diff --git a/nifty5/field.py b/nifty5/field.py
index e22382d8081bc2b8f597b5ee796f6e0e57c74afd..5ba5fba3ae79c920fd503ea4b819429e0f184580 100644
--- a/nifty5/field.py
+++ b/nifty5/field.py
@@ -626,6 +626,11 @@ class Field(object):
raise ValueError("domain mismatch")
return self
+ def extract_part(self, dom):
+ if dom != self._domain:
+ raise ValueError("domain mismatch")
+ return self
+
def unite(self, other):
return self+other
diff --git a/nifty5/multi_field.py b/nifty5/multi_field.py
index a465e1b403043d6e2c052056c64b433e99ec71a1..fe541469708b9e5c89409030b8ee19e394360d09 100644
--- a/nifty5/multi_field.py
+++ b/nifty5/multi_field.py
@@ -217,6 +217,12 @@ class MultiField(object):
return MultiField(subset,
tuple(self[key] for key in subset.keys()))
+ def extract_part(self, subset):
+ if subset is self._domain:
+ return self
+ return MultiField.from_dict({key: self[key] for key in subset.keys()
+ if key in self})
+
def unite(self, other):
"""Merges two MultiFields on potentially different MultiDomains.
diff --git a/nifty5/operators/chain_operator.py b/nifty5/operators/chain_operator.py
index 154fc7098174c17a2d1ceb0d65b44f339c7e0f9d..af46f4fefe5d1914745fd8164bbdb6549b05ed2a 100644
--- a/nifty5/operators/chain_operator.py
+++ b/nifty5/operators/chain_operator.py
@@ -138,6 +138,17 @@ class ChainOperator(LinearOperator):
subs = "\n".join(sub.__repr__() for sub in self._ops)
return "ChainOperator:\n" + utilities.indent(subs)
+ def _simplify_for_constant_input_nontrivial(self, c_inp):
+ from ..multi_domain import MultiDomain
+ if not isinstance(self._domain, MultiDomain):
+ return None, self
+
+ newop = None
+ for op in reversed(self._ops):
+ c_inp, t_op = op.simplify_for_constant_input(c_inp)
+ newop = t_op if newop is None else op(newop)
+ return c_inp, newop
+
# def draw_sample(self, from_inverse=False, dtype=np.float64):
# from ..sugar import from_random
# if len(self._ops) == 1:
diff --git a/nifty5/operators/operator.py b/nifty5/operators/operator.py
index 073579043d9104b53fb97baee3fa84275e5fa0b7..a674ccd5f03ac66d268cdd38d2ca46e1519b9908 100644
--- a/nifty5/operators/operator.py
+++ b/nifty5/operators/operator.py
@@ -146,6 +146,17 @@ class Operator(metaclass=NiftyMeta):
def __repr__(self):
return self.__class__.__name__
+ def simplify_for_constant_input(self, c_inp):
+ if c_inp is None:
+ return None, self
+ if c_inp.domain == self.domain:
+ op = _ConstantOperator(self.domain, self(c_inp))
+ return op(c_inp), op
+ return self._simplify_for_constant_input_nontrivial(c_inp)
+
+ def _simplify_for_constant_input_nontrivial(self, c_inp):
+ return None, self
+
for f in ["sqrt", "exp", "log", "tanh", "sigmoid", 'sin', 'cos', 'tan',
'sinh', 'cosh', 'absolute', 'sinc', 'one_over']:
@@ -157,6 +168,72 @@ for f in ["sqrt", "exp", "log", "tanh", "sigmoid", 'sin', 'cos', 'tan',
setattr(Operator, f, func(f))
+class _ConstCollector(object):
+ def __init__(self):
+ self._const = None
+ self._nc = set()
+
+ def mult(self, const, fulldom):
+ if const is None:
+ self._nc |= set(fulldom)
+ else:
+ self._nc |= set(fulldom) - set(const)
+ if self._const is None:
+ from ..multi_field import MultiField
+ self._const = MultiField.from_dict(
+ {key: const[key] for key in const if key not in self._nc})
+ else:
+ from ..multi_field import MultiField
+ self._const = MultiField.from_dict(
+ {key: self._const[key]*const[key]
+ for key in const if key not in self._nc})
+
+ def add(self, const, fulldom):
+ if const is None:
+ self._nc |= set(fulldom.keys())
+ else:
+ from ..multi_field import MultiField
+ self._nc |= set(fulldom.keys()) - set(const.keys())
+ if self._const is None:
