def __call__(self, X):
        X = X.T
        m, n = X.shape
        mean = X.mean(axis=0)
        rval = N.zeros((n, n))
        for i in xrange(0, m, self.batch_size):
            B = X[i:i + self.batch_size, :] - mean
            rval += N.dot(B.T, B)
        return rval / float(m - 1)
.. todo::
dataset/ETHPy150Open lisa-lab/pylearn2/pylearn2/models/pca.py/Cov.__call__