DAMASK_EICMD/processing/post/averageDown

149 lines
5.3 KiB
Python
Executable File

#!/usr/bin/python
import os,re,sys,math,string,numpy
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 = """
Average each data block of size 'packing' into single values thus reducing the former resolution
to resolution/packing. (Requires numpy.)
$Id: averageDown 266 2011-05-29 19:38:42Z MPIE\p.eisenlohr $
""")
parser.add_option('-m','--memory', dest='memory', action='store_true', \
help='load complete file into memory [%default]')
parser.add_option('-r','--resolution', dest='res', type='int', nargs=3, \
help='resolution in fast, medium, and slow dimension [%default]')
parser.add_option('-p','--packing', dest='packing', type='int', nargs=3, \
help='number of data points to average down in each dimension [%default]')
parser.set_defaults(memory = False)
parser.set_defaults(resolution = [32,32,32])
parser.set_defaults(packing = [2,2,2])
(options,filenames) = parser.parse_args()
if len(options.resolution) < 3:
parser.error('resolution needs three parameters...')
if len(options.packing) < 3:
parser.error('packing needs three parameters...')
options.packing = numpy.array(options.packing)
# ------------------------------------------ setup file handles ---------------------------------------
files = []
if filenames == []:
files.append({'name':'STDIN', 'input':sys.stdin, 'output':sys.stdout})
else:
for name in filenames:
if os.path.exists(name):
(head,tail) = os.path.split(name)
files.append({'name':name, 'input':open(name), 'output':open(os.path.join(head,'avgDown_%s'%tail),'w')})
# ------------------------------------------ loop over input files ---------------------------------------
for file in files:
print file['name']
# get labels by either read the first row, or - if keyword header is present - the last line of the header
firstline = file['input'].readline()
m = re.search('(\d+)\s*head', firstline.lower())
if m:
headerlines = int(m.group(1))
passOn = [file['input'].readline() for i in range(1,headerlines)]
headers = file['input'].readline().split()
else:
headerlines = 1
passOn = []
headers = firstline.split()
if options.memory:
data = file['input'].readlines()
else:
data = []
# ------------------------------------------ assemble header ---------------------------------------
output = '%i\theader'%(headerlines+1) + '\n' + \
''.join(passOn) + \
string.replace('$Id: averageDown 266 2011-05-29 19:38:42Z MPIE\p.eisenlohr $','\n','\\n')+ '\t' + \
' '.join(sys.argv[1:]) + '\n' + \
'\t'.join(headers) + '\n' # build extended header
if not options.memory:
file['output'].write(output)
output = ''
# ------------------------------------------ read file ---------------------------------------
averagedDown = numpy.zeros([options.res[2]/options.packing[2],
options.res[1]/options.packing[1],
options.res[0]/options.packing[0],
len(headers)])
idx = 0
for line in {True : data,
False : file['input']}[options.memory]:
items = numpy.array(map(float,line.split()[:len(headers)]))
if len(items) < len(headers):
continue
loc = location(idx,options.res)//options.packing
averagedDown[loc[2],loc[1],loc[0],:] += items
idx += 1
averagedDown /= options.packing[0]*options.packing[1]*options.packing[2]
for z in range(options.res[2]/options.packing[2]):
for y in range(options.res[1]/options.packing[1]):
for x in range(options.res[0]/options.packing[0]):
output += '\t'.join(map(str,averagedDown[z,y,x,:])) + '\n'
file['input'].close()
# ------------------------------------------ output result ---------------------------------------
file['output'].write(output)
if file['name'] != 'STDIN':
file['output'].close