diff --git a/processing/post/rotateData.py b/processing/post/rotateData.py new file mode 100755 index 000000000..83542fa5b --- /dev/null +++ b/processing/post/rotateData.py @@ -0,0 +1,142 @@ +#!/usr/bin/env python +# -*- coding: UTF-8 no BOM -*- + +import os,re,sys,math,numpy,string +import damask +from collections import defaultdict +from optparse import OptionParser, Option + +scriptID = '$Id$' +scriptName = scriptID.split()[1] + +# ----------------------------- +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 = """ +Uniformly scale values of scalar, vector, or tensor columns by given factor. + +""" + string.replace(scriptID,'\n','\\n') +) + +parser.add_option('-v','--vector', dest = 'vector', action = 'extend', type = 'string', + help = 'column heading of vector to scale', + metavar = '') +parser.add_option('-t','--tensor', dest = 'tensor', action = 'extend', type = 'string', + help = 'column heading of tensor to scale', + metavar = '') +parser.add_option('-r', '--rotation', dest = 'rotation', type = 'float', nargs = 4, + help = 'angle and axis to rotate data') +parser.add_option('-d', '--degrees', dest = 'degrees', action = 'store_true', + help = 'angles are given in degrees [%default]') + +parser.set_defaults(vector = []) +parser.set_defaults(tensor = []) +parser.set_defaults(rotation = [0.,1.,1.,1.]) # no rotation about 1,1,1 +parser.set_defaults(degrees = False) + +(options,filenames) = parser.parse_args() + +datainfo = { # list of requested labels per datatype + 'vector': {'len':3, + 'label':[]}, + 'tensor': {'len':9, + 'label':[]}, + } + + +if options.vector != []: datainfo['vector']['label'] += options.vector +if options.tensor != []: datainfo['tensor']['label'] += options.tensor + +toRadians = math.pi/180.0 if options.degrees else 1.0 # rescale degrees to radians +r = damask.Quaternion().fromAngleAxis(toRadians*options.rotation[0],options.rotation[1:]) +R = r.asMatrix() + +# ------------------------------------------ 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.stderr}) + +#--- loop over input files ------------------------------------------------------------------------ +for file in files: + if file['name'] != 'STDIN': file['croak'].write('\033[1m'+scriptName+'\033[0m: '+file['name']+'\n') + else: file['croak'].write('\033[1m'+scriptName+'\033[0m\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(scriptName,'\n','\\n') + \ + '\t' + ' '.join(sys.argv[1:])) + +# --------------- figure out columns to process --------------------------------------- + active = defaultdict(list) + column = defaultdict(dict) + + for datatype,info in datainfo.items(): + for label in info['label']: + foundIt = False + for key in ['1_'+label,label]: + if key in table.labels: + foundIt = True + active[datatype].append(label) + column[datatype][label] = table.labels.index(key) # remember columns of requested data + if not foundIt: + file['croak'].write('column %s not found...\n'%label) + +# ------------------------------------------ assemble header --------------------------------------- + + table.head_write() + +# ------------------------------------------ process data --------------------------------------- + + outputAlive = True + while outputAlive and table.data_read(): # read next data line of ASCII table + + datatype = 'vector' + for label in active[datatype] if datatype in active else []: # loop over all requested labels + table.data[column[datatype][label]:column[datatype][label]+datainfo[datatype]['len']] = \ + r * numpy.array(map(float, + table.data[column[datatype][label]:\ + column[datatype][label]+datainfo[datatype]['len']])) + + datatype = 'tensor' + for label in active[datatype] if datatype in active else []: # loop over all requested labels + table.data[column[datatype][label]:column[datatype][label]+column[datatype]['len']] = \ + (numpy.array(map(float, + table.data[column[datatype][label]:\ + column[datatype][label]+column[datatype]['len']])).reshape(numpy.sqrt(datainfo[datatype]['len']),\ + numpy.sqrt(datainfo[datatype]['len'])) * R).reshape(datainfo[datatype]['len']) + + outputAlive = table.data_write() # output processed line + +# ------------------------------------------ output result --------------------------------------- + + outputAlive and table.output_flush() # just in case of buffered ASCII table + + if file['name'] != 'STDIN': + file['input'].close() # close input ASCII table + file['output'].close() # close output ASCII table + os.rename(file['name']+'_tmp',file['name']) # overwrite old one with tmp new diff --git a/processing/post/scaleData.py b/processing/post/scaleData.py new file mode 100755 index 000000000..cdfc85f15 --- /dev/null +++ b/processing/post/scaleData.py @@ -0,0 +1,138 @@ +#!