diff --git a/nifty5/__init__.py b/nifty5/__init__.py
index da3a6cf244fc709ca23c9653580cd42d9ad8b258..e4c782f32ea3203ce24451a4f35c33e7718e2f48 100644
--- a/nifty5/__init__.py
+++ b/nifty5/__init__.py
@@ -16,6 +16,7 @@ from .domains.log_rg_space import LogRGSpace
from .domain_tuple import DomainTuple
from .field import Field
+from .operators.operator import Operator
from .operators.central_zero_padder import CentralZeroPadder
from .operators.diagonal_operator import DiagonalOperator
from .operators.dof_distributor import DOFDistributor
@@ -92,7 +93,6 @@ from .energies.kl import SampledKullbachLeiblerDivergence
from .energies.hamiltonian import Hamiltonian
from .energies.energy_adapter import EnergyAdapter
-from .operator import Operator
from .linearization import Linearization
# We deliberately don't set __all__ here, because we don't want people to do a
diff --git a/nifty5/energies/hamiltonian.py b/nifty5/energies/hamiltonian.py
index 659cefb66ac7a0d6e9bda169bb7496245b9e07a7..1fc3867cdef409082512111ca92fe6dc1e3763bf 100644
--- a/nifty5/energies/hamiltonian.py
+++ b/nifty5/energies/hamiltonian.py
@@ -19,7 +19,7 @@
from __future__ import absolute_import, division, print_function
from ..compat import *
-from ..operator import Operator
+from ..operators.operator import Operator
from ..library.gaussian_energy import GaussianEnergy
from ..operators.sampling_enabler import SamplingEnabler
diff --git a/nifty5/energies/kl.py b/nifty5/energies/kl.py
index 99fb600ed192e8698419a4e60baca529cc544104..d1fbf1d2dfcde1d27d6fc3cbc35fa58bbfc4b0ac 100644
--- a/nifty5/energies/kl.py
+++ b/nifty5/energies/kl.py
@@ -19,7 +19,7 @@
from __future__ import absolute_import, division, print_function
from ..compat import *
-from ..operator import Operator
+from ..operators.operator import Operator
from ..utilities import my_sum
diff --git a/nifty5/library/amplitude_model.py b/nifty5/library/amplitude_model.py
index ef53fe22101a5474b0a269da5300caeedd32b471..846b3f721cb9b02d68567b4579a69f608ca3ec55 100644
--- a/nifty5/library/amplitude_model.py
+++ b/nifty5/library/amplitude_model.py
@@ -27,7 +27,7 @@ from ..field import Field
from ..multi.multi_field import MultiField
from ..multi.multi_domain import MultiDomain
from ..sugar import makeOp, sqrt
-from ..operator import Operator
+from ..operators.operator import Operator
def _ceps_kernel(dof_space, k, a, k0):
diff --git a/nifty5/library/bernoulli_energy.py b/nifty5/library/bernoulli_energy.py
index cbf7739026cd8d98f431fc454bf1e86feeee52cd..39a6de3b503605c0160af335085fff83fdebefba 100644
--- a/nifty5/library/bernoulli_energy.py
+++ b/nifty5/library/bernoulli_energy.py
@@ -19,7 +19,7 @@
from __future__ import absolute_import, division, print_function
from ..compat import *
-from ..operator import Operator
+from ..operators.operator import Operator
from ..operators.sandwich_operator import SandwichOperator
from ..sugar import makeOp
diff --git a/nifty5/library/correlated_fields.py b/nifty5/library/correlated_fields.py
index e7ad3fe58f056d88de25f1b058c05582cbe2dbd9..c89fb04fe319c1596e85b375d0058f3996b40eff 100644
--- a/nifty5/library/correlated_fields.py
+++ b/nifty5/library/correlated_fields.py
@@ -25,7 +25,7 @@ from ..multi.multi_domain import MultiDomain
from ..operators.domain_distributor import DomainDistributor
from ..operators.harmonic_transform_operator import HarmonicTransformOperator
