def check_format(self, full_check=True):
"""check whether the matrix format is valid
*Parameters*:
full_check:
True - rigorous check, O(N) operations : default
False - basic check, O(1) operations
"""
M, N = self.shape
R, C = self.blocksize
# index arrays should have integer data types
if self.indptr.dtype.kind != 'i':
warn("indptr array has non-integer dtype (%s)" \
% self.indptr.dtype.name )
if self.indices.dtype.kind != 'i':
warn("indices array has non-integer dtype (%s)" \
% self.indices.dtype.name )
# only support 32-bit ints for now
self.indptr = np.asarray(self.indptr, np.intc)
self.indices = np.asarray(self.indices, np.intc)
self.data = to_native(self.data)
# check array shapes
if np.rank(self.indices) != 1 or np.rank(self.indptr) != 1:
raise ValueError, "indices, and indptr should be rank 1"
if np.rank(self.data) != 3:
raise ValueError, "data should be rank 3"
# check index pointer
if (len(self.indptr) != M / R + 1):
raise ValueError, \
"index pointer size (%d) should be (%d)" % \
(len(self.indptr), M/R + 1)
if (self.indptr[0] != 0):
raise ValueError, "index pointer should start with 0"
# check index and data arrays
if (len(self.indices) != len(self.data)):
raise ValueError, "indices and data should have the same size"
if (self.indptr[-1] > len(self.indices)):
raise ValueError, \
"Last value of index pointer should be less than "\
"the size of index and data arrays"
self.prune()
if full_check:
#check format validity (more expensive)
if self.nnz > 0:
if self.indices.max() >= N / C:
print "max index", self.indices.max()
raise ValueError, "column index values must be < %d" % (N /
C)
if self.indices.min() < 0:
raise ValueError, "column index values must be >= 0"
if diff(self.indptr).min() < 0:
raise ValueError, 'index pointer values must form a " \
def _check(self):
""" Checks data structure for consistency """
nnz = self.nnz
# index arrays should have integer data types
if self.row.dtype.kind != 'i':
warn("row index array has non-integer dtype (%s) " \
% self.row.dtype.name )
if self.col.dtype.kind != 'i':
warn("col index array has non-integer dtype (%s) " \
% self.col.dtype.name )
# only support 32-bit ints for now
self.row = np.asarray(self.row, dtype=np.intc)
self.col = np.asarray(self.col, dtype=np.intc)
self.data = to_native(self.data)
if nnz > 0:
if self.row.max() >= self.shape[0]:
raise ValueError('row index exceedes matrix dimensions')
if self.col.max() >= self.shape[1]:
raise ValueError('column index exceedes matrix dimensions')
if self.row.min() < 0:
raise ValueError('negative row index found')
if self.col.min() < 0:
raise ValueError('negative column index found')
def _check(self):
""" Checks data structure for consistency """
nnz = self.nnz
# index arrays should have integer data types
if self.row.dtype.kind != 'i':
warn("row index array has non-integer dtype (%s) " \
% self.row.dtype.name )
if self.col.dtype.kind != 'i':
warn("col index array has non-integer dtype (%s) " \
% self.col.dtype.name )
# only support 32-bit ints for now
self.row = np.asarray(self.row, dtype=np.intc)
self.col = np.asarray(self.col, dtype=np.intc)
self.data = to_native(self.data)
if nnz > 0:
if self.row.max() >= self.shape[0]:
raise ValueError('row index exceedes matrix dimensions')
if self.col.max() >= self.shape[1]:
raise ValueError('column index exceedes matrix dimensions')
if self.row.min() < 0:
raise ValueError('negative row index found')
if self.col.min() < 0:
raise ValueError('negative column index found')
def check_format(self, full_check=True):
"""check whether the matrix format is valid
Parameters
==========
- full_check : {bool}
- True - rigorous check, O(N) operations : default
- False - basic check, O(1) operations
"""
#use _swap to determine proper bounds
major_name,minor_name = self._swap(('row','column'))
major_dim,minor_dim = self._swap(self.shape)
# index arrays should have integer data types
if self.indptr.dtype.kind != 'i':
warn("indptr array has non-integer dtype (%s)" \
% self.indptr.dtype.name )
if self.indices.dtype.kind != 'i':
warn("indices array has non-integer dtype (%s)" \
% self.indices.dtype.name )
# only support 32-bit ints for now
self.indptr = np.asarray(self.indptr, dtype=np.intc)
self.indices = np.asarray(self.indices, dtype=np.intc)
self.data = to_native(self.data)
# check array shapes
if np.rank(self.data) != 1 or np.rank(self.indices) != 1 or np.rank(self.indptr) != 1:
raise ValueError('data, indices, and indptr should be rank 1')
# check index pointer
if (len(self.indptr) != major_dim + 1 ):