/usr/bin/env python +# -*- coding: UTF-8 no BOM -*- + +import os,re,sys,math,numpy,string +import damask +from collections import defaultdict +from optparse import OptionParser, Option + +scriptID = '$Id$' +scriptName = scriptID.split()[1] + +# ----------------------------- +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 = """ +Uniformly scale values of scalar, vector, or tensor columns by given factor. + +""" + string.replace(scriptID,'\n','\\n') +) + +parser.add_option('-s','--scalar', dest='scalar', action='extend', type='string', + help='column heading of scalar to scale', + metavar='') +parser.add_option('-v','--vector', dest='vector', action='extend', type='string', + help='column heading of vector to scale', + metavar='') +parser.add_option('-t','--tensor', dest='tensor', action='extend', type='string', + help='column heading of tensor to scale', + metavar='') +parser.add_option('-f','--factor', dest='factor', action='extend', type='string', + help='list of scalar, vector, and tensor scaling factors (in this order!)', + metavar='') + +parser.set_defaults(scalar = []) +parser.set_defaults(vector = []) +parser.set_defaults(tensor = []) +parser.set_defaults(factor = []) + +(options,filenames) = parser.parse_args() + +options.factor = numpy.array(map(float,options.factor)) +datainfo = { # list of requested labels per datatype + 'scalar': {'len':1, + 'label':[]}, + 'vector': {'len':3, + 'label':[]}, + 'tensor': {'len':9, + 'label':[]}, + } + +length = 0 +if options.scalar != []: datainfo['scalar']['label'] += options.scalar; length += len(options.scalar) +if options.vector != []: datainfo['vector']['label'] += options.vector; length += len(options.vector) +if options.tensor != []: datainfo['tensor']['label'] += options.tensor; length += len(options.tensor) +if len(options.factor) != length: + parser.error('Length of scaling vector does not match column count.') + +# ------------------------------------------ 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.stderr}) + +#--- loop over input files ------------------------------------------------------------------------ +for file in files: + if file['name'] != 'STDIN': file['croak'].write('\033[1m'+scriptName+'\033[0m: '+file['name']+'\n') + else: file['croak'].write('\033[1m'+scriptName+'\033[0m\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(scriptName,'\n','\\n') + \ + '\t' + ' '.join(sys.argv[1:])) + +# --------------- figure out columns to process --------------------------------------- + active = defaultdict(list) + column = defaultdict(dict) + + for datatype,info in datainfo.items(): + for label in info['label']: + foundIt = False + for key in ['1_'+label,label]: + if key in table.labels: + foundIt = True + active[datatype].append(label) + column[datatype][label] = table.labels.index(key) # remember columns of requested data + if not foundIt: + file['croak'].write('column %s not found...\n'%label) + +# ------------------------------------------ assemble header --------------------------------------- + + table.head_write() + +# ------------------------------------------ process data --------------------------------------- + + outputAlive = True + while outputAlive and table.data_read(): # read next data line of ASCII table + + i = 0 + for datatype,labels in sorted(active.items(),key=lambda x:datainfo[x[0]]['len']): # loop over scalar,vector,tensor + for label in labels: # loop over all requested labels + for j in xrange(datainfo[datatype]['len']): # loop over entity elements + table.data[column[datatype][label]+j] = float(table.data[column[datatype][label]+j]) * options.factor[i] + i += 1 + + outputAlive = table.data_write() # output processed line + +# ------------------------------------------ output result --------------------------------------- + + outputAlive and table.output_flush() # just in case of buffered ASCII table + + if file['name'] != 'STDIN': + file['input'].close() # close input ASCII table + file['output'].close() # close output ASCII table + os.rename(file['name']+'_tmp',file['name']) # overwrite old one with tmp new diff --git a/processing/post/shiftData.py b/processing/post/shiftData.py new file mode 100755 index 000000000..877bccbd6 --- /dev/null +++ b/processing/post/shiftData.py @@ -0,0 +1,141 @@ +#!