#!/usr/bin/env python import os,re,sys,math,string,numpy,damask,time 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 numpy.array([ 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[0] * res[1] ) # -------------------------------------------------------------------- # MAIN # -------------------------------------------------------------------- parser = OptionParser(option_class=extendableOption, usage='%prog [options] [file[s]]', description = """ Blows up each value to a surrounding data block of size 'packing' thus increasing the former resolution to resolution*packing. (Requires numpy.) """ + string.replace('$Id: averageDown.py 1857 2012-10-31 10:06:11Z MPIE\m.diehl $','\n','\\n') ) parser.add_option('-c','--coordinates', dest='coords', type='string',\ help='column heading for coordinates [%default]') parser.add_option('-p','--packing', dest='packing', type='int', nargs=3, \ help='dimension of packed group %default') parser.add_option('-r','--resolution', dest='resolution', type='int', nargs=3, \ help='resolution in x,y,z [autodetect]') parser.add_option('-d','--dimension', dest='dimension', type='float', nargs=3, \ help='dimension in x,y,z [autodetect]') parser.set_defaults(coords = 'ip') parser.set_defaults(packing = [2,2,2]) parser.set_defaults(resolution = [0,0,0]) parser.set_defaults(dimension = [0.0,0.0,0.0]) (options,filenames) = parser.parse_args() if len(options.packing) < 3: parser.error('packing needs three parameters...') options.packing = numpy.array(options.packing) prefix = 'blowUp%ix%ix%i_'%(options.packing[0],options.packing[1],options.packing[2]) # ------------------------------------------ setup file handles --------------------------------------- files = [] if filenames == []: files.append({'name':'STDIN', 'input':sys.stdin, 'output':sys.stdout}) else: for name in filenames: name = os.path.relpath(name) if os.path.exists(name): files.append({'name':name, 'input':open(name), 'output':open(os.path.join(os.path.dirname(name),prefix+os.path.basename(name)),'w')}) # ------------------------------------------ loop over input files --------------------------------------- for file in files: if file['name'] != 'STDIN': print file['name'], table = damask.ASCIItable(file['input'],file['output'],False) # make unbuffered ASCII_table table.head_read() # read ASCII header info table.info_append(string.replace('$Id: averageDown.py 1857 2012-10-31 10:06:11Z MPIE\m.diehl $','\n','\\n') + \ '\t' + ' '.join(sys.argv[1:])) try: locationCol = table.labels.index('%s.x'%options.coords) # columns containing location data elemCol = table.labels.index('elem') # columns containing location data except ValueError: print 'no coordinate data or element data found...' continue if (any(options.resolution)==0 or any(options.dimension)==0.0): grid = [{},{},{}] while table.data_read(): # read next data line of ASCII table for j in xrange(3): grid[j][str(table.data[locationCol+j])] = True # remember coordinate along x,y,z resolution = numpy.array([len(grid[0]),\ len(grid[1]),\ len(grid[2]),],'i') # resolution is number of distinct coordinates found dimension = resolution/numpy.maximum(numpy.ones(3,'d'),resolution-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 else: resolution = numpy.array(options.resolution,'i') dimension = numpy.array(options.dimension,'d') if resolution[2] == 1: options.packing[2] = 1 dimension[2] = min(dimension[:2]/resolution[:2]) # z spacing equal to smaller of x or y spacing packing = numpy.array(options.packing,'i') outSize = resolution*packing print '\t%s @ %s --> %s'%(dimension,resolution,outSize) # ------------------------------------------ assemble header --------------------------------------- table.head_write() # ------------------------------------------ process data --------------------------------------- table.data_rewind() data = numpy.zeros(outSize.tolist()+[len(table.labels)]) p = numpy.zeros(3,'i') for p[2] in xrange(resolution[2]): for p[1] in xrange(resolution[1]): for p[0] in xrange(resolution[0]): d = p*packing table.data_read() data[d[0]:d[0]+packing[0], d[1]:d[1]+packing[1], d[2]:d[2]+packing[2], : ] = numpy.tile(numpy.array(table.data_asFloat(),'d'),packing.tolist()+[1]) # tile to match blowUp voxel size elementSize = dimension/resolution/packing elem = 1 for c in xrange(outSize[2]): for b in xrange(outSize[1]): for a in xrange(outSize[0]): data[a,b,c,locationCol:locationCol+3] = [a+0.5,b+0.5,c+0.5]*elementSize data[a,b,c,elemCol] = elem table.data = data[a,b,c,:].tolist() table.data_write() # output processed line elem += 1 # ------------------------------------------ output result --------------------------------------- table.output_flush() # just in case of buffered ASCII table # ------------------------------------------ close file handles --------------------------------------- for file in files: file['input'].close() # close input ASCII table if file['name'] != 'STDIN': file['output'].close() # close output ASCII table