moved useful ASCII post processing scripts from my Code repository into the DAMASK post-proc.
This commit is contained in:
Philip Eisenlohr
parent
daa45306f2
commit
b252b467e8
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#!/usr/bin/python
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import os,re,sys,math,numpy,string
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from optparse import OptionParser, Option
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# -----------------------------
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class extendableOption(Option):
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# -----------------------------
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# used for definition of new option parser action 'extend', which enables to take multiple option arguments
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# taken from online tutorial http://docs.python.org/library/optparse.html
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ACTIONS = Option.ACTIONS + ("extend",)
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STORE_ACTIONS = Option.STORE_ACTIONS + ("extend",)
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TYPED_ACTIONS = Option.TYPED_ACTIONS + ("extend",)
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ALWAYS_TYPED_ACTIONS = Option.ALWAYS_TYPED_ACTIONS + ("extend",)
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def take_action(self, action, dest, opt, value, values, parser):
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if action == "extend":
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lvalue = value.split(",")
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values.ensure_value(dest, []).extend(lvalue)
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else:
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Option.take_action(self, action, dest, opt, value, values, parser)
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def prefixMultiply(what,len):
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return {True: ['%i_%s'%(i+1,what) for i in range(len)],
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False:[what]}[len>1]
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# --------------------------------------------------------------------
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# MAIN
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# --------------------------------------------------------------------
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parser = OptionParser(option_class=extendableOption, usage='%prog options [file[s]]', description = """
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Add column(s) containing Cauchy stress based on given column(s) of
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deformation gradient and first Piola--Kirchhoff stress.
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$Id: addCauchy 263 2011-05-25 17:42:50Z MPIE\p.eisenlohr $
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""")
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parser.add_option('-m','--memory', dest='memory', action='store_true', \
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help='load complete file into memory [%default]')
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parser.add_option('-f','--defgrad', dest='defgrad', type='string', \
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help='heading of columns containing deformation gradient [%default]')
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parser.add_option('-p','--stress', dest='stress', type='string', \
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help='heading of columns containing first Piola--Kirchhoff stress [%default]')
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parser.set_defaults(memory = False)
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parser.set_defaults(defgrad = 'f')
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parser.set_defaults(stress = 'p')
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(options,filenames) = parser.parse_args()
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if options.defgrad == None or options.stress == None:
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parser.error('missing data column...')
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datainfo = { # list of requested labels per datatype
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'defgrad': {'len':9,
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'label':[]},
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'stress': {'len':9,
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'label':[]},
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}
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datainfo['defgrad']['label'].append(options.defgrad)
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datainfo['stress']['label'].append(options.stress)
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# ------------------------------------------ setup file handles ---------------------------------------
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files = []
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if filenames == []:
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files.append({'name':'STDIN', 'handle':sys.stdin})
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else:
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for name in filenames:
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if os.path.exists(name):
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files.append({'name':name, 'input':open(name), 'output':open(name+'_tmp','w')})
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# ------------------------------------------ loop over input files ---------------------------------------
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for file in files:
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print file['name']
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# get labels by either read the first row, or - if keyword header is present - the last line of the header
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firstline = file['input'].readline()
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m = re.search('(\d+)\s*head', firstline.lower())
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if m:
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headerlines = int(m.group(1))
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passOn = [file['input'].readline() for i in range(1,headerlines)]
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headers = file['input'].readline().split()
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else:
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headerlines = 1
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passOn = []
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headers = firstline.split()
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if options.memory:
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data = file['input'].readlines()
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else:
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data = []
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for i,l in enumerate(headers):
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if l.startswith('1_'):
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if re.match('\d+_',l[2:]) or i == len(headers)-1 or not headers[i+1].endswith(l[2:]):
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headers[i] = l[2:]
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active = {}
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column = {}
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head = []
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for datatype,info in datainfo.items():
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for label in info['label']:
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key = {True :'1_%s',
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False:'%s' }[info['len']>1]%label
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if key not in headers:
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sys.stderr.write('column %s not found...\n'%key)
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else:
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if datatype not in active: active[datatype] = []
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if datatype not in column: column[datatype] = {}
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active[datatype].append(label)
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column[datatype][label] = headers.index(key)
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head += prefixMultiply('Cauchy',datainfo[datatype]['len'])
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# ------------------------------------------ assemble header ---------------------------------------
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output = '%i\theader'%(headerlines+1) + '\n' + \
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''.join(passOn) + \
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string.replace('$Id: addCauchy 263 2011-05-25 17:42:50Z MPIE\p.eisenlohr $','\n','\\n')+ '\t' + \
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' '.join(sys.argv[1:]) + '\n' + \
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'\t'.join(headers + head) + '\n' # build extended header
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if not options.memory:
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file['output'].write(output)
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output = ''
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# ------------------------------------------ read file ---------------------------------------
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for line in {True : data,
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False : file['input']}[options.memory]:
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items = line.split()[:len(headers)]
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if len(items) < len(headers):
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continue
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output += '\t'.join(items)
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F = numpy.array(map(float,items[column['defgrad'][active['defgrad'][0]]:
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column['defgrad'][active['defgrad'][0]]+datainfo['defgrad']['len']]),'d').reshape(3,3)
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P = numpy.array(map(float,items[column['stress'][active['stress'][0]]:
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column['stress'][active['stress'][0]]+datainfo['stress']['len']]),'d').reshape(3,3)
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output += '\t'+'\t'.join(map(str,1.0/numpy.linalg.det(F)*numpy.dot(P,F.T).reshape(9))) # [Cauchy] = (1/det(F)) * [P].[F_transpose]
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output += '\n'
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if not options.memory:
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file['output'].write(output)
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output = ''
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file['input'].close()
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# ------------------------------------------ output result ---------------------------------------
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if options.memory:
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file['output'].write(output)
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if file['name'] != 'STDIN':
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file['output'].close
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os.rename(file['name']+'_tmp',file['name'])
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@ -0,0 +1,172 @@
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#!/usr/bin/python
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import os,re,sys,math,string
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from optparse import OptionParser, Option
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# -----------------------------
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class extendableOption(Option):
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# -----------------------------
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# used for definition of new option parser action 'extend', which enables to take multiple option arguments
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# taken from online tutorial http://docs.python.org/library/optparse.html
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ACTIONS = Option.ACTIONS + ("extend",)
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STORE_ACTIONS = Option.STORE_ACTIONS + ("extend",)
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TYPED_ACTIONS = Option.TYPED_ACTIONS + ("extend",)
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ALWAYS_TYPED_ACTIONS = Option.ALWAYS_TYPED_ACTIONS + ("extend",)
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def take_action(self, action, dest, opt, value, values, parser):
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if action == "extend":
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lvalue = value.split(",")
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values.ensure_value(dest, []).extend(lvalue)
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else:
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Option.take_action(self, action, dest, opt, value, values, parser)
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def determinant(m):
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return +m[0]*m[4]*m[8] \
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+m[1]*m[5]*m[6] \
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+m[2]*m[3]*m[7] \
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-m[2]*m[4]*m[6] \
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-m[1]*m[3]*m[8] \
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-m[0]*m[5]*m[7] \
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# --------------------------------------------------------------------
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# MAIN
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# --------------------------------------------------------------------
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parser = OptionParser(option_class=extendableOption, usage='%prog options [file[s]]', description = """
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Add column(s) containing determinant of requested tensor column(s).
