136 lines
5.6 KiB
Python
Executable File
136 lines
5.6 KiB
Python
Executable File
#!/usr/bin/env python
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import os,re,sys,math,numpy,string,damask
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from optparse import OptionParser, Option
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scriptID = '$Id$'
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scriptName = scriptID.split()[1]
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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 Mises(what,tensor):
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dev = tensor - numpy.trace(tensor)/3.0*numpy.eye(3)
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symdev = 0.5*(dev+dev.T)
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return math.sqrt(numpy.sum(symdev*symdev.T)*
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{
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'stress': 3.0/2.0,
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'strain': 2.0/3.0,
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}[what.lower()])
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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 vonMises equivalent values for symmetric part of requested strains and/or stresses.
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""" + string.replace(scriptID,'\n','\\n')
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)
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parser.add_option('-e','--strain', dest='strain', action='extend', type='string', \
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help='heading(s) of columns containing strain tensors')
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parser.add_option('-s','--stress', dest='stress', action='extend', type='string', \
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help='heading(s) of columns containing stress tensors')
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parser.set_defaults(strain = [])
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parser.set_defaults(stress = [])
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(options,filenames) = parser.parse_args()
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if len(options.strain) + len(options.stress) == 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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'strain': {'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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if options.strain != None: datainfo['strain']['label'] += options.strain
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if options.stress != None: datainfo['stress']['label'] += 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', 'input':sys.stdin, 'output':sys.stdout, 'croak':sys.stderr})
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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'), 'croak':sys.stderr})
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# ------------------------------------------ loop over input files ---------------------------------------
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for file in files:
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if file['name'] != 'STDIN': file['croak'].write('\033[1m'+scriptName+'\033[0m: '+file['name']+'\n')
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else: file['croak'].write('\033[1m'+scriptName+'\033[0m\n')
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table = damask.ASCIItable(file['input'],file['output'],False) # make unbuffered ASCII_table
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table.head_read() # read ASCII header info
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table.info_append(string.replace(scriptID,'\n','\\n') + '\t' + ' '.join(sys.argv[1:]))
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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 table.labels:
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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] = table.labels.index(key) # remember columns of requested data
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table.labels_append('Mises(%s)'%label) # extend ASCII header with new labels
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# ------------------------------------------ assemble header ---------------------------------------
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table.head_write()
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# ------------------------------------------ process data ---------------------------------------
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while table.data_read(): # read next data line of ASCII table
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for datatype,labels in active.items(): # loop over vector,tensor
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for label in labels: # loop over all requested norms
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table.data_append(Mises(datatype,
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numpy.array(map(float,table.data[column[datatype][label]:
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column[datatype][label]+datainfo[datatype]['len']]),'d').reshape(3,3)))
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table.data_write() # output processed line
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# ------------------------------------------ output result ---------------------------------------
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table.output_flush() # just in case of buffered ASCII table
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file['input'].close() # close input ASCII table
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if file['name'] != 'STDIN':
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file['output'].close # close output ASCII table
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os.rename(file['name']+'_tmp',file['name']) # overwrite old one with tmp new
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