+ self._const = MultiField.from_dict(
+ {key: const[key]
+ for key in const.keys() if key not in self._nc})
+ else:
+ self._const = self._const.unite(const)
+ self._const = MultiField.from_dict(
+ {key: self._const[key]
+ for key in self._const if key not in self._nc})
+
+ @property
+ def constfield(self):
+ return self._const
+
+
+class _ConstantOperator(Operator):
+ def __init__(self, dom, output):
+ from ..sugar import makeDomain
+ self._domain = makeDomain(dom)
+ self._target = output.domain
+ self._output = output
+
+ def apply(self, x):
+ from ..linearization import Linearization
+ from .simple_linear_operators import NullOperator
+ from ..domain_tuple import DomainTuple
+ self._check_input(x)
+ if not isinstance(x, Linearization):
+ return self._output
+ if x.want_metric and self._target is DomainTuple.scalar_domain():
+ met = NullOperator(self._domain, self._domain)
+ else:
+ met = None
+ return x.new(self._output, NullOperator(self._domain, self._target),
+ met)
+
+ def __repr__(self):
+ return 'ConstantOperator <- {}'.format(self.domain.keys())
+
+
class _FunctionApplier(Operator):
def __init__(self, domain, funcname):
from ..sugar import makeDomain
@@ -229,6 +306,17 @@ class _OpChain(_CombinedOperator):
x = op(x)
return x
+ def _simplify_for_constant_input_nontrivial(self, c_inp):
+ from ..multi_domain import MultiDomain
+ if not isinstance(self._domain, MultiDomain):
+ return None, self
+
+ newop = None
+ for op in reversed(self._ops):
+ c_inp, t_op = op.simplify_for_constant_input(c_inp)
+ newop = t_op if newop is None else op(newop)
+ return c_inp, newop
+
def __repr__(self):
subs = "\n".join(sub.__repr__() for sub in self._ops)
return "_OpChain:\n" + indent(subs)
@@ -261,6 +349,21 @@ class _OpProd(Operator):
makeOp(lin2._val)(lin1._jac), False)
return lin1.new(lin1._val*lin2._val, op(x.jac))
+ def _simplify_for_constant_input_nontrivial(self, c_inp):
+ f1, o1 = self._op1.simplify_for_constant_input(
+ c_inp.extract_part(self._op1.domain))
+ f2, o2 = self._op2.simplify_for_constant_input(
+ c_inp.extract_part(self._op2.domain))
+
+ from ..multi_domain import MultiDomain
+ if not isinstance(self._target, MultiDomain):
+ return None, _OpProd(o1, o2)
+
+ cc = _ConstCollector()
+ cc.mult(f1, o1.target)
+ cc.mult(f2, o2.target)
+ return cc.constfield, _OpProd(o1, o2)
+
def __repr__(self):
subs = "\n".join(sub.__repr__() for sub in (self._op1, self._op2))
return "_OpProd:\n"+indent(subs)
@@ -293,6 +396,21 @@ class _OpSum(Operator):
res = res.add_metric(lin1._metric + lin2._metric)
return res
+ def _simplify_for_constant_input_nontrivial(self, c_inp):
+ f1, o1 = self._op1.simplify_for_constant_input(
+ c_inp.extract_part(self._op1.domain))
+ f2, o2 = self._op2.simplify_for_constant_input(
+ c_inp.extract_part(self._op2.domain))
+
+ from ..multi_domain import MultiDomain
+ if not isinstance(self._target, MultiDomain):
+ return None, _OpSum(o1, o2)
+
+ cc = _ConstCollector()
+ cc.add(f1, o1.target)
+ cc.add(f2, o2.target)
+ return cc.constfield, _OpSum(o1, o2)
+
def __repr__(self):
subs = "\n".join(sub.__repr__() for sub in (self._op1, self._op2))
return "_OpSum:\n"+indent(subs)
diff --git a/nifty5/operators/scaling_operator.py b/nifty5/operators/scaling_operator.py
index 1e14b62ed13de6c5e3cddfa0b1f8b6f6c3366ee3..a4b20ab07044e05c2e2eaaf24711e5688bd69401 100644
--- a/nifty5/operators/scaling_operator.py
+++ b/nifty5/operators/scaling_operator.py
@@ -35,14 +35,6 @@ class ScalingOperator(EndomorphicOperator):
-----
:class:`Operator` supports the multiplication with a scalar. So one does
not need instantiate :class:`ScalingOperator` explicitly in most cases.
