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post processing scripts are working again. 

@Philip: definining one offset for shiftData and one factor for scaleData for tensor/vector/special>1 seems to be more reasonable than per component
This commit is contained in:
Martin Diehl 2014-08-25 21:13:39 +00:00
parent fa45d376a1
commit 6cdcdecdfa
3 changed files with 34 additions and 34 deletions
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4
processing/post/binXY.py
View File

@ -72,7 +72,7 @@ for file in files:
skip = int(file['input'].readline().split()[0]) skip = int(file['input'].readline().split()[0])
for i in xrange(skip): headers = file['input'].readline().split() for i in xrange(skip): headers = file['input'].readline().split()
data = np.loadtxt(file['input'],usecols=np.array(options.data+((options.weight,) if options.weight != None else ()))-1) data = np.loadtxt(file['input'],usecols=np.array(options.data+((options.weight,) if options.weight != None else ()))-1)
table.input_close() # close input ASCII table file['input'].close() # close input ASCII table
for i in (0,1): # check data range for x and y for i in (0,1): # check data range for x and y
if (range[i] == 0.0).all(): range[i] = [data[:,i].min(),data[:,i].max()] if (range[i] == 0.0).all(): range[i] = [data[:,i].min(),data[:,i].max()]
@ -113,7 +113,7 @@ for file in files:
file['output'].write('1\thead\n') file['output'].write('1\thead\n')
file['output'].write('bin_%s\tbin_%s\tz\n'%(headers[options.data[0]-1],headers[options.data[1]-1])) file['output'].write('bin_%s\tbin_%s\tz\n'%(headers[options.data[0]-1],headers[options.data[1]-1]))
np.savetxt(file['output'],result) np.savetxt(file['output'],result)
table.output_close() # close output ASCII table file['output'].close() # close output ASCII table
if file['name'] != 'STDIN': if file['name'] != 'STDIN':
os.rename(file['name']+'_tmp',\ os.rename(file['name']+'_tmp',\
os.path.join(os.path.dirname(file['name']),prefix+os.path.basename(file['name']))) os.path.join(os.path.dirname(file['name']),prefix+os.path.basename(file['name'])))

16
processing/post/scaleData.py
View File

@ -15,20 +15,20 @@ scriptName = scriptID.split()[1][:-3]
# -------------------------------------------------------------------- # --------------------------------------------------------------------
parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [file[s]]', description = """ parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [file[s]]', description = """
Uniformly scale values of scalar, vector, or tensor columns by given factor. Uniformly scale values scalar/special, vector, or tensor columns by given factor.
""", version = scriptID) """, version = scriptID)
parser.add_option('-s','--special', dest='special', action='extend', type='string', metavar='<string LIST>', parser.add_option('-s','--special', dest='special', action='extend', type='string', metavar='<string LIST>',
help='heading of columns containing field values of special dimension') help='heading of columns containing field values of special dimension')
parser.add_option('-d','--dimension', dest='N', action='store', type='int', metavar='int', parser.add_option('-d','--dimension',dest='N', type='int', metavar='int',
help='dimension of special field values [%default]') help='dimension of special field values [%default]')
parser.add_option('-v','--vector', dest='vector', action='extend', metavar='<string LIST>', parser.add_option('-v','--vector', dest='vector', action='extend', metavar='<string LIST>',
help='column heading of vector to scale') help='column heading of vector to scale')
parser.add_option('-t','--tensor', dest='tensor', action='extend', metavar='<string LIST>', parser.add_option('-t','--tensor', dest='tensor', action='extend', metavar='<string LIST>',
help='column heading of tensor to scale') help='column heading of tensor to scale')
parser.add_option('-f','--factor', dest='factor', action='extend', metavar='<float LIST>', parser.add_option('-f','--factor', dest='factor', action='extend', metavar='<float LIST>',
help='list of scalar, vector, and tensor scaling factors (in this order!)') help='list of scalar/special, vector, and tensor scaling factors (in this order!)')
parser.set_defaults(special = []) parser.set_defaults(special = [])
parser.set_defaults(vector = []) parser.set_defaults(vector = [])
@ -40,7 +40,7 @@ parser.set_defaults(N = 1)
options.factor = np.array(options.factor,'d') options.factor = np.array(options.factor,'d')
datainfo = { # list of requested labels per datatype datainfo = { # list of requested labels per datatype
'scalar': {'len':options.N, 'special': {'len':options.N,
'label':[]}, 'label':[]},
'vector': {'len':3, 'vector': {'len':3,
'label':[]}, 'label':[]},
@ -49,9 +49,9 @@ datainfo = { # lis
} }
length = 0 length = 0
if options.special != []: datainfo['special']['label'] += options.special; length += len(options.scalar)*datainfo['special']['len'] if options.special != []: datainfo['special']['label'] += options.special; length += len(options.special)
if options.vector != []: datainfo['vector']['label'] += options.vector; length += len(options.vector)*datainfo['vector']['len'] if options.vector != []: datainfo['vector']['label'] += options.vector; length += len(options.vector)
if options.tensor != []: datainfo['tensor']['label'] += options.tensor; length += len(options.tensor)*datainfo['tensor']['len'] if options.tensor != []: datainfo['tensor']['label'] += options.tensor; length += len(options.tensor)
if len(options.factor) != length: if len(options.factor) != length:
parser.error('length of scaling vector does not match column count...') parser.error('length of scaling vector does not match column count...')
@ -93,7 +93,7 @@ for file in files:
outputAlive = True outputAlive = True
while outputAlive and table.data_read(): # read next data line of ASCII table while outputAlive and table.data_read(): # read next data line of ASCII table
i = 0 i = 0
for datatype,labels in sorted(active.items(),key=lambda x:datainfo[x[0]]['len']): # loop over scalar,vector,tensor for datatype,labels in sorted(active.items(),key=lambda x:datainfo[x[0]]['len']): # loop over special,vector,tensor
for label in labels: # loop over all requested labels for label in labels: # loop over all requested labels
for j in xrange(datainfo[datatype]['len']): # loop over entity elements for j in xrange(datainfo[datatype]['len']): # loop over entity elements
table.data[column[datatype][label]+j] = float(table.data[column[datatype][label]+j]) * options.factor[i] table.data[column[datatype][label]+j] = float(table.data[column[datatype][label]+j]) * options.factor[i]

