some further improvements on ASCII table handling
This commit is contained in:
Martin Diehl
parent
0252fea3d7
commit
e7c282a02d
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@ -67,7 +67,7 @@ for file in files:
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for label,formula in zip(options.labels,options.formulas):
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interpolator = []
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for column in re.findall(r'#(.+?)#',formula): # loop over column labels in formula
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for column in re.findall(r'#(.+?)#',formula): # loop over column labels in formula
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formula = formula.replace('#'+column+'#','%f')
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if column in specials:
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interpolator += ['specials["%s"]'%column]
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@ -87,7 +87,7 @@ for file in files:
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if label not in brokenFormula:
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evaluator[label] = "'" + formula + "'%(" + ','.join(interpolator) + ")"
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# ------------------------------------------ calculate one result to get length of labels ------
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# ------------------------------------------ calculate one result to get length of labels ---------
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table.data_read()
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labelLen = {}
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for label in options.labels:
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@ -102,23 +102,20 @@ for file in files:
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table.labels_append(label)
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else:
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table.labels_append(['%i_%s'%(i+1,label) for i in xrange(labelLen[label])])
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table.head_write()
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# ------------------------------------------ process data ---------------------------------------
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outputAlive = True
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table.data_rewind()
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while outputAlive and table.data_read(): # read next data line of ASCII table
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specials['_row_'] += 1 # count row
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while outputAlive and table.data_read(): # read next data line of ASCII table
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specials['_row_'] += 1 # count row
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for label in options.labels: table.data_append(unravel(eval(eval(evaluator[label]))))
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outputAlive = table.data_write() # output processed line
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outputAlive = table.data_write() # output processed line
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# ------------------------------------------ output result ---------------------------------------
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outputAlive and table.output_flush() # just in case of buffered ASCII table
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outputAlive and table.output_flush() # just in case of buffered ASCII table
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file['input'].close() # close input ASCII table
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file['input'].close() # close input ASCII table (works for stdin)
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file['output'].close() # close output ASCII table (works for stdout)
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if file['name'] != 'STDIN':
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file['output'].close() # close output ASCII table
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os.rename(file['name']+'_tmp',file['name']) # overwrite old one with tmp new
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os.rename(file['name']+'_tmp',file['name']) # overwrite old one with tmp new
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@ -1,7 +1,8 @@
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#!/usr/bin/env python
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# -*- coding: UTF-8 no BOM -*-
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import os,re,sys,math,numpy,string
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import os,re,sys,math,string
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import numpy as np
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from collections import defaultdict
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from optparse import OptionParser
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import damask
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@ -24,7 +25,6 @@ parser.add_option('-f','--defgrad', dest='defgrad', type='string', metavar='
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help='heading of columns containing deformation gradient [%default]')
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parser.add_option('-p','--stress', dest='stress', type='string', metavar='string', \
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help='heading of columns containing first Piola--Kirchhoff stress [%default]')
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parser.set_defaults(defgrad = 'f')
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parser.set_defaults(stress = 'p')
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@ -33,7 +33,7 @@ parser.set_defaults(stress = 'p')
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if options.defgrad == None or options.stress == None:
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parser.error('missing data column...')