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$Id: addDeterminant 278 2011-06-15 17:57:42Z MPIE\p.eisenlohr $
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""")
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parser.add_option('-m','--memory', dest='memory', action='store_true', \
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help='load complete file into memory [%default]')
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parser.add_option('-t','--tensor', dest='tensor', action='extend', type='string', \
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help='heading of columns containing tensor field values')
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parser.set_defaults(memory = False)
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parser.set_defaults(vector = [])
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parser.set_defaults(tensor = [])
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(options,filenames) = parser.parse_args()
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if len(options.vector) + len(options.tensor) == 0:
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parser.error('no data column specified...')
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datainfo = { # list of requested labels per datatype
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'vector': {'len':3,
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'label':[]},
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'tensor': {'len':9,
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'label':[]},
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}
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if options.vector != None: datainfo['vector']['label'] += options.vector
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if options.tensor != None: datainfo['tensor']['label'] += options.tensor
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# ------------------------------------------ setup file handles ---------------------------------------
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files = []
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if filenames == []:
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files.append({'name':'STDIN', 'input':sys.stdin, 'output':sys.stdout})
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else:
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for name in filenames:
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if os.path.exists(name):
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files.append({'name':name, 'input':open(name), 'output':open(name+'_tmp','w')})
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# ------------------------------------------ loop over input files ---------------------------------------
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for file in files:
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print file['name']
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# get labels by either read the first row, or - if keyword header is present - the last line of the header
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firstline = file['input'].readline()
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m = re.search('(\d+)\s*head', firstline.lower())
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if m:
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headerlines = int(m.group(1))
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passOn = [file['input'].readline() for i in range(1,headerlines)]
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headers = file['input'].readline().split()
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else:
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headerlines = 1
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passOn = []
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headers = firstline.split()
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if options.memory:
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data = file['input'].readlines()
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else:
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data = []
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for i,l in enumerate(headers):
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if l.startswith('1_'):
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if re.match('\d+_',l[2:]) or i == len(headers)-1 or not headers[i+1].endswith(l[2:]):
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headers[i] = l[2:]
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active = {}
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column = {}
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head = []
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for datatype,info in datainfo.items():
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for label in info['label']:
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key = {True :'1_%s',
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False:'%s' }[info['len']>1]%label
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if key not in headers:
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sys.stderr.write('column %s not found...\n'%key)
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else:
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if datatype not in active: active[datatype] = []
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if datatype not in column: column[datatype] = {}
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active[datatype].append(label)
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column[datatype][label] = headers.index(key)
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head.append('det(%s)'%label)
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# ------------------------------------------ assemble header ---------------------------------------
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output = '%i\theader'%(headerlines+1) + '\n' + \
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''.join(passOn) + \
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string.replace('$Id: addDeterminant 278 2011-06-15 17:57:42Z MPIE\p.eisenlohr $','\n','\\n')+ '\t' + \
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' '.join(sys.argv[1:]) + '\n' + \
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'\t'.join(headers + head) + '\n' # build extended header
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if not options.memory:
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file['output'].write(output)
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output = ''
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# ------------------------------------------ read file ---------------------------------------
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for line in {True : data,
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False : file['input']}[options.memory]:
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items = line.split()[:len(headers)]
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if len(items) < len(headers):
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continue
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output += '\t'.join(items)
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for datatype,labels in active.items():
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for label in labels:
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theValue = determinant(map(float,items[column[datatype][label]:
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column[datatype][label]+datainfo[datatype]['len']]))
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output += '\t%f'%theValue
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output += '\n'
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if not options.memory:
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file['output'].write(output)
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output = ''
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file['input'].close()
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# ------------------------------------------ output result ---------------------------------------
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if options.memory:
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file['output'].write(output)
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if file['name'] != 'STDIN':
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file['output'].close
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os.rename(file['name']+'_tmp',file['name'])
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@ -0,0 +1,221 @@
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#!/usr/bin/python
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import os,re,sys,math,string
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from optparse import OptionParser, Option
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# -----------------------------
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class extendableOption(Option):
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# -----------------------------
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# used for definition of new option parser action 'extend', which enables to take multiple option arguments
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# taken from online tutorial http://docs.python.org/library/optparse.html
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ACTIONS = Option.ACTIONS + ("extend",)
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STORE_ACTIONS = Option.STORE_ACTIONS + ("extend",)
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TYPED_ACTIONS = Option.TYPED_ACTIONS + ("extend",)
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ALWAYS_TYPED_ACTIONS = Option.ALWAYS_TYPED_ACTIONS + ("extend",)
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def take_action(self, action, dest, opt, value, values, parser):
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if action == "extend":
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lvalue = value.split(",")
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values.ensure_value(dest, []).extend(lvalue)
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else:
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Option.take_action(self, action, dest, opt, value, values, parser)
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def location(idx,res):
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return ( idx % res[0], \
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(idx // res[0]) % res[1], \
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(idx // res[0] // res[1]) % res[2] )
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def index(location,res):
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return ( location[0] % res[0] + \
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(location[1] % res[1]) * res[0] + \
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(location[2] % res[2]) * res[0] * res[1] )
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def prefixMultiply(what,len):
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return {True: ['%i_%s'%(i+1,what) for i in range(len)],
|
||||||
|
False:[what]}[len>1]
|
||||||
|
|
||||||
|
|
||||||
|
# --------------------------------------------------------------------
|
||||||
|
# MAIN
|
||||||
|
# --------------------------------------------------------------------
|
||||||
|
|
||||||
|
FDcoefficients = [ \
|
||||||
|
[1.0/2.0, 0.0, 0.0, 0.0],\
|
||||||
|
[2.0/3.0,-1.0/12.0, 0.0, 0.0],\
|
||||||
|
[3.0/4.0,-3.0/20.0,1.0/ 60.0, 0.0],\
|
||||||
|
[4.0/5.0,-1.0/ 5.0,4.0/105.0,-1.0/280.0],\
|
||||||
|
]
|
||||||
|
parser = OptionParser(option_class=extendableOption, usage='%prog options [file[s]]', description = """
|
||||||
|
Add column(s) containing divergence of requested column(s).