from ..operators.power_distributor import PowerDistributor
-from ..operator import Operator
+from ..operators.operator import Operator
class CorrelatedField(Operator):
diff --git a/nifty5/library/gaussian_energy.py b/nifty5/library/gaussian_energy.py
index 68a4ee0b31b8a4572a4f126615936a925f9d0a6e..56a64ea8047ef76970ae152d0d8a117a3f34fbff 100644
--- a/nifty5/library/gaussian_energy.py
+++ b/nifty5/library/gaussian_energy.py
@@ -19,8 +19,9 @@
from __future__ import absolute_import, division, print_function
from ..compat import *
-from ..operator import Operator
+from ..operators.operator import Operator
from ..operators.sandwich_operator import SandwichOperator
+from ..domain_tuple import DomainTuple
class GaussianEnergy(Operator):
@@ -28,6 +29,7 @@ class GaussianEnergy(Operator):
super(GaussianEnergy, self).__init__()
self._mean = mean
self._icov = None if covariance is None else covariance.inverse
+ self._target = DomainTuple.scalar_domain()
def __call__(self, x):
residual = x if self._mean is None else x-self._mean
diff --git a/nifty5/library/poissonian_energy.py b/nifty5/library/poissonian_energy.py
index 5d8578014d10ea9d553e6a87978a2de812527825..1358ea653ffc23be8d1549ea6f6eac816b95983c 100644
--- a/nifty5/library/poissonian_energy.py
+++ b/nifty5/library/poissonian_energy.py
@@ -21,7 +21,7 @@ from __future__ import absolute_import, division, print_function
from numpy import inf, isnan
from ..compat import *
-from ..operator import Operator
+from ..operators.operator import Operator
from ..operators.sandwich_operator import SandwichOperator
from ..sugar import makeOp
diff --git a/nifty5/operator.py b/nifty5/operator.py
deleted file mode 100644
index 1fe232cfd2d3c8847f15ece5b7833a6ac2e27879..0000000000000000000000000000000000000000
--- a/nifty5/operator.py
+++ /dev/null
@@ -1,42 +0,0 @@
-from __future__ import absolute_import, division, print_function
-
-from .compat import *
-from .utilities import NiftyMetaBase
-
-
-class Operator(NiftyMetaBase()):
- """Transforms values living on one domain into values living on another
- domain, and can also provide the Jacobian.
- """
-
- def chain(self, x):
- if not callable(x):
- raise TypeError("callable needed")
- ops1 = self._ops if isinstance(self, OpChain) else (self,)
- ops2 = x._ops if isinstance(x, OpChain) else (x,)
- return OpChain(ops1+ops2)
-
- def __call__(self, x):
- """Returns transformed x
-
- Parameters
- ----------
- x : Linearization
- input
-
- Returns
- -------
- Linearization
- output
- """
- raise NotImplementedError
-
-
-class OpChain(Operator):
- def __init__(self, ops):
- self._ops = tuple(ops)
-
- def __call__(self, x):
- for op in reversed(self._ops):
- x = op(x)
- return x
diff --git a/nifty5/operators/linear_operator.py b/nifty5/operators/linear_operator.py
index eac78bd8323a7c89a11e26a91990c26a2bf86287..46301f4f5a22e8f33a0000aeb206d3c27fa21a53 100644
--- a/nifty5/operators/linear_operator.py
+++ b/nifty5/operators/linear_operator.py
@@ -23,7 +23,7 @@ import abc
import numpy as np
from ..compat import *
-from ..operator import Operator
+from .operator import Operator
class LinearOperator(Operator):
@@ -86,21 +86,6 @@ class LinearOperator(Operator):
def __init__(self):
pass
- @abc.abstractproperty
- def domain(self):
- # FIXME Adopt documentation to MultiDomains
- """DomainTuple : the operator's input domain
-
- The domain on which the Operator's input Field lives."""