12
processing/post/shiftData.py
View File

@ -15,13 +15,13 @@ scriptName = scriptID.split()[1][:-3]
# -------------------------------------------------------------------- # --------------------------------------------------------------------
parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [file[s]]', description = """ parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [file[s]]', description = """
Shift values of scalar, vector, or tensor columns by given offset. Shift values of scalar/special, vector, or tensor columns by given offset.
""", version = scriptID) """, version = scriptID)
parser.add_option('-s','--special', dest='special', action='extend', type='string', metavar='<string LIST>', parser.add_option('-s','--special', dest='special', action='extend', type='string', metavar='<string LIST>',
help='heading of columns containing field values of special dimension') help='heading of columns containing field values of special dimension')
parser.add_option('-d','--dimension', dest='N', action='store', type='int', metavar='int', parser.add_option('-d','--dimension',dest='N', type='int', metavar='int',
help='dimension of special field values [%default]') help='dimension of special field values [%default]')
parser.add_option('-v','--vector', dest='vector', action='extend', metavar='<string LIST>', parser.add_option('-v','--vector', dest='vector', action='extend', metavar='<string LIST>',
help='column heading to shift by vector') help='column heading to shift by vector')
@ -49,9 +49,9 @@ datainfo = {
} }
length = 0 length = 0
if options.special != []: datainfo['special']['label'] += options.special; length += len(options.scalar)*datainfo['special']['len'] if options.special != []: datainfo['special']['label'] += options.special; length += len(options.special)
if options.vector != []: datainfo['vector']['label'] += options.vector; length += len(options.vector)*datainfo['vector']['len'] if options.vector != []: datainfo['vector']['label'] += options.vector; length += len(options.vector)
if options.tensor != []: datainfo['tensor']['label'] += options.tensor; length += len(options.tensor)*datainfo['tensor']['len'] if options.tensor != []: datainfo['tensor']['label'] += options.tensor; length += len(options.tensor)
if len(options.delta) != length: if len(options.delta) != length:
parser.error('length of offset vector does not match column types...') parser.error('length of offset vector does not match column types...')
@ -79,7 +79,7 @@ for file in files:
for datatype,info in datainfo.items(): for datatype,info in datainfo.items():
for label in info['label']: for label in info['label']:
key = '1_'+label if info['len'] > 1 else label # non-scalar labels have to start with '1_' key = '1_'+label if info['len'] > 1 else label # non-special labels have to start with '1_'
if key in table.labels: if key in table.labels:
active[datatype].append(label) active[datatype].append(label)
column[datatype][label] = table.labels.index(key) # remember columns of requested data column[datatype][label] = table.labels.index(key) # remember columns of requested data