def granger_partial_r(i): ''' Depracated ''' n = i.n_nodes cc = granger_r(i) ccc_mean = np.zeros((n, n)) ccc_max = np.zeros((n, n)) ccc_min = np.zeros((n, n)) ccc = np.zeros((n, n, n)) granger_a = load_r_file('gc1a.R', "granger_a") for ii in range(n): xii, _ = i.get(ii) for jj in range(n): xjj, _ = i.get(jj) for kk in range(n): xkk, _ = i.get(kk) d = np.vstack((xii.T, xjj.T, xkk.T)).T temp = granger_a.granger_part(d, 1)[0] if math.isnan(temp) or math.isinf(temp): temp = 0.0 ccc[ii][jj][kk] = temp ccc_mean[ii][jj] = np.mean(ccc[ii][jj][:]) ccc_max[ii][jj] = np.max(ccc[ii][jj][:]) ccc_min[ii][jj] = np.min(ccc[ii][jj][:]) return ccc_max
def granger_r(x1, x2): d = np.vstack((np.matrix(x1), np.matrix(x2))).T granger_a = load_r_file('gc1a.R', "granger_a") return granger_a.granger(d, 1)[0]