|
||||||
|
Operates on periodic ordered three-dimensional data sets.
|
||||||
|
Deals with both vector- and tensor-valued fields.
|
||||||
|
|
||||||
|
$Id: addDivergence 264 2011-05-25 17:43:45Z MPIE\p.eisenlohr $
|
||||||
|
""")
|
||||||
|
|
||||||
|
|
||||||
|
parser.add_option('-a','--accuracy', dest='accuracy', type='int', \
|
||||||
|
help='degree of central difference accuracy [%default]')
|
||||||
|
parser.add_option('-v','--vector', dest='vector', action='extend', type='string', \
|
||||||
|
help='heading of columns containing vector field values')
|
||||||
|
parser.add_option('-t','--tensor', dest='tensor', action='extend', type='string', \
|
||||||
|
help='heading of columns containing tensor field values')
|
||||||
|
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.set_defaults(accuracy = 8)
|
||||||
|
parser.set_defaults(vector = [])
|
||||||
|
parser.set_defaults(tensor = [])
|
||||||
|
parser.set_defaults(dim = [1.0,1.0,1.0])
|
||||||
|
accuracyChoices = [2,4,6,8]
|
||||||
|
|
||||||
|
(options,filenames) = parser.parse_args()
|
||||||
|
|
||||||
|
if len(options.vector) + len(options.tensor) == 0:
|
||||||
|
parser.error('no data column specified...')
|
||||||
|
if len(options.dim) < 3:
|
||||||
|
parser.error('improper dimension specification...')
|
||||||
|
if not options.res or len(options.res) < 3:
|
||||||
|
parser.error('improper resolution specification...')
|
||||||
|
if options.accuracy not in accuracyChoices:
|
||||||
|
parser.error('accuracy must be chosen from %s...'%(', '.join(accuracyChoices)))
|
||||||
|
accuracy = options.accuracy//2-1
|
||||||
|
|
||||||
|
datainfo = { # list of requested labels per datatype
|
||||||
|
'vector': {'len':3,
|
||||||
|
'label':[]},
|
||||||
|
'tensor': {'len':9,
|
||||||
|
'label':[]},
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
if options.vector != None: datainfo['vector']['label'] += options.vector
|
||||||
|
if options.tensor != None: datainfo['tensor']['label'] += options.tensor
|
||||||
|
|
||||||
|
# ------------------------------------------ setup file handles ---------------------------------------
|
||||||
|
|
||||||
|
files = []
|
||||||
|
if filenames == []:
|
||||||
|
files.append({'name':'STDIN', 'handle':sys.stdin})
|
||||||
|
else:
|
||||||
|
for name in filenames:
|
||||||
|
if os.path.exists(name):
|
||||||
|
files.append({'name':name, 'handle':open(name)})
|
||||||
|
|
||||||
|
# ------------------------------------------ loop over input files ---------------------------------------
|
||||||
|
|
||||||
|
for file in files:
|
||||||
|
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
|
||||||
|
|
||||||
|
headerlines = 1
|
||||||
|
m = re.search('(\d+)\s*head', content[0].lower())
|
||||||
|
if m:
|
||||||
|
headerlines = int(m.group(1))
|
||||||
|
passOn = content[1:headerlines]
|
||||||
|
headers = content[headerlines].split()
|
||||||
|
data = content[headerlines+1:]
|
||||||
|
|
||||||
|
regexp = re.compile('1_\d+_')
|
||||||
|
for i,l in enumerate(headers):
|
||||||
|
if regexp.match(l):
|
||||||
|
headers[i] = l[2:]
|
||||||
|
|
||||||
|
active = {}
|
||||||
|
column = {}
|
||||||
|
values = {}
|
||||||
|
head = []
|
||||||
|
|
||||||
|
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:
|
||||||
|
print 'column %s not found...'%key
|
||||||
|
else:
|
||||||
|
if datatype not in active: active[datatype] = []
|
||||||
|
if datatype not in column: column[datatype] = {}
|
||||||
|
if datatype not in values: values[datatype] = {}
|
||||||
|
active[datatype].append(label)
|
||||||
|
column[datatype][label] = headers.index(key)
|
||||||
|
values[datatype][label] = [[0.0 for i in range(datainfo[datatype]['len'])] \
|
||||||
|
for j in range(options.res[0]*options.res[1]*options.res[2])]
|
||||||
|
head += prefixMultiply('div%i(%s)'%(options.accuracy,label),datainfo[datatype]['len']/3)
|
||||||
|
|
||||||
|
# ------------------------------------------ assemble header ---------------------------------------
|
||||||
|
|
||||||
|
output = '%i\theader'%(headerlines+1) + '\n' + \
|
||||||
|
''.join(passOn) + \
|
||||||
|
string.replace('$Id: addDivergence 264 2011-05-25 17:43:45Z MPIE\p.eisenlohr $','\n','\\n')+ '\t' + \
|
||||||
