#!/usr/bin/python import os,re,sys,math,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) # definition of element-wise p-norms for matrices # p = 1 def absnorm(object): return sum(map(abs, object)) # p = 2 def frobeniusnorm(object): return math.sqrt(sum([x*x for x in object])) # p = infinity def maxnorm(object): return max(map(abs, 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. """ + string.replace('$Id$','\n','\\n') ) parser.add_option('-n','--norm', dest='norm', action='store', type='choice', choices=('absnorm','frobeniusnorm','maxnorm'), \ help='used p-norm, choose either absnorm, frobeniusnorm, or maxnorm [DEFAULT=%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('-s','--slipsystem ', dest='slipsystem', action='extend', type='string', \ help='heading of columns containing values per slipsystem') parser.add_option('-i','--nslipsystems',dest='Nslipsystems', action='store', type='int', \ help='number of slip systems [DEFAULT=%default]') parser.set_defaults(norm = 'frobeniusnorm') parser.set_defaults(vector = []) parser.set_defaults(tensor = []) parser.set_defaults(slipsystem = []) parser.set_defaults(Nslipsystems = 12) (options,filenames) = parser.parse_args() if len(options.vector) + len(options.tensor) + len(options.slipsystem)== 0: parser.error('no data column specified...') datainfo = { # list of requested labels per datatype 'vector': {'len':3, 'label':[]}, 'tensor': {'len':9, 'label':[]}, 'slipsystem': {'len':options.Nslipsystems, 'label':[]}, } if options.vector != None: datainfo['vector']['label'] += options.vector if options.tensor != None: datainfo['tensor']['label'] += options.tensor if options.slipsystem != None:datainfo['slipsystem']['label'] += options.slipsystem # ------------------------------------------ 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: if file['name'] != 'STDIN': print file['name'] 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: 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] = table.labels.index(key) # remember columns of requested data table.labels_append('%s(%s)'%(options.norm,label)) # 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 eval("table.data_append(%s(map(float,table.data[column[datatype][label]:column[datatype][label]+datainfo[datatype]['len']])))"%options.norm) table.data_write() # output processed line # ------------------------------------------ output result --------------------------------------- table.output_flush() # just in case of buffered ASCII table file['input'].close() # close input ASCII table if file['name'] != 'STDIN': file['output'].close # close output ASCII table os.rename(file['name']+'_tmp',file['name']) # overwrite old one with tmp new