DAMASK_EICMD/processing/post/addDebugInformation

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#!/usr/bin/python
import os,re,sys,math,string,numpy,postprocessingMath
from optparse import OptionParser, Option
# -----------------------------
class extendableOption(Option):
# -----------------------------
# used for definition of new option parser action 'extend', which enables to take multiple option arguments
# taken from online tutorial http://docs.python.org/library/optparse.html
ACTIONS = Option.ACTIONS + ("extend",)
STORE_ACTIONS = Option.STORE_ACTIONS + ("extend",)
TYPED_ACTIONS = Option.TYPED_ACTIONS + ("extend",)
ALWAYS_TYPED_ACTIONS = Option.ALWAYS_TYPED_ACTIONS + ("extend",)
def take_action(self, action, dest, opt, value, values, parser):
if action == "extend":
lvalue = value.split(",")
values.ensure_value(dest, []).extend(lvalue)
else:
Option.take_action(self, action, dest, opt, value, values, parser)
def location(idx,res):
return ( idx % res[0], \
(idx // res[0]) % res[1], \
(idx // res[0] // res[1]) % res[2] )
def index(location,res):
return ( location[0] % res[0] + \
(location[1] % res[1]) * res[0] + \
(location[2] % res[2]) * res[0] * res[1] )
# --------------------------------------------------------------------
# MAIN
# --------------------------------------------------------------------
parser = OptionParser(option_class=extendableOption, usage='%prog options file[s]', description = """
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Add column containing debug information
Operates on periodic ordered three-dimensional data sets.
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""" + string.replace('$Id$','\n','\\n')
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)
parser.add_option('--no-shape','-s', dest='shape', action='store_false', \
help='do not calcuate shape mismatch [%default]')
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parser.add_option('--no-volume','-v', dest='volume', action='store_false', \
help='do not calculate volume mismatch [%default]')
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parser.add_option('-d','--dimension', dest='dim', type='float', nargs=3, \
help='physical dimension of data set in x (fast) y z (slow) [%default]')
parser.add_option('-r','--resolution', dest='res', type='int', nargs=3, \
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')
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parser.set_defaults(volume = True)
parser.set_defaults(shape = True)
parser.set_defaults(defgrad = ['f'])
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(options,filenames) = parser.parse_args()
if not options.res or len(options.res) < 3:
parser.error('improper resolution specification...')
if not options.dim or len(options.dim) < 3:
parser.error('improper dimension specification...')
defgrad = {}
defgrad_av = {}
centroids = {}
nodes = {}
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datainfo = { # list of requested labels per datatype
'defgrad': {'len':9,
'label':[]},
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}
if options.defgrad != None: datainfo['defgrad']['label'] += options.defgrad
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# ------------------------------------------ setup file handles ---------------------------------------
files = []
if filenames == []:
parser.error('no data file specified')
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else:
for name in filenames:
if os.path.exists(name):
files.append({'name':name, 'input':open(name), 'output':open(name+'_tmp','w')})
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# ------------------------------------------ loop over input files ---------------------------------------
for file in files:
print file['name']
# get labels by either read the first row, or - if keyword header is present - the last line of the header
firstline = file['input'].readline()
m = re.search('(\d+)\s*head', firstline.lower())
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if m:
headerlines = int(m.group(1))
passOn = [file['input'].readline() for i in range(1,headerlines)]
headers = file['input'].readline().split()
else:
headerlines = 1
passOn = []
headers = firstline.split()
data = file['input'].readlines()
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for i,l in enumerate(headers):
if l.startswith('1_'):
if re.match('\d+_',l[2:]) or i == len(headers)-1 or not headers[i+1].endswith(l[2:]):
headers[i] = l[2:]
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active = {}
column = {}
head = []
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for datatype,info in datainfo.items():
for label in info['label']:
key = {True :'1_%s',
False:'%s' }[info['len']>1]%label
if key not in headers:
sys.stderr.write('column %s not found...\n'%key)
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else:
if datatype not in active: active[datatype] = []
if datatype not in column: column[datatype] = {}
active[datatype].append(label)
column[datatype][label] = headers.index(key)
if options.shape: head += 'mismatch_shape(%s)'%label
if options.volume: head += 'mismatch_volume(%s)'%label
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# ------------------------------------------ assemble header ---------------------------------------
output = '%i\theader'%(headerlines+1) + '\n' + \
''.join(passOn) + \
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string.replace('$Id$','\n','\\n')+ '\t' + \
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' '.join(sys.argv[1:]) + '\n' + \
'\t'.join(headers + head) + '\n' # build extended header
# ------------------------------------------ read deformation tensors ---------------------------------------
for datatype,labels in active.items():
for label in labels:
defgrad[label] = numpy.array([0.0 for i in xrange(9*options.res[0]*options.res[1]*options.res[2])],'d').\
reshape((options.res[0],options.res[1],options.res[2],3,3))
idx = 0
for line in data:
items = line.split()[:len(headers)] # take only valid first items
if len(items) < len(headers): # too short lines get dropped
continue
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 ---------------------------------------
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idx = 0
for line in data:
items = line.split()[:len(headers)]
if len(items) < len(headers):
continue
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output += '\t'.join(items)
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for datatype,labels in active.items():
for label in labels:
if options.shape: output += '\t%f'%shape_mismatch[label][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
file['input'].close()
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# ------------------------------------------ output result ---------------------------------------
file['output'].write(output)
file['output'].close
os.rename(file['name']+'_tmp',file['name'])