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datainfo = { # list of requested labels per datatype
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datainfo = { # list of requested labels per datatype
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'defgrad': {'mandatory': True,
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'len':9,
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'label':[]},
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@ -46,7 +46,6 @@ datainfo = { # lis
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datainfo['defgrad']['label'].append(options.defgrad)
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datainfo['stress']['label'].append(options.stress)
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# ------------------------------------------ setup file handles ---------------------------------------
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files = []
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if filenames == []:
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@ -61,8 +60,8 @@ for file in files:
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if file['name'] != 'STDIN': file['croak'].write('\033[1m'+scriptName+'\033[0m: '+file['name']+'\n')
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else: file['croak'].write('\033[1m'+scriptName+'\033[0m\n')
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table = damask.ASCIItable(file['input'],file['output'],False) # make unbuffered ASCII_table
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table.head_read() # read ASCII header info
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table = damask.ASCIItable(file['input'],file['output'],False) # make unbuffered ASCII_table
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table.head_read() # read ASCII header info
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table.info_append(string.replace(scriptID,'\n','\\n') + '\t' + ' '.join(sys.argv[1:]))
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active = defaultdict(list)
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@ -75,36 +74,34 @@ for file in files:
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False:'%s' }[info['len']>1]%label
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if key not in table.labels:
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file['croak'].write('column %s not found...\n'%key)
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missingColumns |= info['mandatory'] # break if label is mandatory
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missingColumns |= info['mandatory'] # break if label is mandatory
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else:
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active[datatype].append(label)
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column[datatype][label] = table.labels.index(key) # remember columns of requested data
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column[datatype][label] = table.labels.index(key) # remember columns of requested data
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if missingColumns:
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continue
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# ------------------------------------------ assemble header ---------------------------------------
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table.labels_append(['%i_Cauchy'%(i+1)
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for i in xrange(datainfo['stress']['len'])]) # extend ASCII header with new labels
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# ------------------------------------------ assemble header ---------------------------------------
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for i in xrange(datainfo['stress']['len'])]) # extend ASCII header with new labels
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table.head_write()
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# ------------------------------------------ process data ---------------------------------------
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outputAlive = True
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while outputAlive and table.data_read(): # read next data line of ASCII table
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table.data_rewind()
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while outputAlive and table.data_read(): # read next data line of ASCII table
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F = np.array(map(float,table.data[column['defgrad'][active['defgrad'][0]]:
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column['defgrad'][active['defgrad'][0]]+datainfo['defgrad']['len']]),'d').reshape(3,3)
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P = np.array(map(float,table.data[column['stress'][active['stress'][0]]:
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column['stress'][active['stress'][0]]+datainfo['stress']['len']]),'d').reshape(3,3)
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F = numpy.array(map(float,table.data[column['defgrad'][active['defgrad'][0]]:
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column['defgrad'][active['defgrad'][0]]+datainfo['defgrad']['len']]),'d').reshape(3,3)
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P = numpy.array(map(float,table.data[column['stress'][active['stress'][0]]:
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column['stress'][active['stress'][0]]+datainfo['stress']['len']]),'d').reshape(3,3)
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table.data_append(list(1.0/numpy.linalg.det(F)*numpy.dot(P,F.T).reshape(9))) # [Cauchy] = (1/det(F)) * [P].[F_transpose]
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outputAlive = table.data_write() # output processed line
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table.data_append(list(1.0/np.linalg.det(F)*np.dot(P,F.T).reshape(9))) # [Cauchy] = (1/det(F)) * [P].[F_transpose]
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outputAlive = table.data_write() # output processed line
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# ------------------------------------------ output result ---------------------------------------
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table.output_flush() # just in case of buffered ASCII table
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outputAlive and table.output_flush() # just in case of buffered ASCII table
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file['input'].close() # close input ASCII table
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file['input'].close() # close input ASCII table (works for stdin)
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file['output'].close() # close output ASCII table (works for stdout)
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if file['name'] != 'STDIN':
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file['output'].close() # close output ASCII table
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os.rename(file['name']+'_tmp',file['name']) # overwrite old one with tmp new
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os.rename(file['name']+'_tmp',file['name']) # overwrite old one with tmp new
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@ -1,174 +1,144 @@
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#!/usr/bin/env python
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# -*- coding: UTF-8 no BOM -*-
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import os,re,sys,math,string,numpy,damask
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from optparse import OptionParser, Option
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import os,re,sys,math,string
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import numpy as np
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from collections import defaultdict
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from optparse import OptionParser
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import damask
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# -----------------------------
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class extendableOption(Option):
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# -----------------------------
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# used for definition of new option parser action 'extend', which enables to take multiple option arguments
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# taken from online tutorial http://docs.python.org/library/optparse.html
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scriptID = '$Id$'
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scriptName = scriptID.split()[1]
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ACTIONS = Option.ACTIONS + ("extend",)
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STORE_ACTIONS = Option.STORE_ACTIONS + ("extend",)
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TYPED_ACTIONS = Option.TYPED_ACTIONS + ("extend",)
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ALWAYS_TYPED_ACTIONS = Option.ALWAYS_TYPED_ACTIONS + ("extend",)
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def take_action(self, action, dest, opt, value, values, parser):
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if action == "extend":
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lvalue = value.split(",")
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values.ensure_value(dest, []).extend(lvalue)
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else:
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Option.take_action(self, action, dest, opt, value, values, parser)
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def location(idx,res):
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return ( idx % res[0], \
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(idx // res[0]) % res[1], \
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(idx // res[0] // res[1]) % res[2] )
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def index(location,res):
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return ( location[0] % res[0] + \
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(location[1] % res[1]) * res[0] + \
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(location[2] % res[2]) * res[0] * res[1] )
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# --------------------------------------------------------------------
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# MAIN
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# --------------------------------------------------------------------
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parser = OptionParser(option_class=extendableOption, usage='%prog options file[s]', description = """
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parser = OptionParser(option_class=damask.extendableOption, usage='%prog options file[s]', description = """
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Add column containing debug information
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Operates on periodic ordered three-dimensional data sets.
