From 29cc00c2d4dd86d6649d4ddd676601ecae943b6d Mon Sep 17 00:00:00 2001 From: KatolaZ Date: Tue, 12 May 2015 00:36:26 +0100 Subject: [PATCH] more efficient costruction of the Laplacian --- python/multired.py | 22 +++++++++++++--------- 1 file changed, 13 insertions(+), 9 deletions(-) diff --git a/python/multired.py b/python/multired.py index be5ddbf..f885c12 100644 --- a/python/multired.py +++ b/python/multired.py @@ -125,9 +125,11 @@ class layer: self.N, _x = matrix.shape #K = np.multiply(self.adj_matr.sum(0), np.ones((self.N,self.N))) #D = np.diag(np.diag(K)) - K = self.adj_matr.sum(0) - D = csr_matrix((self.N, self.N)) - D.setdiag(eye(self.N) * K.transpose()) + K = self.adj_matr.sum(0).reshape((1, self.N)).tolist()[0] + D = csr_matrix((K, (range(self.N), range(self.N)) ), shape=(self.N, self.N)) + #K = self.adj_matr.sum(0) + #D = csr_matrix((self.N, self.N)) + #D.setdiag(eye(self.N) * K.transpose()) self.laplacian = csr_matrix(D - self.adj_matr) K = self.laplacian.diagonal().sum() self.resc_laplacian = csr_matrix(self.laplacian / K) @@ -140,9 +142,9 @@ class layer: self.adj_matr = self.adj_matr + self.adj_matr.transpose() #K = np.multiply(self.adj_matr.sum(0), np.ones((self.N,self.N))) #D = np.diag(np.diag(K)) - K = self.adj_matr.sum(0) - D = csr_matrix((self.N, self.N)) - D.setdiag(eye(self.N) * K.transpose()) + K = self.adj_matr.sum(0).reshape((1, self.N)).tolist()[0] + D = csr_matrix((K, (range(self.N), range(self.N)) ), shape=(self.N, self.N)) + #D.setdiag(eye(self.N) * K.transpose()) self.laplacian = csr_matrix(D - self.adj_matr) K = self.laplacian.diagonal().sum() self.resc_laplacian = csr_matrix(self.laplacian / K) @@ -179,9 +181,11 @@ class layer: self.adj_matr = copy.copy(other_layer.adj_matr) #K = np.multiply(self.adj_matr.sum(0), np.ones((self.N,self.N))) #D = np.diag(np.diag(K)) - K = self.adj_matr.sum(0) - D = csr_matrix((self.N, self.N)) - D.setdiag(eye(self.N) * K. transpose()) + K = self.adj_matr.sum(0).reshape((1, self.N)).tolist()[0] + D = csr_matrix((K, (range(self.N), range(self.N)) ), shape=(self.N, self.N)) + #K = self.adj_matr.sum(0) + #D = csr_matrix((self.N, self.N)) + #D.setdiag(eye(self.N) * K. transpose()) self.laplacian = csr_matrix(D - self.adj_matr) K = self.laplacian.diagonal().sum() self.resc_laplacian = csr_matrix(self.laplacian / K)