- raise NotImplementedError
-
- @abc.abstractproperty
- def target(self):
- """DomainTuple : the operator's output domain
-
- The domain on which the Operator's output Field lives."""
- raise NotImplementedError
-
def _flip_modes(self, trafo):
from .operator_adapter import OperatorAdapter
return self if trafo == 0 else OperatorAdapter(self, trafo)
diff --git a/nifty5/operators/operator.py b/nifty5/operators/operator.py
new file mode 100644
index 0000000000000000000000000000000000000000..99f54d4947e4ee23dea9fd356a521540cd255ab6
--- /dev/null
+++ b/nifty5/operators/operator.py
@@ -0,0 +1,108 @@
+from __future__ import absolute_import, division, print_function
+import abc
+
+from ..compat import *
+from ..utilities import NiftyMetaBase
+
+
+class Operator(NiftyMetaBase()):
+ """Transforms values living on one domain into values living on another
+ domain, and can also provide the Jacobian.
+ """
+
+ def domain(self):
+ """DomainTuple or MultiDomain : the operator's input domain
+
+ The domain on which the Operator's input Field lives."""
+ return self._domain
+
+ def target(self):
+ """DomainTuple or MultiDomain : the operator's output domain
+
+ The domain on which the Operator's output Field lives."""
+ return self._target
+
+ def __matmul__(self, x):
+ if not isinstance(x, Operator):
+ return NotImplemented
+ return OpChain.make((self, x))
+ ops1 = self._ops if isinstance(self, OpChain) else (self,)
+ ops2 = x._ops if isinstance(x, OpChain) else (x,)
+ return OpChain(ops1+ops2)
+
+ def chain(self, x):
+ res = self.__matmul__(x)
+ if res == NotImplemented:
+ raise TypeError("operator expected")
+ return res
+
+ def __call__(self, x):
+ """Returns transformed x
+
+ Parameters
+ ----------
+ x : Linearization
+ input
+
+ Returns
+ -------
+ Linearization
+ output
+ """
+ raise NotImplementedError
+
+
+class _CombinedOperator(Operator):
+ def __init__(self, ops, _callingfrommake=False):
+ if not _callingfrommake:
+ raise NotImplementedError
+ self._ops = tuple(ops)
+
+ @classmethod
+ def unpack(cls, ops, res):
+ for op in ops:
+ if isinstance(op, cls):
+ res = cls.unpack(op, res)
+ else:
+ res = res + [op]
+ return res
+
+ @classmethod
+ def make(cls, ops):
+ res = cls.unpack(ops, [])
+ if len(res) == 1:
+ return res[0]
+ return cls(res, _callingfrommake=True)
+
+
+class _OpChain(_CombinedOperator):
+ def __init__(self, ops, _callingfrommake=False):
+ super(_OpChain, self).__init__(ops, _callingfrommake)
+ self._domain = self._ops[-1].domain
+ self._target = self._ops[0].target
+
+ def __call__(self, x):
+ for op in reversed(self._ops):
+ x = op(x)
+ return x
+
+
+class _OpProd(_CombinedOperator):
+ def __init__(self, ops, _callingfrommake=False):
+ super(_OpProd, self).__init__(ops, _callingfrommake)
+ self._domain = self._ops[0].domain
+ self._target = self._ops[0].target
+
+ def __call__(self, x):
+ return my_prod(map(lambda op: op(x) for op in self._ops))
+
+
+class _OpSum(_CombinedOperator):
+ def __init__(self, ops, _callingfrommake=False):
+ super(_OpSum, self).__init__(ops, _callingfrommake)
+ self._domain = domain_union([op.domain for op in self._ops])
+ self._target = domain_union([op.target for op in self._ops])
+
+
+ def __call__(self, x):
+ raise NotImplementedError