DAMASK_EICMD/processing/post/addNorm.py

148 lines
6.3 KiB
Python
Raw Normal View History

#!/usr/bin/python
2011-12-15 14:23:18 +05:30
import os,re,sys,math,string,damask
from optparse import OptionParser, Option
# -----------------------------
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 absnorm(object):
return sum(map(abs, object))
# p = 2
def frobeniusnorm(object):
return math.sqrt(sum([x*x for x in object]))
# p = infinity
def maxnorm(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.
2011-08-18 13:30:19 +05:30
""" + string.replace('$Id$','\n','\\n')
)
parser.add_option('-n','--norm', dest='norm', action='store', type='choice', choices=('absnorm','frobeniusnorm','maxnorm'), \
help='used p-norm, choose either absnorm, frobeniusnorm, or maxnorm [DEFAULT=%default]')
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','--slipsystem ', dest='slipsystem', action='extend', type='string', \
help='heading of columns containing values per slipsystem')
parser.add_option('-i','--nslipsystems',dest='Nslipsystems', action='store', type='int', \
help='number of slip systems [DEFAULT=%default]')
parser.set_defaults(norm = 'frobeniusnorm')
parser.set_defaults(vector = [])
parser.set_defaults(tensor = [])
parser.set_defaults(slipsystem = [])
parser.set_defaults(Nslipsystems = 12)
(options,filenames) = parser.parse_args()
if len(options.vector) + len(options.tensor) + len(options.slipsystem)== 0:
parser.error('no data column specified...')
datainfo = { # list of requested labels per datatype
'vector': {'len':3,
'label':[]},
'tensor': {'len':9,
'label':[]},
'slipsystem': {'len':options.Nslipsystems,
'label':[]},
}
if options.vector != None: datainfo['vector']['label'] += options.vector
if options.tensor != None: datainfo['tensor']['label'] += options.tensor
if options.slipsystem != None:datainfo['slipsystem']['label'] += options.slipsystem
# ------------------------------------------ setup file handles ---------------------------------------
files = []
if filenames == []:
files.append({'name':'STDIN', 'input':sys.stdin, 'output':sys.stdout})
else:
for name in filenames:
if os.path.exists(name):
files.append({'name':name, 'input':open(name), 'output':open(name+'_tmp','w')})
# ------------------------------------------ loop over input files ---------------------------------------
for file in files:
if file['name'] != 'STDIN': print file['name']
2011-12-15 14:23:18 +05:30
table = damask.ASCIItable(file['input'],file['output'],False) # make unbuffered ASCII_table
table.head_read() # read ASCII header info
table.info_append(string.replace('$Id$','\n','\\n') + \
'\t' + ' '.join(sys.argv[1:]))
active = {}
column = {}
head = []
for datatype,info in datainfo.items():
for label in info['label']:
key = {True :'1_%s',
False:'%s' }[info['len']>1]%label
if key not in table.labels:
sys.stderr.write('column %s not found...\n'%key)
else:
if datatype not in active: active[datatype] = []
if datatype not in column: column[datatype] = {}
active[datatype].append(label)
column[datatype][label] = table.labels.index(key) # remember columns of requested data
table.labels_append('%s(%s)'%(options.norm,label)) # extend ASCII header with new labels
# ------------------------------------------ assemble header ---------------------------------------
table.head_write()
# ------------------------------------------ process data ---------------------------------------
while 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(%s(map(float,table.data[column[datatype][label]:column[datatype][label]+datainfo[datatype]['len']])))"%options.norm)
table.data_write() # output processed line
# ------------------------------------------ output result ---------------------------------------
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