def cov_embedding(covariances): """Returns for a list of matrices a list of transformed matrices in matrix form, with 1. on the diagonal """ ce = CovEmbedding() covariances = ce.fit_transform(covariances) # shape n(n+1)/2 if covariances is None: return None # changed from k=1 to k=0 by Salma return np.asarray([untri(c, k=0, fill=1.) for c in covariances])
def cov_embedding(covariances): ce = CovEmbedding() covariances = ce.fit_transform(covariances) if covariances is None: return None return np.asarray([untri(c, k=1, fill=1.0) for c in covariances])