109 lines
5.7 KiB
Python
Executable File
109 lines
5.7 KiB
Python
Executable File
#!/usr/bin/env python
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# -*- coding: UTF-8 no BOM -*-
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import os,sys,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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scriptID = '$Id$'
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scriptName = os.path.splitext(scriptID.split()[1])[0]
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# --------------------------------------------------------------------
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# MAIN
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# --------------------------------------------------------------------
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parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [file[s]]', description = """
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Uniformly scale values in scalar/special, vector, or tensor columns by given factor.
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""", version = scriptID)
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parser.add_option('-s','--special', dest='special', action='extend', metavar='<string LIST>',
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help='heading of columns containing field values of special dimension')
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parser.add_option('-d','--dimension',dest='N', type='int', metavar='int',
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help='dimension of special field values [%default]')
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parser.add_option('-v','--vector', dest='vector', action='extend', metavar='<string LIST>',
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help='column heading of vector to scale')
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parser.add_option('-t','--tensor', dest='tensor', action='extend', metavar='<string LIST>',
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help='column heading of tensor to scale')
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parser.add_option('-f','--factor', dest='factor', action='extend', metavar='<float LIST>',
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help='list of scalar/special, vector, and tensor scaling factors (in this order!)')
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parser.set_defaults(special = [])
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parser.set_defaults(vector = [])
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parser.set_defaults(tensor = [])
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parser.set_defaults(factor = [])
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parser.set_defaults(N = 1)
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(options,filenames) = parser.parse_args()
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options.factor = np.array(options.factor,'d')
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datainfo = { # list of requested labels per datatype
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'special': {'len':options.N,
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'label':[]},
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'vector': {'len':3,
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'label':[]},
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'tensor': {'len':9,
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'label':[]},
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}
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length = 0
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if options.special != []: datainfo['special']['label'] += options.special; length += len(options.special)
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if options.vector != []: datainfo['vector']['label'] += options.vector; length += len(options.vector)
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if options.tensor != []: datainfo['tensor']['label'] += options.tensor; length += len(options.tensor)
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if len(options.factor) != length:
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parser.error('length of scaling vector does not match column count...')
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# --- loop over input files -------------------------------------------------------------------------
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if filenames == []:
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filenames = ['STDIN']
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for name in filenames:
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if name == 'STDIN':
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file = {'name':'STDIN', 'input':sys.stdin, 'output':sys.stdout, 'croak':sys.stderr}
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file['croak'].write('\033[1m'+scriptName+'\033[0m\n')
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else:
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if not os.path.exists(name): continue
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file = {'name':name, 'input':open(name), 'output':open(name+'_tmp','w'), 'croak':sys.stderr}
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file['croak'].write('\033[1m'+scriptName+'\033[0m: '+file['name']+'\n')
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table = damask.ASCIItable(file['input'],file['output'],buffered=False) # make unbuffered ASCII_table
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table.head_read() # read ASCII header info
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table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:]))
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# --------------- figure out columns to process ---------------------------------------------------
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active = defaultdict(list)
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column = defaultdict(dict)
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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_'+label if info['len'] > 1 else label
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if key in table.labels:
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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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else:
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file['croak'].write('column %s not found...\n'%label)
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# ------------------------------------------ assemble header ---------------------------------------
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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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i = 0
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for datatype,labels in sorted(active.items(),key=lambda x:datainfo[x[0]]['len']): # loop over special,vector,tensor
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for label in labels: # loop over all requested labels
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for j in xrange(datainfo[datatype]['len']): # loop over entity elements
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table.data[column[datatype][label]+j] = float(table.data[column[datatype][label]+j]) * options.factor[i]
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i += 1
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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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table.input_close() # close input ASCII table (works for stdin)
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table.output_close() # close output ASCII table (works for stdout)
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if file['name'] != 'STDIN':
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os.rename(file['name']+'_tmp',file['name']) # overwrite old one with tmp new
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