#!/usr/bin/env python import pdb, os, sys, gc, math, re, threading, time, struct from optparse import OptionParser, OptionGroup, Option, SUPPRESS_HELP releases = {'2010':['linux64',''], '2008r1':[''], '2007r1':[''], '2005r3':[''], } # ----------------------------- class vector: # mimic py_post node object # ----------------------------- x,y,z = [None,None,None] def __init__(self,coords): self.x = coords[0] self.y = coords[1] self.z = coords[2] # ----------------------------- class element: # mimic py_post element object # ----------------------------- items = [] type = None def __init__(self,nodes,type): self.items = nodes self.type = type # ----------------------------- class elemental_scalar: # mimic py_post element_scalar object # ----------------------------- id = None value = None def __init__(self,node,value): self.id = node self.value = value # ----------------------------- class MPIEspectral_result: # mimic py_post result object # ----------------------------- file = None dataOffset = 0 N_elemental_scalars = 0 resolution = [0,0,0] dimension = [0.0,0.0,0.0] theTitle = '' wd = '' geometry = '' extrapolate = '' N_increments = 0 increment = 0 time = 0.0 # this is a dummy at the moment, we need to parse the load file and figure out what time a particular increment corresponds to N_nodes = 0 N_node_scalars = 0 N_elements = 0 N_element_scalars = 0 N_element_tensors = 0 def __init__(self,filename): self.file = open(filename, 'rb') self.theTitle = self._keyedString('load') self.wd = self._keyedString('workingdir') self.geometry = self._keyedString('geometry') self.N_increments = self._keyedInt('increments') self.N_element_scalars = self._keyedInt('materialpoint_sizeResults') self.resolution = self._keyedPackedArray('resolution',3,'i') self.N_nodes = (self.resolution[0]+1)*(self.resolution[1]+1)*(self.resolution[2]+1) self.N_elements = self.resolution[0]*self.resolution[1]*self.resolution[2] self.dimension = self._keyedPackedArray('dimension',3,'d') self.file.seek(0) self.dataOffset = self.file.read(2048).find('eoh')+7 def __str__(self): return '\n'.join([ 'title: %s'%self.theTitle, 'workdir: %s'%self.wd, 'geometry: %s'%self.geometry, 'extrapolation: %s'%self.extrapolate, 'increments: %i'%self.N_increments, 'increment: %i'%self.increment, 'nodes: %i'%self.N_nodes, 'resolution: %s'%(','.join(map(str,self.resolution))), 'dimension: %s'%(','.join(map(str,self.dimension))), 'elements: %i'%self.N_elements, 'nodal_scalars: %i'%self.N_node_scalars, 'elemental scalars: %i'%self.N_element_scalars, 'elemental tensors: %i'%self.N_element_tensors, ] ) def _keyedPackedArray(self,identifier,length = 3,type = 'd'): match = {'d': 8,'i': 4} self.file.seek(0) m = re.search('%s%s'%(identifier,'(.{%i})'%(match[type])*length),self.file.read(2048),re.DOTALL) values = [] if m: for i in m.groups(): values.append(struct.unpack(type,i)[0]) return values def _keyedInt(self,identifier): value = None self.file.seek(0) m = re.search('%s%s'%(identifier,'(.{4})'),self.file.read(2048),re.DOTALL) if m: value = struct.unpack('i',m.group(1))[0] return value def _keyedString(self,identifier): value = None self.file.seek(0) m = re.search(r'(.{4})%s(.*?)\1'%identifier,self.file.read(2048),re.DOTALL) if m: value = m.group(2) return value def title(self): return self.theTitle def moveto(self,inc): self.increment = inc def extrapolation(self,value): self.extrapolate = value def node_sequence(self,n): return n-1 def node_id(self,n): return n+1 def node(self,n): a = self.resolution[0]+1 b = self.resolution[1]+1 c = self.resolution[2]+1 return vector([self.dimension[0] * (n%a) / self.resolution[0], self.dimension[1] * ((n/a)%b) / self.resolution[1], self.dimension[2] * ((n/a/b)%c) / self.resolution[2], ]) def element_sequence(self,e): return e-1 def element_id(self,e): return e+1 def element(self,e): a = self.resolution[0]+1 b = self.resolution[1]+1 c = self.resolution[2]+1 basenode = 1 + e+e/self.resolution[0] + e/self.resolution[0]/self.resolution[1]*a basenode2 = basenode+a*b return (element([basenode ,basenode +1,basenode +a+1,basenode +a, basenode2,basenode2+1,basenode2+a+1,basenode2+a, ],117)) def increments(self): return self.N_increments def nodes(self): return self.N_nodes def node_scalars(self): return self.N_node_scalars def elements(self): return self.N_elements def element_scalars(self): return self.N_element_scalars def element_scalar(self,e,idx): self.file.seek(self.dataOffset+(self.increment*(4+self.N_elements*self.N_element_scalars*8+4) + 4+(e*self.N_element_scalars + idx)*8)) value = struct.unpack('d',self.file.read(8))[0] return [elemental_scalar(node,value) for node in self.element(e).items] def element_scalar_label(elem,idx): return 'User Defined Variable %i'%(idx+1) def element_tensors(self): return self.N_element_tensors # ----------------------------- class MyOption(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) # ----------------------------- class backgroundMessage(threading.Thread): # ----------------------------- def __init__(self): threading.Thread.__init__(self) self.message = '' self.new_message = '' self.counter = 0 self.symbols = ['- ', '\ ', '| ', '/ ',] self.waittime = 0.5 def __quit__(self): length = len(self.message) + len(self.symbols[self.counter]) sys.stderr.write(chr(8)*length + ' '*length + chr(8)*length) sys.stderr.write('') def run(self): while not threading.enumerate()[0]._Thread__stopped: time.sleep(self.waittime) self.update_message() self.__quit__() def set_message(self, new_message): self.new_message = new_message self.print_message() def print_message(self): length = len(self.message) + len(self.symbols[self.counter]) sys.stderr.write(chr(8)*length + ' '*length + chr(8)*length) # delete former message sys.stderr.write(self.symbols[self.counter] + self.new_message) # print new message self.message = self.new_message def update_message(self): self.counter = (self.counter + 1)%len(self.symbols) self.print_message() # ----------------------------- def ipCoords(elemType, nodalCoordinates): # # returns IP coordinates for a given element # ----------------------------- nodeWeightsPerNode = { 7: [ [27.0, 9.0, 3.0, 9.0, 9.0, 3.0, 1.0, 3.0], [ 9.0, 27.0, 9.0, 3.0, 3.0, 9.0, 3.0, 1.0], [ 3.0, 9.0, 27.0, 9.0, 1.0, 3.0, 9.0, 3.0], [ 9.0, 3.0, 9.0, 27.0, 3.0, 1.0, 3.0, 9.0], [ 9.0, 3.0, 1.0, 3.0, 27.0, 9.0, 3.0, 9.0], [ 3.0, 9.0, 3.0, 1.0, 9.0, 27.0, 9.0, 3.0], [ 1.0, 3.0, 9.0, 3.0, 3.0, 9.0, 27.0, 9.0], [ 3.0, 1.0, 3.0, 9.0, 9.0, 3.0, 9.0, 27.0] ], 117: [ [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0] ], 125: [ [ 3.0, 0.0, 0.0, 4.0, 1.0, 4.0], [ 0.0, 3.0, 0.0, 4.0, 4.0, 1.0], [ 0.0, 0.0, 3.0, 1.0, 4.0, 4.0],], 136: [ [42.0, 15.0, 15.0, 14.0, 5.0, 5.0], [15.0, 42.0, 15.0, 5.0, 14.0, 5.0], [15.0, 15.0, 42.0, 5.0, 5.0, 14.0], [14.0, 5.0, 5.0, 42.0, 15.0, 15.0], [ 5.0, 14.0, 5.0, 15.0, 42.0, 15.0], [ 5.0, 5.0, 14.0, 15.0, 15.0, 42.0] ], } ipCoordinates = [[0.0,0.0,0.0] for i in range(len(nodalCoordinates))] for ip in range(len(nodeWeightsPerNode[elemType])): for node in range(len(nodeWeightsPerNode[elemType][ip])): for i in range(3): ipCoordinates[ip][i] += nodeWeightsPerNode[elemType][ip][node] * nodalCoordinates[node][i] for i in range(3): ipCoordinates[ip][i] /= sum(nodeWeightsPerNode[elemType][ip]) return ipCoordinates # ----------------------------- def substituteLocation(string, mesh, coords): # # do variable interpolation in group and filter strings # ----------------------------- substitute = string substitute = substitute.replace('elem', str(mesh[0])) substitute = substitute.replace('node', str(mesh[1])) substitute = substitute.replace('grain', str(mesh[2])) substitute = substitute.replace('x', '%.6g'%coords[0]) substitute = substitute.replace('y', '%.6g'%coords[1]) substitute = substitute.replace('z', '%.6g'%coords[2]) return substitute # ----------------------------- def heading(glue,parts): # # joins pieces from parts by glue. second to last entry in pieces tells multiplicity # ----------------------------- header = [] for pieces in parts: if pieces[-2] == 0: del pieces[-2] header.append(glue.join(map(str,pieces))) return header # ----------------------------- def mapIncremental(label, mapping, N, base, new): # # applies the function defined by "mapping" # (can be either 'min','max','avg', 'sum', or user specified) # to a list of data # ----------------------------- theMap = { 'min': lambda n,b,a: min(b,a), 'max': lambda n,b,a: max(b,a), 'avg': lambda n,b,a: (n*b+a)/(n+1), 'sum': lambda n,b,a: b+a, 'unique': lambda n,b,a: {True:a,False:'n/a'}[n==0 or b==a] } if mapping in theMap: mapped = map(theMap[mapping],[N]*len(base),base,new) # map one of the standard functions to data if label.lower() == 'orientation': # orientation is special case:... orientationNorm = math.sqrt(sum([q*q for q in mapped])) # ...calc norm of average quaternion mapped = map(lambda x: x/orientationNorm, mapped) # ...renormalize quaternion else: try: mapped = eval('map(%s,N*len(base),base,new)'%map) # map user defined function to colums in chunks except: mapped = ['n/a']*len(base) return mapped # ----------------------------- def OpenPostfile(name,type): # # open postfile with extrapolation mode "translate" # ----------------------------- p = {\ 'spectral': MPIEspectral_result,\ 'marc': post_open,\ }[type]\ (name+ {\ 'marc': '.t16',\ 'spectral': '.spectralOut',\ }[type] ) p.extrapolation('translate') p.moveto(1) return p # ----------------------------- def ParseOutputFormat(filename,what,me): # # parse .output* files in order to get a list of outputs # ----------------------------- format = {'outputs':{},'specials':{'brothers':[]}} for prefix in ['']+map(str,range(1,17)): if os.path.exists(prefix+filename+'.output'+what): break try: file = open(prefix+filename+'.output'+what) content = file.readlines() file.close() except: return format tag = '' tagID = 0 for line in content: if re.match("\s*$",line) or re.match("#",line): # skip blank lines and comments continue m = re.match("\[(.+)\]",line) # look for block indicator if m: # next section tag = m.group(1) tagID += 1 format['specials']['brothers'].append(tag) if tag == me or (me.isdigit() and tagID == int(me)): format['specials']['_id'] = tagID format['outputs'] = [] tag = me else: # data from section if tag == me: (output,length) = line.split() output.lower() if length.isdigit(): length = int(length) if re.match("\((.+)\)",output): # special data, e.g. (Ngrains) format['specials'][output] = length elif length > 0: format['outputs'].append([output,length]) return format # ----------------------------- def ParsePostfile(p,filename, outputFormat): # # parse postfile in order to get position and labels of outputs # needs "outputFormat" for mapping of output names to postfile output indices # ----------------------------- # --- build statistics stat = { \ 'IndexOfLabel': {}, \ 'Title': p.title(), \ 'Extrapolation': p.extrapolate, \ 'NumberOfIncrements': p.increments(), \ 'NumberOfNodes': p.nodes(), \ 'NumberOfNodalScalars': p.node_scalars(), \ 'LabelOfNodalScalar': [None]*p.node_scalars() , \ 'NumberOfElements': p.elements(), \ 'NumberOfElementalScalars': p.element_scalars(), \ 'LabelOfElementalScalar': [None]*p.element_scalars() , \ 'NumberOfElementalTensors': p.element_tensors(), \ 'LabelOfElementalTensor': [None]*p.element_tensors(), \ } # --- find labels for labelIndex in range(stat['NumberOfNodalScalars']): label = p.node_scalar_label(labelIndex) stat['IndexOfLabel'][label] = labelIndex stat['LabelOfNodalScalar'][labelIndex] = label for labelIndex in range(stat['NumberOfElementalScalars']): label = p.element_scalar_label(labelIndex) stat['IndexOfLabel'][label] = labelIndex stat['LabelOfElementalScalar'][labelIndex] = label for labelIndex in range(stat['NumberOfElementalTensors']): label = p.element_tensor_label(labelIndex) stat['IndexOfLabel'][label] = labelIndex stat['LabelOfElementalTensor'][labelIndex] = label if 'User Defined Variable 1' in stat['IndexOfLabel']: stat['IndexOfLabel']['GrainCount'] = stat['IndexOfLabel']['User Defined Variable 1'] if 'GrainCount' in stat['IndexOfLabel']: # does the result file contain relevant user defined output at all? startIndex = stat['IndexOfLabel']['GrainCount'] - 1 # We now have to find a mapping for each output label as defined in the .output* files to the output position in the post file # Since we know where the user defined outputs start ("startIndex"), we can simply assign increasing indices to the labels # given in the .output* file offset = 2 stat['LabelOfElementalScalar'][startIndex + offset] = 'HomogenizationCount' for var in outputFormat['Homogenization']['outputs']: if var[1] > 1: for i in range(var[1]): stat['IndexOfLabel']['%i_%s'%(i+1,var[0])] = startIndex + offset + (i+1) else: stat['IndexOfLabel']['%s'%(var[0])] = startIndex + offset + 1 offset += var[1] for grain in range(outputFormat['Homogenization']['specials']['(ngrains)']): stat['IndexOfLabel']['%i_CrystalliteCount'%(grain+1)] = startIndex + offset + 1 offset += 1 for var in outputFormat['Crystallite']['outputs']: if var[1] > 1: for i in range(var[1]): stat['IndexOfLabel']['%i_%i_%s'%(grain+1,i+1,var[0])] = startIndex + offset + (i+1) else: stat['IndexOfLabel']['%i_%s'%(grain+1,var[0])] = startIndex + offset + 1 offset += var[1] stat['IndexOfLabel']['%i_ConstitutiveCount'%(grain+1)] = startIndex + offset + 1 offset += 1 for var in outputFormat['Constitutive']['outputs']: if var[1] > 1: for i in range(var[1]): stat['IndexOfLabel']['%i_%i_%s'%(grain+1,i+1,var[0])] = startIndex + offset + (i+1) else: stat['IndexOfLabel']['%i_%s'%(grain+1,var[0])] = startIndex + offset + 1 offset += var[1] return stat # ----------------------------- def SummarizePostfile(stat,where=sys.stdout): # ----------------------------- where.write('\n\n') where.write('title:\t%s'%stat['Title'] + '\n\n') where.write('extraplation:\t%s'%stat['Extrapolation'] + '\n\n') where.write('increments:\t%i'%(stat['NumberOfIncrements']) + '\n\n') where.write('nodes:\t%i'%stat['NumberOfNodes'] + '\n\n') where.write('elements:\t%i'%stat['NumberOfElements'] + '\n\n') where.write('nodal scalars:\t%i'%stat['NumberOfNodalScalars'] + '\n\n ' + '\n '.join(stat['LabelOfNodalScalar']) + '\n\n') where.write('elemental scalars:\t%i'%stat['NumberOfElementalScalars'] + '\n\n ' + '\n '.join(stat['LabelOfElementalScalar']) + '\n\n') where.write('elemental tensors:\t%i'%stat['NumberOfElementalTensors'] + '\n\n ' + '\n '.join(stat['LabelOfElementalTensor']) + '\n\n') return True # ----------------------------- # MAIN FUNCTION STARTS HERE # ----------------------------- # --- input parsing parser = OptionParser(option_class=MyOption, usage='%prog [options] resultfile', description = """ Extract data from a .t16 (MSC.Marc) or .spectralOut results file. List of output variables is given by options '--ns','--es','--et','--ho','--cr','--co'. Filter and separations use 'elem','node','grain', and 'x','y','z' as key words. Example: 1) get averaged results in slices perpendicular to x for all positive y coordinates --filter 'y >= 0.0' --separation x --map 'avg' 2) global sum of squared data falling into first quadrant arc between R1 and R2 --filter 'x*x + y*y >= R1*R1 and x*x + y*y <= R2*R2' --map 'lambda list: sum([item*item for item in list])' $Id$ """) parser.add_option('-i','--info', action='store_true', dest='info', \ help='list contents of resultfile [%default]') parser.add_option('-d','--dir', dest='directory', \ help='name of