'NameError: name 'cpca_alpha' is not defined' while using Kernel cPCA

[tauhidstanford]

When I am trying to use Kernel cPCA, it is throwing the following error “NameError: name 'cpca_alpha' is not defined”.

The code snippet is similar to that is used for cPCA and looks like this:

import numpy as np
from contrastive import Kernel_CPCA

N = 400; D = 30; gap=3

In B, all the data pts are from the same distribution, which has different variances in three subspaces.

B = np.zeros((N, D))
B[:,0:10] = np.random.normal(0,10,(N,10))
B[:,10:20] = np.random.normal(0,3,(N,10))
B[:,20:30] = np.random.normal(0,1,(N,10))

In A there are four clusters.

A = np.zeros((N, D))
A[:,0:10] = np.random.normal(0,10,(N,10))

group 1

A[0:100, 10:20] = np.random.normal(0,1,(100,10))
A[0:100, 20:30] = np.random.normal(0,1,(100,10))

group 2

A[100:200, 10:20] = np.random.normal(0,1,(100,10))
A[100:200, 20:30] = np.random.normal(gap,1,(100,10))

group 3

A[200:300, 10:20] = np.random.normal(2*gap,1,(100,10))
A[200:300, 20:30] = np.random.normal(0,1,(100,10))

group 4

A[300:400, 10:20] = np.random.normal(2*gap,1,(100,10))
A[300:400, 20:30] = np.random.normal(gap,1,(100,10))
A_labels = [0]*100+[1]*100+[2]*100+[3]*100

cpca = Kernel_CPCA(standardize=False)
cpca.fit_transform(A, B, plot=False, active_labels=A_labels)