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""" + string.replace('$Id$','\n','\\n')
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""", version = string.replace(scriptID,'\n','\\n')
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)
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parser.add_option('--no-shape','-s', dest='noShape', action='store_false', \
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help='do not calcuate shape mismatch [%default]')
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parser.add_option('--no-volume','-v', dest='noVolume', action='store_false', \
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help='do not calculate volume mismatch [%default]')
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parser.add_option('-c','--coordinates', dest='coords', type='string',\
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parser.add_option('-c','--coordinates', dest='coords', type='string', metavar='string', \
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help='column heading for coordinates [%default]')
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parser.add_option('-f','--deformation', dest='F', action='extend', type='string', \
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help='heading(s) of columns containing deformation tensor values %default')
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parser.add_option('-f','--deformation', dest='defgrad', type='string', metavar='string ', \
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help='column heading for coordinates [%defgrad]')
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parser.set_defaults(noVolume = False)
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parser.set_defaults(noShape = False)
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parser.set_defaults(coords = 'ip')
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parser.set_defaults(F = 'f')
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parser.set_defaults(defgrad = 'f')
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(options,filenames) = parser.parse_args()
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datainfo = { # list of requested labels per datatype
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'F': {'len':9,
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'label':[]},
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datainfo = { # list of requested labels per datatype
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'defgrad': {'len':9,
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'label':[]},
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}
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if options.F != None: datainfo['F']['label'] += options.F
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# ------------------------------------------ setup file handles ---------------------------------------
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datainfo['defgrad']['label'].append(options.defgrad)
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# ------------------------------------------ setup file handles -------------------------------------
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files = []
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if filenames == []:
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files.append({'name':'STDIN', 'input':sys.stdin, 'output':sys.stdout})
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files.append({'name':'STDIN', 'input':sys.stdin, 'output':sys.stdout, 'croak':sys.stderr})
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else:
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for name in filenames:
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if os.path.exists(name):
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files.append({'name':name, 'input':open(name), 'output':open(name+'_tmp','w')})
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# ------------------------------------------ loop over input files ---------------------------------------
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files.append({'name':name, 'input':open(name), 'output':open(name+'_tmp','w'), 'croak':sys.stderr})
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#--- loop over input files ------------------------------------------------------------------------
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for file in files:
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if file['name'] != 'STDIN': print file['name'],
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if file['name'] != 'STDIN': file['croak'].write('\033[1m'+scriptName+'\033[0m: '+file['name']+'\n')
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else: file['croak'].write('\033[1m'+scriptName+'\033[0m\n')
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table = damask.ASCIItable(file['input'],file['output'],False) # make unbuffered ASCII_table
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table.head_read() # read ASCII header info
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table.info_append(string.replace('$Id$','\n','\\n') + \
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'\t' + ' '.join(sys.argv[1:]))
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table = damask.ASCIItable(file['input'],file['output'],False) # make unbuffered ASCII_table
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table.head_read() # read ASCII header info
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table.info_append(string.replace(scriptID,'\n','\\n') + '\t' + ' '.join(sys.argv[1:]))
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# --------------- figure out dimension and resolution
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# --------------- figure out dimension and resolution --------------------------------------------------
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try:
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locationCol = table.labels.index('%s.x'%options.coords) # columns containing location data
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locationCol = table.labels.index('%s.x'%options.coords) # columns containing location data
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except ValueError:
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print 'no coordinate data found...'
