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DAMASK_EICMD
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reworked to match former script layouts and logics. (not yet tested, use at your own risk)

This commit is contained in:
Philip Eisenlohr 2011-08-25 17:55:36 +00:00
parent 282d2d7b97
commit 7aba05ed9f
1 changed files with 82 additions and 70 deletions
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140
processing/post/addDebugInformation Normal file → Executable file
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@ -36,7 +36,7 @@ def index(location,res):
# MAIN # MAIN
# -------------------------------------------------------------------- # --------------------------------------------------------------------
parser = OptionParser(option_class=extendableOption, usage='%prog options [file[s]]', description = """ parser = OptionParser(option_class=extendableOption, usage='%prog options file[s]', description = """
Add column containing debug information Add column containing debug information
Operates on periodic ordered three-dimensional data sets. Operates on periodic ordered three-dimensional data sets.
@ -45,113 +45,128 @@ Operates on periodic ordered three-dimensional data sets.
parser.add_option('--no-shape','-s', dest='shape', action='store_false', \ parser.add_option('--no-shape','-s', dest='shape', action='store_false', \
help='calcuate mismatch of shape [%default]') help='do not calcuate shape mismatch [%default]')
parser.add_option('--no-volume','-v', dest='volume', action='store_false', \ parser.add_option('--no-volume','-v', dest='volume', action='store_false', \
help='calculate mismatch of volume [%default]') help='do not calculate volume mismatch [%default]')
parser.add_option('-d','--dimension', dest='dim', type='float', nargs=3, \ parser.add_option('-d','--dimension', dest='dim', type='float', nargs=3, \
help='physical dimension of data set in x (fast) y z (slow) [%default]') help='physical dimension of data set in x (fast) y z (slow) [%default]')
parser.add_option('-r','--resolution', dest='res', type='int', nargs=3, \ parser.add_option('-r','--resolution', dest='res', type='int', nargs=3, \
help='resolution of data set in x (fast) y z (slow)') help='resolution of data set in x (fast) y z (slow)')
parser.add_option('-f','--deformation', dest='defgrad', action='extend', type='string', \
help='heading(s) of columns containing deformation tensor values %default')
parser.set_defaults(volume = True) parser.set_defaults(volume = True)
parser.set_defaults(shape = True) parser.set_defaults(shape = True)
parser.set_defaults(defgrad = ['f'])
(options,filenames) = parser.parse_args() (options,filenames) = parser.parse_args()
if not options.res or len(options.res) < 3: if not options.res or len(options.res) < 3:
parser.error('improper resolution specification...') parser.error('improper resolution specification...')
if not options.dim or len(options.dim) < 3: if not options.dim or len(options.dim) < 3:
parser.error('improper resolution specification...') parser.error('improper dimension specification...')
defgrad = {}
defgrad_av = {}
centroids = {}
nodes = {}
datainfo = { # list of requested labels per datatype datainfo = { # list of requested labels per datatype
'tensor': {'len':9, 'defgrad': {'len':9,
'label':[]}, 'label':[]},
} }
datainfo['tensor']['label'] += 'f' if options.defgrad != None: datainfo['defgrad']['label'] += options.defgrad
# ------------------------------------------ setup file handles --------------------------------------- # ------------------------------------------ setup file handles ---------------------------------------
files = [] files = []
if filenames == []: if filenames == []:
files.append({'name':'STDIN', 'handle':sys.stdin}) parser.error('no data file specified')
else: else:
for name in filenames: for name in filenames:
if os.path.exists(name): if os.path.exists(name):
files.append({'name':name, 'handle':open(name)}) files.append({'name':name, 'input':open(name), 'output':open(name+'_tmp','w')})
# ------------------------------------------ loop over input files --------------------------------------- # ------------------------------------------ loop over input files ---------------------------------------
for file in files: for file in files:
print file['name'] print file['name']
content = file['handle'].readlines()
file['handle'].close()
# get labels by either read the first row, or - if keyword header is present - the last line of the header # get labels by either read the first row, or - if keyword header is present - the last line of the header
headerlines = 1 firstline = file['input'].readline()
m = re.search('(\d+)\s*head', content[0].lower()) m = re.search('(\d+)\s*head', firstline.lower())
if m: if m:
headerlines = int(m.group(1)) headerlines = int(m.group(1))
passOn = content[1:headerlines] passOn = [file['input'].readline() for i in range(1,headerlines)]
headers = content[headerlines].split() headers = file['input'].readline().split()
data = content[headerlines+1:] else:
headerlines = 1
passOn = []
headers = firstline.split()
data = file['input'].readlines()
regexp = re.compile('1_\d+_')
for i,l in enumerate(headers): for i,l in enumerate(headers):
if regexp.match(l): if l.startswith('1_'):
headers[i] = l[2:] if re.match('\d+_',l[2:]) or i == len(headers)-1 or not headers[i+1].endswith(l[2:]):
headers[i] = l[2:]
active = {} active = {}
column = {} column = {}
values = {}
head = [] head = []
for datatype,info in datainfo.items(): for datatype,info in datainfo.items():
for label in info['label']: for label in info['label']:
key = {True :'1_%s', key = {True :'1_%s',
False:'%s' }[info['len']>1]%label False:'%s' }[info['len']>1]%label
