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DAMASK_EICMD
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corrected bug that added index column values as first output

This commit is contained in:
Philip Eisenlohr 2016-11-29 11:16:50 -05:00
parent 20c5ccc112
commit 231f05e142
1 changed files with 5 additions and 3 deletions
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8
processing/post/addValueMapped.py
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@ -57,6 +57,8 @@ if options.asciitable is not None and os.path.isfile(options.asciitable):
if len(missing_labels) > 0: if len(missing_labels) > 0:
damask.util.croak('column{} {} not found...'.format('s' if len(missing_labels) > 1 else '',', '.join(missing_labels))) damask.util.croak('column{} {} not found...'.format('s' if len(missing_labels) > 1 else '',', '.join(missing_labels)))
index = mappedTable.data[:,0]
data = mappedTable.data[:,1:]
else: else:
parser.error('no indexed ASCIItable given.') parser.error('no indexed ASCIItable given.')
@ -90,6 +92,7 @@ for name in filenames:
table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:])) table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:]))
table.labels_append(mappedTable.labels(raw = True)[1:]) # extend with new labels (except for mapped column) table.labels_append(mappedTable.labels(raw = True)[1:]) # extend with new labels (except for mapped column)
table.head_write() table.head_write()
# ------------------------------------------ process data ------------------------------------------ # ------------------------------------------ process data ------------------------------------------
@ -97,10 +100,9 @@ for name in filenames:
outputAlive = True outputAlive = True
while outputAlive and table.data_read(): # read next data line of ASCII table while outputAlive and table.data_read(): # read next data line of ASCII table
try: try:
table.data_append(mappedTable.data[np.argwhere(mappedTable.data[:,0] == table.data_append(data[np.argwhere(index == float(table.data[mappedColumn]))[0]]) # add data from first matching line
float(table.data[mappedColumn]))[0]]) # add data from first matching line
except IndexError: except IndexError:
table.data_append(np.nan*np.ones_like(mappedTable.data[0])) # or add NaNs table.data_append(np.nan*np.ones_like(data[0])) # or add NaNs
outputAlive = table.data_write() # output processed line outputAlive = table.data_write() # output processed line
# ------------------------------------------ output finalization ----------------------------------- # ------------------------------------------ output finalization -----------------------------------