将此矩阵转换为压缩稀疏行格式
重复的条目将被汇总在一起。
Examples
--------
>>> from numpy import array
>>> from scipy.sparse import coo_matrix
>>> row = array([0, 0, 1, 3, 1, 0, 0])
>>> col = array([0, 2, 1, 3, 1, 0, 0])
>>> data = array([1, 1, 1, 1, 1, 1, 1])
>>> A = coo_matrix((data, (row, col)), shape=(4, 4)).tocsr()
>>> A.toarray()
array([[3, 0, 1, 0],
[0, 2, 0, 0],
[0, 0, 0, 0],
[0, 0, 0, 1]])
def tocsr(self, copy=False):
from .csr import csr_matrix
if self.nnz == 0:
return csr_matrix(self.shape, dtype=self.dtype)
else:
M,N = self.shape
idx_dtype = get_index_dtype((self.row, self.col),
maxval=max(self.nnz, N))
row = self.row.astype(idx_dtype, copy=False)
col = self.col.astype(idx_dtype, copy=False)
indptr = np.empty(M + 1, dtype=idx_dtype)
indices = np.empty_like(col, dtype=idx_dtype)
data = np.empty_like(self.data, dtype=upcast(self.dtype))
coo_tocsr(M, N, self.nnz, row, col, self.data,
indptr, indices, data)
x = csr_matrix((data, indices, indptr), shape=self.shape)
if not self.has_canonical_format:
x.sum_duplicates()
return x
