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large speedup (10x) for unconditional filtering by using read/writeArray

This commit is contained in:
Philip Eisenlohr 2017-08-23 20:54:02 -04:00
parent fc4fb43d48
commit 9e5896a6c5
1 changed files with 12 additions and 7 deletions
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19
processing/post/filterTable.py
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@ -126,18 +126,23 @@ for name in filenames:
table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:]))
table.labels_clear()
table.labels_append(np.array(labels)[order]) # update with new label set
table.labels_append(np.array(labels)[order]) # update with new label set
table.head_write()
# ------------------------------------------ process and output data ------------------------------------------
positions = np.array(positions)[order]
outputAlive = True
while outputAlive and table.data_read(): # read next data line of ASCII table
specials['_row_'] += 1 # count row
if options.condition is None or eval(condition): # valid row ?
table.data = [table.data[position] for position in positions] # retain filtered columns
outputAlive = table.data_write() # output processed line
if options.condition is None: # read full array and filter columns
table.data_readArray(1+positions) # read desired columns (indexed 1,...)
table.data_writeArray() # directly write out
else:
outputAlive = True
while outputAlive and table.data_read(): # read next data line of ASCII table
specials['_row_'] += 1 # count row
if eval(condition): # valid row ?
table.data = [table.data[position] for position in positions] # retain filtered columns
outputAlive = table.data_write() # output processed line
# ------------------------------------------ finalize output -----------------------------------------