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#!/usr/bin/env python3
# encoding: utf-8
"""
_NonUniformDimensionRepresentation.py
Created by Graham Dennis on 2008-07-30.
Copyright (c) 2008-2012, Graham Dennis
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.Geometry.DimensionRepresentation import DimensionRepresentation
from xpdeint.Utilities import lazy_property
class _NonUniformDimensionRepresentation(DimensionRepresentation):
"""
This class represents a dimension with non-uniform spacing. This corresponds
to two main possibilities.
The first is the propagation dimension where each point in this dimension
corresponds to a time at which sampling occurred. This isn't necessarily
uniform.
The second is a Gauss-Lobotto grid for a transverse dimension in the problem.
In this case, the points will not be equally spaced in order to optimise
integration across the dimension. Also, the 'step size' variable in this case
corresponds to the Gauss-Lobotto weight for each grid point and is not directly
related to the separation of two neighbouring grid points. This is perfectly
sensible as the step size is only used as a weight when integrating across
dimensions, which is exactly where the weight should be used.
"""
instanceAttributes = ['stepSizeArray']
instanceDefaults = dict(
stepSizeArray = False
)
@lazy_property
def index(self):
return self.prefix + '_index_' + self.name
@lazy_property
def arrayName(self):
return self.prefix + '_' + self.name
@lazy_property
def stepSizeArrayName(self):
return self.prefix + '_d' + self.name + '_array'
@lazy_property
def stepSize(self):
if self.stepSizeArray:
# We can do this because the step size is only defined inside a loop as the
# step size depends on position.
return 'd' + self.name
else:
return super(_NonUniformDimensionRepresentation, self).stepSize
def openLoop(self, loopingOrder):
if loopingOrder in [self.LoopingOrder.MemoryOrder, self.LoopingOrder.StrictlyAscendingOrder]:
return self.openLoopAscending()
else:
raise NotImplemented
def closeLoop(self, loopingOrder):
if loopingOrder in [self.LoopingOrder.MemoryOrder, self.LoopingOrder.StrictlyAscendingOrder]:
return self.closeLoopAscending()
else:
raise NotImplemented
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