args = arg_parser.parse_args()
res = []
if args.calc:
for (dirpath, dirnames, filenames) in os.walk(args.output):
for filename in filenames:
if filename.endswith("~"): continue
fn = os.path.join(dirpath, filename)
r = calc_stats(fn)
print(r)
res.append(r)
print("{:20} {:8} {:8} {:4} {:8} {:8}".format("Feature", "Total",
"Sampled", "%",
"Accuracy", "Err Rate"))
for r in res:
print("{:20} {:8} {:8} {:4}% {:8} {:8}".format(
r['fn'], r['total'], r['sampled'],
r['sampled'] * 100.0 / r['total'], r['accuracy'],
r['error_rate']))
exit(0)
if args.sample:
(input, output) = args.sample
if os.path.exists(output):
raise RuntimeError(output + " exists")
os.mkdir(output)
report = BulkReport(input)
for fn in report.feature_files():
sample(output, fn)
arg_parser.add_argument("--xpattern", type=str, help="Do not sample lines that include this pattern in the forensic path")
arg_parser.add_argument("--calc", help="Compute the statistics",action="store_true")
arg_parser.add_argument("--trials", type=int, default="5", help="Number of trials to divide into")
arg_parser.add_argument("--quiet",action='store_true',help='do not alert on lines with no classification')
args = arg_parser.parse_args()
res = []
if args.calc:
for (dirpath,dirnames,filenames) in os.walk(args.output):
for filename in filenames:
if filename.endswith("~"): continue
fn = os.path.join(dirpath,filename)
r = calc_stats(fn)
print(r)
res.append(r)
print("{:20} {:8} {:8} {:4} {:8} {:8}".format("Feature","Total","Sampled","%","Accuracy","Err Rate"))
for r in res:
print("{:20} {:8} {:8} {:4}% {:8} {:8}".format(
r['fn'],r['total'],r['sampled'],r['sampled']*100.0/r['total'],r['accuracy'],r['error_rate']))
exit(0)
if args.sample:
(input,output) = args.sample
if os.path.exists(output):
raise RuntimeError(output+" exists")
os.mkdir(output)
report = BulkReport(input)
for fn in report.feature_files():
sample(output,fn)
