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multired
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Removed the last full matrix dangling around

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master
KatolaZ 10 years ago
parent 7a69fe95e4
commit 395bc7cb5c
1 changed files with 13 additions and 7 deletions
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      python/multired.py

20
python/multired.py
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@ -35,7 +35,7 @@
# -------------------------------------------- # --------------------------------------------
# #
# -- 2015/04/23 -- release 0.1 # -- 2015/04/23 -- release 0.1
# # -- 2015/05/11 -- release 0.1.1 -- removed the last full matrices
# #
@ -123,8 +123,10 @@ class layer:
elif matrix != None: elif matrix != None:
self.adj_matr = copy.copy(matrix) self.adj_matr = copy.copy(matrix)
self.N, _x = matrix.shape self.N, _x = matrix.shape
K = np.multiply(self.adj_matr.sum(0), np.ones((self.N,self.N))) #K = np.multiply(self.adj_matr.sum(0), np.ones((self.N,self.N)))
D = np.diag(np.diag(K)) #D = np.diag(np.diag(K))
K = self.adj_matr.sum(0)
D = K * eye(self.N)
self.laplacian = csr_matrix(D - self.adj_matr) self.laplacian = csr_matrix(D - self.adj_matr)
K = self.laplacian.diagonal().sum() K = self.laplacian.diagonal().sum()
self.resc_laplacian = csr_matrix(self.laplacian / K) self.resc_laplacian = csr_matrix(self.laplacian / K)
@ -135,8 +137,10 @@ class layer:
self.N = N self.N = N
self.adj_matr = csr_matrix((self._ww, (self._ii, self._jj)), shape=(self.N, self.N)) self.adj_matr = csr_matrix((self._ww, (self._ii, self._jj)), shape=(self.N, self.N))
self.adj_matr = self.adj_matr + self.adj_matr.transpose() self.adj_matr = self.adj_matr + self.adj_matr.transpose()
K = np.multiply(self.adj_matr.sum(0), np.ones((self.N,self.N))) #K = np.multiply(self.adj_matr.sum(0), np.ones((self.N,self.N)))
D = np.diag(np.diag(K)) #D = np.diag(np.diag(K))
K = self.adj_matr.sum(0)
D = K * eye(self.N)
self.laplacian = csr_matrix(D - self.adj_matr) self.laplacian = csr_matrix(D - self.adj_matr)
K = self.laplacian.diagonal().sum() K = self.laplacian.diagonal().sum()
self.resc_laplacian = csr_matrix(self.laplacian / K) self.resc_laplacian = csr_matrix(self.laplacian / K)
@ -171,8 +175,10 @@ class layer:
self.adj_matr = self.adj_matr + other_layer.adj_matr self.adj_matr = self.adj_matr + other_layer.adj_matr
else: else:
self.adj_matr = copy.copy(other_layer.adj_matr) self.adj_matr = copy.copy(other_layer.adj_matr)
K = np.multiply(self.adj_matr.sum(0), np.ones((self.N,self.N))) #K = np.multiply(self.adj_matr.sum(0), np.ones((self.N,self.N)))
D = np.diag(np.diag(K)) #D = np.diag(np.diag(K))
K = self.adj_matr.sum(0)
D = K * eye(self.N)
self.laplacian = csr_matrix(D - self.adj_matr) self.laplacian = csr_matrix(D - self.adj_matr)
K = self.laplacian.diagonal().sum() K = self.laplacian.diagonal().sum()
self.resc_laplacian = csr_matrix(self.laplacian / K) self.resc_laplacian = csr_matrix(self.laplacian / K)

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