1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
|
#!/usr/bin/env python3
# encoding: utf-8
"""
_Stochastic.py
Created by Graham Dennis on 2008-01-13.
Copyright (c) 2008-2012, Graham Dennis and Joe Hope
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 2 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/>.
"""
from xpdeint.Features._Feature import _Feature
from xpdeint.Vectors.NoiseVector import NoiseVector
from xpdeint.Segments.Integrators.AdaptiveStep import AdaptiveStep as AdaptiveStepIntegrator
from xpdeint.Geometry.NonUniformDimensionRepresentation import NonUniformDimensionRepresentation
from xpdeint.Stochastic.RandomVariables.GaussianRandomVariable import GaussianRandomVariable
from xpdeint.ParserException import ParserException, parserWarning
class _Stochastic (_Feature):
def adaptiveIntegratorsWithNoises(self):
adaptiveIntegratorList = [ai for ai in self.getVar('templates') if isinstance(ai, AdaptiveStepIntegrator) and ai.dynamicNoiseVectors]
return adaptiveIntegratorList
def xsilOutputInfo(self, dict):
return '\n'.join(nv.implementationsForFunctionName('xsilOutputInfo', dict) for nv in self.noiseVectors)
def preflight(self):
super(_Stochastic, self).preflight()
self.noiseVectors = [o for o in self.getVar('templates') if isinstance(o, NoiseVector)]
self.nonUniformDimRepsNeededForGaussianNoise = set()
for nv in [nv for nv in self.noiseVectors if isinstance(nv.randomVariable, GaussianRandomVariable)]:
self.nonUniformDimRepsNeededForGaussianNoise.update(dimRep for dimRep in nv.field.inBasis(nv.initialBasis) if isinstance(dimRep, NonUniformDimensionRepresentation))
|
