DAMASK_EICMD/processing/post/rotateData.py

#!/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='int int int int',
                                    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
      table.data[column[datatype][label]:column[datatype][label]+datainfo[datatype]['len']] = \
         (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'])) * R).reshape(datainfo[datatype]['len'])
    outputAlive = table.data_write()                                                                # output processed line

# ------------------------------------------ output result -----------------------------------------
  outputAlive and table.output_flush() 

  file['input'].close()                                                                             # close input ASCII table (works for stdin)
  file['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