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DAMASK_EICMD
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shortened excessively long lines

This commit is contained in:
Aritra Chakraborty 2016-03-16 15:12:53 -04:00
parent 3a267dc7ff
commit 36c703ecd3
3 changed files with 33 additions and 30 deletions
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15
processing/post/addCurl.py
View File

@ -11,8 +11,8 @@ scriptID = ' '.join([scriptName,damask.version])
def curlFFT(geomdim,field): def curlFFT(geomdim,field):
grid = np.array(np.shape(field)[2::-1]) grid = np.array(np.shape(field)[2::-1])
N = grid.prod() # field size N = grid.prod() # field size
n = np.array(np.shape(field)[3:]).prod() # data size n = np.array(np.shape(field)[3:]).prod() # data size
if n == 3: dataType = 'vector' if n == 3: dataType = 'vector'
elif n == 9: dataType = 'tensor' elif n == 9: dataType = 'tensor'
@ -25,19 +25,19 @@ def curlFFT(geomdim,field):
TWOPIIMG = 2.0j*math.pi TWOPIIMG = 2.0j*math.pi
for i in xrange(grid[2]): for i in xrange(grid[2]):
k_s[0] = i 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] elif i > grid[2]//2: k_s[0] -= grid[2]
for j in xrange(grid[1]): for j in xrange(grid[1]):
k_s[1] = j 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] elif j > grid[1]//2: k_s[1] -= grid[1]
for k in xrange(grid[0]//2+1): for k in xrange(grid[0]//2+1):
k_s[2] = k 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': if dataType == 'tensor':
for l in xrange(3): for l in xrange(3):
@ -154,7 +154,8 @@ for name in filenames:
stack = [table.data] stack = [table.data]
for type, data in items.iteritems(): for type, data in items.iteritems():
for i,label in enumerate(data['active']): 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']]. table.data[:,data['column'][i]:data['column'][i]+data['dim']].
reshape([grid[2],grid[1],grid[0]]+data['shape']))) reshape([grid[2],grid[1],grid[0]]+data['shape'])))

25
processing/post/addDivergence.py
View File

@ -11,34 +11,34 @@ scriptID = ' '.join([scriptName,damask.version])
def divFFT(geomdim,field): def divFFT(geomdim,field):
grid = np.array(np.shape(field)[2::-1]) grid = np.array(np.shape(field)[2::-1])
N = grid.prod() # field size N = grid.prod() # field size
n = np.array(np.shape(field)[3:]).prod() # data size n = np.array(np.shape(field)[3:]).prod() # data size
field_fourier = np.fft.fftpack.rfftn(field,axes=(0,1,2)) 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 # differentiation in Fourier space
k_s=np.zeros([3],'i') k_s=np.zeros([3],'i')
TWOPIIMG = 2.0j*math.pi TWOPIIMG = 2.0j*math.pi
for i in xrange(grid[2]): for i in xrange(grid[2]):
k_s[0] = i 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] elif i > grid[2]//2: k_s[0] -= grid[2]
for j in xrange(grid[1]): for j in xrange(grid[1]):
k_s[1] = j 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] elif j > grid[1]//2: k_s[1] -= grid[1]
for k in xrange(grid[0]//2+1): for k in xrange(grid[0]//2+1):
k_s[2] = k 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 n == 9: # tensor, 3x3 -> 3 if n == 9: # tensor, 3x3 -> 3
for l in xrange(3): for l in xrange(3):
div_fourier[i,j,k,l] = sum(field_fourier[i,j,k,l,0:3]*xi) *TWOPIIMG 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 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)).reshape([N,n/3])
@ -76,7 +76,7 @@ parser.set_defaults(coords = 'ipinitialcoord',
if options.vector is None and options.tensor is None: if options.vector is None and options.tensor is None:
parser.error('no data column specified.') parser.error('no data column specified.')
# --- loop over input files ------------------------------------------------------------------------- # --- loop over input files ------------------------------------------------------------------------
if filenames == []: filenames = [None] if filenames == []: filenames = [None]
@ -134,14 +134,15 @@ for name in filenames:
maxcorner = np.array(map(max,coords)) maxcorner = np.array(map(max,coords))
grid = np.array(map(len,coords),'i') 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 = 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 ----------------------------------- # ------------------------------------------ process value field -----------------------------------
stack = [table.data] stack = [table.data]
for type, data in items.iteritems(): for type, data in items.iteritems():
for i,label in enumerate(data['active']): 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']]. table.data[:,data['column'][i]:data['column'][i]+data['dim']].
reshape([grid[2],grid[1],grid[0]]+data['shape']))) reshape([grid[2],grid[1],grid[0]]+data['shape'])))

23
processing/post/addGradient.py
View File

@ -11,8 +11,8 @@ scriptID = ' '.join([scriptName,damask.version])
def gradFFT(geomdim,field): def gradFFT(geomdim,field):
grid = np.array(np.shape(field)[2::-1]) grid = np.array(np.shape(field)[2::-1])
N = grid.prod() # field size N = grid.prod() # field size
n = np.array(np.shape(field)[3:]).prod() # data size n = np.array(np.shape(field)[3:]).prod() # data size
if n == 3: dataType = 'vector' if n == 3: dataType = 'vector'
elif n == 1: dataType = 'scalar' elif n == 1: dataType = 'scalar'
@ -24,24 +24,24 @@ def gradFFT(geomdim,field):
TWOPIIMG = 2.0j*math.pi TWOPIIMG = 2.0j*math.pi
for i in xrange(grid[2]): for i in xrange(grid[2]):
k_s[0] = i 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] elif i > grid[2]//2: k_s[0] -= grid[2]
for j in xrange(grid[1]): for j in xrange(grid[1]):
k_s[1] = j 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] elif j > grid[1]//2: k_s[1] -= grid[1]
for k in xrange(grid[0]//2+1): for k in xrange(grid[0]//2+1):
k_s[2] = k 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': 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 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)).reshape([N,3*n])
@ -79,7 +79,7 @@ parser.set_defaults(coords = 'ipinitialcoord',
if options.vector is None and options.scalar is None: if options.vector is None and options.scalar is None:
parser.error('no data column specified.') parser.error('no data column specified.')
# --- loop over input files ------------------------------------------------------------------------- # --- loop over input files ------------------------------------------------------------------------
if filenames == []: filenames = [None] if filenames == []: filenames = [None]
@ -124,7 +124,7 @@ for name in filenames:
table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:])) table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:]))
for type, data in items.iteritems(): for type, data in items.iteritems():
for label in data['active']: 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() table.head_write()
# --------------- figure out size and grid --------------------------------------------------------- # --------------- figure out size and grid ---------------------------------------------------------
@ -143,7 +143,8 @@ for name in filenames:
stack = [table.data] stack = [table.data]
for type, data in items.iteritems(): for type, data in items.iteritems():
for i,label in enumerate(data['active']): 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']]. table.data[:,data['column'][i]:data['column'][i]+data['dim']].
reshape([grid[2],grid[1],grid[0]]+data['shape']))) reshape([grid[2],grid[1],grid[0]]+data['shape'])))