|
' '.join(sys.argv[1:]) + '\n' + \
|
||||||
|
'\t'.join(headers + head) + '\n' # build extended header
|
||||||
|
|
||||||
|
# ------------------------------------------ read value field ---------------------------------------
|
||||||
|
|
||||||
|
idx = 0
|
||||||
|
for line in data:
|
||||||
|
items = line.split()[:len(headers)]
|
||||||
|
if len(items) < len(headers):
|
||||||
|
continue
|
||||||
|
|
||||||
|
for datatype,labels in active.items():
|
||||||
|
for label in labels:
|
||||||
|
values[datatype][label][idx] = map(float,items[column[datatype][label]:
|
||||||
|
column[datatype][label]+datainfo[datatype]['len']])
|
||||||
|
idx += 1
|
||||||
|
|
||||||
|
# ------------------------------------------ read file ---------------------------------------
|
||||||
|
|
||||||
|
idx = 0
|
||||||
|
for line in data:
|
||||||
|
items = line.split()[:len(headers)]
|
||||||
|
if len(items) < len(headers):
|
||||||
|
continue
|
||||||
|
|
||||||
|
output += '\t'.join(items)
|
||||||
|
|
||||||
|
(x,y,z) = location(idx,options.res)
|
||||||
|
|
||||||
|
for datatype,labels in active.items():
|
||||||
|
for label in labels:
|
||||||
|
for k in range(datainfo[datatype]['len']/3): # formulas from Mikhail Itskov: Tensor Algebra and Tensor Analysis for Engineers, Springer 2009, p 52
|
||||||
|
theDiv = 0.0
|
||||||
|
for a in range(1+accuracy):
|
||||||
|
theDiv += FDcoefficients[accuracy][a] * \
|
||||||
|
( \
|
||||||
|
(values[datatype][label][index([x+1+a,y,z],options.res)][k*3+0] - \
|
||||||
|
values[datatype][label][index([x-1-a,y,z],options.res)][k*3+0]) * options.res[0] / options.dim[0] + \
|
||||||
|
(values[datatype][label][index([x,y+1+a,z],options.res)][k*3+1] - \
|
||||||
|
values[datatype][label][index([x,y-1-a,z],options.res)][k*3+1]) * options.res[1] / options.dim[1] + \
|
||||||
|
(values[datatype][label][index([x,y,z+1+a],options.res)][k*3+2] - \
|
||||||
|
values[datatype][label][index([x,y,z-1-a],options.res)][k*3+2]) * options.res[2] / options.dim[2] \
|
||||||
|
)
|
||||||
|
output += '\t%f'%theDiv
|
||||||
|
|
||||||
|
output += '\n'
|
||||||
|
idx += 1
|
||||||
|
|
||||||
|
# ------------------------------------------ output result ---------------------------------------
|
||||||
|
|
||||||
|
if file['name'] == 'STDIN':
|
||||||
|
print output
|
||||||
|
else:
|
||||||
|
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'
|
||||||
|
|
@ -0,0 +1,175 @@
|
||||||
|
#!/usr/bin/python
|
||||||
|
|
||||||
|
import os,re,sys,math,numpy,string
|
||||||
|
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 Mises(what,tensor):
|
||||||
|
|
||||||
|
dev = tensor - numpy.trace(tensor)/3.0*numpy.eye(3)
|
||||||
|
symdev = 0.5*(dev+dev.T)
|
||||||
|
return math.sqrt(numpy.sum(symdev*symdev.T)*
|
||||||
|
{
|
||||||
|
'stress': 3.0/2.0,
|
||||||
|
'strain': 2.0/3.0,
|
||||||
|
}[what])
|
||||||
|
|
||||||
|
|
||||||
|
# --------------------------------------------------------------------
|
||||||
|
# MAIN
|
||||||
|
# --------------------------------------------------------------------
|
||||||
|
|
||||||
|
parser = OptionParser(option_class=extendableOption, usage='%prog options [file[s]]', description = """
|
||||||
|
Add vonMises equivalent values for symmetric part of requested strains and/or stresses.
|
||||||
|
|
||||||
|
$Id: addMises 263 2011-05-25 17:42:50Z MPIE\p.eisenlohr $
|
||||||
|
""")
|
||||||
|
|
||||||
|
|
||||||
|
parser.add_option('-m','--memory', dest='memory', action='store_true', \
|
||||||
|
help='load complete file into memory [%default]')
|
||||||
|
parser.add_option('-e','--strain', dest='strain', action='extend', type='string', \
|
||||||
|
help='heading(s) of columns containing strain tensors')
|
||||||
|
parser.add_option('-s','--stress', dest='stress', action='extend', type='string', \
|
||||||
|
help='heading(s) of columns containing stress tensors')
|
||||||
|
|
||||||
|
parser.set_defaults(memory = False)
|
||||||
|
parser.set_defaults(strain = [])
|
||||||
|
parser.set_defaults(stress = [])
|
||||||
|
|
||||||
|
(options,filenames) = parser.parse_args()
|
||||||
|
|
||||||
|
if len(options.strain) + len(options.stress) == 0:
|
||||||
|
parser.error('no data column specified...')
