86 lines
3.5 KiB
Python
Executable File
86 lines
3.5 KiB
Python
Executable File
#!/usr/bin/env python
|
|
# -*- coding: UTF-8 no BOM -*-
|
|
|
|
import os,re,sys,string
|
|
import numpy as np
|
|
from optparse import OptionParser
|
|
import damask
|
|
|
|
scriptID = string.replace('$Id$','\n','\\n')
|
|
scriptName = os.path.splitext(scriptID.split()[1])[0]
|
|
|
|
# --------------------------------------------------------------------
|
|
# MAIN
|
|
# --------------------------------------------------------------------
|
|
|
|
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.
|
|
Output table will contain as many rows as there are different (unique) values in the grouping column.
|
|
|
|
Examples:
|
|
For grain averaged values, replace all rows of particular 'texture' with a single row containing their average.
|
|
""", version = scriptID)
|
|
|
|
parser.add_option('-l','--label', dest='label', type="string", metavar='string',
|
|
help='column label for grouping rows')
|
|
(options,filenames) = parser.parse_args()
|
|
|
|
if options.label == None:
|
|
parser.error('No sorting column specified.')
|
|
|
|
|
|
# --- loop over input files -------------------------------------------------------------------------
|
|
|
|
if filenames == []:
|
|
filenames = ['STDIN']
|
|
|
|
for name in filenames:
|
|
if name == 'STDIN':
|
|
file = {'name':'STDIN', 'input':sys.stdin, 'output':sys.stdout, 'croak':sys.stderr}
|
|
file['croak'].write('\033[1m'+scriptName+'\033[0m\n')
|
|
else:
|
|
if not os.path.exists(name): continue
|
|
file = {'name':name, 'input':open(name), 'output':open(name+'_tmp','w'), 'croak':sys.stderr}
|
|
file['croak'].write('\033[1m'+scriptName+'\033[0m: '+file['name']+'\n')
|
|
|
|
table = damask.ASCIItable(file['input'],file['output'],buffered=False) # make unbuffered ASCII_table
|
|
table.head_read() # read ASCII header info
|
|
|
|
if table.label_dimension(options.label) != 1:
|
|
file['croak'].write('column {0} is not of scalar dimension...\n'.format(options.label))
|
|
table.close(dismiss = True) # close ASCIItable and remove empty file
|
|
continue
|
|
|
|
|
|
# ------------------------------------------ assemble header -----------------------------
|
|
|
|
table.info_append(string.replace(scriptID,'\n','\\n') + \
|
|
'\t' + ' '.join(sys.argv[1:]))
|
|
table.head_write()
|
|
|
|
# ------------------------------------------ process data --------------------------------
|
|
|
|
table.data_readArray()
|
|
rows,cols = table.data.shape
|
|
|
|
table.data = table.data[np.lexsort([table.data[:,table.label_index(options.label)]])]
|
|
|
|
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))
|
|
|
|
for j in xrange(cols) :
|
|
for i in xrange(len(values)) :
|
|
avgTable[i,j] = np.average(table.data[index[i]:index[i+1],j])
|
|
|
|
table.data = avgTable
|
|
|
|
# ------------------------------------------ output result -------------------------------
|
|
|
|
table.data_writeArray()
|
|
table.output_flush() # just in case of buffered ASCII table
|
|
|
|
table.close() # close ASCII table
|
|
if file['name'] != 'STDIN':
|
|
os.rename(file['name']+'_tmp',options.label+'_averaged_'+file['name']) # overwrite old one with tmp new
|