Page MenuHomec4science
Files F60270217

rg.py
No OneTemporary
Actions

File Metadata

Created
Sun, Apr 28, 19:29

rg.py
View Options

# Random Gabors
import numpy as np
import random
from weightmatrices.utils import utils
def get_gabor_kernel(lbda, theta, psi, sigma, gamma, N):
w = np.zeros((N, N))
rm = np.array([[np.cos(theta), np.sin(theta)],[-np.sin(theta), np.cos(theta)]])
for x in range(N):
for y in range(N):
r = np.matmul(rm, np.array([x, y])-(N/2))
w[x, y] = np.exp(-(r[0]**2 + gamma**2*r[1]**2)/(2*sigma**2)) * np.cos(2*np.pi*r[0]/lbda + psi)
return w
# these are heuristic boundaries for random Gabors
def get_random_gabor(N):
return get_gabor_kernel((2*N-N/4)*random.random()+N/4,
2*np.pi*random.random(), 2*np.pi*random.random(),
(N-N/8)*random.random()+N/8, random.random(), N)
def get_weightmatrices_rg(data_matrix, n_h):
N = int(np.sqrt(data_matrix.shape[1]))
W = np.zeros((n_h, N**2))
for i in range(n_h):
W[i, :] = get_random_gabor(N).flatten()
W = utils.normalise_weightmatrix(W)
return W

Event Timeline

c4science · Help