DAMASK_EICMD/processing/post/addCalculation.py

184 lines
8.3 KiB
Python
Executable File

#!/usr/bin/env python2
# -*- coding: UTF-8 no BOM -*-
import os,re,sys
import math # noqa
import numpy as np
from optparse import OptionParser
import damask
scriptName = os.path.splitext(os.path.basename(__file__))[0]
scriptID = ' '.join([scriptName,damask.version])
# --------------------------------------------------------------------
# MAIN
# --------------------------------------------------------------------
parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [file[s]]', description = """
Add or alter column(s) with derived values according to user-defined arithmetic operation between column(s).
Column labels are tagged by '#label#' in formulas. Use ';' for ',' in functions.
Numpy is available as np.
Special variables: #_row_# -- row index
Examples: (1) magnitude of vector -- "np.linalg.norm(#vec#)" (2) rounded root of row number -- "round(math.sqrt(#_row_#);3)"
""", version = scriptID)
parser.add_option('-l','--label',
dest = 'labels',
action = 'extend', metavar = '<string LIST>',
help = '(list of) new column labels')
parser.add_option('-f','--formula',
dest = 'formulas',
action = 'extend', metavar = '<string LIST>',
help = '(list of) formulas corresponding to labels')
parser.add_option('-c','--condition',
dest = 'condition', metavar='string',
help = 'condition to filter rows')
parser.set_defaults(condition = None,
)
(options,filenames) = parser.parse_args()
if options.labels is None or options.formulas is None:
parser.error('no formulas and/or labels specified.')
if len(options.labels) != len(options.formulas):
parser.error('number of labels ({}) and formulas ({}) do not match.'.format(len(options.labels),len(options.formulas)))
for i in xrange(len(options.formulas)):
options.formulas[i] = options.formulas[i].replace(';',',')
# --- loop over input files -------------------------------------------------------------------------
if filenames == []: filenames = [None]
for name in filenames:
try:
table = damask.ASCIItable(name = name,
buffered = False)
output = damask.ASCIItable(name = name,
buffered = False)
except:
continue
damask.util.report(scriptName,name)
# ------------------------------------------ read header -------------------------------------------
table.head_read()
# -----------------------------------------------------------------------------------------------------
specials = { \
'_row_': 0,
}
# ------------------------------------------ Evaluate condition ---------------------------------------
if options.condition:
interpolator = []
condition = options.condition # copy per file, since might be altered inline
breaker = False
for position,operand in enumerate(set(re.findall(r'#(([s]#)?(.+?))#',condition))): # find three groups
condition = condition.replace('#'+operand[0]+'#',
{ '': '{%i}'%position,
's#':'"{%i}"'%position}[operand[1]])
if operand[2] in specials: # special label
interpolator += ['specials["%s"]'%operand[2]]
else:
try:
interpolator += ['%s(table.data[%i])'%({ '':'float',
's#':'str'}[operand[1]],
table.label_index(operand[2]))] # ccould be generalized to indexrange as array lookup
except:
damask.util.croak('column "{}" not found.'.format(operand[2]))
breaker = True
if breaker: continue # found mistake in condition evaluation --> next file
evaluator_condition = "'" + condition + "'.format(" + ','.join(interpolator) + ")"
else: condition = ''
# ------------------------------------------ build formulae ----------------------------------------
evaluator = {}
for label,formula in zip(options.labels,options.formulas):
for column in re.findall(r'#(.+?)#',formula): # loop over column labels in formula
idx = table.label_index(column)
dim = table.label_dimension(column)
if column in specials:
replacement = 'specials["{}"]'.format(column)
elif dim == 1: # scalar input
replacement = 'float(table.data[{}])'.format(idx) # take float value of data column
elif dim > 1: # multidimensional input (vector, tensor, etc.)
replacement = 'np.array(table.data[{}:{}],dtype=float)'.format(idx,idx+dim) # use (flat) array representation
else:
damask.util.croak('column {} not found, skipping {}...'.format(column,label))
options.labels.remove(label)
break
formula = formula.replace('#'+column+'#',replacement)
evaluator[label] = formula
# ------------------------------------------ process data ------------------------------------------
firstLine = True
outputAlive = True
while outputAlive and table.data_read(): # read next data line of ASCII table
specials['_row_'] += 1 # count row
output.data_clear()
# ------------------------------------------ calculate one result to get length of labels ---------
if firstLine:
firstLine = False
labelDim = {}
for label in [x for x in options.labels]:
labelDim[label] = np.size(eval(evaluator[label]))
if labelDim[label] == 0: options.labels.remove(label)
# ------------------------------------------ assemble header ---------------------------------------
output.labels_clear()
tabLabels = table.labels()
for label in tabLabels:
dim = labelDim[label] if label in options.labels \
else table.label_dimension(label)
output.labels_append(['{}_{}'.format(i+1,label) for i in xrange(dim)] if dim > 1 else label)
for label in options.labels:
if label in tabLabels: continue
output.labels_append(['{}_{}'.format(i+1,label) for i in xrange(labelDim[label])]
if labelDim[label] > 1
else label)
output.info = table.info
output.info_append(scriptID + '\t' + ' '.join(sys.argv[1:]))
output.head_write()
# ------------------------------------------ process data ------------------------------------------
for label in output.labels():
oldIndices = table.label_indexrange(label)
Nold = max(1,len(oldIndices)) # Nold could be zero for new columns
Nnew = len(output.label_indexrange(label))
output.data_append(eval(evaluator[label]) if label in options.labels and
(condition == '' or eval(eval(evaluator_condition)))
else np.tile([table.data[i] for i in oldIndices]
if label in tabLabels
else np.nan,
np.ceil(float(Nnew)/Nold))[:Nnew]) # spread formula result into given number of columns
outputAlive = output.data_write() # output processed line
# ------------------------------------------ output finalization -----------------------------------
table.input_close() # close ASCII tables
output.close() # close ASCII tables