diff --git a/processing/post/addSpectralDecomposition.py b/processing/post/addSpectralDecomposition.py new file mode 100755 index 000000000..9caa3c722 --- /dev/null +++ b/processing/post/addSpectralDecomposition.py @@ -0,0 +1,139 @@ +#!/usr/bin/env python + +import os,re,sys,math,numpy,string,damask +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) + + +# -------------------------------------------------------------------- +# MAIN +# -------------------------------------------------------------------- + +parser = OptionParser(option_class=extendableOption, usage='%prog options [file[s]]', description = """ +Add column(s) containing eigenvalues and eigenvectors of requested tensor column(s). + +""" + string.replace('$Id$','\n','\\n') +) + + +parser.add_option('-t','--tensor', dest='tensor', action='extend', type='string', \ + help='heading of columns containing tensor field values') + +parser.set_defaults(tensor = []) + +(options,filenames) = parser.parse_args() + +if len(options.tensor) == 0: + parser.error('no data column specified...') + +datainfo = { # list of requested labels per datatype + 'tensor': {'len':9, + 'label':[]}, + } + + +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, + 'croak':sys.stderr, + }) +else: + for name in filenames: + if os.path.exists(name): + files.append({'name':name, + 'input':open(name), + 'output':open(name+'_tmp','w'), + 'croak':sys.stdout, + }) + +# ------------------------------------------ loop over input files --------------------------------------- + +for file in files: + if file['name'] != 'STDIN': file['croak'].write(file['name']+'\n') + + + table = damask.ASCIItable(file['input'],file['output'],False) # make unbuffered ASCII_table + table.head_read() # read ASCII header info + table.info_append(string.replace('$Id$','\n','\\n') + \ + '\t' + ' '.join(sys.argv[1:])) + + 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 table.labels: + file['croak'].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] = table.labels.index(key) # remember columns of requested data + table.labels_append(['%i_eigval(%s)'%(i+1,label) + for i in xrange(3)]) # extend ASCII header with new labels + table.labels_append(['%i_eigvec(%s)'%(i+1,label) + for i in xrange(9)]) # extend ASCII header with new labels + +# ------------------------------------------ assemble header --------------------------------------- + + table.head_write() + +# ------------------------------------------ process data --------------------------------------- + + while table.data_read(): # read next data line of ASCII table + + for datatype,labels in active.items(): # loop over vector,tensor + for label in labels: # loop over all requested norms + tensor = numpy.array(map(float,table.data[column[datatype][label]: + column[datatype][label]+datainfo[datatype]['len']])).reshape((datainfo[datatype]['len']//3,3)) + (u,v) = numpy.linalg.eig(tensor) + table.data_append(list(u)) + table.data_append(list(v.transpose().reshape(datainfo[datatype]['len']))) + + table.data_write() # output processed line + +# ------------------------------------------ output result --------------------------------------- + + table.output_flush() # just in case of buffered ASCII table + + try: + file['output'].close() # close output ASCII table + except: + pass + try: + file['croak'].close() # stop croaking + except: + pass + try: + file['input'].close() # close input ASCII table + except: + pass + + if file['name'] != 'STDIN': + os.rename(file['name']+'_tmp',file['name']) # overwrite old one with tmp new diff --git a/processing/setup/setup_processing.py b/processing/setup/setup_processing.py index 1318a6bb1..230e657cb 100755 --- a/processing/setup/setup_processing.py +++ b/processing/setup/setup_processing.py @@ -101,6 +101,7 @@ bin_link = { \ 'addCalculation.py', 'addDeterminant.py', 'addDeviator.py', + 'addSpectralDecomposition.py', 'addDivergence.py', 'addCurl.py', 'addMises.py', @@ -116,7 +117,6 @@ bin_link = { \ 'filterTable.py', 'mentat_colorMap.py', 'postResults.py', - 'spectral_iterationCount.py', 'spectral_parseLog.py', 'nodesFromCentroids.py', 'tagLabel.py',