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")