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#!/usr/bin/env python3
# encoding: utf-8
"""
_NoiseVector.py
This contains all the pure-python code for NoiseVector.tmpl
Created by Joe Hope on 2009-08-17.
Copyright (c) 2009-2012, 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.Vectors.VectorElement import VectorElement
from xpdeint.Geometry.NonUniformDimensionRepresentation import NonUniformDimensionRepresentation
from xpdeint.Function import Function
class _NoiseVector (VectorElement):
isNoise = True
def __init__(self, *args, **KWs):
localKWs = self.extractLocalKWs(['staticNoise'], KWs)
VectorElement.__init__(self, *args, **KWs)
self.static = localKWs['staticNoise']
args = []
if not self.static:
args.append(('real', '_step'))
else:
self.isComputed = True
evaluateFunctionName = ''.join(['_', self.id, '_evaluate'])
evaluateFunction = Function(
name = evaluateFunctionName,
args = args,
implementation = self.evaluateFunctionContents
)
self.functions['evaluate'] = evaluateFunction
if not self.static:
splitFunctionName = ''.join(['_', self.id, '_split'])
splitFunction = Function(
name = splitFunctionName,
args = [('real', '_new_step'), ('real', '_old_step'), (self.type + '*', '_old_array')],
implementation = self.splitFunctionContents
)
self.functions['split'] = splitFunction
self.basesNeeded.add(self.initialBasis)
self.needsInitialisation = False
@property
def spatiallyIndependentVolumeElement(self):
reps = self.field.inBasis(self.initialBasis)
result = []
for rep in reps:
if isinstance(rep, NonUniformDimensionRepresentation):
pass
elif rep.type == 'long':
pass # Integer step, so nothing interesting
elif rep.type == 'real':
result.append(rep.stepSize)
result.append(rep.volumePrefactor)
else:
assert False, "Unknown dimension representation type %s" % rep.type
if not result:
return '1.0'
return '(' + ' * '.join(result) + ')'
@property
def nonUniformDimReps(self):
return [rep for rep in self.field.inBasis(self.initialBasis) if isinstance(rep, NonUniformDimensionRepresentation)]
def initialiseGlobalSeeds(self):
return self.randomVariable.generator.initialiseGlobalSeeds()
def initialiseLocalSeeds(self):
return self.randomVariable.generator.initialiseLocalSeeds()
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