|
||||||
|
|
||||||
|
datainfo = { # list of requested labels per datatype
|
||||||
|
'strain': {'len':9,
|
||||||
|
'label':[]},
|
||||||
|
'stress': {'len':9,
|
||||||
|
'label':[]},
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
if options.strain != None: datainfo['strain']['label'] += options.strain
|
||||||
|
if options.stress != None: datainfo['stress']['label'] += options.stress
|
||||||
|
|
||||||
|
|
||||||
|
# ------------------------------------------ setup file handles ---------------------------------------
|
||||||
|
|
||||||
|
files = []
|
||||||
|
if filenames == []:
|
||||||
|
files.append({'name':'STDIN', 'input':sys.stdin, 'output':sys.stdout})
|
||||||
|
else:
|
||||||
|
for name in filenames:
|
||||||
|
if os.path.exists(name):
|
||||||
|
files.append({'name':name, 'input':open(name), 'output':open(name+'_tmp','w')})
|
||||||
|
|
||||||
|
# ------------------------------------------ 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())
|
||||||
|
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()
|
||||||
|
|
||||||
|
if options.memory:
|
||||||
|
data = file['input'].readlines()
|
||||||
|
else:
|
||||||
|
data = []
|
||||||
|
|
||||||
|
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:]
|
||||||
|
|
||||||
|
active = {}
|
||||||
|
column = {}
|
||||||
|
head = []
|
||||||
|
|
||||||
|
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)
|
||||||
|
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)
|
||||||
|
head.append('Mises(%s)'%label)
|
||||||
|
|
||||||
|
# ------------------------------------------ assemble header ---------------------------------------
|
||||||
|
|
||||||
|
output = '%i\theader'%(headerlines+1) + '\n' + \
|
||||||
|
''.join(passOn) + \
|
||||||
|
string.replace('$Id: addMises 263 2011-05-25 17:42:50Z MPIE\p.eisenlohr $','\n','\\n')+ '\t' + \
|
||||||
|
' '.join(sys.argv[1:]) + '\n' + \
|
||||||
|
'\t'.join(headers + head) + '\n' # build extended header
|
||||||
|
|
||||||
|
if not options.memory:
|
||||||
|
file['output'].write(output)
|
||||||
|
output = ''
|
||||||
|
|
||||||
|
# ------------------------------------------ read file ---------------------------------------
|
||||||
|
|
||||||
|
for line in {True : data,
|
||||||
|
False : file['input']}[options.memory]:
|
||||||
|
items = line.split()[:len(headers)]
|
||||||
|
if len(items) < len(headers):
|
||||||
|
continue
|
||||||
|
|
||||||
|
output += '\t'.join(items)
|
||||||
|
|
||||||
|
for datatype,labels in active.items():
|
||||||
|
for label in labels:
|
||||||
|
theMises = Mises(datatype,
|
||||||
|
numpy.array(map(float,items[column[datatype][label]:
|
||||||
|
column[datatype][label]+datainfo[datatype]['len']]),'d').reshape(3,3))
|
||||||
|
output += '\t%f'%theMises
|
||||||
|
|
||||||
|
output += '\n'
|
||||||
|
|
||||||
|
if not options.memory:
|
||||||
|
file['output'].write(output)
|
||||||
|
output = ''
|
||||||
|
|
||||||
|
file['input'].close()
|
||||||
|
|
||||||
|
# ------------------------------------------ output result ---------------------------------------
|
||||||
|
|
||||||
|
if options.memory:
|
||||||
|
file['output'].write(output)
|
||||||
|
|
||||||
|
if file['name'] != 'STDIN':
|
||||||
|
file['output'].close
|
||||||
|
os.rename(file['name']+'_tmp',file['name'])
|
||||||
|
|
@ -0,0 +1,168 @@
|
||||||
|
#!/usr/bin/python
|
||||||
|
|
||||||
|
import os,re,sys,math,string
|
||||||
|
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 L2(object):
|
||||||
|
|
||||||
|
return math.sqrt(sum([x*x for x in object]))
|
||||||
|
|
||||||
|
|
||||||
|
# --------------------------------------------------------------------
|
||||||
|
# MAIN
|
||||||
|
# --------------------------------------------------------------------
|
||||||
|
|
||||||
|
parser = OptionParser(option_class=extendableOption, usage='%prog options [file[s]]', description = """
|
||||||
|
Add column(s) containing norm of requested column(s) being either vectors or tensors.
|
||||||
|
|
||||||
|
$Id: addNorm 263 2011-05-25 17:42:50Z MPIE\p.eisenlohr $
|
||||||
|
""")
|
||||||
|
|
||||||
|
|
||||||
|
parser.add_option('-m','--memory', dest='memory', action='store_true', \
|
||||||
|
help='load complete file into memory [%default]')
|
||||||
|
parser.add_option('-v','--vector', dest='vector', action='extend', type='string', \
|
||||||
|
help='heading of columns containing vector field values')
|
||||||
|
parser.add_option('-t','--tensor', dest='tensor', action='extend', type='string', \
|
||||||
|
help='heading of columns containing tensor field values')
|
||||||
|
|
||||||
|
parser.set_defaults(memory = False)
|
||||||
|
parser.set_defaults(vector = [])
|
||||||
|
parser.set_defaults(tensor = [])
|
||||||
|
|
||||||
|
(options,filenames) = parser.parse_args()
|
||||||
|
|
||||||
|
if len(options.vector) + len(options.tensor) == 0:
|
||||||
|
parser.error('no data column specified...')
