def test_itervars_with_all(): df = results.get_itervars(r, include_itervars=True, include_runattrs=True, include_param_assignments=True, include_config_entries=True) _assert_sequential_index(df) _assert(sanitize_and_compare_csv(df, "itervars_with_all.csv"), "content mismatch") _assert( df.apply(lambda r: r[r["name"]] == r["value"], axis=1).all(), "wrong join")
def get_data(filter): sc = results.get_scalars(filter, include_attrs=True) iv = results.get_itervars(filter) ra = results.get_run_attrs(filter) df = pd.concat([sc, iv, ra]) #print(df) df["value"] = pd.to_numeric(df["value"], errors="ignore") df = pd.pivot_table(df, columns="name", index="runID", dropna=False, aggfunc=aggfunc) #print(df) return df
def get_data(filter): try: sc = results.get_scalars(filter, include_attrs=True) iv = results.get_itervars(filter) ra = results.get_runattrs(filter) except ValueError as e: raise chart.ChartScriptError("Error while querying results: " + str(e)) df = pd.concat([sc, iv, ra]) df["value"] = pd.to_numeric(df["value"], errors="ignore") df = pd.pivot_table(df, columns="name", index="runID", dropna=False, aggfunc=aggfunc) return df
x_module, x_name, x_runattr = module_name_runattr_from_pattern(x_pattern) iso_pattern = params["iso_patterns"].split(";")[0] iso_module, iso_name, iso_runattr = module_name_runattr_from_pattern( iso_pattern) print(x_module, x_name, x_runattr) print(iso_module, iso_name, iso_runattr) avg_repls = bool(strtobool(params['average_replications'])) sc = results.get_scalars(filter_expression, include_itervars=True, include_runattrs=True) iv = results.get_itervars("(" + filter_expression + ") AND NOT name(" + x_runattr + ")", include_itervars=True, include_runattrs=True) iv['module'] = "" df = pd.concat([sc, iv]) df['value'] = pd.to_numeric(df['value']) if x_runattr and iso_runattr: print(df) df = pd.pivot_table(df, index=[x_runattr], columns=[iso_runattr, "replication"], values="value") df.reset_index(inplace=True) print(df) df.rename({x_runattr: 'time'}, axis="columns", inplace=True) # TODO: ugly
def test_itervars(): df = results.get_itervars(r) _assert_sequential_index(df) _assert(sanitize_and_compare_csv(df, "itervars.csv"), "content mismatch")