def initialize(self,evaluation_points=None):
if evaluation_points is not None:
self._evaluation_points = evaluation_points
self._inside = _bempplib.areInside(self._grid,evaluation_points)
self._outside = _np.logical_not(self._inside)
self._space = _bempplib.createRaviartThomas0VectorSpace(self._context,self._grid)
if self._operator_cache:
self._boundary_operator_cache = _tools.OperatorCache(self._operator_cache_tol)
self._potential_operator_cache = _tools.OperatorCache(self._operator_cache_tol)
def transform_to_full_field_domain_solution(grid,incident_wave,domain_solution,times,points):
if _mpi_rank == 0:
incident_values_domain = _np.zeros_like(domain_solution)
inside = _bempplib.areInside(grid,points)
outside = _np.logical_not(inside)
for ind, t in enumerate(times):
incident_values_domain[:,outside,ind] = incident_wave.value(points[:,outside],t)
sol = incident_values_domain - domain_solution
else:
sol = None
return sol
slPotInt = lib.createHelmholtz3dSingleLayerPotentialOperator(context, kInt)
dlPotInt = lib.createHelmholtz3dDoubleLayerPotentialOperator(context, kInt)
slPotExt = lib.createHelmholtz3dSingleLayerPotentialOperator(context, kExt)
dlPotExt = lib.createHelmholtz3dDoubleLayerPotentialOperator(context, kExt)
# Create a grid of points
nPointsX = 201
nPointsY = 201
x, y, z = np.mgrid[-5:5:nPointsX*1j, -5:5:nPointsY*1j, 0:0:1j]
points = np.vstack((x.ravel(), y.ravel(), z.ravel()))
# Split the points into those located inside and outside the scatterer
inside = lib.areInside(grid, points)
outside = np.logical_not(inside)
# Use appropriate Green's representation formulas to evaluate the total field
# inside and outside the scatterer
evalOptions = lib.createEvaluationOptions()
valsExt = (- slPotExt.evaluateAtPoints(uScDeriv, points[:,outside], evalOptions)
+ dlPotExt.evaluateAtPoints(uSc, points[:,outside], evalOptions)
+ uIncData(points[:,outside]))
valsInt = ( slPotInt.evaluateAtPoints(uIntDeriv, points[:,inside], evalOptions)
- dlPotInt.evaluateAtPoints(uInt, points[:,inside], evalOptions))
# Combine the results obtained for points inside and outside the scatterer
# in a single array
slPotInt = lib.createHelmholtz3dSingleLayerPotentialOperator(context, kInt)
dlPotInt = lib.createHelmholtz3dDoubleLayerPotentialOperator(context, kInt)
slPotExt = lib.createHelmholtz3dSingleLayerPotentialOperator(context, kExt)
dlPotExt = lib.createHelmholtz3dDoubleLayerPotentialOperator(context, kExt)
# Create a grid of points
nPointsX = 201
nPointsY = 201
x, y, z = np.mgrid[-5:5:nPointsX*1j, -5:5:nPointsY*1j, 0:0:1j]
points = np.vstack((x.ravel(), y.ravel(), z.ravel()))
# Split the points into those located inside and outside the scatterer
inside = lib.areInside(grid, points)
outside = np.logical_not(inside)
# Use appropriate Green's representation formulas to evaluate the total field
# inside and outside the scatterer
evalOptions = lib.createEvaluationOptions()
valsExt = (- slPotExt.evaluateAtPoints(uScDeriv, points[:,outside], evalOptions)
+ dlPotExt.evaluateAtPoints(uSc, points[:,outside], evalOptions)
+ uIncData(points[:,outside]))
valsInt = ( slPotInt.evaluateAtPoints(uIntDeriv, points[:,inside], evalOptions)
- dlPotInt.evaluateAtPoints(uInt, points[:,inside], evalOptions))
# Combine the results obtained for points inside and outside the scatterer
# in a single array