operator.py 8.28 KB
Newer Older
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
# 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.
Martin Reinecke's avatar
Martin Reinecke committed
17

Martin Reinecke's avatar
Martin Reinecke committed
18
import numpy as np
Martin Reinecke's avatar
Martin Reinecke committed
19
from ..compat import *
Philipp Arras's avatar
Philipp Arras committed
20
from ..utilities import NiftyMetaBase, indent
Martin Reinecke's avatar
Martin Reinecke committed
21 22 23 24 25 26 27


class Operator(NiftyMetaBase()):
    """Transforms values living on one domain into values living on another
    domain, and can also provide the Jacobian.
    """

Martin Reinecke's avatar
Martin Reinecke committed
28
    @property
Martin Reinecke's avatar
Martin Reinecke committed
29 30 31 32
    def domain(self):
        """DomainTuple or MultiDomain : the operator's input domain

            The domain on which the Operator's input Field lives."""
Martin Reinecke's avatar
Martin Reinecke committed
33
        return self._domain
Martin Reinecke's avatar
Martin Reinecke committed
34

Martin Reinecke's avatar
Martin Reinecke committed
35
    @property
Martin Reinecke's avatar
Martin Reinecke committed
36 37 38 39
    def target(self):
        """DomainTuple or MultiDomain : the operator's output domain

            The domain on which the Operator's output Field lives."""
Martin Reinecke's avatar
Martin Reinecke committed
40
        return self._target
Martin Reinecke's avatar
Martin Reinecke committed
41

Martin Reinecke's avatar
Martin Reinecke committed
42 43 44 45 46 47
    @staticmethod
    def _check_domain_equality(dom_op, dom_field):
        if dom_op != dom_field:
            s = "The operator's and field's domains don't match."
            from ..domain_tuple import DomainTuple
            from ..multi_domain import MultiDomain
Sebastian Hutschenreuter's avatar
fix  
Sebastian Hutschenreuter committed
48
            if not isinstance(dom_op, (DomainTuple, MultiDomain,)):
Martin Reinecke's avatar
Martin Reinecke committed
49 50 51 52
                s += " Your operator's domain is neither a `DomainTuple`" \
                     " nor a `MultiDomain`."
            raise ValueError(s)

Martin Reinecke's avatar
cleanup  
Martin Reinecke committed
53 54 55 56 57 58 59 60 61 62
    def scale(self, factor):
        if factor == 1:
            return self
        from .scaling_operator import ScalingOperator
        return ScalingOperator(factor, self.target)(self)

    def conjugate(self):
        from .simple_linear_operators import ConjugationOperator
        return ConjugationOperator(self.target)(self)

Martin Reinecke's avatar
Martin Reinecke committed
63 64 65 66 67
    @property
    def real(self):
        from .simple_linear_operators import Realizer
        return Realizer(self.target)(self)

Martin Reinecke's avatar
cleanup  
Martin Reinecke committed
68 69 70
    def __neg__(self):
        return self.scale(-1)

Martin Reinecke's avatar
Martin Reinecke committed
71 72 73
    def __matmul__(self, x):
        if not isinstance(x, Operator):
            return NotImplemented
Martin Reinecke's avatar
Martin Reinecke committed
74
        return _OpChain.make((self, x))
Martin Reinecke's avatar
Martin Reinecke committed
75

Martin Reinecke's avatar
Martin Reinecke committed
76
    def __mul__(self, x):
77 78 79 80 81
        if isinstance(x, Operator):
            return _OpProd(self, x)
        if np.isscalar(x):
            return self.scale(x)
        return NotImplemented
Martin Reinecke's avatar
Martin Reinecke committed
82

Philipp Arras's avatar
Philipp Arras committed
83 84 85
    def __add__(self, x):
        if not isinstance(x, Operator):
            return NotImplemented
Martin Reinecke's avatar
Martin Reinecke committed
86
        return _OpSum(self, x)
Philipp Arras's avatar
Philipp Arras committed
87

88 89 90 91 92
    def __sub__(self, x):
        if not isinstance(x, Operator):
            return NotImplemented
        return _OpSum(self, -x)

Martin Reinecke's avatar
Martin Reinecke committed
93 94 95 96 97
    def __pow__(self, power):
        if not np.isscalar(power):
            return NotImplemented
        return _OpChain.make((_PowerOp(self.target, power), self))

