77 lines
1.9 KiB
Python
77 lines
1.9 KiB
Python
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""" Functions that operate on sparse matrices
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"""
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__all__ = ['count_blocks','estimate_blocksize']
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from ._base import issparse
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from ._csr import csr_array
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from ._sparsetools import csr_count_blocks
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def estimate_blocksize(A,efficiency=0.7):
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"""Attempt to determine the blocksize of a sparse matrix
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Returns a blocksize=(r,c) such that
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- A.nnz / A.tobsr( (r,c) ).nnz > efficiency
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"""
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if not (issparse(A) and A.format in ("csc", "csr")):
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A = csr_array(A)
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if A.nnz == 0:
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return (1,1)
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if not 0 < efficiency < 1.0:
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raise ValueError('efficiency must satisfy 0.0 < efficiency < 1.0')
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high_efficiency = (1.0 + efficiency) / 2.0
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nnz = float(A.nnz)
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M,N = A.shape
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if M % 2 == 0 and N % 2 == 0:
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e22 = nnz / (4 * count_blocks(A,(2,2)))
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else:
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e22 = 0.0
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if M % 3 == 0 and N % 3 == 0:
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e33 = nnz / (9 * count_blocks(A,(3,3)))
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else:
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e33 = 0.0
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if e22 > high_efficiency and e33 > high_efficiency:
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e66 = nnz / (36 * count_blocks(A,(6,6)))
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if e66 > efficiency:
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return (6,6)
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else:
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return (3,3)
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else:
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if M % 4 == 0 and N % 4 == 0:
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e44 = nnz / (16 * count_blocks(A,(4,4)))
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else:
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e44 = 0.0
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if e44 > efficiency:
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return (4,4)
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elif e33 > efficiency:
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return (3,3)
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elif e22 > efficiency:
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return (2,2)
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else:
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return (1,1)
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def count_blocks(A,blocksize):
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"""For a given blocksize=(r,c) count the number of occupied
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blocks in a sparse matrix A
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"""
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r,c = blocksize
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if r < 1 or c < 1:
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raise ValueError('r and c must be positive')
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if issparse(A):
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if A.format == "csr":
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M,N = A.shape
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return csr_count_blocks(M,N,r,c,A.indptr,A.indices)
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elif A.format == "csc":
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return count_blocks(A.T,(c,r))
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return count_blocks(csr_array(A),blocksize)
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