|
||||||
|
|
||||||
|
datainfo = { # list of requested labels per datatype
|
||||||
|
'vector': {'len':3,
|
||||||
|
'label':[]},
|
||||||
|
'tensor': {'len':9,
|
||||||
|
'label':[]},
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
if options.vector != None: datainfo['vector']['label'] += options.vector
|
||||||
|
if options.tensor != None: datainfo['tensor']['label'] += options.tensor
|
||||||
|
|
||||||
|
|
||||||
|
# ------------------------------------------ setup file handles ---------------------------------------
|
||||||
|
|
||||||
|
files = []
|
||||||
|
if filenames == []:
|
||||||
|
files.append({'name':'STDIN', 'input':sys.stdin, 'output':sys.stdout})
|
||||||
|
else:
|
||||||
|
for name in filenames:
|
||||||
|
if os.path.exists(name):
|
||||||
|
files.append({'name':name, 'input':open(name), 'output':open(name+'_tmp','w')})
|
||||||
|
|
||||||
|
# ------------------------------------------ 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())
|
||||||
|
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()
|
||||||
|
|
||||||
|
if options.memory:
|
||||||
|
data = file['input'].readlines()
|
||||||
|
else:
|
||||||
|
data = []
|
||||||
|
|
||||||
|
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:]
|
||||||
|
|
||||||
|
active = {}
|
||||||
|
column = {}
|
||||||
|
head = []
|
||||||
|
|
||||||
|
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)
|
||||||
|
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)
|
||||||
|
head.append('norm(%s)'%label)
|
||||||
|
|
||||||
|
# ------------------------------------------ assemble header ---------------------------------------
|
||||||
|
|
||||||
|
output = '%i\theader'%(headerlines+1) + '\n' + \
|
||||||
|
''.join(passOn) + \
|
||||||
|
string.replace('$Id: addNorm 263 2011-05-25 17:42:50Z MPIE\p.eisenlohr $','\n','\\n')+ '\t' + \
|
||||||
|
' '.join(sys.argv[1:]) + '\n' + \
|
||||||
|
'\t'.join(headers + head) + '\n' # build extended header
|
||||||
|
|
||||||
|
if not options.memory:
|
||||||
|
file['output'].write(output)
|
||||||
|
output = ''
|
||||||
|
|
||||||
|
# ------------------------------------------ read file ---------------------------------------
|
||||||
|
|
||||||
|
for line in {True : data,
|
||||||
|
False : file['input']}[options.memory]:
|
||||||
|
items = line.split()[:len(headers)]
|
||||||
|
if len(items) < len(headers):
|
||||||
|
continue
|
||||||
|
|
||||||
|
output += '\t'.join(items)
|
||||||
|
|
||||||
|
for datatype,labels in active.items():
|
||||||
|
for label in labels:
|
||||||
|
theNorm = L2(map(float,items[column[datatype][label]:
|
||||||
|
column[datatype][label]+datainfo[datatype]['len']]))
|
||||||
|
output += '\t%f'%theNorm
|
||||||
|
|
||||||
|
output += '\n'
|
||||||
|
|
||||||
|
if not options.memory:
|
||||||
|
file['output'].write(output)
|
||||||
|
output = ''
|
||||||
|
|
||||||
|
file['input'].close()
|
||||||
|
|
||||||
|
# ------------------------------------------ output result ---------------------------------------
|
||||||
|
|
||||||
|
if options.memory:
|
||||||
|
file['output'].write(output)
|
||||||
|
|
||||||
|
if file['name'] != 'STDIN':
|
||||||
|
file['output'].close
|
||||||
|
os.rename(file['name']+'_tmp',file['name'])
|
||||||
|
|
@ -0,0 +1,215 @@
|
||||||
|
#!/usr/bin/python
|
||||||
|
|
||||||
|
import os,re,sys,math,numpy,string
|
||||||
|
from optparse import OptionParser, Option
|
||||||
|
|
||||||
|
def operator(how,vector):
|
||||||
|
return { \
|
||||||
|
'ln': numpy.log(vector)*1.0,\
|
||||||
|
'Biot': vector *1.0,\
|
||||||
|
'Green': vector*vector *0.5,\
|
||||||
|
}[how]
|
||||||
|
|
||||||
|
|
||||||
|
# -----------------------------
|
||||||
|
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 prefixMultiply(what,len):
|
||||||
|
|
||||||
|
return {True: ['%i_%s'%(i+1,what) for i in range(len)],
|
||||||
|
False:[what]}[len>1]
|
||||||
|
|
||||||
|
|
||||||
|
# --------------------------------------------------------------------
|
||||||
|
# MAIN
|
||||||
|
# --------------------------------------------------------------------
|
||||||
|
|
||||||
|
parser = OptionParser(option_class=extendableOption, usage='%prog options [file[s]]', description = """
|
||||||
|
Add column(s) containing given strains based on given stretches of requested deformation gradient column(s).
