143 lines
6.6 KiB
Python
Executable File
143 lines
6.6 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('-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('-r', '--rotation', dest = 'rotation', type = 'float', nargs = 4,
|
|
help = 'angle and axis to rotate data')
|
|
parser.add_option('-d', '--degrees', dest = 'degrees', action = 'store_true',
|
|
help = 'angles are given in degrees [%default]')
|
|
|
|
parser.set_defaults(vector = [])
|
|
parser.set_defaults(tensor = [])
|
|
parser.set_defaults(rotation = [0.,1.,1.,1.]) # no rotation about 1,1,1
|
|
parser.set_defaults(degrees = False)
|
|
|
|
(options,filenames) = parser.parse_args()
|
|
|
|
datainfo = { # list of requested labels per datatype
|
|
'vector': {'len':3,
|
|
'label':[]},
|
|
'tensor': {'len':9,
|
|
'label':[]},
|
|
}
|
|
|
|
|
|
if options.vector != []: datainfo['vector']['label'] += options.vector
|
|
if options.tensor != []: datainfo['tensor']['label'] += options.tensor
|
|
|
|
toRadians = math.pi/180.0 if options.degrees else 1.0 # rescale degrees to radians
|
|
r = damask.Quaternion().fromAngleAxis(toRadians*options.rotation[0],options.rotation[1:])
|
|
R = r.asMatrix()
|
|
|
|
# ------------------------------------------ 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
|
|
|
|
datatype = 'vector'
|
|
for label in active[datatype] if datatype in active else []: # loop over all requested labels
|
|
table.data[column[datatype][label]:column[datatype][label]+datainfo[datatype]['len']] = \
|
|
r * numpy.array(map(float,
|
|
table.data[column[datatype][label]:\
|
|
column[datatype][label]+datainfo[datatype]['len']]))
|
|
|
|
datatype = 'tensor'
|
|
for label in active[datatype] if datatype in active else []: # loop over all requested labels
|
|
table.data[column[datatype][label]:column[datatype][label]+column[datatype]['len']] = \
|
|
(numpy.array(map(float,
|
|
table.data[column[datatype][label]:\
|
|
column[datatype][label]+column[datatype]['len']])).reshape(numpy.sqrt(datainfo[datatype]['len']),\
|
|
numpy.sqrt(datainfo[datatype]['len'])) * R).reshape(datainfo[datatype]['len'])
|
|
|
|
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
|