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# csr.isspmatrix_csr

All Samples(10)  |  Call(6)  |  Derive(0)  |  Import(4)

```__all__ = ['count_blocks','estimate_blocksize']

from .csr import isspmatrix_csr, csr_matrix
from .csc import isspmatrix_csc
from .sparsetools import csr_count_blocks
```
```        - A.nnz / A.tobsr( (r,c) ).nnz > efficiency
"""
if not (isspmatrix_csr(A) or isspmatrix_csc(A)):
A = csr_matrix(A)

```
```        raise ValueError('r and c must be positive')

if isspmatrix_csr(A):
M,N = A.shape
return csr_count_blocks(M,N,r,c,A.indptr,A.indices)
```

```__all__ = ['count_blocks','estimate_blocksize']

from csr import isspmatrix_csr, csr_matrix
from csc import isspmatrix_csc
from sparsetools import csr_count_blocks
```
```        - A.nnz / A.tobsr( (r,c) ).nnz > efficiency
"""
if not (isspmatrix_csr(A) or isspmatrix_csc(A)):
A = csr_matrix(A)

```
```        raise ValueError('r and c must be positive')

if isspmatrix_csr(A):
M,N = A.shape
return csr_count_blocks(M,N,r,c,A.indptr,A.indices)
```

```            C = 1

from .csr import isspmatrix_csr

if isspmatrix_csr(other) and n == 1:
```

```            C = 1