DAMASK_EICMD/processing/post/rotateData.py

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#!/usr/bin/env python
# -*- coding: UTF-8 no BOM -*-
import os,sys,string
import numpy as np
from collections import defaultdict
from optparse import OptionParser
import damask
scriptID = string.replace('$Id$','\n','\\n')
scriptName = scriptID.split()[1][:-3]
# --------------------------------------------------------------------
# MAIN
# --------------------------------------------------------------------
parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [file[s]]', description = """
Uniformly scale values of scalar, vector, or tensor columns by given factor.
""", version = scriptID)
parser.add_option('-v','--vector', dest = 'vector', action = 'extend', metavar = 'string',
help = 'column heading of vector to scale')
parser.add_option('-t','--tensor', dest = 'tensor', action = 'extend', metavar = 'string',
help = 'column heading of tensor to scale')
parser.add_option('-r', '--rotation',dest = 'rotation', type = 'float', nargs = 4, metavar = ' '.join(['float']*4),
help = 'angle and axis to rotate data %default')
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(scriptID + '\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']:
key = '1_'+label
if key in table.labels:
active[datatype].append(label)
column[datatype][label] = table.labels.index(key) # remember columns of requested data
else:
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 * np.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
A = np.array(map(float,table.data[column[datatype][label]:\
column[datatype][label]+datainfo[datatype]['len']])).\
reshape(np.sqrt(datainfo[datatype]['len']),
np.sqrt(datainfo[datatype]['len']))
table.data[column[datatype][label]:\
column[datatype][label]+datainfo[datatype]['len']] = \
np.dot(R,np.dot(A,R.transpose())).reshape(datainfo[datatype]['len'])
outputAlive = table.data_write() # output processed line
# ------------------------------------------ output result -----------------------------------------
outputAlive and table.output_flush()
table.input_close() # close input ASCII table (works for stdin)
table.output_close() # close output ASCII table (works for stdout)
if file['name'] != 'STDIN':
os.rename(file['name']+'_tmp',file['name']) # overwrite old one with tmp new