169 lines
5.6 KiB
Python
Executable File
169 lines
5.6 KiB
Python
Executable File
#!/usr/bin/python
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import os,re,sys,math,string
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from optparse import OptionParser, Option
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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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def L2(object):
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return math.sqrt(sum([x*x for x in object]))
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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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Add column(s) containing norm of requested column(s) being either vectors or tensors.
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""" + string.replace('$Id$','\n','\\n')
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)
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parser.add_option('-m','--memory', dest='memory', action='store_true', \
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help='load complete file into memory [%default]')
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parser.add_option('-v','--vector', dest='vector', action='extend', type='string', \
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help='heading of columns containing vector field values')
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parser.add_option('-t','--tensor', dest='tensor', action='extend', type='string', \
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help='heading of columns containing tensor field values')
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parser.set_defaults(memory = False)
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parser.set_defaults(vector = [])
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parser.set_defaults(tensor = [])
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(options,filenames) = parser.parse_args()
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if len(options.vector) + len(options.tensor) == 0:
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parser.error('no data column specified...')
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datainfo = { # list of requested labels per datatype
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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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if options.vector != None: datainfo['vector']['label'] += options.vector
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if options.tensor != None: datainfo['tensor']['label'] += options.tensor
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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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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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for file in files:
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print file['name']
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# get labels by either read the first row, or - if keyword header is present - the last line of the header
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firstline = file['input'].readline()
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m = re.search('(\d+)\s*head', firstline.lower())
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if m:
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headerlines = int(m.group(1))
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passOn = [file['input'].readline() for i in range(1,headerlines)]
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headers = file['input'].readline().split()
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else:
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headerlines = 1
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passOn = []
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headers = firstline.split()
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if options.memory:
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data = file['input'].readlines()
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else:
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data = []
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for i,l in enumerate(headers):
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if l.startswith('1_'):
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if re.match('\d+_',l[2:]) or i == len(headers)-1 or not headers[i+1].endswith(l[2:]):
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headers[i] = l[2:]
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active = {}
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column = {}
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head = []
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for datatype,info in datainfo.items():
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for label in info['label']:
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key = {True :'1_%s',
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False:'%s' }[info['len']>1]%label
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if key not in headers:
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sys.stderr.write('column %s not found...\n'%key)
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else:
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if datatype not in active: active[datatype] = []
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if datatype not in column: column[datatype] = {}
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active[datatype].append(label)
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column[datatype][label] = headers.index(key)
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head.append('norm(%s)'%label)
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# ------------------------------------------ assemble header ---------------------------------------
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output = '%i\theader'%(headerlines+1) + '\n' + \
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''.join(passOn) + \
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string.replace('$Id$','\n','\\n')+ '\t' + \
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' '.join(sys.argv[1:]) + '\n' + \
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'\t'.join(headers + head) + '\n' # build extended header
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if not options.memory:
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file['output'].write(output)
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output = ''
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# ------------------------------------------ read file ---------------------------------------
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for line in {True : data,
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False : file['input']}[options.memory]:
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items = line.split()[:len(headers)]
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if len(items) < len(headers):
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continue
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output += '\t'.join(items)
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for datatype,labels in active.items():
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for label in labels:
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theNorm = L2(map(float,items[column[datatype][label]:
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column[datatype][label]+datainfo[datatype]['len']]))
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output += '\t%f'%theNorm
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output += '\n'
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if not options.memory:
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file['output'].write(output)
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output = ''
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file['input'].close()
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# ------------------------------------------ output result ---------------------------------------
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if options.memory:
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file['output'].write(output)
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if file['name'] != 'STDIN':
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file['output'].close
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os.rename(file['name']+'_tmp',file['name'])
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