def __truediv__(self, other):
"""Point-wise division by scalar"""
if util.isscalarlike(other):
if self.dtype == numpy.complex64:
# Note: This is a work-around to make the output dtype the same
# as SciPy. It might be SciPy version dependent.
dtype = numpy.float32
else:
if cupy.isscalar(other):
dtype = numpy.float64
else:
dtype = numpy.promote_types(numpy.float64, other.dtype)
d = cupy.array(1. / other, dtype=dtype)
return multiply_by_scalar(self, d)
# TODO(anaruse): Implement divide by dense or sparse matrix
raise NotImplementedError
def __pow__(self, other):
"""Calculates n-th power of the matrix.
This method calculates n-th power of a given matrix. The matrix must
be a squared matrix, and a given exponent must be an integer.
Args:
other (int): Exponent.
Returns:
cupyx.scipy.sparse.spmatrix: A sparse matrix representing n-th
power of this matrix.
"""
m, n = self.shape
if m != n:
raise TypeError('matrix is not square')
if util.isintlike(other):
other = int(other)
if other < 0:
raise ValueError('exponent must be >= 0')
if other == 0:
import cupyx.scipy.sparse
return cupyx.scipy.sparse.identity(m,
dtype=self.dtype,
format='csr')
elif other == 1:
return self.copy()
else:
tmp = self.__pow__(other // 2)
if other % 2:
return self * tmp * tmp
else:
return tmp * tmp
elif util.isscalarlike(other):
raise ValueError('exponent must be an integer')
else:
return NotImplemented