subdirectory to hold output [%default]') parser.add_option('-s','--split', action='store_true', dest='separateFiles', \ help='split output per increment [%default]') parser.add_option('-r','--range', dest='range', type='int', nargs=3, \ help='range of increments to output (start, end, step) [all]') parser.add_option('--sloppy', action='store_true', dest='sloppy', \ help='do not pre-check validity of increment range') parser.add_option('-m','--map', dest='func', type='string', \ help='data reduction mapping ["%default"] out of min, max, avg, sum or user-lambda') parser.add_option('-p','--type', dest='filetype', type='string', \ help = 'type of result file [%default]') group_material = OptionGroup(parser,'Material identifier') group_special = OptionGroup(parser,'Special outputs') group_general = OptionGroup(parser,'General outputs') group_material.add_option('--homogenization', dest='homog', type='string', \ help='homogenization identifier (as string or integer [%default])') group_material.add_option('--crystallite', dest='cryst', type='string', \ help='crystallite identifier (as string or integer [%default])') group_material.add_option('--phase', dest='phase', type='string', \ help='phase identifier (as string or integer [%default])') group_special.add_option('-t','--time', action='store_true', dest='time', \ help='output time of increment [%default]') group_special.add_option('-f','--filter', dest='filter', type='string', \ help='condition(s) to filter results [%default]') group_special.add_option('--separation', action='extend', dest='separation', type='string', \ help='properties to separate results [%default]') group_special.add_option('--sort', action='extend', dest='sort', type='string', \ help='properties to sort results [%default]') group_general.add_option('--ns', action='extend', dest='nodalScalar', type='string', \ help='list of nodal scalars to extract') group_general.add_option('--es', action='extend', dest='elementalScalar', type='string', \ help='list of elemental scalars to extract') group_general.add_option('--et', action='extend', dest='elementalTensor', type='string', \ help='list of elemental tensors to extract') group_general.add_option('--ho', action='extend', dest='homogenizationResult', type='string', \ help='list of homogenization results to extract') group_general.add_option('--cr', action='extend', dest='crystalliteResult', type='string', \ help='list of crystallite results to extract') group_general.add_option('--co', action='extend', dest='constitutiveResult', type='string', \ help='list of constitutive results to extract') parser.add_option_group(group_material) parser.add_option_group(group_general) parser.add_option_group(group_special) parser.set_defaults(info = False) parser.set_defaults(sloppy = False) parser.set_defaults(directory = 'postProc') parser.set_defaults(filetype = 'marc') parser.set_defaults(func = 'avg') parser.set_defaults(homog = '1') parser.set_defaults(cryst = '1') parser.set_defaults(phase = '1') parser.set_defaults(filter = '') parser.set_defaults(separation = []) parser.set_defaults(sort = []) parser.set_defaults(inc = False) parser.set_defaults(time = False) parser.set_defaults(separateFiles = False) (options, files) = parser.parse_args() options.filetype = options.filetype.lower() if options.filetype == 'marc': try: file = open('%s/../MSCpath'%os.path.dirname(os.path.realpath(sys.argv[0]))) MSCpath = os.path.normpath(file.readline().strip()) file.close() except: MSCpath = '/msc' for release,subdirs in sorted(releases.items(),reverse=True): for subdir in subdirs: libPath = '%s/mentat%s/shlib/%s'%(MSCpath,release,subdir) if os.path.exists(libPath): sys.path.append(libPath) break else: continue break try: from py_post import * except: print('error: no valid Mentat release found in %s'%MSCpath) sys.exit(-1) else: def post_open(): return # --- sanity checks if files == []: parser.print_help() parser.error('no file specified...') if not os.path.exists(files[0]): parser.print_help() parser.error('invalid file "%s" specified...'