def identity(shape, dtype=np.float64):
"Returns the identity linear Operator"
if shape[0] != shape[1]:
raise ValueError('Identity operators must be square')
def matvec(x):
return x
return LinearOperator(shape, matvec=matvec, rmatvec=matvec, dtype=dtype)
def diag(d, shape=None, dtype=None):
"Returns a diagonal Linear Operator"
if shape is None:
shape = 2 * (d.size, )
if shape[0] != shape[1]:
raise ValueError('Diagonal operators must be square')
def matvec(x):
return d * x
if dtype is None:
dtype = d.dtype
return LinearOperator(shape, matvec=matvec, rmatvec=matvec, dtype=dtype)
def masubclass(xin=None,
xout=None,
shapein=None,
shapeout=None,
classin=None,
classout=None,
dictin=None,
dictout=None,
matvec=None,
rmatvec=None,
dtype=np.float64,
dtypein=None,
dtypeout=None):
"Wrap linear operation working on ndarray subclasses in MaskedArray style"
if xin is not None:
shapein = xin.shape
classin = xin.__class__
dictin = xin.__dict__
dtype = xin.dtype
if xout is not None:
shapeout = xout.shape
classout = xout.__class__
dictout = xout.__dict__
sizein = np.prod(shapein)
sizeout = np.prod(shapeout)
shape = (sizeout, sizein)
if matvec is not None:
def ndmatvec(x):
xi = classin(x.reshape(shapein))
xi.__dict__ = dictin
return matvec(xi).reshape(sizeout)
else:
raise ValueError('Requires a matvec function')
if rmatvec is not None:
def ndrmatvec(x):
xo = classout(x.reshape(shapeout))
xo.__dict__ = dictout
return rmatvec(xo).reshape(sizein)
else:
ndrmatvec = None
return LinearOperator(shape,
matvec=ndmatvec,
rmatvec=ndrmatvec,
dtype=dtype,
dtypein=dtypein,
dtypeout=dtypeout)
def eye(shape, dtype=np.float64):
"Returns the identity linear Operator"
if shape[0] == shape[1]:
return identity(shape, dtype=dtype)
else:
def matvec(x):
return x[:shape[0]]
def rmatvec(x):
return np.concatenate(x, np.zeros(shape[0] - shape[1]))
return LinearOperator(shape,
matvec=matvec,
rmatvec=rmatvec,
dtype=dtype)
