DAMASK_EICMD/processing/pre/seeds_fromGeom.py

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#!/usr/bin/env python
# -*- coding: UTF-8 no BOM -*-
import os,sys,string
import numpy as np
from optparse import OptionParser
import damask
scriptName = os.path.splitext(os.path.basename(__file__))[0]
scriptID = ' '.join([scriptName,damask.version])
#--------------------------------------------------------------------------------------------------
# MAIN
#--------------------------------------------------------------------------------------------------
parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [file[s]]', description = """
Create seed file taking microstructure indices from given geom file but excluding black-listed grains.
""", version = scriptID)
parser.add_option('-w','--white',
action = 'extend', metavar='<int LIST>',
dest = 'whitelist',
help = 'whitelist of grain IDs')
parser.add_option('-b','--black',
action = 'extend', metavar='<int LIST>',
dest = 'blacklist',
help = 'blacklist of grain IDs')
parser.add_option('-p','--position',
dest = 'position',
type = 'string', metavar = 'string',
help = 'column label for coordinates [%default]')
parser.set_defaults(whitelist = [],
blacklist = [],
position = 'pos',
)
(options,filenames) = parser.parse_args()
options.whitelist = map(int,options.whitelist)
options.blacklist = map(int,options.blacklist)
# --- loop over output files -------------------------------------------------------------------------
if filenames == []: filenames = [None]
for name in filenames:
try:
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table = damask.ASCIItable(name = name,
outname = os.path.splitext(name)[0]+'.seeds' if name else name,
buffered = False, labeled = False)
except:
continue
damask.util.report(scriptName,name)
# --- interpret header ----------------------------------------------------------------------------
table.head_read()
info,extra_header = table.head_getGeom()
damask.util.croak(['grid a b c: %s'%(' x '.join(map(str,info['grid']))),
'size x y z: %s'%(' x '.join(map(str,info['size']))),
'origin x y z: %s'%(' : '.join(map(str,info['origin']))),
'homogenization: %i'%info['homogenization'],
'microstructures: %i'%info['microstructures'],
])
errors = []
if np.any(info['grid'] < 1): errors.append('invalid grid a b c.')
if np.any(info['size'] <= 0.0): errors.append('invalid size x y z.')
if errors != []:
damask.util.croak(errors)
table.close(dismiss = True)
continue
# --- read data ------------------------------------------------------------------------------------
microstructure = table.microstructure_read(info['grid']) # read (linear) microstructure
# --- generate grid --------------------------------------------------------------------------------
x = (0.5 + np.arange(info['grid'][0],dtype=float))/info['grid'][0]*info['size'][0]+info['origin'][0]
y = (0.5 + np.arange(info['grid'][1],dtype=float))/info['grid'][1]*info['size'][1]+info['origin'][1]
z = (0.5 + np.arange(info['grid'][2],dtype=float))/info['grid'][2]*info['size'][2]+info['origin'][2]
xx = np.tile( x, info['grid'][1]* info['grid'][2])
yy = np.tile(np.repeat(y,info['grid'][0] ),info['grid'][2])
zz = np.repeat(z,info['grid'][0]*info['grid'][1])
mask = np.logical_and(np.in1d(microstructure,options.whitelist,invert=False) if options.whitelist != [] else np.full_like(microstructure,True,dtype=bool),
np.in1d(microstructure,options.blacklist,invert=True ) if options.blacklist != [] else np.full_like(microstructure,True,dtype=bool))
# ------------------------------------------ assemble header ---------------------------------------
table.info_clear()
table.info_append(extra_header+[
scriptID + ' ' + ' '.join(sys.argv[1:]),
"grid\ta {grid[0]}\tb {grid[1]}\tc {grid[2]}".format(grid=info['grid']),
"size\tx {size[0]}\ty {size[1]}\tz {size[2]}".format(size=info['size']),
"origin\tx {origin[0]}\ty {origin[1]}\tz {origin[2]}".format(origin=info['origin']),
"homogenization\t{homog}".format(homog=info['homogenization']),
"microstructures\t{microstructures}".format(microstructures=info['microstructures']),
])
table.labels_clear()
table.labels_append(['{dim}_{label}'.format(dim = 1+i,label = options.position) for i in range(3)]+['microstructure'])
table.head_write()
table.output_flush()
# --- write seeds information ------------------------------------------------------------
table.data = np.squeeze(np.dstack((xx,yy,zz,microstructure)))[mask]
table.data_writeArray()
# ------------------------------------------ finalize output ---------------------------------------
table.close()