operator.py 9.16 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
Philipp Arras's avatar
Philipp Arras committed
19
from ..utilities import NiftyMetaBase, indent
Martin Reinecke's avatar
Martin Reinecke committed
20
21
22


class Operator(NiftyMetaBase()):
Philipp Arras's avatar
Philipp Arras committed
23
    """Transforms values defined on one domain into values defined on another
Martin Reinecke's avatar
Martin Reinecke committed
24
25
26
    domain, and can also provide the Jacobian.
    """

Martin Reinecke's avatar
Martin Reinecke committed
27
    @property
Martin Reinecke's avatar
Martin Reinecke committed
28
    def domain(self):
Philipp Arras's avatar
Docs    
Philipp Arras committed
29
        """The domain on which the Operator's input Field is defined.
Martin Reinecke's avatar
Martin Reinecke committed
30

Philipp Arras's avatar
Docs    
Philipp Arras committed
31
32
33
34
        Returns
        -------
        domain : DomainTuple or MultiDomain
        """
Martin Reinecke's avatar
Martin Reinecke committed
35
        return self._domain
Martin Reinecke's avatar
Martin Reinecke committed
36

Martin Reinecke's avatar
Martin Reinecke committed
37
    @property
Martin Reinecke's avatar
Martin Reinecke committed
38
    def target(self):
Philipp Arras's avatar
Docs    
Philipp Arras committed
39
40
41
42
43
44
        """The domain on which the Operator's output Field is defined.

        Returns
        -------
        target : DomainTuple or MultiDomain
        """
Martin Reinecke's avatar
Martin Reinecke committed
45

Martin Reinecke's avatar
Martin Reinecke committed
46
        return self._target
Martin Reinecke's avatar
Martin Reinecke committed
47

Martin Reinecke's avatar
Martin Reinecke committed
48
49
50
51
52
53
    @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
54
            if not isinstance(dom_op, (DomainTuple, MultiDomain,)):
Martin Reinecke's avatar
Martin Reinecke committed
55
56
57
58
                s += " Your operator's domain is neither a `DomainTuple`" \
                     " nor a `MultiDomain`."
            raise ValueError(s)

Martin Reinecke's avatar
cleanup    
Martin Reinecke committed
59
60
61
62
63
64
65
66
67
68
    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
69
70
71
72
73
    @property
    def real(self):
        from .simple_linear_operators import Realizer
        return Realizer(self.target)(self)

Martin Reinecke's avatar
cleanup    
Martin Reinecke committed
74
75
76
    def __neg__(self):
        return self.scale(-1)

Martin Reinecke's avatar
Martin Reinecke committed
77
78
79
    def __matmul__(self, x):
        if not isinstance(x, Operator):
            return NotImplemented
Martin Reinecke's avatar
Martin Reinecke committed
80
        return _OpChain.make((self, x))
Martin Reinecke's avatar
Martin Reinecke committed
81

Martin Reinecke's avatar
Martin Reinecke committed
82
    def __mul__(self, x):
83
84
85
86
87
        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
88

89
90
91
    def __rmul__(self, x):
        return self.__mul__(x)

Philipp Arras's avatar
Philipp Arras committed
92
93
94
    def __add__(self, x):
        if not isinstance(x, Operator):
            return NotImplemented
Martin Reinecke's avatar
Martin Reinecke committed
95
        return _OpSum(self, x)
Philipp Arras's avatar
Philipp Arras committed
96

97
98
99
100
101
    def __sub__(self, x):
        if not isinstance(x, Operator):
            return NotImplemented
        return _OpSum(self, -x)

Martin Reinecke's avatar
Martin Reinecke committed
102
103
104
105
106
    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
107
108
109
    def clip(self, min=None, max=None):
        if min is None and max is None:
            return self
Jakob Knollmueller's avatar
Jakob Knollmueller committed
110
        return _OpChain.make((_Clipper(self.target, min, max), self))
Martin Reinecke's avatar
Martin Reinecke committed
111

Martin Reinecke's avatar
Martin Reinecke committed
112
    def apply(self, x):
113
        """Applies the operator to a Field or MultiField.
Philipp Arras's avatar
Docs    
Philipp Arras committed
114
115
116
117
118
119

        Parameters
        ----------
        x : Field or MultiField
            Input on which the operator shall act. Needs to be defined on
            :attr:`domain`.
120
        """
Martin Reinecke's avatar
Martin Reinecke committed
121
        raise NotImplementedError
Martin Reinecke's avatar
Martin Reinecke committed
122

Philipp Arras's avatar
Philipp Arras committed
123
    def force(self, x):
Philipp Arras's avatar
Docs    
Philipp Arras committed
124
125
        """Extract subset of domain of x according to `self.domain` and apply
        operator."""
Philipp Arras's avatar
Philipp Arras committed
126
127
        return self.apply(x.extract(self.domain))