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file['croak'].write('no coordinate data found...\n'%key)
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continue
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active = defaultdict(list)
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column = defaultdict(dict)
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missingColumns = False
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for datatype,info in datainfo.items():
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for label in info['label']:
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key = '1_%s'%label
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if key not in table.labels:
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file['croak'].write('column %s not found...\n'%key)
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missingColumns = True
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else:
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active[datatype].append(label)
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column[datatype][label] = table.labels.index(key) # remember columns of requested data
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column = table.labels.index(key)
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if missingColumns:
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continue
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# --------------- figure out dimension and resolution ---------------------------------------------
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grid = [{},{},{}]
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while table.data_read(): # read next data line of ASCII table
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while table.data_read(): # read next data line of ASCII table
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for j in xrange(3):
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grid[j][str(table.data[locationCol+j])] = True # remember coordinate along x,y,z
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res = numpy.array([len(grid[0]),\
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len(grid[1]),\
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len(grid[2]),],'i') # resolution is number of distinct coordinates found
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geomdim = res/numpy.maximum(numpy.ones(3,'d'),res-1.0)* \
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numpy.array([max(map(float,grid[0].keys()))-min(map(float,grid[0].keys())),\
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max(map(float,grid[1].keys()))-min(map(float,grid[1].keys())),\
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max(map(float,grid[2].keys()))-min(map(float,grid[2].keys())),\
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],'d') # dimension from bounding box, corrected for cell-centeredness
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grid[j][str(table.data[locationCol+j])] = True # remember coordinate along x,y,z
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res = np.array([len(grid[0]),\
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len(grid[1]),\
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len(grid[2]),],'i') # resolution is number of distinct coordinates found
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geomdim = res/np.maximum(np.ones(3,'d'),res-1.0)* \
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np.array([max(map(float,grid[0].keys()))-min(map(float,grid[0].keys())),\
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max(map(float,grid[1].keys()))-min(map(float,grid[1].keys())),\
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max(map(float,grid[2].keys()))-min(map(float,grid[2].keys())),\
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],'d') # dimension from bounding box, corrected for cell-centeredness
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if res[2] == 1:
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geomdim[2] = min(geomdim[:2]/res[:2])
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N = res.prod()
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print '\t%s @ %s'%(geomdim,res)
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# --------------- figure out columns to process
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key = '1_%s' %options.F
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if key not in table.labels:
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sys.stderr.write('column %s not found...\n'%key)
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else:
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F = numpy.array([0.0 for i in xrange(N*9)]).reshape([3,3]+list(res))
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if not options.noShape: table.labels_append(['shapeMismatch(%s)' %options.F])
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if not options.noVolume: table.labels_append(['volMismatch(%s)'%options.F])
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column = table.labels.index(key)
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# ------------------------------------------ assemble header ---------------------------------------
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if not options.noShape: table.labels_append(['shapeMismatch(%s)' %options.defgrad])
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if not options.noVolume: table.labels_append(['volMismatch(%s)'%options.defgrad])
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table.head_write()
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# ------------------------------------------ read deformation gradient field -----------------------
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table.data_rewind()
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F = np.array([0.0 for i in xrange(N*9)]).reshape([3,3]+list(res))
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idx = 0
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while table.data_read(): # read next data line of ASCII table
