Merge branch 'lightK'

Conflicts:
	python/multired.py
master
KatolaZ 10 years ago
commit f6c8d6f869
  1. 18
      python/multired.py

@ -35,6 +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
# #
@ -122,8 +123,8 @@ 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 = self.adj_matr.sum(0).reshape((1, self.N)).tolist()[0]
D = np.diag(np.diag(K)) D = csr_matrix((K, (range(self.N), range(self.N)) ), shape=(self.N, 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)
@ -134,13 +135,13 @@ 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 = self.adj_matr.sum(0).reshape((1, self.N)).tolist()[0]
D = np.diag(np.diag(K)) D = csr_matrix((K, (range(self.N), range(self.N)) ), shape=(self.N, 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)
self._matrix_called = True self._matrix_called = True
def dump_info(self): def dump_info(self):
N, M = self.adj_matr.shape N, M = self.adj_matr.shape
K = self.adj_matr.nnz K = self.adj_matr.nnz
@ -170,14 +171,15 @@ 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 = self.adj_matr.sum(0).reshape((1, self.N)).tolist()[0]
D = np.diag(np.diag(K)) D = csr_matrix((K, (range(self.N), range(self.N)) ), shape=(self.N, 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)
self._matrix_called = True self._matrix_called = True
def dump_laplacian(self):
print self.laplacian
class multiplex_red: class multiplex_red:

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