有效地初始化一个numpy稀疏矩阵

1 回答

• 1

  您的数据已接近csr格式，因此我建议使用：

  import numpy as np
  from scipy import sparse
  from itertools import chain
  
  # create an example    
  m, n = 20, 10
  X = np.random.random((m, n)) < 0.1
  Y = [list(np.where(y)[0]) for y in X]
  
  # construct the sparse matrix
  indptr = np.fromiter(chain((0,), map(len, Y)), int, len(Y) + 1).cumsum()
  indices = np.fromiter(chain.from_iterable(Y), int, indptr[-1])
  data = np.ones_like(indices)    
  S = sparse.csr_matrix((data, indices, indptr), (m, n))
  # or    
  S = sparse.csr_matrix((data, indices, indptr))
  
  # check
  assert np.all(S==X)
  

  回复于 2024-04-28T11:56:38+08:00