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class spmatrix:
"""This class provides a base class for all sparse matrix classes.
It cannot be instantiated. Most of the work is provided by subclasses.
"""
@property
def _bsr_container(self):
from ._bsr import bsr_matrix
return bsr_matrix
@property
def _coo_container(self):
from ._coo import coo_matrix
return coo_matrix
@property
def _csc_container(self):
from ._csc import csc_matrix
return csc_matrix
@property
def _csr_container(self):
from ._csr import csr_matrix
return csr_matrix
@property
def _dia_container(self):
from ._dia import dia_matrix
return dia_matrix
@property
def _dok_container(self):
from ._dok import dok_matrix
return dok_matrix
@property
def _lil_container(self):
from ._lil import lil_matrix
return lil_matrix
# Restore matrix multiplication
def __mul__(self, other):
return self._matmul_dispatch(other)
def __rmul__(self, other):
return self._rmatmul_dispatch(other)
# Restore matrix power
def __pow__(self, power):
from .linalg import matrix_power
return matrix_power(self, power)
## Backward compatibility
def set_shape(self, shape):
"""Set the shape of the matrix in-place"""
# Make sure copy is False since this is in place
# Make sure format is unchanged because we are doing a __dict__ swap
new_self = self.reshape(shape, copy=False).asformat(self.format)
self.__dict__ = new_self.__dict__
def get_shape(self):
"""Get the shape of the matrix"""
return self._shape
shape = property(fget=get_shape, fset=set_shape,
doc="Shape of the matrix")
def asfptype(self):
"""Upcast matrix to a floating point format (if necessary)"""
return self._asfptype()
def getmaxprint(self):
"""Maximum number of elements to display when printed."""
return self._getmaxprint()
def getformat(self):
"""Matrix storage format"""
return self.format
def getnnz(self, axis=None):
"""Number of stored values, including explicit zeros.
Parameters
----------
axis : None, 0, or 1
Select between the number of values across the whole array, in
each column, or in each row.
"""
return self._getnnz(axis=axis)
def getH(self):
"""Return the Hermitian transpose of this matrix.
See Also
--------
numpy.matrix.getH : NumPy's implementation of `getH` for matrices
"""
return self.conjugate().transpose()
def getcol(self, j):
"""Returns a copy of column j of the matrix, as an (m x 1) sparse
matrix (column vector).
"""
return self._getcol(j)
def getrow(self, i):
"""Returns a copy of row i of the matrix, as a (1 x n) sparse
matrix (row vector).
"""
return self._getrow(i)
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