def __add__(self, other):
# First check if argument is a scalar
if isscalarlike(other):
new = dok_matrix(self.shape, dtype=self.dtype)
# Add this scalar to every element.
M, N = self.shape
for i in xrange(M):
for j in xrange(N):
aij = self.get((i, j), 0) + other
if aij != 0:
new[i, j] = aij
#new.dtype.char = self.dtype.char
elif isinstance(other, dok_matrix):
if other.shape != self.shape:
raise ValueError("matrix dimensions are not equal")
# We could alternatively set the dimensions to the the largest of
# the two matrices to be summed. Would this be a good idea?
new = dok_matrix(self.shape, dtype=self.dtype)
new.update(self)
for key in other.keys():
new[key] += other[key]
elif isspmatrix(other):
csc = self.tocsc()
new = csc + other
elif isdense(other):
new = self.todense() + other
else:
raise TypeError("data type not understood")
return new
def __radd__(self, other):
# First check if argument is a scalar
if isscalarlike(other):
new = dok_matrix(self.shape, dtype=self.dtype)
# Add this scalar to every element.
M, N = self.shape
for i in xrange(M):
for j in xrange(N):
aij = self.get((i, j), 0) + other
if aij != 0:
new[i, j] = aij
elif isinstance(other, dok_matrix):
if other.shape != self.shape:
raise ValueError("matrix dimensions are not equal")
new = dok_matrix(self.shape, dtype=self.dtype)
new.update(self)
for key in other:
new[key] += other[key]
elif isspmatrix(other):
csc = self.tocsc()
new = csc + other
elif isdense(other):
new = other + self.todense()
else:
raise TypeError("data type not understood")
return new
def __add__(self, other):
# First check if argument is a scalar
if isscalarlike(other):
new = dok_matrix(self.shape, dtype=self.dtype)
# Add this scalar to every element.
M, N = self.shape
for i in xrange(M):
for j in xrange(N):
aij = self.get((i, j), 0) + other
if aij != 0:
new[i, j] = aij
#new.dtype.char = self.dtype.char
elif isinstance(other, dok_matrix):
if other.shape != self.shape:
raise ValueError("matrix dimensions are not equal")
# We could alternatively set the dimensions to the the largest of
# the two matrices to be summed. Would this be a good idea?
new = dok_matrix(self.shape, dtype=self.dtype)
new.update(self)
for key in other.keys():
new[key] += other[key]
elif isspmatrix(other):
csc = self.tocsc()
new = csc + other
elif isdense(other):
new = self.todense() + other
else:
raise TypeError("data type not understood")
return new
def __radd__(self, other):
# First check if argument is a scalar
if isscalarlike(other):
new = dok_matrix(self.shape, dtype=self.dtype)
# Add this scalar to every element.
M, N = self.shape
for i in xrange(M):
for j in xrange(N):
aij = self.get((i, j), 0) + other
if aij != 0:
new[i, j] = aij
elif isinstance(other, dok_matrix):
if other.shape != self.shape:
raise ValueError("matrix dimensions are not equal")
new = dok_matrix(self.shape, dtype=self.dtype)
new.update(self)
for key in other:
new[key] += other[key]
elif isspmatrix(other):
csc = self.tocsc()
new = csc + other
elif isdense(other):
new = other + self.todense()
else:
raise TypeError("data type not understood")
return new
def multiply(self, other):
"""Point-wise multiplication by another matrix
"""
if other.shape != self.shape:
raise ValueError('inconsistent shapes')
if isdense(other):
return np.multiply(self.todense(), other)
else:
other = self.__class__(other)
return self._binopt(other, '_elmul_')
def __rsub__(self,other): # other - self
#note: this can't be replaced by other + (-self) for unsigned types
if isscalarlike(other):
# Now we would add this scalar to every element.
raise NotImplementedError, 'adding a scalar to a sparse ' \
'matrix is not supported'
elif isdense(other):
# Convert this matrix to a dense matrix and subtract them
return other - self.todense()
else:
raise NotImplementedError
def multiply(self, other):
"""Point-wise multiplication by another matrix
"""
if other.shape != self.shape:
raise ValueError('inconsistent shapes')
if isdense(other):
return np.multiply(self.todense(),other)
else:
other = self.__class__(other)
return self._binopt(other,'_elmul_')
def __rsub__(self,other): # other - self
#note: this can't be replaced by other + (-self) for unsigned types
if isscalarlike(other):
# Now we would add this scalar to every element.
raise NotImplementedError, 'adding a scalar to a sparse ' \
'matrix is not supported'
elif isdense(other):
# Convert this matrix to a dense matrix and subtract them
return other - self.todense()
else:
raise NotImplementedError
def __sub__(self,other):
# First check if argument is a scalar
if isscalarlike(other):
# Now we would add this scalar to every element.
raise NotImplementedError, 'adding a scalar to a sparse ' \
'matrix is not supported'
elif isspmatrix(other):
if (other.shape != self.shape):
raise ValueError, "inconsistent shapes"
return self._binopt(other,'_minus_')
elif isdense(other):
# Convert this matrix to a dense matrix and subtract them
return self.todense() - other
else:
raise NotImplementedError
def __add__(self,other):
# First check if argument is a scalar
if isscalarlike(other):
# Now we would add this scalar to every element.
raise NotImplementedError('adding a scalar to a CSC or CSR '
'matrix is not supported')
elif isspmatrix(other):
if (other.shape != self.shape):
raise ValueError("inconsistent shapes")
return self._binopt(other,'_plus_')
elif isdense(other):
# Convert this matrix to a dense matrix and add them
return self.todense() + other
else:
raise NotImplementedError