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authorKatolaZ <katolaz@yahoo.it>2015-05-11 23:25:18 +0100
committerKatolaZ <katolaz@yahoo.it>2015-05-11 23:25:18 +0100
commit395bc7cb5ce0ffc49a3a316d847830b1dc61085f (patch)
tree3c17bc475efc71c2a3297b8352868c9a8bf95524 /python
parent7a69fe95e47f2dac5e264f36b2e63cf78f0e15c0 (diff)
Removed the last full matrix dangling around
Diffstat (limited to 'python')
-rw-r--r--python/multired.py20
1 files changed, 13 insertions, 7 deletions
diff --git a/python/multired.py b/python/multired.py
index 3952eec..0023d38 100644
--- a/python/multired.py
+++ b/python/multired.py
@@ -35,7 +35,7 @@
# --------------------------------------------
#
# -- 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:
self.adj_matr = copy.copy(matrix)
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 = 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 = K * eye(self.N)
self.laplacian = csr_matrix(D - self.adj_matr)
K = self.laplacian.diagonal().sum()
self.resc_laplacian = csr_matrix(self.laplacian / K)
@@ -135,8 +137,10 @@ class layer:
self.N = 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()
- K = np.multiply(self.adj_matr.sum(0), np.ones((self.N,self.N)))
- D = np.diag(np.diag(K))
+ #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 = K * eye(self.N)
self.laplacian = csr_matrix(D - self.adj_matr)
K = self.laplacian.diagonal().sum()
self.resc_laplacian = csr_matrix(self.laplacian / K)
@@ -171,8 +175,10 @@ class layer:
self.adj_matr = self.adj_matr + other_layer.adj_matr
else:
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 = 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 = K * eye(self.N)
self.laplacian = csr_matrix(D - self.adj_matr)
K = self.laplacian.diagonal().sum()
self.resc_laplacian = csr_matrix(self.laplacian / K)