diff --git a/processing/post/addCurl.py b/processing/post/addCurl.py index 6789b27d5..d8b1ee025 100755 --- a/processing/post/addCurl.py +++ b/processing/post/addCurl.py @@ -11,8 +11,8 @@ scriptID = ' '.join([scriptName,damask.version]) def curlFFT(geomdim,field): grid = np.array(np.shape(field)[2::-1]) - N = grid.prod() # field size - n = np.array(np.shape(field)[3:]).prod() # data size + N = grid.prod() # field size + n = np.array(np.shape(field)[3:]).prod() # data size if n == 3: dataType = 'vector' elif n == 9: dataType = 'tensor' @@ -25,19 +25,19 @@ def curlFFT(geomdim,field): TWOPIIMG = 2.0j*math.pi for i in xrange(grid[2]): k_s[0] = i - if grid[2]%2 == 0 and i == grid[2]//2: k_s[0] = 0 # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011) + if grid[2]%2 == 0 and i == grid[2]//2: k_s[0] = 0 # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011) elif i > grid[2]//2: k_s[0] -= grid[2] for j in xrange(grid[1]): k_s[1] = j - if grid[1]%2 == 0 and j == grid[1]//2: k_s[1] = 0 # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011) + if grid[1]%2 == 0 and j == grid[1]//2: k_s[1] = 0 # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011) elif j > grid[1]//2: k_s[1] -= grid[1] for k in xrange(grid[0]//2+1): k_s[2] = k - if grid[0]%2 == 0 and k == grid[0]//2: k_s[2] = 0 # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011) + if grid[0]%2 == 0 and k == grid[0]//2: k_s[2] = 0 # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011) - xi = (k_s/geomdim)[2::-1].astype('c16') # reversing the field input order + xi = (k_s/geomdim)[2::-1].astype('c16') # reversing the field input order if dataType == 'tensor': for l in xrange(3): @@ -154,7 +154,8 @@ for name in filenames: stack = [table.data] for type, data in items.iteritems(): for i,label in enumerate(data['active']): - stack.append(curlFFT(size[::-1], # we need to reverse order here, because x is fastest,ie rightmost, but leftmost in our x,y,z notation + # we need to reverse order here, because x is fastest,ie rightmost, but leftmost in our x,y,z notation + stack.append(curlFFT(size[::-1], table.data[:,data['column'][i]:data['column'][i]+data['dim']]. reshape([grid[2],grid[1],grid[0]]+data['shape']))) diff --git a/processing/post/addDivergence.py b/processing/post/addDivergence.py index 99b56ead2..aadaceabf 100755 --- a/processing/post/addDivergence.py +++ b/processing/post/addDivergence.py @@ -11,34 +11,34 @@ scriptID = ' '.join([scriptName,damask.version]) def divFFT(geomdim,field): grid = np.array(np.shape(field)[2::-1]) - N = grid.prod() # field size - n = np.array(np.shape(field)[3:]).prod() # data size + 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 + div_fourier = np.zeros(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') TWOPIIMG = 2.0j*math.pi for i in xrange(grid[2]): k_s[0] = i - if grid[2]%2 == 0 and i == grid[2]//2: k_s[0] = 0 # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011) + if grid[2]%2 == 0 and i == grid[2]//2: k_s[0] = 0 # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011) elif i > grid[2]//2: k_s[0] -= grid[2] for j in xrange(grid[1]): k_s[1] = j - if grid[1]%2 == 0 and j == grid[1]//2: k_s[1] = 0 # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011) + if grid[1]%2 == 0 and j == grid[1]//2: k_s[1] = 0 # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011) elif j > grid[1]//2: k_s[1] -= grid[1] for k in xrange(grid[0]//2+1): k_s[2] = k - if grid[0]%2 == 0 and k == grid[0]//2: k_s[2] = 0 # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011) + if grid[0]%2 == 0 and k == grid[0]//2: k_s[2] = 0 # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011) - xi = (k_s/geomdim)[2::-1].astype('c16') # reversing the field input order - if n == 9: # tensor, 3x3 -> 3 + xi = (k_s/geomdim)[2::-1].astype('c16') # reversing the field input order + if n == 9: # tensor, 3x3 -> 3 for l in xrange(3): div_fourier[i,j,k,l] = sum(field_fourier[i,j,k,l,0:3]*xi) *TWOPIIMG - elif n == 3: # vector, 3 -> 1 + 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]) @@ -76,7 +76,7 @@ parser.set_defaults(coords = 'ipinitialcoord', if options.vector is None and options.tensor is None: parser.error('no data column specified.') -# --- loop over input files ------------------------------------------------------------------------- +# --- loop over input files ------------------------------------------------------------------------ if filenames == []: filenames = [None] @@ -134,14 +134,15 @@ for name in filenames: maxcorner = np.array(map(max,coords)) grid = np.array(map(len,coords),'i') size = grid/np.maximum(np.ones(3,'d'), grid-1.0) * (maxcorner-mincorner) # size from edge to edge = dim * n/(n-1) - size = np.where(grid > 1, size, min(size[grid > 1]/grid[grid > 1])) # spacing for grid==1 equal to smallest among other spacings + size = np.where(grid > 1, size, min(size[grid > 1]/grid[grid > 1])) # spacing for grid==1 equal to smallest among other ones # ------------------------------------------ process value field ----------------------------------- stack = [table.data] for type, data in items.iteritems(): for i,label in enumerate(data['active']): - stack.append(divFFT(size[::-1], # we need to reverse order here, because x is fastest,ie rightmost, but leftmost in our x,y,z notation + # we need to reverse order here, because x is fastest,ie rightmost, but leftmost in our x,y,z notation + stack.append(divFFT(size[::-1], table.data[:,data['column'][i]:data['column'][i]+data['dim']]. reshape([grid[2],grid[1],grid[0]]+data['shape']))) diff --git a/processing/post/addGradient.py b/processing/post/addGradient.py index 0d7caa829..555e587de 100755 --- a/processing/post/addGradient.py +++ b/processing/post/addGradient.py @@ -11,8 +11,8 @@ scriptID = ' '.join([scriptName,damask.version]) def gradFFT(geomdim,field): grid = np.array(np.shape(field)[2::-1]) - N = grid.prod() # field size - n = np.array(np.shape(field)[3:]).prod() # data size + 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' @@ -24,24 +24,24 @@ def gradFFT(geomdim,field): TWOPIIMG = 2.0j*math.pi for i in xrange(grid[2]): k_s[0] = i - if grid[2]%2 == 0 and i == grid[2]//2: k_s[0] = 0 # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011) + if grid[2]%2 == 0 and i == grid[2]//2: k_s[0] = 0 # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011) elif i > grid[2]//2: k_s[0] -= grid[2] for j in xrange(grid[1]): k_s[1] = j - if grid[1]%2 == 0 and j == grid[1]//2: k_s[1] = 0 # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011) + if grid[1]%2 == 0 and j == grid[1]//2: k_s[1] = 0 # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011) elif j > grid[1]//2: k_s[1] -= grid[1] for k in xrange(grid[0]//2+1): k_s[2] = k - if grid[0]%2 == 0 and k == grid[0]//2: k_s[2] = 0 # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011) + if grid[0]%2 == 0 and k == grid[0]//2: k_s[2] = 0 # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011) - xi = (k_s/geomdim)[2::-1].astype('c16') # reversing the field order + xi = (k_s/geomdim)[2::-1].astype('c16') # reversing the field order - grad_fourier[i,j,k,0,:] = field_fourier[i,j,k,0]*xi *TWOPIIMG # vector field from scalar data + grad_fourier[i,j,k,0,:] = field_fourier[i,j,k,0]*xi *TWOPIIMG # vector field from scalar data if dataType == 'vector': - grad_fourier[i,j,k,1,:] = field_fourier[i,j,k,1]*xi *TWOPIIMG # tensor field from vector data + 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]) @@ -79,7 +79,7 @@ parser.set_defaults(coords = 'ipinitialcoord', if options.vector is None and options.scalar is None: parser.error('no data column specified.') -# --- loop over input files ------------------------------------------------------------------------- +# --- loop over input files ------------------------------------------------------------------------ if filenames == []: filenames = [None] @@ -124,7 +124,7 @@ for name in filenames: table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:])) for type, data in items.iteritems(): for label in data['active']: - table.labels_append(['{}_gradFFT({})'.format(i+1,label) for i in xrange(3 * data['dim'])]) # extend ASCII header with new labels # grad increases the field dimension by one + table.labels_append(['{}_gradFFT({})'.format(i+1,label) for i in xrange(3 * data['dim'])]) # extend ASCII header with new labels table.head_write() # --------------- figure out size and grid --------------------------------------------------------- @@ -143,7 +143,8 @@ for name in filenames: stack = [table.data] for type, data in items.iteritems(): for i,label in enumerate(data['active']): - stack.append(gradFFT(size[::-1], # we need to reverse order here, because x is fastest,ie rightmost, but leftmost in our x,y,z notation + # we need to reverse order here, because x is fastest,ie rightmost, but leftmost in our x,y,z notation + stack.append(gradFFT(size[::-1], table.data[:,data['column'][i]:data['column'][i]+data['dim']]. reshape([grid[2],grid[1],grid[0]]+data['shape'])))