def _get_kernel(self, X, y = None):
if self.kernel == "rbf":
if y is None:
return pairwise.rbf_kernel(X, X, gamma = self.gamma)
else:
return pairwise.rbf_kernel(X, y, gamma = self.gamma)
elif self.kernel == "img":
return self._img_rbf_kernel(X)
elif self.kernel == "knn":
if self.nn_fit is None:
self.nn_fit = NearestNeighbors(self.n_neighbors).fit(X)
if y is None:
return self.nn_fit.kneighbors_graph(self.nn_fit._fit_X,
self.n_neighbors, mode = 'connectivity')
else:
return self.nn_fit.kneighbors(y, return_distance = False)
else:
raise ValueError("%s is not a valid kernel. Only rbf and knn"
" are supported at this time" % self.kernel)
def _img_rbf_kernel(self, X):
A = np.diag(np.ones(X.shape[0]))
index = 0
for i in range(0, self.img_dims[1]):
for j in range(0, self.img_dims[0]):
if i - 1 >= 0:
# Directly above.
other = index - self.img_dims[0]
rbf = pairwise.rbf_kernel(X[index], X[other], gamma = self.gamma)
A[index, other] = rbf
A[other, index] = rbf
if i + 1 < self.img_dims[1]:
# Directly below.
other = index + self.img_dims[0]
rbf = pairwise.rbf_kernel(X[index], X[other], gamma = self.gamma)
A[index, other] = rbf
A[other, index] = rbf
if j - 1 >= 0:
# Directly to the left.
other = index - 1
rbf = pairwise.rbf_kernel(X[index], X[other], gamma = self.gamma)
A[index, other] = rbf
A[other, index] = rbf
if j + 1 < self.img_dims[0]:
# Directly to the right.
other = index + 1
rbf = pairwise.rbf_kernel(X[index], X[other], gamma = self.gamma)
A[index, other] = rbf
A[other, index] = rbf
if i - 1 >= 0 and j - 1 >= 0:
# Upper left corner.
other = index - self.img_dims[0] - 1
rbf = pairwise.rbf_kernel(X[index], X[other], gamma = self.gamma)
A[index, other] = rbf
A[other, index] = rbf
if i - 1 >= 0 and j + 1 < self.img_dims[0]:
# Upper right corner.
other = index - self.img_dims[0] + 1
rbf = pairwise.rbf_kernel(X[index], X[other], gamma = self.gamma)
A[index, other] = rbf
A[other, index] = rbf
if i + 1 < self.img_dims[1] and j - 1 >= 0:
# Lower left corner.
other = index + self.img_dims[0] - 1
rbf = pairwise.rbf_kernel(X[index], X[other], gamma = self.gamma)
A[index, other] = rbf
A[other, index] = rbf
if i + 1 < self.img_dims[1] and j + 1 < self.img_dims[0]:
# Lower right corner.
other = index + self.img_dims[0] + 1
rbf = pairwise.rbf_kernel(X[index], X[other], gamma = self.gamma)
A[index, other] = rbf
A[other, index] = rbf
index += 1
return scipy.sparse.csc_matrix(A)