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)