-
- Formally, this operator always supports all operation modes (times,
- adjoint_times, inverse_times and inverse_adjoint_times), even if `factor`
- is 0 or infinity. It is the user's responsibility to apply the operator
- only in appropriate ways (e.g. call inverse_times only if `factor` is
- nonzero).
-
- This shortcoming will hopefully be fixed in the future.
"""
def __init__(self, factor, domain):
@@ -52,7 +44,10 @@ class ScalingOperator(EndomorphicOperator):
raise TypeError("Scalar required")
self._factor = factor
self._domain = makeDomain(domain)
- self._capability = self._all_ops
+ if self._factor == 0.:
+ self._capability = self.TIMES | self.ADJOINT_TIMES
+ else:
+ self._capability = self._all_ops
def apply(self, x, mode):
self._check_input(x, mode)
diff --git a/nifty5/operators/simple_linear_operators.py b/nifty5/operators/simple_linear_operators.py
index 3c1b54f4be5a62f7e7a51483a672b87746312d4f..096ebb2a24fb03d0a99bff835d79a9dd63a50b00 100644
--- a/nifty5/operators/simple_linear_operators.py
+++ b/nifty5/operators/simple_linear_operators.py
@@ -315,3 +315,23 @@ class NullOperator(LinearOperator):
def apply(self, x, mode):
self._check_input(x, mode)
return self._nullfield(self._tgt(mode))
+
+
+class _PartialExtractor(LinearOperator):
+ def __init__(self, domain, target):
+ if not isinstance(domain, MultiDomain):
+ raise TypeError("MultiDomain expected")
+ if not isinstance(target, MultiDomain):
+ raise TypeError("MultiDomain expected")
+ self._domain = domain
+ self._target = target
+ for key in self._target.keys():
+ if not (self._domain[key] is not self._target[key]):
+ raise ValueError("domain mismatch")
+ self._capability = self.TIMES | self.ADJOINT_TIMES
+
+ def apply(self, x, mode):
+ self._check_input(x, mode)
+ if mode == self.TIMES:
+ return x.extract(self._target)
+ return MultiField.from_dict({key: x[key] for key in x.domain.keys()})
diff --git a/nifty5/operators/sum_operator.py b/nifty5/operators/sum_operator.py
index 9cfe1328c6eaa4b59401a606fa6279473d881a8c..d9a3c00c51a8cf3fdcd77a313e3d5f93c661e13d 100644
--- a/nifty5/operators/sum_operator.py
+++ b/nifty5/operators/sum_operator.py
@@ -23,6 +23,7 @@ from ..sugar import domain_union
from ..utilities import indent
from .block_diagonal_operator import BlockDiagonalOperator
from .linear_operator import LinearOperator
+from .simple_linear_operators import NullOperator
class SumOperator(LinearOperator):
@@ -59,6 +60,9 @@ class SumOperator(LinearOperator):
negnew += [not n for n in op._neg]
else:
negnew += list(op._neg)
+# FIXME: this needs some more work to keep the domain and target unchanged!