%files[0]) if options.filetype not in ['marc','spectral']: parser.print_help() parser.error('file type "%s" not supported...'%options.filetype) if options.constitutiveResult and not options.phase: parser.print_help() parser.error('constitutive results require phase...') if options.nodalScalar and ( options.elementalScalar or options.elementalTensor or options.homogenizationResult or options.crystalliteResult or options.constitutiveResult ): parser.print_help() parser.error('not allowed to mix nodal with elemental results...') if not options.nodalScalar: options.nodalScalar = [] if not options.elementalScalar: options.elementalScalar = [] if not options.elementalTensor: options.elementalTensor = [] if not options.homogenizationResult: options.homogenizationResult = [] if not options.crystalliteResult: options.crystalliteResult = [] if not options.constitutiveResult: options.constitutiveResult = [] options.sort.reverse() options.separation.reverse() # --- start background messaging bg = backgroundMessage() bg.start() # --- parse .output and .t16 files filename = os.path.splitext(files[0])[0] dirname = os.path.abspath(os.path.dirname(filename))+os.sep+options.directory if not os.path.isdir(dirname): os.mkdir(dirname,0755) outputFormat = {} me = { 'Homogenization': options.homog, 'Crystallite': options.cryst, 'Constitutive': options.phase, } bg.set_message('parsing .output files...') for what in me: outputFormat[what] = ParseOutputFormat(filename, what, me[what]) if not '_id' in outputFormat[what]['specials']: print "'%s' not found in <%s>"%(me[what], what) print '\n'.join(map(lambda x:' '+x, outputFormat[what]['specials']['brothers'])) sys.exit(1) bg.set_message('opening result file...') p = OpenPostfile(filename,options.filetype) bg.set_message('parsing result file...') stat = ParsePostfile(p, filename, outputFormat) if options.filetype == 'marc': stat['NumberOfIncrements'] -= 1 # t16 contains one "virtual" increment (at 0) # --- sanity check for output variables # for mentat variables (nodalScalar,elementalScalar,elementalTensor) we simply have to check whether the label is found in the stat[indexOfLabel] dictionary # for user defined variables (homogenizationResult,crystalliteResult,constitutiveResult) we have to check the corresponding outputFormat, since the namescheme in stat['IndexOfLabel'] is different for opt in ['nodalScalar','elementalScalar','elementalTensor','homogenizationResult','crystalliteResult','constitutiveResult']: if eval('options.%s'%opt): for label in eval('options.%s'%opt): if (opt in ['nodalScalar','elementalScalar','elementalTensor'] and not label in stat['IndexOfLabel']) \ or (opt in ['homogenizationResult','crystalliteResult','constitutiveResult'] \ and (not outputFormat[opt[:-6].capitalize()]['outputs'] or not label in zip(*outputFormat[opt[:-6].capitalize()]['outputs'])[0])): parser.error('%s "%s" unknown...'%(opt,label)) # --- output info if options.info: if options.filetype == 'marc': print '\n\nMentat release %s'%release SummarizePostfile(stat,sys.stderr) print '\nUser Defined Outputs' for what in me: print '\n ',what,':' for output in outputFormat[what]['outputs']: print ' ',output sys.exit(0) # --- get output data from .t16 file increments = range(stat['NumberOfIncrements']) if options.filetype == 'marc': offset_inc = 1 else: offset_inc = 0 if options.range: options.range = list(options.range) if options.sloppy: increments = range(options.range[0],options.range[1]+1,options.range[2]) else: increments = range( max(0,options.range[0]), min(stat['NumberOfIncrements'],options.range[1]+1), options.range[2]) # --------------------------- build group membership -------------------------------- p.moveto(increments[0]+offset_inc) index = {} groups = [] groupCount = 0 memberCount = 0 if options.nodalScalar: for n in xrange(stat['NumberOfNodes']): if n%1000 == 0: bg.set_message('scan node %i...'