139 lines
6.3 KiB
Python
139 lines
6.3 KiB
Python
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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 damask
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from collections import defaultdict
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from optparse import OptionParser, Option
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scriptID = '$Id$'
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scriptName = scriptID.split()[1]
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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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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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# --------------------------------------------------------------------
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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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Uniformly scale values of scalar, vector, or tensor columns by given factor.
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""" + string.replace(scriptID,'\n','\\n')
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)
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parser.add_option('-s','--scalar', dest='scalar', action='extend', type='string',
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help='column heading of scalar to scale',
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metavar='<label(s)>')
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parser.add_option('-v','--vector', dest='vector', action='extend', type='string',
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help='column heading of vector to scale',
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metavar='<label(s)>')
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parser.add_option('-t','--tensor', dest='tensor', action='extend', type='string',
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help='column heading of tensor to scale',
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metavar='<label(s)>')
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parser.add_option('-f','--factor', dest='factor', action='extend', type='string',
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help='list of scalar, vector, and tensor scaling factors (in this order!)',
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metavar='<float(s)>')
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parser.set_defaults(scalar = [])
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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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(options,filenames) = parser.parse_args()
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options.factor = numpy.array(map(float,options.factor))
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datainfo = { # list of requested labels per datatype
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'scalar': {'len':1,
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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.scalar != []: datainfo['scalar']['label'] += options.scalar; length += len(options.scalar)
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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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# ------------------------------------------ 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, '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'), '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': 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(scriptName,'\n','\\n') + \
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'\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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foundIt = False
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for key in ['1_'+label,label]:
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if key in table.labels:
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foundIt = True
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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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if not foundIt:
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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 scalar,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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if file['name'] != 'STDIN':
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file['input'].close() # close input ASCII table
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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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