operator.py 14.7 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 ..utilities import NiftyMeta, indent
Martin Reinecke's avatar
Martin Reinecke committed
20
21


Martin Reinecke's avatar
Martin Reinecke committed
22
class Operator(metaclass=NiftyMeta):
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
    def scale(self, factor):
        if factor == 1:
            return self
        from .scaling_operator import ScalingOperator
63
        return ScalingOperator(self.target, factor)(self)
Martin Reinecke's avatar
cleanup    
Martin Reinecke committed
64
65
66
67
68

    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

82
83
84
85
86
    def __rmatmul__(self, x):
        if not isinstance(x, Operator):
            return NotImplemented
        return _OpChain.make((x, self))

Philipp Arras's avatar
Philipp Arras committed
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
    def partial_insert(self, x):
        from ..multi_domain import MultiDomain
        if not isinstance(x, Operator):
            raise TypeError
        if not isinstance(self.domain, MultiDomain):
            raise TypeError
        if not isinstance(x.target, MultiDomain):
            raise TypeError
        bigdom = MultiDomain.union([self.domain, x.target])
        k1, k2 = set(self.domain.keys()), set(x.target.keys())
        le, ri = k2 - k1, k1 - k2
        leop, riop = self, x
        if len(ri) > 0:
            riop = riop + self.identity_operator(
                MultiDomain.make({kk: bigdom[kk]
                                  for kk in ri}))
        if len(le) > 0:
            leop = leop + self.identity_operator(
                MultiDomain.make({kk: bigdom[kk]
                                  for kk in le}))
        return leop @ riop

    @staticmethod
    def identity_operator(dom):
        from .block_diagonal_operator import BlockDiagonalOperator
        from .scaling_operator import ScalingOperator
        idops = {kk: ScalingOperator(dd, 1.) for kk, dd in dom.items()}
        return BlockDiagonalOperator(dom, idops)

Martin Reinecke's avatar
Martin Reinecke committed
116
    def __mul__(self, x):
117
118
119
120
121
        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
122

123
124
125
    def __rmul__(self, x):
        return self.__mul__(x)

Philipp Arras's avatar
Philipp Arras committed
126
127
128
    def __add__(self, x):
        if not isinstance(x, Operator):
            return NotImplemented
Martin Reinecke's avatar
Martin Reinecke committed
129
        return _OpSum(self, x)
Philipp Arras's avatar
Philipp Arras committed
130

131
132
133
134
135
    def __sub__(self, x):
        if not isinstance(x, Operator):
            return NotImplemented
        return _OpSum(self, -x)

Martin Reinecke's avatar
Martin Reinecke committed
136
137
138
139
140
    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
141
142
143
    def clip(self, min=None, max=None):
        if min is None and max is None:
            return self
Jakob Knollmueller's avatar
Jakob Knollmueller committed
144
        return _OpChain.make((_Clipper(self.target, min, max), self))
Martin Reinecke's avatar
Martin Reinecke committed
145

Martin Reinecke's avatar
Martin Reinecke committed
146
    def apply(self, x):
147
        """Applies the operator to a Field or MultiField.
Philipp Arras's avatar
Docs    
Philipp Arras committed
148
149
150
151
152
153

        Parameters
        ----------
        x : Field or MultiField
            Input on which the operator shall act. Needs to be defined on
            :attr:`domain`.
154
        """
Martin Reinecke's avatar
Martin Reinecke committed
155
        raise NotImplementedError
Martin Reinecke's avatar
Martin Reinecke committed
156

Philipp Arras's avatar
Philipp Arras committed
157
    def force(self, x):
Philipp Arras's avatar
Docs    
Philipp Arras committed
158
159
        """Extract subset of domain of x according to `self.domain` and apply
        operator."""
Philipp Arras's avatar
Philipp Arras committed
160
161
        return self.apply(x.extract(self.domain))

162
163
164
    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
165
        self._check_domain_equality(self._domain, d)
166

Martin Reinecke's avatar
Martin Reinecke committed
167
    def __call__(self, x):
Martin Reinecke's avatar
Martin Reinecke committed
168
169
170
        if isinstance(x, Operator):
            return _OpChain.make((self, x))
        return self.apply(x)
Martin Reinecke's avatar
Martin Reinecke committed
171

Martin Reinecke's avatar
Martin Reinecke committed
172
173
174
175
176
177
178
179
    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
180
181
182
    def __repr__(self):
        return self.__class__.__name__

183
    def simplify_for_constant_input(self, c_inp):
Martin Reinecke's avatar
cleanup    
Martin Reinecke committed
184
        if c_inp is None:
185
            return None, self
Martin Reinecke's avatar
cleanup    
Martin Reinecke committed
186
187
188
189
190
191
192
        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
193

Martin Reinecke's avatar
Martin Reinecke committed
194

195
196
for f in ["sqrt", "exp", "log", "sin", "cos", "tan", "sinh", "cosh", "tanh",
          "sinc", "sigmoid", "absolute", "one_over", "log10", "log1p", "expm1"]:
Martin Reinecke's avatar
Martin Reinecke committed
197
198
    def func(f):
        def func2(self):
199
            fa = _FunctionApplier(self.target, f)
Martin Reinecke's avatar
Martin Reinecke committed
200
201
202
203
204
            return _OpChain.make((fa, self))
        return func2
    setattr(Operator, f, func(f))