%n) myNodeID = p.node_id(n) myNodeCoordinates = [p.node(n).x, p.node(n).y, p.node(n).z] myElemID = 0 myGrainID = 0 # --- filter valid locations filter = substituteLocation(options.filter, [myElemID,myNodeID,myGrainID], myNodeCoordinates) # generates an expression that is only true for the locations specified by options.filter if filter != '' and not eval(filter): # for all filter expressions that are not true:... continue # ... ignore this data point and continue with next # --- group data locations grp = substituteLocation('#'.join(options.separation), [myElemID,myNodeID,myGrainID], myNodeCoordinates) # generates a unique key for a group of separated data based on the separation criterium for the location if grp not in index: # create a new group if not yet present index[grp] = groupCount groups[groupCount] = [[0,0,0,0.0,0.0,0.0]] # initialize with avg location groupCount += 1 groups[index[grp]][0][:3] = mapIncremental('','unique', len(groups[index[grp]])-1, groups[index[grp]][0][:3], [myElemID,myNodeID,myGrainID]) # keep only if unique average location groups[index[grp]][0][3:] = mapIncremental('','avg', len(groups[index[grp]])-1, groups[index[grp]][0][3:], myNodeCoordinates) # incrementally update average location groups[index[grp]].append([myElemID,myNodeID,myGrainID,0]) # append a new list defining each group member memberCount += 1 else: for e in xrange(stat['NumberOfElements']): if e%1000 == 0: bg.set_message('scan elem %i...'%e) myElemID = p.element_id(e) myIpCoordinates = ipCoords(p.element(e).type, map(lambda node: [node.x, node.y, node.z], map(p.node, map(p.node_sequence,p.element(e).items)))) for n,myNodeID in enumerate(p.element(e).items): for g in range(('GrainCount' in stat['IndexOfLabel'] and int(p.element_scalar(e, stat['IndexOfLabel']['GrainCount'])[0].value)) or 1): myGrainID = g + 1 # --- filter valid locations filter = substituteLocation(options.filter, [myElemID,myNodeID,myGrainID], myIpCoordinates[n]) # generates an expression that is only true for the locations specified by options.filter if filter != '' and not eval(filter): # for all filter expressions that are not true:... continue # ... ignore this data point and continue with next # --- group data locations grp = substituteLocation('#'.join(options.separation), [myElemID,myNodeID,myGrainID], myIpCoordinates[n]) # generates a unique key for a group of separated data based on the separation criterium for the location if grp not in index: # create a new group if not yet present index[grp] = groupCount groups.append([[0,0,0,0.0,0.0,0.0]]) # initialize with avg location groupCount += 1 groups[index[grp]][0][:3] = mapIncremental('','unique', len(groups[index[grp]])-1, groups[index[grp]][0][:3], [myElemID,myNodeID,myGrainID]) # keep only if unique average location groups[index[grp]][0][3:] = mapIncremental('','avg', len(groups[index[grp]])-1, groups[index[grp]][0][3:], myIpCoordinates[n]) # incrementally update average location groups[index[grp]].append([myElemID,myNodeID,myGrainID,n]) # append a new list defining each group member memberCount += 1 # --------------------------- sort groups -------------------------------- where = { 'elem': 0, 'node': 1, 'grain': 2, 'x': 3, 'y': 4, 'z': 5, } sortProperties = [] for item in options.separation: if item not in options.sort: sortProperties.append(item) theKeys = [] for criterium in options.sort+sortProperties: if criterium in where: theKeys.append('x[0][%i]'%where[criterium]) sortKeys = eval('lambda x:(%s)'%(','.join(theKeys))) bg.set_message('sorting groups...') groups.sort(key = sortKeys) # in-place sorting to save mem fileOpen = False