loss_function.py

def _compute_loss_function(self, X, pi, mu, sigma):
    """Computes lower bound loss function
        
    Parameters:
    -----------
    X: (N x d), data 
        
    Returns:
    ---------
    pi: (C)
    mu: (C x d)
    sigma: (C x d x d)
    """
    N = X.shape[0]
    C = self.gamma.shape[1]
    self.loss = np.zeros((N, C))

    for c in range(C):
        dist = mvn(self.mu[c], self.sigma[c],allow_singular=True)
        self.loss[:,c] = self.gamma[:,c] * (np.log(self.pi[c]+0.00001)+dist.logpdf(X)-np.log(self.gamma[:,c]+0.000001))
    self.loss = np.sum(self.loss)
    return self.loss