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