def load():
(dummy, args) = parser.parse_args(values=settings)
if hasattr(settings, 'LIST_TESTS') and settings.LIST_TESTS:
list_tests()
for a in args:
if os.path.exists(a):
if settings.SCALE_MODE and settings.INPUT:
settings.SCALE_DATA.append(a)
else:
settings.INPUT.append(a)
else:
settings.load_test_or_host(a)
settings.load_rcfile()
if settings.SCALE_DATA:
scale_data = []
for filename in settings.SCALE_DATA:
if filename in settings.INPUT:
# Do not load input file twice - makes it easier to select a set
# of files for plot scaling and supply each one to -i without
# having to change the other command line options each time.
continue
r = resultset.load(filename)
scale_data.append(r)
settings.SCALE_DATA = scale_data
settings.load_test(informational=True)
if hasattr(settings, 'LIST_PLOTS') and settings.LIST_PLOTS:
list_plots()
return settings
def load_input(self, settings):
settings = settings.copy()
results = []
test_name = None
for filename in settings.INPUT:
r = resultset.load(filename, settings.ABSOLUTE_TIME)
if test_name is not None and test_name != r.meta(
"NAME") and not settings.GUI:
raise RuntimeError(
"Result sets must be from same test (found %s/%s)" %
(test_name, r.meta("NAME")))
test_name = r.meta("NAME")
if results and settings.CONCATENATE:
results[0].concatenate(r)
else:
results.append(r)
if settings.GUI:
load_gui(settings)
settings.update(results[0].meta())
settings.load_test(informational=True)
# Look for missing data series, and if they are computed from other
# values, try to compute them.
for res in results:
settings.compute_missing_results(res)
formatter = formatters.new(settings)
formatter.format(results)
def load():
(dummy,args) = parser.parse_args(values=settings)
if hasattr(settings, 'LIST_TESTS') and settings.LIST_TESTS:
list_tests()
for a in args:
if os.path.exists(a):
if settings.SCALE_MODE and settings.INPUT:
settings.SCALE_DATA.append(a)
else:
settings.INPUT.append(a)
else:
settings.load_test_or_host(a)
settings.load_rcfile()
if settings.SCALE_DATA:
scale_data = []
for filename in settings.SCALE_DATA:
if filename in settings.INPUT:
# Do not load input file twice - makes it easier to select a set
# of files for plot scaling and supply each one to -i without
# having to change the other command line options each time.
continue
r = resultset.load(filename)
scale_data.append(r)
settings.SCALE_DATA = scale_data
settings.load_test(informational=True)
if hasattr(settings, 'LIST_PLOTS') and settings.LIST_PLOTS:
list_plots()
return settings
def load_input(self, settings):
settings = settings.copy()
results = []
test_name = None
for filename in settings.INPUT:
r = resultset.load(filename, settings.ABSOLUTE_TIME)
if test_name is not None and test_name != r.meta("NAME") and not settings.GUI:
raise RuntimeError("Result sets must be from same test (found %s/%s)" % (test_name, r.meta("NAME")))
test_name = r.meta("NAME")
if results and settings.CONCATENATE:
results[0].concatenate(r)
else:
results.append(r)
if settings.GUI:
load_gui(settings)
settings.update(results[0].meta())
settings.load_test(informational=True)
# Look for missing data series, and if they are computed from other
# values, try to compute them.
for res in results:
settings.compute_missing_results(res)
formatter = formatters.new(settings)
formatter.format(results)