Martin Reinecke's avatar
Martin Reinecke committed
98 99
    def apply(self, x):
        raise NotImplementedError
Martin Reinecke's avatar
Martin Reinecke committed
100

Philipp Arras's avatar
Philipp Arras committed
101
    def force(self, x):
Philipp Arras's avatar
Philipp Arras committed
102
        """Extract correct subset of domain of x and apply operator."""
Philipp Arras's avatar
Philipp Arras committed
103 104
        return self.apply(x.extract(self.domain))

105 106 107
    def _check_input(self, x):
        from ..linearization import Linearization
        d = x.target if isinstance(x, Linearization) else x.domain
Martin Reinecke's avatar
Martin Reinecke committed
108
        self._check_domain_equality(self._domain, d)
109

Martin Reinecke's avatar
Martin Reinecke committed
110
    def __call__(self, x):
Martin Reinecke's avatar
Martin Reinecke committed
111 112 113
        if isinstance(x, Operator):
            return _OpChain.make((self, x))
        return self.apply(x)
Martin Reinecke's avatar
Martin Reinecke committed
114

Martin Reinecke's avatar
Martin Reinecke committed
115 116 117 118 119 120 121 122
    def ducktape(self, name):
        from .simple_linear_operators import ducktape
        return self(ducktape(self, None, name))

    def ducktape_left(self, name):
        from .simple_linear_operators import ducktape
        return ducktape(None, self, name)(self)

Martin Reinecke's avatar
Martin Reinecke committed
123 124 125
    def __repr__(self):
        return self.__class__.__name__

Martin Reinecke's avatar
Martin Reinecke committed
126

Philipp Arras's avatar
Philipp Arras committed
127
for f in ["sqrt", "exp", "log", "tanh", "positive_tanh", 'clipped_exp']:
Martin Reinecke's avatar
Martin Reinecke committed
128 129
    def func(f):
        def func2(self):
130
            fa = _FunctionApplier(self.target, f)
Martin Reinecke's avatar
Martin Reinecke committed
131 132 133 134 135 136 137 138
            return _OpChain.make((fa, self))
        return func2
    setattr(Operator, f, func(f))


class _FunctionApplier(Operator):
    def __init__(self, domain, funcname):
        from ..sugar import makeDomain
Martin Reinecke's avatar
Martin Reinecke committed
139
        self._domain = self._target = makeDomain(domain)
Martin Reinecke's avatar
Martin Reinecke committed
140 141
        self._funcname = funcname

Martin Reinecke's avatar
Martin Reinecke committed
142
    def apply(self, x):
143
        self._check_input(x)
Martin Reinecke's avatar
Martin Reinecke committed
144 145 146
        return getattr(x, self._funcname)()


Martin Reinecke's avatar
Martin Reinecke committed
147 148 149 150 151 152 153 154 155 156 157
class _PowerOp(Operator):
    def __init__(self, domain, power):
        from ..sugar import makeDomain
        self._domain = self._target = makeDomain(domain)
        self._power = power

    def apply(self, x):
        self._check_input(x)
        return x**self._power


Martin Reinecke's avatar
Martin Reinecke committed
158 159 160 161 162 163 164 165 166 167
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):
Martin Reinecke's avatar
Martin Reinecke committed
168
                res = cls.unpack(op._ops, res)
Martin Reinecke's avatar
Martin Reinecke committed
169 170 171 172 173 174 175 176 177 178 179 180 181 182 183
            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)
Martin Reinecke's avatar
Martin Reinecke committed
184 185
        self._domain = self._ops[-1].domain
        self._target = self._ops[0].target
Martin Reinecke's avatar
Martin Reinecke committed
186 187 188
        for i in range(1, len(self._ops)):
            if self._ops[i-1].domain != self._ops[i].target:
                raise ValueError("domain mismatch")
Martin Reinecke's avatar
Martin Reinecke committed
189

Martin Reinecke's avatar
Martin Reinecke committed
190
    def apply(self, x):
191
        self._check_input(x)
Martin Reinecke's avatar
Martin Reinecke committed
192 193 194 195 196
        for op in reversed(self._ops):
            x = op(x)
        return x