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(x,y,z) = location(idx,res) # figure out (x,y,z) position from line count
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(x,y,z) = damask.gridLocation(idx,res) # figure out (x,y,z) position from line count
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idx += 1
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F[0:3,0:3,x,y,z] = numpy.array(map(float,table.data[column:column+9]),'d').reshape(3,3)
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F[0:3,0:3,x,y,z] = np.array(map(float,table.data[column:column+9]),'d').reshape(3,3)
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Favg = damask.core.math.tensorAvg(F)
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if (res[0]%2 != 0 or res[1]%2 != 0 or (res[2] != 1 and res[2]%2 !=0)):
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print 'using linear reconstruction for uneven resolution'
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centres = damask.core.mesh.deformedCoordsLin(geomdim,F,Favg)
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else:
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centres = damask.core.mesh.deformedCoordsFFT(geomdim,F,1.0,Favg)
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centres = damask.core.mesh.deformedCoordsFFT(geomdim,F,Favg,[1.0,1.0,1.0])
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nodes = damask.core.mesh.nodesAroundCentres(geomdim,Favg,centres)
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if not options.noShape: shapeMismatch = damask.core.mesh.shapeMismatch( geomdim,F,nodes,centres)
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if not options.noVolume: volumeMismatch = damask.core.mesh.volumeMismatch(geomdim,F,nodes)
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# ------------------------------------------ process data ---------------------------------------
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table.data_rewind()
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outputAlive = True
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idx = 0
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while table.data_read(): # read next data line of ASCII table
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(x,y,z) = location(idx,res) # figure out (x,y,z) position from line count
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while outputAlive and table.data_read(): # read next data line of ASCII table
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(x,y,z) = damask.gridLocation(idx,res ) # figure out (x,y,z) position from line count
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idx += 1
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if not options.noShape: table.data_append( shapeMismatch[x,y,z])
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if not options.noVolume: table.data_append(volumeMismatch[x,y,z])
|
||||
|
||||
table.data_write() # output processed line
|
||||
outputAlive = table.data_write() # output processed line
|
||||
|
||||
# ------------------------------------------ output result ---------------------------------------
|
||||
outputAlive and table.output_flush() # just in case of buffered ASCII table
|
||||
|
||||
table.output_flush() # just in case of buffered ASCII table
|
||||
|
||||
file['input'].close() # close input ASCII table
|
||||
file['input'].close() # close input ASCII table (works for stdin)
|
||||
file['output'].close() # close output ASCII table (works for stdout)
|
||||
if file['name'] != 'STDIN':
|
||||
file['output'].close # close output ASCII table
|
||||
os.rename(file['name']+'_tmp',file['name']) # overwrite old one with tmp new
|
||||
os.rename(file['name']+'_tmp',file['name']) # overwrite old one with tmp new
|
||||
|
|
|
|||
|
|
@ -1,59 +1,33 @@
|
|||
#!/usr/bin/env python
|
||||
# -*- coding: UTF-8 no BOM -*-
|
||||
|
||||
import os,re,sys,math,string,numpy,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)
|
||||
|
||||
def location(idx,res):
|
||||
return ( idx % res[0], \
|
||||
( idx // res[0]) % res[1], \
|
||||
( idx // res[0] // res[1]) % res[2] )
|
||||
|
||||
def index(location,res):
|
||||
return ( location[0] % res[0] + \
|
||||
( location[1] % res[1]) * res[0] + \
|
||||
( location[2] % res[2]) * res[1] * res[0] )
|
||||
|
||||
import os,re,sys,math,string
|
||||
import numpy as np
|
||||
from optparse import OptionParser
|
||||
import damask
|
||||
|
||||
scriptID = '$Id$'
|
||||
scriptName = scriptID.split()[1]
|
||||
|
||||
# --------------------------------------------------------------------
|
||||
# MAIN
|
||||
# --------------------------------------------------------------------
|
||||
|
||||
parser = OptionParser(option_class=extendableOption, usage='%prog options [file[s]]', description = """
|
||||
parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [file[s]]', description = """
|
||||
Add column(s) containing curl of requested column(s).
|
||||
Operates on periodic ordered three-dimensional data sets.
|
||||
Deals with both vector- and tensor-valued fields.
|
||||
|
||||
""" + string.replace('$Id$','\n','\\n')
|
||||
""", version=string.replace('$Id$','\n','\\n')
|
||||
)
|
||||
|
||||
|
||||
parser.add_option('-c','--coordinates', dest='coords', type='string',\
|
||||
parser.add_option('-c','--coordinates', dest='coords', type='string', metavar='string', \
|
||||
help='column heading for coordinates [%default]')
|
||||
parser.add_option('-v','--vector', dest='vector', action='extend', type='string', \
|
||||
parser.add_option('-v','--vector', dest='vector', action='extend', type='string', metavar='<string LIST>', \
|
||||
help='heading of columns containing vector field values')
|
||||
parser.add_option('-t','--tensor', dest='tensor', action='extend', type='string', \
|
||||
parser.add_option('-t','--tensor', dest='tensor', action='extend', type='string', metavar='<string LIST>', \
|
||||
help='heading of columns containing tensor field values')
|
||||
|
||||
parser.set_defaults(coords = 'ip')
|
||||
parser.set_defaults(vector = [])
|
||||
parser.set_defaults(tensor = [])
|
||||
|
|
@ -63,7 +37,7 @@ parser.set_defaults(tensor = [])
|
|||
if len(options.vector) + len(options.tensor) == 0:
|
||||
parser.error('no data column specified...')
