DAMASK_EICMD/processing/post/addNorm.py

155 lines
6.5 KiB
Python
Executable File

#!/usr/bin/env python
# -*- coding: UTF-8 no BOM -*-
import os,re,sys,math,string,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)
# definition of element-wise p-norms for matrices
# p = 1
def normAbs(object):
return sum(map(abs, object))
# p = 2
def normFrobenius(object):
return math.sqrt(sum([x*x for x in object]))
# p = infinity
def normMax(object):
return max(map(abs, object))
# --------------------------------------------------------------------
# MAIN
# --------------------------------------------------------------------
parser = OptionParser(option_class=extendableOption, usage='%prog options [file[s]]', description = """
Add column(s) containing norm of requested column(s) being either vectors or tensors.
""" + string.replace(scriptID,'\n','\\n')
)
normChoices = ['abs','frobenius','max']
parser.add_option('-n','--norm', dest='norm', action='store', type='choice', choices=normChoices, \
help='type of element-wise p-norm (%s) [2]'%(','.join(map(str,normChoices))))
parser.add_option('-v','--vector', dest='vector', action='extend', type='string', \
help='heading of columns containing vector field values')
parser.add_option('-t','--tensor', dest='tensor', action='extend', type='string', \
help='heading of columns containing tensor field values')
parser.add_option('-s','--special', dest='special', action='extend', type='string', \
help='heading of columns containing field values of special dimension')
parser.add_option('-d','--dimension', dest='N', action='store', type='int', \
help='dimension of special field values [%default]')
parser.set_defaults(norm = 'frobenius')
parser.set_defaults(vector = [])
parser.set_defaults(tensor = [])
parser.set_defaults(special = [])
parser.set_defaults(N = 12)
(options,filenames) = parser.parse_args()
if len(options.vector) + len(options.tensor) + len(options.special)== 0:
parser.error('no data column specified...')
datainfo = { # list of requested labels per datatype
'vector': {'len':3,
'label':[]},
'tensor': {'len':9,
'label':[]},
'special': {'len':options.N,
'label':[]},
}
if options.vector != None: datainfo['vector']['label'] += options.vector
if options.tensor != None: datainfo['tensor']['label'] += options.tensor
if options.special != None: datainfo['special']['label'] += options.special
# ------------------------------------------ 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(scriptID,'\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
table.labels_append('norm%s(%s)'%(options.norm.capitalize(),label)) # extend ASCII header with new labels
if not foundIt:
file['croak'].write('column %s not found...\n'%label)
break
# ------------------------------------------ assemble header ---------------------------------------
table.head_write()
# ------------------------------------------ process data ---------------------------------------
outputAlive = True
while outputAlive and table.data_read(): # read next data line of ASCII table
for datatype,labels in active.items(): # loop over vector,tensor
for label in labels: # loop over all requested norms
eval("table.data_append(norm%s(map(float,table.data[column[datatype][label]:column[datatype][label]+datainfo[datatype]['len']])))"%options.norm.capitalize())
outputAlive = table.data_write() # output processed line
# ------------------------------------------ output result ---------------------------------------
outputAlive and table.output_flush() # just in case of buffered ASCII table
file['input'].close() # close input ASCII table
if file['name'] != 'STDIN':
file['output'].close() # close output ASCII table
os.rename(file['name']+'_tmp',file['name']) # overwrite old one with tmp new