raise ValueError("index pointer size (%d) should be (%d)" %
(len(self.indptr), major_dim + 1))
if (self.indptr[0] != 0):
raise ValueError("index pointer should start with 0")
# check index and data arrays
if (len(self.indices) != len(self.data)):
raise ValueError("indices and data should have the same size")
if (self.indptr[-1] > len(self.indices)):
raise ValueError("Last value of index pointer should be less than "
"the size of index and data arrays")
self.prune()
if full_check:
#check format validity (more expensive)
if self.nnz > 0:
if self.indices.max() >= minor_dim:
raise ValueError("%s index values must be < %d" %
(minor_name,minor_dim))
if self.indices.min() < 0:
raise ValueError("%s index values must be >= 0" %
minor_name)
if np.diff(self.indptr).min() < 0:
raise ValueError("index pointer values must form a "
"non-decreasing sequence")
def check_format(self, full_check=True):
"""check whether the matrix format is valid
Parameters
==========
- full_check : {bool}
- True - rigorous check, O(N) operations : default
- False - basic check, O(1) operations
"""
#use _swap to determine proper bounds
major_name,minor_name = self._swap(('row','column'))
major_dim,minor_dim = self._swap(self.shape)
# index arrays should have integer data types
if self.indptr.dtype.kind != 'i':
warn("indptr array has non-integer dtype (%s)" \
% self.indptr.dtype.name )
if self.indices.dtype.kind != 'i':
warn("indices array has non-integer dtype (%s)" \
% self.indices.dtype.name )
# only support 32-bit ints for now
self.indptr = np.asarray(self.indptr, dtype=np.intc)
self.indices = np.asarray(self.indices, dtype=np.intc)
self.data = to_native(self.data)
# check array shapes
if np.rank(self.data) != 1 or np.rank(self.indices) != 1 or np.rank(self.indptr) != 1:
raise ValueError('data, indices, and indptr should be rank 1')
# check index pointer
if (len(self.indptr) != major_dim + 1 ):
raise ValueError("index pointer size (%d) should be (%d)" %
(len(self.indptr), major_dim + 1))
if (self.indptr[0] != 0):
raise ValueError("index pointer should start with 0")
# check index and data arrays
if (len(self.indices) != len(self.data)):
raise ValueError("indices and data should have the same size")
if (self.indptr[-1] > len(self.indices)):
raise ValueError("Last value of index pointer should be less than "
"the size of index and data arrays")
self.prune()
if full_check:
#check format validity (more expensive)
if self.nnz > 0:
if self.indices.max() >= minor_dim:
raise ValueError("%s index values must be < %d" %
(minor_name,minor_dim))
if self.indices.min() < 0:
raise ValueError("%s index values must be >= 0" %
minor_name)
if np.diff(self.indptr).min() < 0:
raise ValueError("index pointer values must form a "
"non-decreasing sequence")
def check_format(self, full_check=True):
"""check whether the matrix format is valid
*Parameters*:
full_check:
True - rigorous check, O(N) operations : default
False - basic check, O(1) operations
"""
M,N = self.shape
R,C = self.blocksize
# index arrays should have integer data types
if self.indptr.dtype.kind != 'i':
warn("indptr array has non-integer dtype (%s)" \
% self.indptr.dtype.name )
if self.indices.dtype.kind != 'i':
warn("indices array has non-integer dtype (%s)" \
% self.indices.dtype.name )
# only support 32-bit ints for now
self.indptr = np.asarray(self.indptr, np.intc)
self.indices = np.asarray(self.indices, np.intc)
self.data = to_native(self.data)
# check array shapes
if np.rank(self.indices) != 1 or np.rank(self.indptr) != 1:
raise ValueError,"indices, and indptr should be rank 1"
if np.rank(self.data) != 3:
raise ValueError,"data should be rank 3"
# check index pointer
if (len(self.indptr) != M/R + 1 ):
raise ValueError, \
"index pointer size (%d) should be (%d)" % \
(len(self.indptr), M/R + 1)
if (self.indptr[0] != 0):
raise ValueError,"index pointer should start with 0"
# check index and data arrays
if (len(self.indices) != len(self.data)):
raise ValueError,"indices and data should have the same size"
if (self.indptr[-1] > len(self.indices)):
raise ValueError, \
"Last value of index pointer should be less than "\
"the size of index and data arrays"
self.prune()
if full_check:
#check format validity (more expensive)
if self.nnz > 0:
if self.indices.max() >= N/C:
print "max index",self.indices.max()
raise ValueError, "column index values must be < %d" % (N/C)
if self.indices.min() < 0:
raise ValueError, "column index values must be >= 0"
if diff(self.indptr).min() < 0:
raise ValueError,'index pointer values must form a " \
