DAMASK_EICMD/processing/post/scaleData.py

139 lines
6.3 KiB
Python
Executable File

#!/usr/bin/env python
# -*- coding: UTF-8 no BOM -*-
import os,re,sys,math,numpy,string
import damask
from collections import defaultdict
from optparse import OptionParser, Option
scriptID = '$Id$'
scriptName = scriptID.split()[1]
# -----------------------------
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)
# --------------------------------------------------------------------
# MAIN
# --------------------------------------------------------------------
parser = OptionParser(option_class=extendableOption, usage='%prog options [file[s]]', description = """
Uniformly scale values of scalar, vector, or tensor columns by given factor.
""" + string.replace(scriptID,'\n','\\n')
)
parser.add_option('-s','--scalar', dest='scalar', action='extend', type='string',
help='column heading of scalar to scale',
metavar='<label(s)>')
parser.add_option('-v','--vector', dest='vector', action='extend', type='string',
help='column heading of vector to scale',
metavar='<label(s)>')
parser.add_option('-t','--tensor', dest='tensor', action='extend', type='string',
help='column heading of tensor to scale',
metavar='<label(s)>')
parser.add_option('-f','--factor', dest='factor', action='extend', type='string',
help='list of scalar, vector, and tensor scaling factors (in this order!)',
metavar='<float(s)>')
parser.set_defaults(scalar = [])
parser.set_defaults(vector = [])
parser.set_defaults(tensor = [])
parser.set_defaults(factor = [])
(options,filenames) = parser.parse_args()
options.factor = numpy.array(map(float,options.factor))
datainfo = { # list of requested labels per datatype
'scalar': {'len':1,
'label':[]},
'vector': {'len':3,
'label':[]},
'tensor': {'len':9,
'label':[]},
}
length = 0
if options.scalar != []: datainfo['scalar']['label'] += options.scalar; length += len(options.scalar)
if options.vector != []: datainfo['vector']['label'] += options.vector; length += len(options.vector)
if options.tensor != []: datainfo['tensor']['label'] += options.tensor; length += len(options.tensor)
if len(options.factor) != length:
parser.error('Length of scaling vector does not match column count.')
# ------------------------------------------ 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(name+'_tmp','w'), 'croak':sys.stderr})
#--- 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'],False) # make unbuffered ASCII_table
table.head_read() # read ASCII header info
table.info_append(string.replace(scriptName,'\n','\\n') + \
'\t' + ' '.join(sys.argv[1:]))
# --------------- 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)
# ------------------------------------------ assemble header ---------------------------------------
table.head_write()
# ------------------------------------------ process data ---------------------------------------
outputAlive = True
while outputAlive and table.data_read(): # read next data line of ASCII table
i = 0
for datatype,labels in sorted(active.items(),key=lambda x:datainfo[x[0]]['len']): # loop over scalar,vector,tensor
for label in labels: # loop over all requested labels
for j in xrange(datainfo[datatype]['len']): # loop over entity elements
table.data[column[datatype][label]+j] = float(table.data[column[datatype][label]+j]) * options.factor[i]
i += 1
outputAlive = table.data_write() # output processed line
# ------------------------------------------ output result ---------------------------------------
outputAlive and table.output_flush() # just in case of buffered ASCII table
if file['name'] != 'STDIN':
file['input'].close() # close input ASCII table
file['output'].close() # close output ASCII table
os.rename(file['name']+'_tmp',file['name']) # overwrite old one with tmp new