|
||||
|
||||
datainfo = { # list of requested labels per datatype
|
||||
datainfo = { # list of requested labels per datatype
|
||||
'vector': {'len':3,
|
||||
'label':[]},
|
||||
'tensor': {'len':9,
|
||||
|
|
@ -73,43 +47,40 @@ datainfo = { # lis
|
|||
if options.vector != None: datainfo['vector']['label'] += options.vector
|
||||
if options.tensor != None: datainfo['tensor']['label'] += options.tensor
|
||||
|
||||
# ------------------------------------------ setup file handles ---------------------------------------
|
||||
|
||||
# ------------------------------------------ setup file handles ------------------------------------
|
||||
files = []
|
||||
if filenames == []:
|
||||
files.append({'name':'STDIN', 'input':sys.stdin, 'output':sys.stdout})
|
||||
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')})
|
||||
|
||||
|
||||
# ------------------------------------------ loop over input files ---------------------------------------
|
||||
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': print file['name'],
|
||||
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('$Id$','\n','\\n') + \
|
||||
'\t' + ' '.join(sys.argv[1:]))
|
||||
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 dimension and resolution
|
||||
# --------------- figure out dimension and resolution ----------------------------------------------
|
||||
try:
|
||||
locationCol = table.labels.index('%s.x'%options.coords) # columns containing location data
|
||||
locationCol = table.labels.index('%s.x'%options.coords) # columns containing location data
|
||||
except ValueError:
|
||||
print 'no coordinate data found...'
|
||||
file['croak'].write('no coordinate data found...\n'%key)
|
||||
continue
|
||||
|
||||
grid = [{},{},{}]
|
||||
while table.data_read(): # read next data line of ASCII table
|
||||
for j in xrange(3):
|
||||
grid[j][str(table.data[locationCol+j])] = True # remember coordinate along x,y,z
|
||||
resolution = numpy.array([len(grid[0]),\
|
||||
resolution = np.array([len(grid[0]),\
|
||||
len(grid[1]),\
|
||||
len(grid[2]),],'i') # resolution is number of distinct coordinates found
|
||||
dimension = resolution/numpy.maximum(numpy.ones(3,'d'),resolution-1.0)* \
|
||||
numpy.array([max(map(float,grid[0].keys()))-min(map(float,grid[0].keys())),\
|
||||
dimension = resolution/np.maximum(np.ones(3,'d'),resolution-1.0)* \
|
||||
np.array([max(map(float,grid[0].keys()))-min(map(float,grid[0].keys())),\
|
||||
max(map(float,grid[1].keys()))-min(map(float,grid[1].keys())),\
|
||||
max(map(float,grid[2].keys()))-min(map(float,grid[2].keys())),\
|
||||
],'d') # dimension from bounding box, corrected for cell-centeredness
|
||||
|
|
@ -117,8 +88,6 @@ for file in files:
|
|||
dimension[2] = min(dimension[:2]/resolution[:2])
|
||||
|
||||
N = resolution.prod()
|
||||
print '\t%s @ %s'%(dimension,resolution)
|
||||
|
||||
|
||||
# --------------- figure out columns to process
|
||||
active = {}
|
||||
|
|
@ -140,59 +109,54 @@ for file in files:
|
|||
if datatype not in values: values[datatype] = {}
|
||||
if datatype not in curl: curl[datatype] = {}
|
||||
active[datatype].append(label)
|
||||
column[datatype][label] = table.labels.index(key) # remember columns of requested data
|
||||
values[datatype][label] = numpy.array([0.0 for i in xrange(N*datainfo[datatype]['len'])]).\
|
||||
column[datatype][label] = table.labels.index(key) # remember columns of requested data
|
||||
values[datatype][label] = np.array([0.0 for i in xrange(N*datainfo[datatype]['len'])]).\
|
||||
reshape(list(resolution)+[datainfo[datatype]['len']//3,3])
|
||||
curl[datatype][label] = numpy.array([0.0 for i in xrange(N*datainfo[datatype]['len'])]).\
|
||||
curl[datatype][label] = np.array([0.0 for i in xrange(N*datainfo[datatype]['len'])]).\
|
||||
reshape(list(resolution)+[datainfo[datatype]['len']//3,3])
|
||||
table.labels_append(['%i_curlFFT(%s)'%(i+1,label)
|
||||
for i in xrange(datainfo[datatype]['len'])]) # extend ASCII header with new labels
