# scipy/scipy

### Subversion checkout URL

You can clone with
or
.
Fetching contributors…

Cannot retrieve contributors at this time

97 lines (80 sloc) 2.759 kB
 """ Functions that operate on sparse matrices """ __all__ = ['count_blocks','estimate_blocksize'] from csr import isspmatrix_csr, csr_matrix from csc import isspmatrix_csc from sparsetools import csr_count_blocks def extract_diagonal(A): raise NotImplementedError('use .diagonal() instead') #def extract_diagonal(A): # """extract_diagonal(A) returns the main diagonal of A.""" # #TODO extract k-th diagonal # if isspmatrix_csr(A) or isspmatrix_csc(A): # fn = getattr(sparsetools, A.format + "_diagonal") # y = empty( min(A.shape), dtype=upcast(A.dtype) ) # fn(A.shape[0],A.shape[1],A.indptr,A.indices,A.data,y) # return y # elif isspmatrix_bsr(A): # M,N = A.shape # R,C = A.blocksize # y = empty( min(M,N), dtype=upcast(A.dtype) ) # fn = sparsetools.bsr_diagonal(M//R, N//C, R, C, \ # A.indptr, A.indices, ravel(A.data), y) # return y # else: # return extract_diagonal(csr_matrix(A)) def estimate_blocksize(A,efficiency=0.7): """Attempt to determine the blocksize of a sparse matrix Returns a blocksize=(r,c) such that - A.nnz / A.tobsr( (r,c) ).nnz > efficiency """ if not (isspmatrix_csr(A) or isspmatrix_csc(A)): A = csr_matrix(A) if A.nnz == 0: return (1,1) if not 0 < efficiency < 1.0: raise ValueError('efficiency must satisfy 0.0 < efficiency < 1.0') high_efficiency = (1.0 + efficiency) / 2.0 nnz = float(A.nnz) M,N = A.shape if M % 2 == 0 and N % 2 == 0: e22 = nnz / ( 4 * count_blocks(A,(2,2)) ) else: e22 = 0.0 if M % 3 == 0 and N % 3 == 0: e33 = nnz / ( 9 * count_blocks(A,(3,3)) ) else: e33 = 0.0 if e22 > high_efficiency and e33 > high_efficiency: e66 = nnz / ( 36 * count_blocks(A,(6,6)) ) if e66 > efficiency: return (6,6) else: return (3,3) else: if M % 4 == 0 and N % 4 == 0: e44 = nnz / ( 16 * count_blocks(A,(4,4)) ) else: e44 = 0.0 if e44 > efficiency: return (4,4) elif e33 > efficiency: return (3,3) elif e22 > efficiency: return (2,2) else: return (1,1) def count_blocks(A,blocksize): """For a given blocksize=(r,c) count the number of occupied blocks in a sparse matrix A """ r,c = blocksize if r < 1 or c < 1: 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) elif isspmatrix_csc(A): return count_blocks(A.T,(c,r)) else: return count_blocks(csr_matrix(A),blocksize)
Something went wrong with that request. Please try again.