as plt

In [5]:

x = torch.arange(16)[None, :] + torch.arange(16)[:, None]

modes = ('zero', 'constant', 'replicate', 'dft', 'dct1', 'dct2', 'dst1', 'dst2')

for i, mode in enumerate(modes):
    plt.subplot(2, 4, i+1)
    opt = dict(value=128) if mode == 'constant' else {}
    plt.imshow(pad(x, [8, 8], side='both', mode=mode, **opt))
    plt.axis('off')
    plt.title(mode)
plt.show()

x = torch.arange(16)[None, :] + torch.arange(16)[:, None] modes = ('zero', 'constant', 'replicate', 'dft', 'dct1', 'dct2', 'dst1', 'dst2') for i, mode in enumerate(modes): plt.subplot(2, 4, i+1) opt = dict(value=128) if mode == 'constant' else {} plt.imshow(pad(x, [8, 8], side='both', mode=mode, **opt)) plt.axis('off') plt.title(mode) plt.show()