#!/usr/bin/env python
# -*- coding: UTF-8 no BOM -*-
import os,sys,string
import numpy as np
from optparse import OptionParser
import damask
scriptID = string.replace('$Id$','\n','\\n')
scriptName = os.path.splitext(scriptID.split()[1])[0]
# --------------------------------------------------------------------
# MAIN
# --------------------------------------------------------------------
parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [file[s]]', description = """
Average each data block of size 'packing' into single values thus reducing the former grid to grid/packing.
""", version = scriptID)
parser.add_option('-c','--coordinates', dest='coords', metavar='string',
help='column heading for coordinates [%default]')
parser.add_option('-p','--packing', dest='packing', type='int', nargs=3, metavar='int int int',
help='size of packed group %default')
parser.add_option('--shift', dest='shift', type='int', nargs=3, metavar='int int int',
help='shift vector of packing stencil %default')
parser.add_option('-g', '--grid', dest='grid', type='int', nargs=3, metavar='int int int',
help='grid in x,y,z [autodetect]')
parser.add_option('-s', '--size', dest='size', type='float', nargs=3, metavar='float float float',
help='size in x,y,z [autodetect]')
parser.set_defaults(coords = 'ipinitialcoord')
parser.set_defaults(packing = [2,2,2])
parser.set_defaults(shift = [0,0,0])
parser.set_defaults(grid = [0,0,0])
parser.set_defaults(size = [0.0,0.0,0.0])
(options,filenames) = parser.parse_args()
options.packing = np.array(options.packing)
options.shift = np.array(options.shift)
prefix = 'averagedDown%ix%ix%i_'%(options.packing[0],options.packing[1],options.packing[2])
if np.any(options.shift != 0):
prefix += 'shift%+i%+i%+i_'%(options.shift[0],options.shift[1],options.shift[2])
# ------------------------------------------ setup file handles ------------------------------------
files = []
for name in filenames:
if os.path.exists(name):
files.append({'name':name, 'input':open(name), 'output':open(name+'_tmp','w'), 'croak':sys.stderr})
#--- loop over input files -------------------------------------------------------------------------
for file in files:
file['croak'].write('\033[1m'+scriptName+'\033[0m: '+file['name']+'\n')
table = damask.ASCIItable(file['input'],file['output'],False) # make unbuffered ASCII_table
table.head_read() # read ASCII header info
table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:]))
# --------------- figure out size and grid ---------------------------------------------------------
try:
elemCol = table.labels.index('elem')
locationCol = table.labels.index('1_%s'%options.coords) # columns containing location data
except ValueError:
try:
locationCol = table.labels.index('%s.x'%options.coords) # columns containing location data (legacy naming scheme)
except ValueError:
file['croak'].write('no coordinate (1_%s/%s.x) and/or elem data found...\n'%(options.coords,options.coords))
continue
if (any(options.grid)==0 or any(options.size)==0.0):
coords = [{},{},{}]
while table.data_read(): # read next data line of ASCII table
for j in xrange(3):
coords[j][str(table.data[locationCol+j])] = True # remember coordinate along x,y,z
grid = np.array([len(coords[0]),\
len(coords[1]),\
len(coords[2]),],'i') # resolution is number of distinct coordinates found
size = grid/np.maximum(np.ones(3,'d'),grid-1.0)* \
np.array([max(map(float,coords[0].keys()))-min(map(float,coords[0].keys())),\
max(map(float,coords[1].keys()))-min(map(float,coords[1].keys())),\
max(map(float,coords[2].keys()))-min(map(float,coords[2].keys())),\
],'d') # size from bounding box, corrected for cell-centeredness
origin = np.array([min(map(float,coords[0].keys())),\
min(map(float,coords[1].keys())),\
min(map(float,coords[2].keys())),\
],'d') - 0.5 * size / grid
else:
grid = np.array(options.grid,'i')
size = np.array(options.size,'d')
origin = np.zeros(3,'d')
for i, res in enumerate(grid):
if res == 1:
options.packing[i] = 1
options.shift[i] = 0
mask = np.ones(3,dtype=bool)
mask[i]=0
size[i] = min(size[mask]/grid[mask]) # third spacing equal to smaller of other spacing
packing = np.array(options.packing,'i')
shift = np.array(options.shift,'i')
downSized = np.maximum(np.ones(3,'i'),grid//packing)
outSize = np.ceil(np.array(grid,'d')/np.array(packing,'d'))
# ------------------------------------------ assemble header ---------------------------------------
table.head_write()
# ------------------------------------------ process data ------------------------------------------
table.data_rewind()
data = np.zeros(outSize.tolist()+[len(table.labels)])
p = np.zeros(3,'i')
for p[2] in xrange(grid[2]):
for p[1] in xrange(grid[1]):
for p[0] in xrange(grid[0]):
d = ((p-shift)%grid)//packing
table.data_read()
data[d[0],d[1],d[2],:] += np.array(table.data_asFloat(),'d') # convert to np array
data /= packing.prod()
elementSize = size/grid*packing
posOffset = (shift+[0.5,0.5,0.5])*elementSize
elem = 1
for c in xrange(downSized[2]):
for b in xrange(downSized[1]):
for a in xrange(downSized[0]):
for i,x in enumerate([a,b,c]):
data[a,b,c,locationCol+i] = posOffset[i] + x*elementSize[i] + origin[i]
data[a,b,c,elemCol] = elem
table.data = data[a,b,c,:].tolist()
outputAlive = table.data_write() # output processed line
elem += 1
# ------------------------------------------ output result -----------------------------------------
outputAlive and table.output_flush() # just in case of buffered ASCII table
table.input_close() # close input ASCII table
table.output_close() # close output ASCII table
os.rename(file['name']+'_tmp',\
os.path.join(os.path.dirname(file['name']),prefix+os.path.basename(file['name'])))