assembleHeader = True header = [] standard = ['inc'] + \ {True: ['time'], False:[]}[options.time] + \ ['elem','node','grain'] + \ {True: ['node.x','node.y','node.z'], False:['ip.x','ip.y','ip.z']}[options.nodalScalar != []] # --------------------------- loop over increments -------------------------------- time_start = time.time() for incCount,increment in enumerate(increments): p.moveto(increment+offset_inc) # --------------------------- file management -------------------------------- if options.separateFiles: if fileOpen: file.close() fileOpen = False outFilename = eval('"'+eval("'%%s_inc%%0%ii.txt'%(math.log10(max(increments+[1]))+1)")+'"%(dirname + os.sep + os.path.split(filename)[1],increment)') else: outFilename = '%s.txt'%(dirname + os.sep + os.path.split(filename)[1]) if not fileOpen: file = open(outFilename,'w') fileOpen = True file.write('2\theader\n') file.write('$Id$\n') headerWritten = False file.flush() # --------------------------- read and map data per group -------------------------------- member = 0 for i,group in enumerate(groups): N = 0 # group member counter for (e,n,g,n_local) in group[1:]: # loop over group members member += 1 if member%1000 == 0: time_delta = ((len(increments)*memberCount)/float(member+incCount*memberCount)-1.0)*(time.time()-time_start) bg.set_message('(%02i:%02i:%02i) processing point %i of %i from increment %i...'%(time_delta//3600,time_delta%3600//60,time_delta%60,member,memberCount,increment)) newby = [] # current member's data if options.elementalScalar: for label in options.elementalScalar: if assembleHeader: header += [label.replace(' ','')] newby.append({'label':label, 'len':1, 'content':[ p.element_scalar(p.element_sequence(e),stat['IndexOfLabel'][label])[n_local].value ]}) if options.elementalTensor: for label in options.elementalTensor: if assembleHeader: header += heading('.',[[label.replace(' ',''),component] for component in ['intensity','t11','t22','t33','t12','t23','t13']]) myTensor = p.element_tensor(p.element_sequence(e),stat['IndexOfLabel'][label])[n_local] newby.append({'label':label, 'len':length, 'content':[ myTensor.intensity, myTensor.t11, myTensor.t22, myTensor.t33, myTensor.t12, myTensor.t23, myTensor.t13, ]}) if options.homogenizationResult or \ options.crystalliteResult or \ options.constitutiveResult: for (label,resultType) in zip(options.homogenizationResult + options.crystalliteResult + options.constitutiveResult, ['Homogenization']*len(options.homogenizationResult) + ['Crystallite']*len(options.crystalliteResult) + ['Constitutive']*len(options.constitutiveResult) ): outputIndex = list(zip(*outputFormat[resultType]['outputs'])[0]).index(label) # find the position of this output in the outputFormat length = int(outputFormat[resultType]['outputs'][outputIndex][1]) if resultType == 'Homogenization': thisHead = heading('_',[[component,label] for component in range(int(length>1),length+int(length>1))]) else: thisHead = heading('_',[[g,component,label] for component in range(int(length>1),length+int(length>1))]) if assembleHeader: header += thisHead newby.append({'label':label, 'len':length, 'content':[ p.element_scalar(p.element_sequence(e),stat['IndexOfLabel'][head])[n_local].value for head in thisHead ]}) assembleHeader = False if N == 0: mappedResult = [float(x) for x in xrange(len(header))] pos = 0 for chunk in newby: mappedResult[pos:pos+chunk['len']] = mapIncremental(chunk['label'],options.func, N,mappedResult[pos:pos+chunk['len']],chunk['content']) pos += chunk['len'] N += 1 # --- write data row to file --- if not headerWritten: file.write('\t'.join(standard + header) + '\n') headerWritten = True file.write('\t'.join(map(str,[increment] + \ {True:[p.time],False:[]}[options.time] + \ group[0] + \ mappedResult) ) + '\n') if fileOpen: file.close() # --------------------------- DONE --------------------------------