205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
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(
Martin Reinecke's avatar
Martin Reinecke committed
233
234
                    {key: const[key]
                     for key in const.keys() if key not in self._nc})
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
            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
Martin Reinecke's avatar
fixes    
Martin Reinecke committed
256
        from ..domain_tuple import DomainTuple
257
258
259
        self._check_input(x)
        if not isinstance(x, Linearization):
            return self._output
Martin Reinecke's avatar
fixes    
Martin Reinecke committed
260
261
262
263
264
265
        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)
266
267
268

    def __repr__(self):
        return 'ConstantOperator <- {}'.format(self.domain.keys())
Philipp Arras's avatar
Philipp Arras committed
269
270


Martin Reinecke's avatar
Martin Reinecke committed
271
272
273
class _FunctionApplier(Operator):
    def __init__(self, domain, funcname):
        from ..sugar import makeDomain
Martin Reinecke's avatar
Martin Reinecke committed
274
        self._domain = self._target = makeDomain(domain)
Martin Reinecke's avatar
Martin Reinecke committed
275
276
        self._funcname = funcname

Martin Reinecke's avatar
Martin Reinecke committed
277
    def apply(self, x):
278
        self._check_input(x)
Martin Reinecke's avatar
Martin Reinecke committed
279
280
281
        return getattr(x, self._funcname)()


Martin Reinecke's avatar
Martin Reinecke committed
282
283
284
285
286
287
288
289
290
291
292
293
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
294
295
296
297
298
299
300
301
302
303
304
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
305
306
307
308
309
310
311
312
313
314
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
315
                res = cls.unpack(op._ops, res)
Martin Reinecke's avatar
Martin Reinecke committed
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
            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
331
332
        self._domain = self._ops[-1].domain
        self._target = self._ops[0].target
Martin Reinecke's avatar
Martin Reinecke committed
333
334
335
        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
336

Martin Reinecke's avatar
Martin Reinecke committed
337
    def apply(self, x):
338
        self._check_input(x)
Martin Reinecke's avatar
Martin Reinecke committed
339
340
341
342
        for op in reversed(self._ops):
            x = op(x)
        return x

Martin Reinecke's avatar
cleanup    
Martin Reinecke committed
343
    def _simplify_for_constant_input_nontrivial(self, c_inp):
344
345
346
347
348
349
350
351
352
        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
Martin Reinecke's avatar
Martin Reinecke committed
353

Philipp Arras's avatar
Philipp Arras committed
354
355
356
357
358
    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
359
360
361
362
363
364
365
366
367
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
368

Martin Reinecke's avatar
Martin Reinecke committed
369
    def apply(self, x):
Martin Reinecke's avatar
Martin Reinecke committed
370
371
        from ..linearization import Linearization
        from ..sugar import makeOp
372
        self._check_input(x)
Martin Reinecke's avatar
Martin Reinecke committed
373
        lin = isinstance(x, Linearization)
374
375
376
        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
377
        if not lin:
378
            return self._op1(v1) * self._op2(v2)
379
380
381
        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
382
383
        op = (makeOp(lin1._val)(lin2._jac))._myadd(
            makeOp(lin2._val)(lin1._jac), False)
384
        return lin1.new(lin1._val*lin2._val, op(x.jac))
Martin Reinecke's avatar
Martin Reinecke committed
385

Martin Reinecke's avatar
cleanup    
Martin Reinecke committed
386
    def _simplify_for_constant_input_nontrivial(self, c_inp):
387
388
389
390
391
392
393
394
395
396
397
398
399
        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)
Martin Reinecke's avatar
Martin Reinecke committed
400

Philipp Arras's avatar
Philipp Arras committed
401
402
403
404
405
    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
406
407
class _OpSum(Operator):
    def __init__(self, op1, op2):
Philipp Arras's avatar
Philipp Arras committed
408
        from ..sugar import domain_union
Martin Reinecke's avatar
Martin Reinecke committed
409
410
411
412
        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
413
414

    def apply(self, x):
Martin Reinecke's avatar
Martin Reinecke committed
415
        from ..linearization import Linearization
416
        self._check_input(x)
Martin Reinecke's avatar
Martin Reinecke committed
417
418
419
420
421
422
        lin = isinstance(x, Linearization)
        v = x._val if lin else x
        v1 = v.extract(self._op1.domain)
        v2 = v.extract(self._op2.domain)
        if not lin:
            return self._op1(v1).unite(self._op2(v2))
423
424
425
        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
426
        op = lin1._jac._myadd(lin2._jac, False)
Martin Reinecke's avatar
bug fix    
Martin Reinecke committed
427
        res = lin1.new(lin1._val.unite(lin2._val), op(x.jac))
Martin Reinecke's avatar
Martin Reinecke committed
428
        if lin1._metric is not None and lin2._metric is not None:
Reimar H Leike's avatar
Reimar H Leike committed
429
            from .sandwich_operator import SandwichOperator
Philipp Arras's avatar
PEP8    
Philipp Arras committed
430
431
            met = lin1._metric._myadd(lin2._metric, False)
            met = SandwichOperator.make(x.jac, met)
Reimar H Leike's avatar
Reimar H Leike committed
432
            res = res.add_metric(met)
Philipp Arras's avatar
Philipp Arras committed
433
        return res
434

Martin Reinecke's avatar
cleanup    
Martin Reinecke committed
435
    def _simplify_for_constant_input_nontrivial(self, c_inp):
436
437
438
439
440
441
442
443
444
445
446
447
448
        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)
Philipp Arras's avatar
Philipp Arras committed
449
450
451
452

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