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DAMASK_EICMD
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should work now with odd resolution as well

This commit is contained in:
Martin Diehl 2016-04-11 20:25:24 +02:00
parent 18f18aa4b9
commit 70afa462b2
3 changed files with 13 additions and 9 deletions
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7
processing/post/addCurl.py
View File

@ -10,6 +10,7 @@ scriptName = os.path.splitext(os.path.basename(__file__))[0]
scriptID = ' '.join([scriptName,damask.version])
def curlFFT(geomdim,field):
shapeFFT = np.array(np.shape(field))[0:3]
grid = np.array(np.shape(field)[2::-1])
N = grid.prod() # field size
n = np.array(np.shape(field)[3:]).prod() # data size
@ -17,8 +18,8 @@ def curlFFT(geomdim,field):
if n == 3: dataType = 'vector'
elif n == 9: dataType = 'tensor'
field_fourier = np.fft.fftpack.rfftn(field,axes=(0,1,2))
curl_fourier = np.zeros(field_fourier.shape,'c16')
field_fourier = np.fft.fftpack.rfftn(field,axes=(0,1,2),s=shapeFFT)
curl_fourier = np.empty(field_fourier.shape,'c16')
# differentiation in Fourier space
k_s = np.zeros([3],'i')
@ -55,7 +56,7 @@ def curlFFT(geomdim,field):
curl_fourier[i,j,k,2] = ( field_fourier[i,j,k,1]*xi[0]\
-field_fourier[i,j,k,0]*xi[1]) *TWOPIIMG
return np.fft.fftpack.irfftn(curl_fourier,axes=(0,1,2)).reshape([N,n])
return np.fft.fftpack.irfftn(curl_fourier,axes=(0,1,2),s=shapeFFT).reshape([N,n])
# --------------------------------------------------------------------

7
processing/post/addDivergence.py
View File

@ -10,12 +10,13 @@ scriptName = os.path.splitext(os.path.basename(__file__))[0]
scriptID = ' '.join([scriptName,damask.version])
def divFFT(geomdim,field):
shapeFFT = np.array(np.shape(field))[0:3]
grid = np.array(np.shape(field)[2::-1])
N = grid.prod() # field size
n = np.array(np.shape(field)[3:]).prod() # data size
field_fourier = np.fft.fftpack.rfftn(field,axes=(0,1,2))
div_fourier = np.zeros(field_fourier.shape[0:len(np.shape(field))-1],'c16') # size depents on whether tensor or vector
field_fourier = np.fft.fftpack.rfftn(field,axes=(0,1,2),s=shapeFFT)
div_fourier = np.empty(field_fourier.shape[0:len(np.shape(field))-1],'c16') # size depents on whether tensor or vector
# differentiation in Fourier space
k_s=np.zeros([3],'i')
@ -41,7 +42,7 @@ def divFFT(geomdim,field):
elif n == 3: # vector, 3 -> 1
div_fourier[i,j,k] = sum(field_fourier[i,j,k,0:3]*xi) *TWOPIIMG
return np.fft.fftpack.irfftn(div_fourier,axes=(0,1,2)).reshape([N,n/3])
return np.fft.fftpack.irfftn(div_fourier,axes=(0,1,2),s=shapeFFT).reshape([N,n/3])
# --------------------------------------------------------------------

8
processing/post/addGradient.py
View File

@ -10,14 +10,16 @@ scriptName = os.path.splitext(os.path.basename(__file__))[0]
scriptID = ' '.join([scriptName,damask.version])
def gradFFT(geomdim,field):
shapeFFT = np.array(np.shape(field))[0:3]
grid = np.array(np.shape(field)[2::-1])
N = grid.prod() # field size
n = np.array(np.shape(field)[3:]).prod() # data size
if n == 3: dataType = 'vector'
elif n == 1: dataType = 'scalar'
field_fourier = np.fft.fftpack.rfftn(field,axes=(0,1,2))
grad_fourier = np.zeros(field_fourier.shape+(3,),'c16')
field_fourier = np.fft.fftpack.rfftn(field,axes=(0,1,2),s=shapeFFT)
grad_fourier = np.empty(field_fourier.shape+(3,),'c16')
# differentiation in Fourier space
k_s = np.zeros([3],'i')
@ -44,7 +46,7 @@ def gradFFT(geomdim,field):
grad_fourier[i,j,k,1,:] = field_fourier[i,j,k,1]*xi *TWOPIIMG # tensor field from vector data
grad_fourier[i,j,k,2,:] = field_fourier[i,j,k,2]*xi *TWOPIIMG
return np.fft.fftpack.irfftn(grad_fourier,axes=(0,1,2)).reshape([N,3*n])
return np.fft.fftpack.irfftn(grad_fourier,axes=(0,1,2),s=shapeFFT).reshape([N,3*n])
# --------------------------------------------------------------------