Interpolation & Convolution.

convolution.py

import numpy as np
import torch
import matplotlib.pyplot as plt

# Create a tensor
a = torch.tensor(data=[0, 0, -3, -1, 1, 3, 0, 0, 0], dtype=torch.float)
b = torch.tensor(data=[0, 0.5, 1.5, 3, 3.5, 3, 1.5, 0.5, 0], dtype=torch.float)

# We need a 3d tensor for interpolation
a = a.unsqueeze(0).unsqueeze(0)
b = b.unsqueeze(0).unsqueeze(0)

# Interpolate a and b for better convolution resolution
a = torch.nn.functional.interpolate(
    input=a,
    size=1000,
    mode='linear'
).squeeze(0).squeeze(0)

b = torch.nn.functional.interpolate(
    input=b,
    size=1000,
    mode='linear'
)

# Squeeze the tensor back to 1d
a = a.squeeze(0).squeeze(0)
b = b.squeeze(0).squeeze(0)

# Do a convolution: a * b
c = np.convolve(
    a=a.numpy(),
    v=b.numpy(),
    mode='same'
)

# Plot the original data
plt.plot(a, 'r')
plt.plot(b, 'g')
plt.show()

# Plot the convolution
plt.plot(c, 'b')
plt.show()