|
||||||
|
|
||||||
|
$Id: addStrainTensors 274 2011-06-14 12:59:39Z MPIE\o.guevenc $
|
||||||
|
""")
|
||||||
|
|
||||||
|
|
||||||
|
parser.add_option('-m','--memory', dest='memory', action='store_true', \
|
||||||
|
help='load complete file into memory [%default]')
|
||||||
|
parser.add_option('-u','--right', action='store_true', dest='right', \
|
||||||
|
help='calculate strains based on right Cauchy--Green deformation, i.e., C and U')
|
||||||
|
parser.add_option('-v','--left', action='store_true', dest='left', \
|
||||||
|
help='calculate strains based on left Cauchy--Green deformation, i.e., B and V')
|
||||||
|
parser.add_option('-l','--logarithmic', action='store_true', dest='logarithmic', \
|
||||||
|
help='calculate logarithmic strain tensor')
|
||||||
|
parser.add_option('-b','--biot', action='store_true', dest='biot', \
|
||||||
|
help='calculate biot strain tensor')
|
||||||
|
parser.add_option('-g','--green', action='store_true', dest='green', \
|
||||||
|
help='calculate green strain tensor')
|
||||||
|
parser.add_option('-f','--deformation', dest='defgrad', action='extend', type='string', \
|
||||||
|
help='heading(s) of columns containing deformation tensor values %default')
|
||||||
|
|
||||||
|
parser.set_defaults(memory = False)
|
||||||
|
parser.set_defaults(right = False)
|
||||||
|
parser.set_defaults(left = False)
|
||||||
|
parser.set_defaults(logarithmic = False)
|
||||||
|
parser.set_defaults(biot = False)
|
||||||
|
parser.set_defaults(green = False)
|
||||||
|
parser.set_defaults(defgrad = ['f'])
|
||||||
|
|
||||||
|
(options,filenames) = parser.parse_args()
|
||||||
|
|
||||||
|
stretches = []
|
||||||
|
stretch = {}
|
||||||
|
strains = []
|
||||||
|
|
||||||
|
if options.right: stretches.append('U')
|
||||||
|
if options.left: stretches.append('V')
|
||||||
|
if options.logarithmic: strains.append('ln')
|
||||||
|
if options.biot: strains.append('Biot')
|
||||||
|
if options.green: strains.append('Green')
|
||||||
|
|
||||||
|
datainfo = { # list of requested labels per datatype
|
||||||
|
'defgrad': {'len':9,
|
||||||
|
'label':[]},
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
if options.defgrad != None: datainfo['defgrad']['label'] += options.defgrad
|
||||||
|
|
||||||
|
|
||||||
|
# ------------------------------------------ setup file handles ---------------------------------------
|
||||||
|
|
||||||
|
files = []
|
||||||
|
if filenames == []:
|
||||||
|
files.append({'name':'STDIN', 'input':sys.stdin, 'output':sys.stdout})
|
||||||
|
else:
|
||||||
|
for name in filenames:
|
||||||
|
if os.path.exists(name):
|
||||||
|
files.append({'name':name, 'input':open(name), 'output':open(name+'_tmp','w')})
|
||||||
|
|
||||||
|
# ------------------------------------------ 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())
|
||||||
|
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()
|
||||||
|
|
||||||
|
if options.memory:
|
||||||
|
data = file['input'].readlines()
|
||||||
|
else:
|
||||||
|
data = []
|
||||||
|
|
||||||
|
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:]
|
||||||
|
|
||||||
|
active = {}
|
||||||
|
column = {}
|
||||||
|
head = []
|
||||||
|
|
||||||
|
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)
|
||||||
|
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)
|
||||||
|
for theStretch in stretches:
|
||||||
|
for theStrain in strains:
|
||||||
|
head += prefixMultiply('%s(%s)'%(theStrain,theStretch), 9)
|
||||||
|
|
||||||
|
# ------------------------------------------ assemble header ---------------------------------------
|
||||||
|
|
||||||
|
output = '%i\theader'%(headerlines+1) + '\n' + \
|
||||||
|
''.join(passOn) + \
|
||||||
|
string.replace('$Id: addStrainTensors 274 2011-06-14 12:59:39Z MPIE\o.guevenc $','\n','\\n')+ '\t' + \
|
||||||
|
' '.join(sys.argv[1:]) + '\n' + \
|
||||||
|
'\t'.join(headers + head) + '\n' # build extended header
|
||||||
|
|
||||||
|
if not options.memory:
|
||||||
|
file['output'].write(output)
|
||||||
|
output = ''
|
||||||
|
|
||||||
|
# ------------------------------------------ read file ---------------------------------------
|
||||||
|
|
||||||
|
for line in {True : data,
|
||||||
|
False : file['input']}[options.memory]:
|
||||||
|
items = line.split()[:len(headers)]
|
||||||
|
if len(items) < len(headers):
|
||||||
|
continue
|
||||||
|
|
||||||
|
output += '\t'.join(items)
|
||||||
|
|
||||||
|
for datatype,labels in active.items():
|
||||||
|
for label in labels:
|
||||||
|
defgrad = numpy.array(map(float,items[column[datatype][label]:
|
||||||
|
column[datatype][label]+datainfo[datatype]['len']]),'d').reshape(3,3)
|
||||||
|
(U,S,Vh) = numpy.linalg.svd(defgrad)
|
||||||
|
R = numpy.dot(U,Vh)
|
||||||
|
stretch['U'] = numpy.dot(numpy.linalg.inv(R),defgrad)
|
||||||
|
stretch['V'] = numpy.dot(defgrad,numpy.linalg.inv(R))
|
||||||
|
for theStretch in stretches:
|
||||||
|
for i in range(9):
|
||||||
|
if stretch[theStretch][i%3,i//3] < 1e-15:
|
||||||
|
stretch[theStretch][i%3,i//3] = 0.0
|
||||||
|
(D,V) = numpy.linalg.eig(stretch[theStretch]) # eigen decomposition (of symmetric matrix)
|
||||||
|
for i,eigval in enumerate(D):
|
||||||
|
if eigval < 0.0: # flip negative eigenvalues
|
||||||
|
D[i] = -D[i]
|
||||||
|
V[:,i] = -V[:,i]
|
||||||
|
if numpy.dot(V[:,i],V[:,(i+1)%3]) != 0.0: # check each vector for orthogonality
|
||||||
|
V[:,(i+1)%3] = numpy.cross(V[:,(i+2)%3],V[:,i]) # correct next vector
|
||||||
|
V[:,(i+1)%3] /= numpy.sqrt(numpy.dot(V[:,(i+1)%3],V[:,(i+1)%3].conj())) # and renormalize (hyperphobic?)
|
||||||
|
for theStrain in strains:
|
||||||
|
d = operator(theStrain,D) # operate on eigenvalues of U or V
|
||||||
|
I = operator(theStrain,numpy.ones(3)) # operate on eigenvalues of I (i.e. [1,1,1])
|
||||||
|
eps = (numpy.dot(V,numpy.dot(numpy.diag(d),V.T)).real-numpy.diag(I)).reshape(9) # build tensor back from eigenvalue/vector basis
|
||||||
|
output += '\t'+'\t'.join(map(str,eps))
|
||||||
|
|
||||||
|
|
||||||
|
output += '\n'
|
||||||
|
|
||||||
|
if not options.memory:
|
||||||
|
file['output'].write(output)
|
||||||
|
output = ''
|
||||||
|
|
||||||
|
file['input'].close()
|
||||||
|
|
||||||
|
# ------------------------------------------ output result ---------------------------------------
|
||||||
|
|
||||||
|
if options.memory:
|
||||||
|
file['output'].write(output)
|
||||||
|
|
||||||
|
if file['name'] != 'STDIN':
|
||||||
|
file['output'].close
|
||||||
|
os.rename(file['name']+'_tmp',file['name'])
|
||||||
|
|
@ -0,0 +1,148 @@
|
||||||
|
#!/usr/bin/python
|
||||||
|
|
||||||
|
import os,re,sys,math,string,numpy
|
||||||
|
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 numpy.array([ 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 = """
|
||||||
|
Average each data block of size 'packing' into single values thus reducing the former resolution
|
||||||
|
to resolution/packing. (Requires numpy.)