128
129
130
    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
131
        self._check_domain_equality(self._domain, d)
132

Martin Reinecke's avatar
Martin Reinecke committed
133
    def __call__(self, x):
Martin Reinecke's avatar
Martin Reinecke committed
134
135
136
        if isinstance(x, Operator):
            return _OpChain.make((self, x))
        return self.apply(x)
Martin Reinecke's avatar
Martin Reinecke committed
137

Martin Reinecke's avatar
Martin Reinecke committed
138
139
140
141
142
143
144
145
    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
146
147
148
    def __repr__(self):
        return self.__class__.__name__

Martin Reinecke's avatar
Martin Reinecke committed
149

Martin Reinecke's avatar
Martin Reinecke committed
150
for f in ["sqrt", "exp", "log", "tanh", "sigmoid", 'sin', 'cos', 'tan',
151
          'sinh', 'cosh', 'absolute', 'sinc', 'one_over']:
Martin Reinecke's avatar
Martin Reinecke committed
152
153
    def func(f):
        def func2(self):
154
            fa = _FunctionApplier(self.target, f)
Martin Reinecke's avatar
Martin Reinecke committed
155
156
157
158
159
160
161
162
            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
163
        self._domain = self._target = makeDomain(domain)
Martin Reinecke's avatar
Martin Reinecke committed
164
165
        self._funcname = funcname

Martin Reinecke's avatar
Martin Reinecke committed
166
    def apply(self, x):
167
        self._check_input(x)
Martin Reinecke's avatar
Martin Reinecke committed
168
169
170
        return getattr(x, self._funcname)()


Martin Reinecke's avatar
Martin Reinecke committed
171
172
173
174
175
176
177
178
179
180
181
182
class _Clipper(Operator):
    def __init__(self, domain, min=None, max=None):
        from ..sugar import makeDomain
        self._domain = self._target = makeDomain(domain)
        self._min = min
        self._max = max

    def apply(self, x):
        self._check_input(x)
        return x.clip(self._min, self._max)


Martin Reinecke's avatar
Martin Reinecke committed
183
184
185
186
187
188
189
190
191
192
193
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
194
195
196
197
198
199
200
201
202
203
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
204
                res = cls.unpack(op._ops, res)
Martin Reinecke's avatar
Martin Reinecke committed
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
            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
220
221
        self._domain = self._ops[-1].domain
        self._target = self._ops[0].target
Martin Reinecke's avatar
Martin Reinecke committed
222
223
224
        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
225

Martin Reinecke's avatar
Martin Reinecke committed
226
    def apply(self, x):
227
        self._check_input(x)
Martin Reinecke's avatar
Martin Reinecke committed
228
229
230
231
        for op in reversed(self._ops):
            x = op(x)
        return x

Philipp Arras's avatar
Philipp Arras committed
232
233
234
235
236
    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
237
238
239
240
241
242
243
244
245
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
246

Martin Reinecke's avatar
Martin Reinecke committed
247
    def apply(self, x):
Martin Reinecke's avatar
Martin Reinecke committed
248
249
        from ..linearization import Linearization
        from ..sugar import makeOp
250
        self._check_input(x)
Martin Reinecke's avatar
Martin Reinecke committed
251
        lin = isinstance(x, Linearization)
252
253
254
        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
255
        if not lin:
256
            return self._op1(v1) * self._op2(v2)
257
258
259
        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
260
261
        op = (makeOp(lin1._val)(lin2._jac))._myadd(
            makeOp(lin2._val)(lin1._jac), False)
262
        return lin1.new(lin1._val*lin2._val, op(x.jac))
Martin Reinecke's avatar
Martin Reinecke committed
263

Philipp Arras's avatar
Philipp Arras committed
264
265
266
267
268
    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
269
270
class _OpSum(Operator):
    def __init__(self, op1, op2):
Philipp Arras's avatar
Philipp Arras committed
271
        from ..sugar import domain_union
Martin Reinecke's avatar
Martin Reinecke committed
272
273
274
275
        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
276
277

    def apply(self, x):
Martin Reinecke's avatar
Martin Reinecke committed
278
        from ..linearization import Linearization
279
        self._check_input(x)
Martin Reinecke's avatar
Martin Reinecke committed
280
281
282
283
        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
284
        res = None
Martin Reinecke's avatar
Martin Reinecke committed
285
286
        if not lin:
            return self._op1(v1).unite(self._op2(v2))
287
288
289
        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
290
        op = lin1._jac._myadd(lin2._jac, False)
Martin Reinecke's avatar
bug fix    
Martin Reinecke committed
291
        res = lin1.new(lin1._val.unite(lin2._val), op(x.jac))
Martin Reinecke's avatar
Martin Reinecke committed
292
293
        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
294
        return res
Philipp Arras's avatar
Philipp Arras committed
295
296
297
298

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