+# elif isinstance(op, NullOperator):
+# pass
else:
opsnew.append(op)
negnew.append(ng)
@@ -193,6 +197,9 @@ class SumOperator(LinearOperator):
"cannot draw from inverse of this operator")
res = None
for op in self._ops:
+ from .simple_linear_operators import NullOperator
+ if isinstance(op, NullOperator):
+ continue
tmp = op.draw_sample(from_inverse, dtype)
res = tmp if res is None else res.unite(tmp)
return res
@@ -200,3 +207,29 @@ class SumOperator(LinearOperator):
def __repr__(self):
subs = "\n".join(sub.__repr__() for sub in self._ops)
return "SumOperator:\n"+indent(subs)
+
+ def _simplify_for_constant_input_nontrivial(self, c_inp):
+ f = []
+ o = []
+ for op in self._ops:
+ tf, to = op.simplify_for_constant_input(
+ c_inp.extract_part(op.domain))
+ f.append(tf)
+ o.append(to)
+
+ from ..multi_domain import MultiDomain
+ if not isinstance(self._target, MultiDomain):
+ fullop = None
+ for to, n in zip(o, self._neg):
+ op = to if not n else -to
+ fullop = op if fullop is None else fullop + op
+ return None, fullop
+
+ from .operator import _ConstCollector
+ cc = _ConstCollector()
+ fullop = None
+ for tf, to, n in zip(f, o, self._neg):
+ cc.add(tf, to.target)
+ op = to if not n else -to
+ fullop = op if fullop is None else fullop + op
+ return cc.constfield, fullop
diff --git a/test/test_operators/test_simplification.py b/test/test_operators/test_simplification.py
new file mode 100644
index 0000000000000000000000000000000000000000..bce790f27c226383479802e13239395b31f17573
--- /dev/null
+++ b/test/test_operators/test_simplification.py
@@ -0,0 +1,55 @@
+# This program is free software: you can redistribute it and/or modify
+# it under the terms of the GNU General Public License as published by
+# the Free Software Foundation, either version 3 of the License, or
+# (at your option) any later version.
+#
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+# GNU General Public License for more details.
+#
+# You should have received a copy of the GNU General Public License
+# along with this program. If not, see <http://www.gnu.org/licenses/>.
+#
+# Copyright(C) 2013-2019 Max-Planck-Society
+#
+# NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik.
+
+import pytest
+from numpy.testing import assert_allclose, assert_equal
+
+import nifty5 as ift
+
+
+def test_simplification():
+ from nifty5.operators.operator import _ConstantOperator
+ f1 = ift.Field.full(ift.RGSpace(10),2.)
+ op = ift.FFTOperator(f1.domain)
+ _, op2 = op.simplify_for_constant_input(f1)
+ assert_equal(isinstance(op2, _ConstantOperator), True)
+ assert_allclose(op(f1).local_data, op2(f1).local_data)
+
+ dom = {"a": ift.RGSpace(10)}
+ f1 = ift.full(dom,2.)
+ op = ift.FFTOperator(f1.domain["a"]).ducktape("a")
+ _, op2 = op.simplify_for_constant_input(f1)
+ assert_equal(isinstance(op2, _ConstantOperator), True)
+ assert_allclose(op(f1).local_data, op2(f1).local_data)
+
+ dom = {"a": ift.RGSpace(10), "b": ift.RGSpace(5)}
+ f1 = ift.full(dom,2.)
+ pdom = {"a": ift.RGSpace(10)}
+ f2 = ift.full(pdom,2.)
+ o1 = ift.FFTOperator(f1.domain["a"])
+ o2 = ift.FFTOperator(f1.domain["b"])
+ op = (o1.ducktape("a").ducktape_left("a") +
+ o2.ducktape("b").ducktape_left("b"))
+ _, op2 = op.simplify_for_constant_input(f2)
+ assert_equal(isinstance(op2._op1, _ConstantOperator), True)
+ assert_allclose(op(f1)["a"].local_data, op2(f1)["a"].local_data)
+ assert_allclose(op(f1)["b"].local_data, op2(f1)["b"].local_data)
+ lin = ift.Linearization.make_var(ift.MultiField.full(op2.domain, 2.), True)
+ assert_allclose(op(lin).val["a"].local_data,
+ op2(lin).val["a"].local_data)
+ assert_allclose(op(lin).val["b"].local_data,
+ op2(lin).val["b"].local_data)