numerics.py 文件源码

def unvech_kh(v, cols_stacked=True, norm_conserved=False):
    # Restore matrix dimension and add triangular
    v = v.flatten()
    d = int(0.5 * (np.sqrt(8 * len(v) + 1) - 1))
    X = np.empty((d, d))
    triu_idx_r = []
    triu_idx_c = []
    # Find appropriate indexes
    if cols_stacked:
        for c in range(0, d):
            for r in range(0, c+1):
                triu_idx_r.append(r)
                triu_idx_c.append(c)
    else:
        for r in range(0, d):
            for c in range(r, d):
                triu_idx_r.append(r)
                triu_idx_c.append(c)
    # Restore original matrix
    triu_idx = (triu_idx_r, triu_idx_c)
    X[triu_idx] = v
    X[np.tril_indices(d)] = X.T[np.tril_indices(d)]
    # Undo rescaling on off diagonal elements
    if norm_conserved:
        X[np.triu_indices(d, 1)] /= np.sqrt(2)
        X[np.tril_indices(d, -1)] /= np.sqrt(2)
    return X