DAMASK_EICMD/processing/pre/seeds_fromTable.py

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#!/usr/bin/env python
# -*- coding: UTF-8 no BOM -*-
import os,sys,string,itertools
import numpy as np
from optparse import OptionParser
from collections import defaultdict
import damask
scriptID = string.replace('$Id$','\n','\\n')
scriptName = scriptID.split()[1][:-3]
#--------------------------------------------------------------------------------------------------
# MAIN
#--------------------------------------------------------------------------------------------------
synonyms = {
'grid': ['resolution'],
'size': ['dimension'],
}
identifiers = {
'grid': ['a','b','c'],
'size': ['x','y','z'],
'origin': ['x','y','z'],
}
mappings = {
'grid': lambda x: int(x),
'size': lambda x: float(x),
'origin': lambda x: float(x),
'homogenization': lambda x: int(x),
'microstructures': lambda x: int(x),
}
parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [file[s]]', description = """
Create seed file by taking microstructure indices from given ASCIItable column.
White and black-listing of microstructure indices is possible.
Examples:
--white 1,2,5 --index grainID isolates grainID entries of value 1, 2, and 5;
--black 1 --index grainID takes all grainID entries except for value 1.
""", version = scriptID)
parser.add_option('-p', '--positions', dest = 'pos', type = 'string',
help = 'coordinate label')
parser.add_option('--boundingbox', dest = 'box', type = 'float', nargs = 6,
help = 'min (x,y,z) and max (x,y,z) to specify bounding box [auto]')
parser.add_option('-i', '--index', dest = 'index', type = 'string',
help = 'microstructure index label')
parser.add_option('-w','--white', dest = 'whitelist', action = 'extend', type = 'string', \
help = 'white list of microstructure indices', metavar = '<LIST>')
parser.add_option('-b','--black', dest = 'blacklist', action = 'extend', type = 'string', \
help = 'black list of microstructure indices', metavar = '<LIST>')
parser.set_defaults(pos = 'pos')
parser.set_defaults(index = 'microstructure')
parser.set_defaults(box = ())
parser.set_defaults(whitelist = [])
parser.set_defaults(blacklist = [])
(options,filenames) = parser.parse_args()
datainfo = { # list of requested labels per datatype
'scalar': {'len':1,
'label':[]},
'vector': {'len':3,
'label':[]},
}
if options.pos != None: datainfo['vector']['label'] += [options.pos]
if options.index != None: datainfo['scalar']['label'] += [options.index]
options.whitelist = map(int,options.whitelist)
options.blacklist = map(int,options.blacklist)
#--- 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(os.path.splitext(name)[0]+'.seeds','w'),
'croak':sys.stdout,
})
#--- 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'],buffered = False)
table.head_read()
# --------------- 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)
break
# ------------------------------------------ process data ---------------------------------------
table.data_readArray(list(itertools.chain.from_iterable(map(lambda x:[x+i for i in range(datainfo['vector']['len'])],
[column['vector'][label] for label in active['vector']]))) +
[column['scalar'][label] for label in active['scalar']])
#--- finding bounding box ------------------------------------------------------------------------------------
boundingBox = np.array((np.amin(table.data[:,0:3],axis = 0),np.amax(table.data[:,0:3],axis = 0)))
if len(options.box) == 6:
boundingBox[0,:] = np.minimum(options.box[0:3],boundingBox[0,:])
boundingBox[1,:] = np.maximum(options.box[3:6],boundingBox[1,:])
#--- rescaling coordinates ------------------------------------------------------------------------------------
table.data[:,0:3] -= boundingBox[0,:]
table.data[:,0:3] /= boundingBox[1,:]-boundingBox[0,:]
#--- filtering of grain voxels ------------------------------------------------------------------------------------
mask = np.logical_and(\
np.ones_like(table.data[:,3],bool) \
if options.whitelist == [] \
else np.in1d(table.data[:,3].ravel(), options.whitelist).reshape(table.data[:,3].shape),
np.ones_like(table.data[:,3],bool) \
if options.blacklist == [] \
else np.invert(np.in1d(table.data[:,3].ravel(), options.blacklist).reshape(table.data[:,3].shape))
)
table.data = table.data[mask]
# ------------------------------------------ output result ---------------------------------------
# ------------------------------------------ assemble header ---------------------------------------
table.info = [
scriptID,
'size %s'%(' '.join(list(itertools.chain.from_iterable(zip(['x','y','z'],
map(str,boundingBox[1,:]-boundingBox[0,:])))))),
]
table.labels_clear()
table.labels_append(['x','y','z','microstructure']) # implicitly switching label processing/writing on
table.head_write()
table.data_writeArray()
table.output_flush()
table.input_close() # close input ASCII table
if file['name'] != 'STDIN':
table.output_close() # close output ASCII table