#!/usr/bin/env python import os,re,sys,math,string,numpy,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) def location(idx,res): return ( idx % res[0], \ ( idx // res[0]) % res[1], \ ( idx // res[0] // res[1]) % res[2] ) def index(location,res): return ( location[0] % res[0] + \ ( location[1] % res[1]) * res[0] + \ ( location[2] % res[2]) * res[1] * res[0] ) # -------------------------------------------------------------------- # MAIN # -------------------------------------------------------------------- parser = OptionParser(option_class=extendableOption, usage='%prog options [file[s]]', description = """ Add column(s) containing deformed configuration of requested column(s). Operates on periodic ordered three-dimensional data sets. """ + string.replace('$Id$','\n','\\n') ) parser.add_option('-c','--coordinates', dest='coords', type='string',\ help='column heading for coordinates [%default]') parser.add_option('-d','--defgrad', dest='defgrad', type='string', \ help='heading of columns containing tensor field values') parser.add_option('-l', '--linear', dest='linearreconstruction', action='store_true',\ help='use linear reconstruction of geometry [%default]') parser.set_defaults(coords = 'ip') parser.set_defaults(defgrad = 'f' ) parser.set_defaults(linearreconstruction = False) (options,filenames) = parser.parse_args() # ------------------------------------------ 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:])) # --------------- figure out dimension and resolution try: locationCol = table.labels.index('%s.x'%options.coords) # columns containing location data except ValueError: print 'no coordinate data found...' continue grid = [{},{},{}] while table.data_read(): # read next data line of ASCII table if str(table.data[locationCol+1]) in grid[1] and len(grid[1])>1: # geomdim[1] and res[1] already figured out, skip layers table.data_skipLines(len(grid[1])*len(grid[0])-1) else: if str(table.data[locationCol]) in grid[0]: # geomdim[0] and res[0] already figured out, skip lines table.data_skipLines(len(grid[0])-1) for j in xrange(3): grid[j][str(table.data[locationCol+j])] = True # remember coordinate along x,y,z res = numpy.array([len(grid[0]),\ len(grid[1]),\ len(grid[2]),],'i') # resolution is number of distinct coordinates found geomdim = res/numpy.maximum(numpy.ones(3,'d'),res-1.0)* \ numpy.array([max(map(float,grid[0].keys()))-min(map(float,grid[0].keys())),\ max(map(float,grid[1].keys()))-min(map(float,grid[1].keys())),\ max(map(float,grid[2].keys()))-min(map(float,grid[2].keys())),\ ],'d') # dimension from bounding box, corrected for cell-centeredness if res[2] == 1: geomdim[2] = min(geomdim[:2]/res[:2]) N = res.prod() print '\t%s @ %s'%(geomdim,res) # --------------- figure out columns to process key = '1_%s' %options.defgrad if key not in table.labels: sys.stderr.write('column %s not found...\n'%key) else: defgrad = numpy.array([0.0 for i in xrange(N*9)]).reshape(list(res)+[3,3]) table.labels_append(['ip_deformed.%s'%(coord) for coord in 'x','y','z']) # extend ASCII header with new labels column = table.labels.index(key) # ------------------------------------------ assemble header --------------------------------------- table.head_write() # ------------------------------------------ read value field --------------------------------------- table.data_rewind() idx = 0 while table.data_read(): # read next data line of ASCII table (x,y,z) = location(idx,res) # figure out (x,y,z) position from line count idx += 1 defgrad[x,y,z] = numpy.array(map(float,table.data[column:column+9]),'d').reshape(3,3) # ------------------------------------------ process value field ---------------------------- defgrad_av = damask.core.math.tensorAvg(defgrad) if options.linearreconstruction: centroids = damask.core.mesh.deformed_fft(res,geomdim,defgrad_av,1.0,defgrad) else: centroids = damask.core.mesh.deformed_fft(res,geomdim,defgrad_av,1.0,defgrad) # ------------------------------------------ process data --------------------------------------- table.data_rewind() idx = 0 while table.data_read(): # read next data line of ASCII table (x,y,z) = location(idx,res) # figure out (x,y,z) position from line count idx += 1 table.data_append(list(centroids[x,y,z])) 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