用scipy库生成稀疏矩阵

方法一：

?

1 2 3 4 5 6 7 8

import scipy as spy from scipy.sparse import csc_matrix   m = 2 n = 3 A = spy.sparse.rand(m, n, density=0.5, format='csc', dtype=None).toarray() print(A)   # [[0.         0.12812445 0.23608898]            #  [0.99904052 0.         0.        ]]

 

方法二：

?

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

import scipy as spy from scipy.sparse import csc_matrix   m = 2 n = 3 A = spy.sparse.rand(m, n, density=0.5, format='csc', dtype=None) print(A)   #  (0, 0)    0.538816734003357            #  (0, 1)    0.39676747423066994            #  (1, 2)    0.4191945144032948   print(A.nonzero())  # (array([0, 0, 1], dtype=int32), array([0, 1, 2], dtype=int32)) print(A.data)       # [0.53881673 0.39676747 0.41919451]   matrix = csc_matrix((A.data, (A.nonzero()[0], A.nonzero()[1])), shape=(m, n)).toarray() print(matrix)       # [[0.53881673 0.39676747 0.        ]                     #  [0.         0.         0.41919451]]