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)