def tocsr(self):
"""Return a copy of this matrix in Compressed Sparse Row format
Duplicate entries will be summed together.
Example
-------
>>> 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.todense()
matrix([[3, 0, 1, 0],
[0, 2, 0, 0],
[0, 0, 0, 0],
[0, 0, 0, 1]])
"""
from csr import csr_matrix
if self.nnz == 0:
return csr_matrix(self.shape, dtype=self.dtype)
else:
M,N = self.shape
indptr = np.empty(M + 1, dtype=np.intc)
indices = np.empty(self.nnz, dtype=np.intc)
data = np.empty(self.nnz, dtype=upcast(self.dtype))
coo_tocsr(M, N, self.nnz, \
self.row, self.col, self.data, \
indptr, indices, data)
A = csr_matrix((data, indices, indptr), shape=self.shape)
A.sum_duplicates()
return A
def tocsr(self):
"""Return a copy of this matrix in Compressed Sparse Row format
Duplicate entries will be summed together.
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.todense()
matrix([[3, 0, 1, 0],
[0, 2, 0, 0],
[0, 0, 0, 0],
[0, 0, 0, 1]])
"""
from csr import csr_matrix
if self.nnz == 0:
return csr_matrix(self.shape, dtype=self.dtype)
else:
M, N = self.shape
indptr = np.empty(M + 1, dtype=np.intc)
indices = np.empty(self.nnz, dtype=np.intc)
data = np.empty(self.nnz, dtype=upcast(self.dtype))
coo_tocsr(M, N, self.nnz, \
self.row, self.col, self.data, \
indptr, indices, data)
A = csr_matrix((data, indices, indptr), shape=self.shape)
A.sum_duplicates()
return A