|
||||
for i in xrange(datainfo[datatype]['len'])]) # extend ASCII header with new labels
|
||||
|
||||
|
||||
# ------------------------------------------ assemble header ---------------------------------------
|
||||
|
||||
table.head_write()
|
||||
|
||||
# ------------------------------------------ read value field ---------------------------------------
|
||||
|
||||
# ------------------------------------------ read value field --------------------------------------
|
||||
table.data_rewind()
|
||||
|
||||
idx = 0
|
||||
while table.data_read(): # read next data line of ASCII table
|
||||
(x,y,z) = location(idx,resolution) # figure out (x,y,z) position from line count
|
||||
while table.data_read(): # read next data line of ASCII table
|
||||
(x,y,z) = damask.gridLocation(idx,resolution) # figure out (x,y,z) position from line count
|
||||
idx += 1
|
||||
for datatype,labels in active.items(): # loop over vector,tensor
|
||||
for label in labels: # loop over all requested curls
|
||||
values[datatype][label][x,y,z] = numpy.array(
|
||||
map(float,table.data[column[datatype][label]:
|
||||
column[datatype][label]+datainfo[datatype]['len']]),'d').reshape(datainfo[datatype]['len']//3,3)
|
||||
for datatype,labels in active.items(): # loop over vector,tensor
|
||||
for label in labels: # loop over all requested curls
|
||||
values[datatype][label][x,y,z] = np.array(
|
||||
map(float,table.data[column[datatype][label]:
|
||||
column[datatype][label]+datainfo[datatype]['len']]),'d') \
|
||||
.reshape(datainfo[datatype]['len']//3,3)
|
||||
|
||||
# ------------------------------------------ process value field ---------------------------------------
|
||||
|
||||
for datatype,labels in active.items(): # loop over vector,tensor
|
||||
for label in labels: # loop over all requested curls
|
||||
# ------------------------------------------ process value field -----------------------------------
|
||||
for datatype,labels in active.items(): # loop over vector,tensor
|
||||
for label in labels: # loop over all requested curls
|
||||
curl[datatype][label] = damask.core.math.curlFFT(dimension,values[datatype][label])
|
||||
|
||||
# ------------------------------------------ process data ---------------------------------------
|
||||
|
||||
table.data_rewind()
|
||||
outputAlive = True
|
||||
idx = 0
|
||||
while table.data_read(): # read next data line of ASCII table
|
||||
(x,y,z) = location(idx,resolution) # figure out (x,y,z) position from line count
|
||||
while outputAlive and table.data_read(): # read next data line of ASCII table
|
||||
(x,y,z) = damask.gridLocation(idx,resolution) # figure out (x,y,z) position from line count
|
||||
idx += 1
|
||||
|
||||
for datatype,labels in active.items(): # loop over vector,tensor
|
||||
for label in labels: # loop over all requested norms
|
||||
for datatype,labels in active.items(): # loop over vector,tensor
|
||||
for label in labels: # loop over all requested norms
|
||||
table.data_append(list(curl[datatype][label][x,y,z].reshape(datainfo[datatype]['len'])))
|
||||
|
||||
table.data_write() # output processed line
|
||||
outputAlive = table.data_write() # output processed line
|
||||
|
||||
|
||||
# ------------------------------------------ output result ---------------------------------------
|
||||
outputAlive and table.output_flush() # just in case of buffered ASCII table
|
||||
|
||||
table.output_flush() # just in case of buffered ASCII table
|
||||
|
||||
file['input'].close() # close input ASCII table
|
||||
file['input'].close() # close input ASCII table (works for stdin)
|
||||
file['output'].close() # close output ASCII table (works for stdout)
|
||||
if file['name'] != 'STDIN':
|
||||
file['output'].close # close output ASCII table
|
||||
os.rename(file['name']+'_tmp',file['name']) # overwrite old one with tmp new
|
||||
os.rename(file['name']+'_tmp',file['name']) # overwrite old one with tmp new
|
||||
|
|
|
|||
Loading…
Reference in New Issue