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DAMASK_EICMD
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generalized to user-specified mapping function instead of hardwired avg

This commit is contained in:
Philip Eisenlohr 2016-08-25 12:15:03 -04:00
parent eb9f6c939c
commit 85abf84186
1 changed files with 34 additions and 13 deletions
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47
processing/post/averageTable.py
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@ -2,6 +2,7 @@
# -*- coding: UTF-8 no BOM -*-
import os,sys
import math # noqa
import numpy as np
from optparse import OptionParser
import damask
@ -14,7 +15,7 @@ scriptID = ' '.join([scriptName,damask.version])
# --------------------------------------------------------------------
parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [file[s]]', description = """
Replace all rows for which column 'label' has identical values by a single row containing their average.
Apply a user-specified function to condense all rows for which column 'label' has identical values into a single row.
Output table will contain as many rows as there are different (unique) values in the grouping column.
Examples:
@ -25,11 +26,33 @@ parser.add_option('-l','--label',
dest = 'label',
type = 'string', metavar = 'string',
help = 'column label for grouping rows')
parser.add_option('-f','--function',
dest = 'function',
type = 'string', metavar = 'string',
help = 'mapping function [%default]')
parser.add_option('-a','--all',
dest = 'all',
action = 'store_true'
help = 'apply mapping function also to grouping column')
parser.set_defaults(function = 'np.average')
(options,filenames) = parser.parse_args()
funcModule,funcName = options.function.split('.')
try:
mapFunction = getattr(locals().get(funcModule) or
globals().get(funcModule) or
__import__(funcModule),
funcName)
except:
mapFunction = None
if options.label is None:
parser.error('no grouping column specified.')
if not hasattr(mapFunction,'__call__'):
parser.error('function "{}" is not callable.'.format(options.function))
# --- loop over input files -------------------------------------------------------------------------
@ -38,10 +61,6 @@ if filenames == []: filenames = [None]
for name in filenames:
try: table = damask.ASCIItable(name = name,
outname = os.path.join(
os.path.split(name)[0],
options.label+'_averaged_'+os.path.split(name)[1]
) if name else name,
buffered = False)
except: continue
damask.util.report(scriptName,name)
@ -53,6 +72,8 @@ for name in filenames:
damask.util.croak('column {} is not of scalar dimension.'.format(options.label))
table.close(dismiss = True) # close ASCIItable and remove empty file
continue
else:
grpColumn = table.label_index(options.label)
# ------------------------------------------ assemble info ---------------------------------------
@ -64,17 +85,17 @@ for name in filenames:
table.data_readArray()
rows,cols = table.data.shape
table.data = table.data[np.lexsort([table.data[:,table.label_index(options.label)]])]
table.data = table.data[np.lexsort([table.data[:,grpColumn]])] # sort data by grpColumn
values,index = np.unique(table.data[:,table.label_index(options.label)], return_index = True)
index = np.append(index,rows)
avgTable = np.empty((len(values), cols))
values,index = np.unique(table.data[:,grpColumn], return_index = True) # unique grpColumn values and their positions
index = np.append(index,rows) # add termination position
grpTable = np.empty((len(values), cols)) # initialize output
for j in xrange(cols) :
for i in xrange(len(values)) :
avgTable[i,j] = np.average(table.data[index[i]:index[i+1],j])
for i in xrange(len(values)): # iterate over groups (unique values in grpColumn)
grpTable[i] = np.apply_along_axis(mapFunction,0,table.data[index[i]:index[i+1]]) # apply mapping function
if not options.all: grpTable[i,grpColumn] = table.data[index[i],grpColumn] # restore grouping column value
table.data = avgTable
table.data = grpTable
# ------------------------------------------ output result -------------------------------