raise chart.ChartScriptError("The result filter returned no data.")
title, legend = utils.extract_label_columns(df)
df.sort_values(by=[l for i, l in legend], axis='index', inplace=True)
# This is how much of the standard deviation will give the 25th and 75th
# percentiles, assuming normal distribution.
# >>> math.sqrt(2) * scipy.special.erfinv(0.5)
coeff = 0.6744897501960817
boxes = [(r.min, r.mean - r.stddev * coeff, r.mean, r.mean + r.stddev * coeff,
r.max) for r in df.itertuples(index=False) if r.count > 0]
labels = [
", ".join([getattr(r, l[1]) for l in legend])
for r in df.itertuples(index=False) if r.count > 0
]
utils.customized_box_plot(boxes, labels)
title = utils.make_chart_title(df, title, legend)
if "title" in props and props["title"]:
title = props["title"]
utils.set_plot_title(title)
plt.tight_layout()
utils.postconfigure_plot(props)
utils.export_image_if_needed(props)
utils.export_data_if_needed(df, props)
title, legend = utils.extract_label_columns(df)
df.sort_values(by=[l for i, l in legend], axis='index', inplace=True)
ax = plt.gca()
# This is how much of the standard deviation will give the 25th and 75th
# percentiles, assuming normal distribution.
# >>> math.sqrt(2) * scipy.special.erfinv(0.5)
coeff = 0.6744897501960817
boxes = [(r.min, r.mean - r.stddev * coeff, r.mean, r.mean + r.stddev * coeff,
r.max) for r in df.itertuples(index=False) if r.count > 0]
utils.customized_box_plot(boxes, ax)
utils.set_plot_title(utils.make_chart_title(df, title, legend))
ax.set_xticklabels([
utils.make_legend_label(legend, r) for r in df.itertuples(index=False)
if r.count > 0
])
utils.make_fancy_xticklabels(ax)
plt.tight_layout()
utils.postconfigure_plot(props)
utils.export_image_if_needed(props)
utils.export_data_if_needed(df, props)
df, [xaxis_itervar],
"The iteration variable for the X axis could not be found")
utils.assert_columns_exist(
df, [yaxis_itervar],
"The iteration variable for the Y axis could not be found")
if xaxis_itervar == yaxis_itervar:
raise chart.ChartScriptError(
"The itervar for the X and Y axes are the same: " + xaxis_itervar)
df[xaxis_itervar] = pd.to_numeric(df[xaxis_itervar], errors="ignore")
df[yaxis_itervar] = pd.to_numeric(df[yaxis_itervar], errors="ignore")
title_cols, legend_cols = utils.extract_label_columns(df, props)
title = utils.make_chart_title(df, title_cols)
unique_names = df["name"].unique()
if len(unique_names) != 1:
raise chart.ChartScriptError("Selected scalars must share the same name.")
scalar_name = unique_names[0]
df = pd.pivot_table(df,
columns=[xaxis_itervar],
index=yaxis_itervar,
values="value",
dropna=False)
ax = plt.gcf().add_subplot(111, projection='3d')