can deal with "veterans" and "newbies" meaning over ride existing with new
This commit is contained in:
Aritra Chakraborty
parent
920cf2c849
commit
304fdf1ebe
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@ -1,4 +1,4 @@
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#!/usr/bin/env python2.7
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#!/usr/bin/env python2
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# -*- coding: UTF-8 no BOM -*-
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import os,re,sys
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@ -6,10 +6,15 @@ import math
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import numpy as np
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from optparse import OptionParser
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import damask
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import collections
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scriptName = os.path.splitext(os.path.basename(__file__))[0]
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scriptID = ' '.join([scriptName,damask.version])
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def listify(x):
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return (x if isinstance(x, collections.Iterable) else [x])
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# --------------------------------------------------------------------
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# MAIN
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# --------------------------------------------------------------------
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@ -55,13 +60,9 @@ for i in xrange(len(options.formulas)):
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if filenames == []: filenames = [None]
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for name in filenames:
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try:
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table = damask.ASCIItable(name = name,
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buffered = False)
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output = damask.ASCIItable(name = name,
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buffered = False)
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except:
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continue
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try: table = damask.ASCIItable(name = name,
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buffered = False)
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except: continue
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damask.util.report(scriptName,name)
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# ------------------------------------------ read header -------------------------------------------
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@ -129,53 +130,46 @@ for name in filenames:
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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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output.data_clear()
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# ------------------------------------------ calculate one result to get length of labels ---------
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if firstLine:
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firstLine = False
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labelDim = {}
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for label in [x for x in options.labels]:
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labelDim[label] = np.size(eval(evaluator[label]))
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if labelDim[label] == 0: options.labels.remove(label)
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resultDim = {}
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for label in list(options.labels): # iterate over stable copy
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resultDim[label] = np.size(eval(evaluator[label])) # get dimension of formula[label]
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if resultDim[label] == 0: options.labels.remove(label) # remove label if invalid result
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veterans = list(set(options.labels)&set(table.labels(raw=False)+table.labels(raw=True)) ) # intersection of requested and existing
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newbies = list(set(options.labels)-set(table.labels(raw=False)+table.labels(raw=True)) ) # requested but not existing
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for veteran in list(veterans):
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if resultDim[veteran] != table.label_dimension(veteran):
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damask.util.croak('{} is ignored due to inconsistent dimension...'.format(veteran))
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veterans.remove(veteran) # ignore culprit
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for newby in newbies:
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table.labels_append(['{}_{}'.format(i+1,newby) for i in xrange(resultDim[newby])]
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if resultDim[newby] > 1 else newby)
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# ------------------------------------------ assemble header ---------------------------------------
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output.labels_clear()
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tabLabels = table.labels()
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for label in tabLabels:
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dim = labelDim[label] if label in options.labels \
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else table.label_dimension(label)
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output.labels_append(['{}_{}'.format(i+1,label) for i in xrange(dim)] if dim > 1 else label)
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for label in options.labels:
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if label in tabLabels: continue
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output.labels_append(['{}_{}'.format(i+1,label) for i in xrange(labelDim[label])]
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if labelDim[label] > 1
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else label)
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output.info = table.info
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output.info_append(scriptID + '\t' + ' '.join(sys.argv[1:]))
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output.head_write()
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table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:]))
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table.head_write()
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# ------------------------------------------ process data ------------------------------------------
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for label in output.labels():
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oldIndices = table.label_indexrange(label)
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Nold = max(1,len(oldIndices)) # Nold could be zero for new columns
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Nnew = len(output.label_indexrange(label))
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output.data_append(eval(evaluator[label]) if label in options.labels and
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(options.condition is None or eval(eval(evaluator_condition)))
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else np.tile([table.data[i] for i in oldIndices]
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if label in tabLabels
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else np.nan,
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np.ceil(float(Nnew)/Nold))[:Nnew]) # spread formula result into given number of columns
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if options.condition is None or eval(eval(evaluator_condition)): # condition for veteran replacement fulfilled
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for veteran in veterans: # evaluate formulae that overwrite
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table.data[table.label_index(veteran):
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table.label_index(veteran)+table.label_dimension(veteran)] = \
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listify(eval(evaluator[veteran]))
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for newby in newbies: # evaluate formulae that append
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table.data_append(listify(eval(evaluator[newby])))
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outputAlive = output.data_write() # output processed line
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outputAlive = table.data_write() # output processed line
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# ------------------------------------------ output finalization -----------------------------------
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table.input_close() # close ASCII tables
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output.close() # close ASCII tables
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table.close() # close ASCII table
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