183 lines
7.7 KiB
Python
Executable File
183 lines
7.7 KiB
Python
Executable File
#!/usr/bin/env python
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# -*- coding: UTF-8 no BOM -*-
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import os,sys,string,itertools,numpy,damask
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from collections import defaultdict
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from optparse import OptionParser, Option
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scriptID = '$Id$'
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scriptName = scriptID.split()[1]
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# -----------------------------
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class extendableOption(Option):
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# -----------------------------
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# used for definition of new option parser action 'extend', which enables to take multiple option arguments
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# taken from online tutorial http://docs.python.org/library/optparse.html
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ACTIONS = Option.ACTIONS + ("extend",)
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STORE_ACTIONS = Option.STORE_ACTIONS + ("extend",)
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TYPED_ACTIONS = Option.TYPED_ACTIONS + ("extend",)
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ALWAYS_TYPED_ACTIONS = Option.ALWAYS_TYPED_ACTIONS + ("extend",)
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def take_action(self, action, dest, opt, value, values, parser):
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if action == "extend":
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lvalue = value.split(",")
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values.ensure_value(dest, []).extend(lvalue)
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else:
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Option.take_action(self, action, dest, opt, value, values, parser)
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#--------------------------------------------------------------------------------------------------
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# MAIN
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#--------------------------------------------------------------------------------------------------
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synonyms = {
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'grid': ['resolution'],
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'size': ['dimension'],
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}
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identifiers = {
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'grid': ['a','b','c'],
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'size': ['x','y','z'],
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'origin': ['x','y','z'],
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}
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mappings = {
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'grid': lambda x: int(x),
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'size': lambda x: float(x),
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'origin': lambda x: float(x),
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'homogenization': lambda x: int(x),
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'microstructures': lambda x: int(x),
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}
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parser = OptionParser(option_class=extendableOption, usage='%prog options [file[s]]', description = """
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Create seed file by taking microstructure indices from given ASCIItable column.
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White and black-listing of microstructure indices is possible.
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Examples:
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--white 1,2,5 --index grainID isolates grainID entries of value 1, 2, and 5;
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--black 1 --index grainID takes all grainID entries except for value 1.
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""" + string.replace(scriptID,'\n','\\n')
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)
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parser.add_option('-p', '--positions', dest = 'pos', type = 'string',
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help = 'coordinate label')
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parser.add_option('--boundingbox', dest = 'box', type = 'float', nargs = 6,
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help = 'min (x,y,z) and max (x,y,z) to specify bounding box [auto]')
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parser.add_option('-i', '--index', dest = 'index', type = 'string',
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help = 'microstructure index label')
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parser.add_option('-w','--white', dest = 'whitelist', action = 'extend', type = 'string', \
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help = 'white list of microstructure indices', metavar = '<LIST>')
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parser.add_option('-b','--black', dest = 'blacklist', action = 'extend', type = 'string', \
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help = 'black list of microstructure indices', metavar = '<LIST>')
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parser.set_defaults(pos = 'pos')
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parser.set_defaults(index = 'microstructure')
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parser.set_defaults(box = [])
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parser.set_defaults(whitelist = [])
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parser.set_defaults(blacklist = [])
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(options,filenames) = parser.parse_args()
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datainfo = { # list of requested labels per datatype
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'scalar': {'len':1,
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'label':[]},
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'vector': {'len':3,
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'label':[]},
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}
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if options.pos != None: datainfo['vector']['label'] += [options.pos]
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if options.index != None: datainfo['scalar']['label'] += [options.index]
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options.whitelist = map(int,options.whitelist)
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options.blacklist = map(int,options.blacklist)
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#--- setup file handles --------------------------------------------------------------------------
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files = []
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if filenames == []:
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files.append({'name':'STDIN',
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'input':sys.stdin,
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'output':sys.stdout,
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'croak':sys.stderr,
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})
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else:
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for name in filenames:
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if os.path.exists(name):
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files.append({'name':name,
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'input':open(name),
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'output':open(os.path.splitext(name)[0]+'.seeds','w'),
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'croak':sys.stdout,
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})
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#--- loop over input files ------------------------------------------------------------------------
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for file in files:
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if file['name'] != 'STDIN': file['croak'].write('\033[1m'+scriptName+'\033[0m: '+file['name']+'\n')
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else: file['croak'].write('\033[1m'+scriptName+'\033[0m\n')
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theTable = damask.ASCIItable(file['input'],file['output'],buffered = False)
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theTable.head_read()
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# --------------- figure out columns to process
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active = defaultdict(list)
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column = defaultdict(dict)
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for datatype,info in datainfo.items():
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for label in info['label']:
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foundIt = False
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for key in ['1_'+label,label]:
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if key in theTable.labels:
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foundIt = True
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active[datatype].append(label)
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column[datatype][label] = theTable.labels.index(key) # remember columns of requested data
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if not foundIt:
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file['croak'].write('column %s not found...\n'%label)
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break
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# ------------------------------------------ process data ---------------------------------------
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theTable.data_readArray(list(itertools.chain.from_iterable(map(lambda x:[x+i for i in range(datainfo['vector']['len'])],
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[column['vector'][label] for label in active['vector']]))) +
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[column['scalar'][label] for label in active['scalar']])
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#--- finding bounding box ------------------------------------------------------------------------------------
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boundingBox = numpy.array((numpy.amin(theTable.data[:,0:3],axis = 0),numpy.amax(theTable.data[:,0:3],axis = 0)))
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if len(options.box) == 6:
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boundingBox[0,:] = numpy.minimum(options.box[0:3],boundingBox[0,:])
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boundingBox[1,:] = numpy.maximum(options.box[3:6],boundingBox[1,:])
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#--- rescaling coordinates ------------------------------------------------------------------------------------
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theTable.data[:,0:3] -= boundingBox[0,:]
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theTable.data[:,0:3] /= boundingBox[1,:]-boundingBox[0,:]
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#--- filtering of grain voxels ------------------------------------------------------------------------------------
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mask = numpy.logical_and(\
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numpy.ones_like(theTable.data[:,3],bool) \
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if options.whitelist == [] \
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else numpy.in1d(theTable.data[:,3].ravel(), options.whitelist).reshape(theTable.data[:,3].shape),
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numpy.ones_like(theTable.data[:,3],bool) \
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if options.blacklist == [] \
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else numpy.invert(numpy.in1d(theTable.data[:,3].ravel(), options.blacklist).reshape(theTable.data[:,3].shape))
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)
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theTable.data = theTable.data[mask]
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# ------------------------------------------ output result ---------------------------------------
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# ------------------------------------------ assemble header ---------------------------------------
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theTable.info = [
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scriptID,
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'size %s'%(' '.join(list(itertools.chain.from_iterable(zip(['x','y','z'],
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map(str,boundingBox[1,:]-boundingBox[0,:])))))),
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]
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theTable.labels_clear()
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theTable.labels_append(['x','y','z','microstructure']) # implicitly switching label processing/writing on
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theTable.head_write()
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theTable.data_writeArray()
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theTable.output_flush()
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table.input_close() # close input ASCII table
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if file['name'] != 'STDIN':
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table.output_close() # close output ASCII table
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