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DAMASK_EICMD
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fixed broken functionality by adopting new ASCIItable class output for data_readArray().

This commit is contained in:
Tias Maiti 2015-07-15 16:57:03 +00:00
parent d676fdc1ce
commit 6ebc490207
1 changed files with 34 additions and 29 deletions
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63
processing/post/averageTable.py
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@ -6,7 +6,7 @@ import numpy as np
from optparse import OptionParser from optparse import OptionParser
import damask import damask
scriptID = string.replace('$Id: AverageTable.py 3878 2015-02-22 19:26:52Z t.maiti $','\n','\\n') scriptID = string.replace('$Id$','\n','\\n')
scriptName = os.path.splitext(scriptID.split()[1])[0] scriptName = os.path.splitext(scriptID.split()[1])[0]
# -------------------------------------------------------------------- # --------------------------------------------------------------------
@ -14,53 +14,58 @@ scriptName = os.path.splitext(scriptID.split()[1])[0]
# -------------------------------------------------------------------- # --------------------------------------------------------------------
parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [file[s]]', description = """ parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [file[s]]', description = """
Replace all rows for which the indicator column has identical values by a single row containing their average. 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 indicator column. Output table will contain as many rows as there are different (unique) values in the grouping column.
Examples: Examples:
For grain averaged values, replace all rows of particular #texture# with a single row containing their average. For grain averaged values, replace all rows of particular 'texture' with a single row containing their average.
""", version = scriptID) """, version = scriptID)
parser.add_option('-l','--label', dest='key', type="string", metavar='label', parser.add_option('-l','--label', dest='label', type="string", metavar='string',
help='column label for averaging rows') help='column label for grouping rows')
(options,filenames) = parser.parse_args() (options,filenames) = parser.parse_args()
if options.key == None: if options.label == None:
parser.error('No sorting column specified.') parser.error('No sorting column specified.')
# ------------------------------------------ setup file handles --------------------------------------- # --- loop over input files -------------------------------------------------------------------------
files = []
if filenames == []: if filenames == []:
files.append({'name':'STDIN', 'input':sys.stdin, 'output':sys.stdout, 'croak':sys.stderr}) filenames = ['STDIN']
else:
for name in filenames:
if os.path.exists(name):
files.append({'name':name, 'input':open(name), 'output':open(name+'_tmp','w'), 'croak':sys.stderr})
# ------------------------------------------ loop over input files ----------------------- 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')
for file in files: table = damask.ASCIItable(file['input'],file['output'],buffered=False) # make unbuffered ASCII_table
if file['name'] != 'STDIN': file['croak'].write('\033[1m'+scriptName+'\033[0m: '+file['name']+'\n') table.head_read() # read ASCII header info
else: file['croak'].write('\033[1m'+scriptName+'\033[0m\n')
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
table = damask.ASCIItable(file['input'],file['output'],False) # make unbuffered ASCII_table
table.head_read() # read ASCII header info
table.info_append(string.replace(scriptID,'\n','\\n') + \
'\t' + ' '.join(sys.argv[1:]))
# ------------------------------------------ assemble header ----------------------------- # ------------------------------------------ assemble header -----------------------------
table.info_append(string.replace(scriptID,'\n','\\n') + \
'\t' + ' '.join(sys.argv[1:]))
table.head_write() table.head_write()
# ------------------------------------------ process data -------------------------------- # ------------------------------------------ process data --------------------------------
rows, cols = table.data_readArray() table.data_readArray()
rows,cols = table.data.shape
table.data = table.data[np.lexsort([table.data[:,table.label_index(options.key)]])] table.data = table.data[np.lexsort([table.data[:,table.label_index(options.label)]])]
values, index = np.unique(table.data[:,table.label_index(options.key)], return_index=True) values,index = np.unique(table.data[:,table.label_index(options.label)], return_index=True)
index = np.append(index,rows) index = np.append(index,rows)
avgTable = np.empty((len(values), cols)) avgTable = np.empty((len(values), cols))
@ -69,12 +74,12 @@ for file in files:
avgTable[i,j] = np.average(table.data[index[i]:index[i+1],j]) avgTable[i,j] = np.average(table.data[index[i]:index[i+1],j])
table.data = avgTable table.data = avgTable
table.data_writeArray()
# ------------------------------------------ output result ------------------------------- # ------------------------------------------ output result -------------------------------
table.output_flush() # just in case of buffered ASCII table table.data_writeArray()
table.output_flush() # just in case of buffered ASCII table
table.input_close() # close input ASCII table table.close() # close ASCII table
if file['name'] != 'STDIN': if file['name'] != 'STDIN':
table.output_close() # close output ASCII table
os.rename(file['name']+'_tmp',options.key+'_averaged_'+file['name']) # overwrite old one with tmp new os.rename(file['name']+'_tmp',options.key+'_averaged_'+file['name']) # overwrite old one with tmp new