now using fft reconstruction in 3Dvisualize, linear python code for reconstruction is removed
This commit is contained in:
Martin Diehl
parent
c399a06c97
commit
8a5e28d5a6
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@ -6,7 +6,7 @@
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# computed using the FEM solvers. Until now, its capable to handle elements with one IP in a regular order
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# computed using the FEM solvers. Until now, its capable to handle elements with one IP in a regular order
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# written by M. Diehl, m.diehl@mpie.de
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# written by M. Diehl, m.diehl@mpie.de
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import os,sys,threading,re,numpy,time
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import os,sys,threading,re,numpy,time, postprocessingMath
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from optparse import OptionParser, OptionGroup, Option, SUPPRESS_HELP
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from optparse import OptionParser, OptionGroup, Option, SUPPRESS_HELP
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# -----------------------------
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# -----------------------------
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@ -147,90 +147,6 @@ def mesh(res,geomdim,defgrad_av,centroids):
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return nodes
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return nodes
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# +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
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def deformed(res,geomdimension,defgrad):
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# +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
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corner = numpy.array([[0, 0, 0],
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[1, 0, 0],
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[1, 1, 0],
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[0, 1, 0],
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[1, 1, 1],
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[0, 1, 1],
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[0, 0, 1],
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[1, 0, 1]])
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step = numpy.array([[ 1, 1, 1],
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[-1, 1, 1],
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[-1,-1, 1],
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[ 1,-1, 1],
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[-1,-1,-1],
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[ 1,-1,-1],
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[ 1, 1,-1],
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[-1, 1,-1]])
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order = numpy.array([[0, 1, 2],
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[0, 2, 1],
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[1, 0, 2],
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[1, 2, 0],
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[2, 0, 1],
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[2, 1, 0]])
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coord = numpy.zeros([8,6,res[0],res[1],res[2],3], 'd')
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coord_avgOrder = numpy.zeros([8,res[0],res[1],res[2],3], 'd')
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coord_avgCorner = numpy.zeros([res[0],res[1],res[2],3], 'd')
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myStep = numpy.zeros(3,'d')
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rear = numpy.zeros(3,'i')
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init = numpy.zeros(3,'i')
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oppo = numpy.zeros(3,'i')
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me = numpy.zeros(3,'i')
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ones = numpy.ones( 3,'i')
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fones = numpy.ones( 3,'d')
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defgrad_av=numpy.average(numpy.average(numpy.average(defgrad,0),0),0)
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for s in range(8): # corners
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init = corner[s]*(res-ones)
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oppo = corner[(s+4)%8]*(res-ones)
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sys.stdout.write('.'*(8-s)+' '*s+'\r')
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sys.stdout.flush()
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for o in range(6): # orders
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for k in range(init[order[o,2]],oppo[order[o,2]]+step[s,order[o,2]],step[s,order[o,2]]):
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rear[order[o,1]] = init[order[o,1]]
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for j in range(init[order[o,1]],oppo[order[o,1]]+step[s,order[o,1]],step[s,order[o,1]]):
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rear[order[o,0]] = init[order[o,0]]
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for i in range(init[order[o,0]],oppo[order[o,0]]+step[s,order[o,0]],step[s,order[o,0]]):
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me[order[o,0]] = i
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me[order[o,1]] = j
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me[order[o,2]] = k
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if (numpy.all(me == init)):
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coord[s,o,me[0],me[1],me[2]] = geomdimension * (numpy.dot(defgrad_av,corner[s]) + \
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numpy.dot(defgrad[me[0],me[1],me[2]],0.5*step[s]/res))
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else:
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myStep = (me-rear)*geomdimension/res
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coord[s,o,me[0],me[1],me[2]] = coord[s,o,rear[0],rear[1],rear[2]] + \
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0.5*numpy.dot(defgrad[me[0],me[1],me[2]] + \
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defgrad[rear[0],rear[1],rear[2]],myStep)
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rear[:] = me[:]
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coord_avgOrder[s] = numpy.average(coord[s],0)
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for k in range(res[2]):
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for j in range(res[1]):
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for i in range(res[0]):
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parameter_coords = (2.0*numpy.array([i,j,k])-res+fones)/(res-fones)
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pos = fones + parameter_coords
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neg = fones - parameter_coords
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coord_avgCorner[i,j,k] = ( coord_avgOrder[0,i,j,k] *neg[0]*neg[1]*neg[2]\
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+ coord_avgOrder[1,i,j,k] *pos[0]*neg[1]*neg[2]\
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+ coord_avgOrder[2,i,j,k] *pos[0]*pos[1]*neg[2]\
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+ coord_avgOrder[3,i,j,k] *neg[0]*pos[1]*neg[2]\
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+ coord_avgOrder[4,i,j,k] *pos[0]*pos[1]*pos[2]\
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+ coord_avgOrder[5,i,j,k] *neg[0]*pos[1]*pos[2]\
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+ coord_avgOrder[6,i,j,k] *neg[0]*neg[1]*pos[2]\
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+ coord_avgOrder[7,i,j,k] *pos[0]*neg[1]*pos[2])*0.125
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print ' '
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return coord_avgCorner, defgrad_av
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# ++++++++++++++++++++++++++++++++++++++++++++++++++++
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# ++++++++++++++++++++++++++++++++++++++++++++++++++++
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def vtk_writeASCII_mesh(mesh,data,res):
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def vtk_writeASCII_mesh(mesh,data,res):
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# ++++++++++++++++++++++++++++++++++++++++++++++++++++
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# ++++++++++++++++++++++++++++++++++++++++++++++++++++
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@ -504,11 +420,15 @@ for filename in args:
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print 'resolution',res
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print 'resolution',res
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print 'dimension',dim
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print 'dimension',dim
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defgrad_av = postprocessingMath.tensor_avg(res[0],res[1],res[2],\
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(centroids, defgrad_av) = deformed(res,dim,
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numpy.reshape(values[:,column['tensor'][options.defgrad]:
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column['tensor'][options.defgrad]+9],
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(res[0],res[1],res[2],3,3)))
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print defgrad_av
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centroids = postprocessingMath.deformed_fft(res[0],res[1],res[2],dim,\
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numpy.reshape(values[:,column['tensor'][options.defgrad]:
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numpy.reshape(values[:,column['tensor'][options.defgrad]:
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column['tensor'][options.defgrad]+9],
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column['tensor'][options.defgrad]+9],
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(res[0],res[1],res[2],3,3)))
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(res[0],res[1],res[2],3,3)),defgrad_av,1.0)
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ms = mesh(res,dim,defgrad_av,centroids)
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ms = mesh(res,dim,defgrad_av,centroids)
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fields = {\
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fields = {\
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