#!/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 = '$Id$' scriptName = os.path.splitext(scriptID.split()[1])[0] # -------------------------------------------------------------------- # MAIN # -------------------------------------------------------------------- parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [file[s]]', description = """ Uniformly scale column values by given factor. """, version = scriptID) parser.add_option('-l','--label', dest = 'label', action = 'extend', metavar = '', help ='column(s) to scale') parser.add_option('-f','--factor', dest = 'factor', action = 'extend', metavar='', help = 'factor(s) per column') parser.set_defaults(label = [], ) (options,filenames) = parser.parse_args() if len(options.label) != len(options.factor): parser.error('number of column labels and factors do not match.') # --- loop over input files ------------------------------------------------------------------------- if filenames == []: filenames = [None] for name in filenames: try: table = damask.ASCIItable(name = name, buffered = False) except: continue table.report_name(scriptName,name) # ------------------------------------------ read header ------------------------------------------ table.head_read() errors = [] remarks = [] columns = [] dims = [] factors = [] for what,factor in zip(options.label,options.factor): col = table.label_index(what) if col < 0: remarks.append('column {} not found...'.format(what,type)) else: columns.append(col) factors.append(float(factor)) dims.append(table.label_dimension(what)) if remarks != []: table.croak(remarks) if errors != []: table.croak(errors) table.close(dismiss = True) continue # ------------------------------------------ assemble header --------------------------------------- table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:])) table.head_write() # ------------------------------------------ process data ------------------------------------------ outputAlive = True while outputAlive and table.data_read(): # read next data line of ASCII table for col,dim,factor in zip(columns,dims,factors): # loop over items table.data[col:col+dim] = factor * np.array(table.data[col:col+dim],'d') outputAlive = table.data_write() # output processed line # ------------------------------------------ output finalization ----------------------------------- table.close() # close ASCII tables