/usr/bin/env python +# -*- coding: UTF-8 no BOM -*- + +import os,re,sys,math,numpy,string +import damask +from collections import defaultdict +from optparse import OptionParser, Option + +scriptID = '$Id$' +scriptName = scriptID.split()[1] + +# ----------------------------- +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 = """ +Shift values of scalar, vector, or tensor columns by given offset. + +""" + string.replace(scriptID,'\n','\\n') +) + +parser.add_option('-s','--scalar', dest='scalar', action='extend', type='string', + help='column heading to shift by scalar', + metavar='') +parser.add_option('-v','--vector', dest='vector', action='extend', type='string', + help='column heading to shift by vector', + metavar='') +parser.add_option('-t','--tensor', dest='tensor', action='extend', type='string', + help='column heading to shift by tensor', + metavar='') +parser.add_option('-d','--delta', dest='delta', action='extend', type='string', + help='list of scalar, vector, and tensor shifts (in this order!)', + metavar='') + +parser.set_defaults(scalar = []) +parser.set_defaults(vector = []) +parser.set_defaults(tensor = []) +parser.set_defaults(delta = []) + +(options,filenames) = parser.parse_args() + +options.delta = numpy.array(map(float,options.delta)) +datainfo = { # list of requested labels per datatype + 'scalar': {'len':1, + 'label':[]}, + 'vector': {'len':3, + 'label':[]}, + 'tensor': {'len':9, + 'label':[]}, + } + +length = 0 +if options.scalar != []: datainfo['scalar']['label'] += options.scalar; length += len(options.scalar)*datainfo['scalar']['len'] +if options.vector != []: datainfo['vector']['label'] += options.vector; length += len(options.vector)*datainfo['vector']['len'] +if options.tensor != []: datainfo['tensor']['label'] += options.tensor; length += len(options.tensor)*datainfo['tensor']['len'] +if len(options.delta) != length: + parser.error('Length of offset vector does not match column types.') + +# ------------------------------------------ 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.stderr}) + +#--- loop over input files ------------------------------------------------------------------------ +for file in files: + if file['name'] != 'STDIN': file['croak'].write('\033[1m'+scriptName+'\033[0m: '+file['name']+'\n') + else: file['croak'].write('\033[1m'+scriptName+'\033[0m\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(scriptName,'\n','\\n') + \ + '\t' + ' '.join(sys.argv[1:])) + +# --------------- figure out columns to process --------------------------------------- + active = defaultdict(list) + column = defaultdict(dict) + + for datatype,info in datainfo.items(): + for label in info['label']: + foundIt = False + for key in ['1_'+label,label]: + if key in table.labels: + foundIt = True + active[datatype].append(label) + column[datatype][label] = table.labels.index(key) # remember columns of requested data + if not foundIt: + file['croak'].write('column %s not found...\n'%label) + +# ------------------------------------------ assemble header --------------------------------------- + + table.head_write() + +# ------------------------------------------ process data --------------------------------------- + + outputAlive = True + while outputAlive and table.data_read(): # read next data line of ASCII table + + i = 0 + for datatype,labels in sorted(active.items(),key=lambda x:datainfo[x[0]]['len']): # loop over scalar,vector,tensor +# file['croak'].write('%s\n'%datatype) + for label in labels: # loop over all requested labels +# file['croak'].write('%s\n'%label) + for j in xrange(datainfo[datatype]['len']): # loop over entity elements +# file['croak'].write('%s\n'%table.data[column[datatype][label]+j]) + table.data[column[datatype][label]+j] = float(table.data[column[datatype][label]+j]) + options.delta[i] + i += 1 + + outputAlive = table.data_write() # output processed line + +# ------------------------------------------ output result --------------------------------------- + + outputAlive and table.output_flush() # just in case of buffered ASCII table + + if file['name'] != 'STDIN': + file['input'].close() # close input ASCII table + file['output'].close() # close output ASCII table + os.rename(file['name']+'_tmp',file['name']) # overwrite old one with tmp new