|
||||||
|
|
||||||
|
$Id: averageDown 266 2011-05-29 19:38:42Z MPIE\p.eisenlohr $
|
||||||
|
""")
|
||||||
|
|
||||||
|
|
||||||
|
parser.add_option('-m','--memory', dest='memory', action='store_true', \
|
||||||
|
help='load complete file into memory [%default]')
|
||||||
|
parser.add_option('-r','--resolution', dest='res', type='int', nargs=3, \
|
||||||
|
help='resolution in fast, medium, and slow dimension [%default]')
|
||||||
|
parser.add_option('-p','--packing', dest='packing', type='int', nargs=3, \
|
||||||
|
help='number of data points to average down in each dimension [%default]')
|
||||||
|
|
||||||
|
parser.set_defaults(memory = False)
|
||||||
|
parser.set_defaults(resolution = [32,32,32])
|
||||||
|
parser.set_defaults(packing = [2,2,2])
|
||||||
|
|
||||||
|
(options,filenames) = parser.parse_args()
|
||||||
|
|
||||||
|
if len(options.resolution) < 3:
|
||||||
|
parser.error('resolution needs three parameters...')
|
||||||
|
if len(options.packing) < 3:
|
||||||
|
parser.error('packing needs three parameters...')
|
||||||
|
options.packing = numpy.array(options.packing)
|
||||||
|
|
||||||
|
# ------------------------------------------ setup file handles ---------------------------------------
|
||||||
|
|
||||||
|
files = []
|
||||||
|
if filenames == []:
|
||||||
|
files.append({'name':'STDIN', 'input':sys.stdin, 'output':sys.stdout})
|
||||||
|
else:
|
||||||
|
for name in filenames:
|
||||||
|
if os.path.exists(name):
|
||||||
|
(head,tail) = os.path.split(name)
|
||||||
|
files.append({'name':name, 'input':open(name), 'output':open(os.path.join(head,'avgDown_%s'%tail),'w')})
|
||||||
|
|
||||||
|
# ------------------------------------------ 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())
|
||||||
|
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()
|
||||||
|
|
||||||
|
if options.memory:
|
||||||
|
data = file['input'].readlines()
|
||||||
|
else:
|
||||||
|
data = []
|
||||||
|
|
||||||
|
# ------------------------------------------ assemble header ---------------------------------------
|
||||||
|
|
||||||
|
output = '%i\theader'%(headerlines+1) + '\n' + \
|
||||||
|
''.join(passOn) + \
|
||||||
|
string.replace('$Id: averageDown 266 2011-05-29 19:38:42Z MPIE\p.eisenlohr $','\n','\\n')+ '\t' + \
|
||||||
|
' '.join(sys.argv[1:]) + '\n' + \
|
||||||
|
'\t'.join(headers) + '\n' # build extended header
|
||||||
|
|
||||||
|
if not options.memory:
|
||||||
|
file['output'].write(output)
|
||||||
|
output = ''
|
||||||
|
|
||||||
|
# ------------------------------------------ read file ---------------------------------------
|
||||||
|
|
||||||
|
averagedDown = numpy.zeros([options.res[2]/options.packing[2],
|
||||||
|
options.res[1]/options.packing[1],
|
||||||
|
options.res[0]/options.packing[0],
|
||||||
|
len(headers)])
|
||||||
|
|
||||||
|
idx = 0
|
||||||
|
for line in {True : data,
|
||||||
|
False : file['input']}[options.memory]:
|
||||||
|
items = numpy.array(map(float,line.split()[:len(headers)]))
|
||||||
|
if len(items) < len(headers):
|
||||||
|
continue
|
||||||
|
|
||||||
|
loc = location(idx,options.res)//options.packing
|
||||||
|
averagedDown[loc[2],loc[1],loc[0],:] += items
|
||||||
|
|
||||||
|
idx += 1
|
||||||
|
|
||||||
|
averagedDown /= options.packing[0]*options.packing[1]*options.packing[2]
|
||||||
|
for z in range(options.res[2]/options.packing[2]):
|
||||||
|
for y in range(options.res[1]/options.packing[1]):
|
||||||
|
for x in range(options.res[0]/options.packing[0]):
|
||||||
|
output += '\t'.join(map(str,averagedDown[z,y,x,:])) + '\n'
|
||||||
|
|
||||||
|
file['input'].close()
|
||||||
|
|
||||||
|
# ------------------------------------------ output result ---------------------------------------
|
||||||
|
|
||||||
|
file['output'].write(output)
|
||||||
|
|
||||||
|
if file['name'] != 'STDIN':
|
||||||
|
file['output'].close
|
||||||
|
|
@ -21,6 +21,12 @@ bin_link = { \
|
||||||
],
|
],
|
||||||
'post' : [
|
'post' : [
|
||||||
'3Dvisualize',
|
'3Dvisualize',
|
||||||
|
'addCauchy',
|
||||||
|
'addDeterminant',
|
||||||
|
'addDivergence',
|
||||||
|
'addMises',
|
||||||
|
'addNorm',
|
||||||
|
'addStrainTensors',
|
||||||
'mentat_colorMap',
|
'mentat_colorMap',
|
||||||
'postResults',
|
'postResults',
|
||||||
'spectral_iterationCount',
|
'spectral_iterationCount',
|
||||||
|
|
|
||||||
Loading…
Reference in New Issue