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DAMASK_EICMD
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fixed (potentially) buggy rotation of tensors. convention is: 

with A v = b
v' = R v
A' = R A R^T
such that
A' v' = R A R^T  R v = R A v (= R b = b', i.e. old result transformed into other coordinate basis)
This commit is contained in:
Philip Eisenlohr 2014-08-22 15:32:48 +00:00
parent df27115472
commit 99e3c9a397
1 changed files with 14 additions and 10 deletions
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14
processing/post/rotateData.py
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@ -23,7 +23,7 @@ parser.add_option('-v','--vector', dest = 'vector', action = 'extend', metavar=
help = 'column heading of vector to scale')
parser.add_option('-t','--tensor', dest = 'tensor', action = 'extend', metavar = 'string',
help = 'column heading of tensor to scale')
parser.add_option('-r', '--rotation',dest = 'rotation', type = 'float', nargs = 4, metavar='int int int int',
parser.add_option('-r', '--rotation',dest = 'rotation', type = 'float', nargs = 4, metavar = ' '.join(['float']*4),
help = 'angle and axis to rotate data %default')
parser.add_option('-d', '--degrees', dest = 'degrees', action = 'store_true',
help = 'angles are given in degrees [%default]')
@ -86,7 +86,9 @@ for file in files:
# ------------------------------------------ process data ------------------------------------------
outputAlive = True
while outputAlive and table.data_read(): # read next data line of ASCII table
datatype = 'vector'
for label in active[datatype] if datatype in active else []: # loop over all requested labels
table.data[column[datatype][label]:column[datatype][label]+datainfo[datatype]['len']] = \
r * np.array(map(float,
@ -96,11 +98,13 @@ for file in files:
datatype = 'tensor'
for label in active[datatype] if datatype in active else []: # loop over all requested labels
table.data[column[datatype][label]:column[datatype][label]+datainfo[datatype]['len']] = \
(np.array(map(float,table.data[column[datatype][label]:\
A = np.array(map(float,table.data[column[datatype][label]:\
column[datatype][label]+datainfo[datatype]['len']])).\
reshape(np.sqrt(datainfo[datatype]['len']),\
np.sqrt(datainfo[datatype]['len'])) * R).reshape(datainfo[datatype]['len'])
reshape(np.sqrt(datainfo[datatype]['len']),
np.sqrt(datainfo[datatype]['len']))
table.data[column[datatype][label]:\
column[datatype][label]+datainfo[datatype]['len']] = \
np.dot(R,np.dot(A,R.transpose())).reshape(datainfo[datatype]['len'])
outputAlive = table.data_write() # output processed line
# ------------------------------------------ output result -----------------------------------------