Philipp Arras's avatar
Philipp Arras committed
197 198 199 200 201
    def __repr__(self):
        subs = "\n".join(sub.__repr__() for sub in self._ops)
        return "_OpChain:\n" + indent(subs)


Martin Reinecke's avatar
Martin Reinecke committed
202 203 204 205 206 207 208 209 210
class _OpProd(Operator):
    def __init__(self, op1, op2):
        from ..sugar import domain_union
        self._domain = domain_union((op1.domain, op2.domain))
        self._target = op1.target
        if op1.target != op2.target:
            raise ValueError("target mismatch")
        self._op1 = op1
        self._op2 = op2
Martin Reinecke's avatar
Martin Reinecke committed
211

Martin Reinecke's avatar
Martin Reinecke committed
212
    def apply(self, x):
Martin Reinecke's avatar
Martin Reinecke committed
213 214
        from ..linearization import Linearization
        from ..sugar import makeOp
215
        self._check_input(x)
Martin Reinecke's avatar
Martin Reinecke committed
216
        lin = isinstance(x, Linearization)
217 218 219
        v = x._val if lin else x
        v1 = v.extract(self._op1.domain)
        v2 = v.extract(self._op2.domain)
Martin Reinecke's avatar
Martin Reinecke committed
220
        if not lin:
221
            return self._op1(v1) * self._op2(v2)
222 223 224
        wm = x.want_metric
        lin1 = self._op1(Linearization.make_var(v1, wm))
        lin2 = self._op2(Linearization.make_var(v2, wm))
Martin Reinecke's avatar
Martin Reinecke committed
225 226
        op = (makeOp(lin1._val)(lin2._jac))._myadd(
            makeOp(lin2._val)(lin1._jac), False)
227
        return lin1.new(lin1._val*lin2._val, op(x.jac))
Martin Reinecke's avatar
Martin Reinecke committed
228 229


Philipp Arras's avatar
Philipp Arras committed
230 231 232 233 234
    def __repr__(self):
        subs = "\n".join(sub.__repr__() for sub in (self._op1, self._op2))
        return "_OpProd:\n"+indent(subs)


Martin Reinecke's avatar
Martin Reinecke committed
235 236
class _OpSum(Operator):
    def __init__(self, op1, op2):
Philipp Arras's avatar
Philipp Arras committed
237
        from ..sugar import domain_union
Martin Reinecke's avatar
Martin Reinecke committed
238 239 240 241
        self._domain = domain_union((op1.domain, op2.domain))
        self._target = domain_union((op1.target, op2.target))
        self._op1 = op1
        self._op2 = op2
Philipp Arras's avatar
Philipp Arras committed
242 243

    def apply(self, x):
Martin Reinecke's avatar
Martin Reinecke committed
244
        from ..linearization import Linearization
245
        self._check_input(x)
Martin Reinecke's avatar
Martin Reinecke committed
246 247 248 249
        lin = isinstance(x, Linearization)
        v = x._val if lin else x
        v1 = v.extract(self._op1.domain)
        v2 = v.extract(self._op2.domain)
Philipp Arras's avatar
Philipp Arras committed
250
        res = None
Martin Reinecke's avatar
Martin Reinecke committed
251 252
        if not lin:
            return self._op1(v1).unite(self._op2(v2))
253 254 255
        wm = x.want_metric
        lin1 = self._op1(Linearization.make_var(v1, wm))
        lin2 = self._op2(Linearization.make_var(v2, wm))
Martin Reinecke's avatar
Martin Reinecke committed
256
        op = lin1._jac._myadd(lin2._jac, False)
Martin Reinecke's avatar
bug fix  
Martin Reinecke committed
257
        res = lin1.new(lin1._val.unite(lin2._val), op(x.jac))
Martin Reinecke's avatar
Martin Reinecke committed
258 259
        if lin1._metric is not None and lin2._metric is not None:
            res = res.add_metric(lin1._metric + lin2._metric)
Philipp Arras's avatar
Philipp Arras committed
260
        return res
Philipp Arras's avatar
Philipp Arras committed
261 262 263 264

    def __repr__(self):
        subs = "\n".join(sub.__repr__() for sub in (self._op1, self._op2))
        return "_OpSum:\n"+indent(subs)