if key not in headers: if key not in headers:
print 'column %s not found...'%key sys.stderr.write('column %s not found...\n'%key)
else: else:
if datatype not in active: active[datatype] = [] if datatype not in active: active[datatype] = []
if datatype not in column: column[datatype] = {} if datatype not in column: column[datatype] = {}
active[datatype].append(label) active[datatype].append(label)
column[datatype][label]=headers.index(key) column[datatype][label] = headers.index(key)
if options.shape: head += 'mismatch_shape(%s)'%label
defgrad = numpy.array([0.0 for i in range(9*options.res[0]*options.res[1]*options.res[2])]).\ if options.volume: head += 'mismatch_volume(%s)'%label
reshape((options.res[0],options.res[1],options.res[2],3,3))
if options.shape: head += ['shape_mismatch']
if options.volume: head += ['volume_mismatch']
# ------------------------------------------ assemble header --------------------------------------- # ------------------------------------------ assemble header ---------------------------------------
output = '%i\theader'%(headerlines+1) + '\n' + \ output = '%i\theader'%(headerlines+1) + '\n' + \
''.join(passOn) + \ ''.join(passOn) + \
string.replace('$Id$','\n','\\n')+ '\t' + \ string.replace('$Id$','\n','\\n')+ '\t' + \
' '.join(sys.argv[1:]) + '\n' + \ ' '.join(sys.argv[1:]) + '\n' + \
'\t'.join(headers + head) + '\n' # build extended header '\t'.join(headers + head) + '\n' # build extended header
# ------------------------------------------ read value field ---------------------------------------
idx = 0 # ------------------------------------------ read deformation tensors ---------------------------------------
for line in data:
items = line.split()[:len(headers)] for datatype,labels in active.items():
if len(items) < len(headers): for label in labels:
continue defgrad[label] = numpy.array([0.0 for i in xrange(9*options.res[0]*options.res[1]*options.res[2])],'d').\
for datatype,labels in active.items(): reshape((options.res[0],options.res[1],options.res[2],3,3))
for label in labels:
defgrad[location(idx,options.res)[0]][location(idx,options.res)[1]][location(idx,options.res)[2]]\ idx = 0
= numpy.reshape(items[column[datatype][label]:column[datatype][label]+9],(3,3)) for line in data:
idx += 1 items = line.split()[:len(headers)] # take only valid first items
defgrad_av = postprocessingMath.tensor_avg(options.res[0],options.res[1],options.res[2],defgrad) if len(items) < len(headers): # too short lines get dropped
centroids = postprocessingMath.deformed_fft(options.res[0],options.res[1],options.res[2],options.dim,defgrad,defgrad_av,1.0) continue
nodes = postprocessingMath.mesh(options.res[0],options.res[1],options.res[2],options.dim,defgrad_av,centroids)
defgrad[label][location(idx,options.res)[0]]\
[location(idx,options.res)[1]]\
[location(idx,options.res)[2]]\
= numpy.array(map(float,items[column[datatype][label]:
column[datatype][label]+datainfo[datatype]['len']]),'d').reshape(3,3)
defgrad_av[label] = postprocessingMath.tensor_avg(options.res[0],options.res[1],options.res[2],defgrad[label])
centroids[label] = postprocessingMath.deformed_fft(options.res[0],options.res[1],options.res[2],options.dim,defgrad[label],defgrad_av[label],1.0)
nodes[label] = postprocessingMath.mesh(options.res[0],options.res[1],options.res[2],options.dim,defgrad_av[label],centroids[label])
if options.shape: shape_mismatch[label] = postprocessingMath.shape_compare( options.res[0],options.res[1],options.res[2],options.dim,nodes[label],centroids[label],defgrad[label])
if options.volume: volume_mismatch[label] = postprocessingMath.volume_compare(options.res[0],options.res[1],options.res[2],options.dim,nodes[label], defgrad[label])
idx += 1
# ------------------------------------------ read file --------------------------------------- # ------------------------------------------ read file ---------------------------------------
if options.shape:
shape_mismatch = postprocessingMath.shape_compare(options.res[0],options.res[1],options.res[2],options.dim,nodes,centroids,defgrad)
if options.volume:
volume_mismatch = postprocessingMath.volume_compare(options.res[0],options.res[1],options.res[2],options.dim,nodes,defgrad)
idx = 0 idx = 0
for line in data: for line in data:
items = line.split()[:len(headers)] items = line.split()[:len(headers)]
@ -161,21 +176,18 @@ for file in files:
output += '\t'.join(items) output += '\t'.join(items)
for datatype,labels in active.items(): for datatype,labels in active.items():
if options.shape: for label in labels:
output += '\t%f'%shape_mismatch[location(idx,options.res)[0]][location(idx,options.res)[1]][location(idx,options.res)[2]]
if options.volume: if options.shape: output += '\t%f'%shape_mismatch[label][location(idx,options.res)[0]][location(idx,options.res)[1]][location(idx,options.res)[2]]
output += '\t%f'%volume_mismatch[location(idx,options.res)[0]][location(idx,options.res)[1]][location(idx,options.res)[2]] if options.volume: output += '\t%f'%volume_mismatch[label][location(idx,options.res)[0]][location(idx,options.res)[1]][location(idx,options.res)[2]]
output += '\n'
idx += 1 output += '\n'
idx += 1
file['input'].close()
# ------------------------------------------ output result --------------------------------------- # ------------------------------------------ output result ---------------------------------------
if file['name'] == 'STDIN': file['output'].write(output)
print output file['output'].close
else: os.rename(file['name']+'_tmp',file['name'])
file['handle'] = open(file['name']+'_tmp','w')
try:
file['handle'].write(output)
file['handle'].close()
os.rename(file['name']+'_tmp',file['name'])
except:
print 'error during writing',file['name']+'_tmp'