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Plot predicted objective value

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Alinson S. Xavier
2020-02-26 15:45:02 -06:00
parent 32510d077d
commit 5eee00c626
8 changed files with 50 additions and 21 deletions
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46
benchmark/benchmark.py
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@@ -118,52 +118,72 @@ def charts():
sense = results.loc[0, "Sense"]
if sense == "min":
primal_column = "Relative Upper Bound"
obj_column = "Upper Bound"
predicted_obj_column = "Predicted UB"
else:
primal_column = "Relative Lower Bound"
obj_column = "Lower Bound"
predicted_obj_column = "Predicted LB"
palette={
"baseline": "#9b59b6",
"ml-exact": "#3498db",
"ml-heuristic": "#95a5a6"
}
fig, axes = plt.subplots(nrows=1,
ncols=3,
figsize=(10,4),
gridspec_kw={'width_ratios': [3, 3, 2]},
)
fig, (ax1, ax2, ax3, ax4) = plt.subplots(nrows=1,
ncols=4,
figsize=(12,4),
gridspec_kw={'width_ratios': [2, 1, 1, 2]},
)
sns.stripplot(x="Solver",
y="Wallclock Time",
data=results,
ax=axes[0],
ax=ax1,
jitter=0.25,
palette=palette,
size=4.0,
);
sns.barplot(x="Solver",
y="Wallclock Time",
data=results,
ax=axes[0],
ax=ax1,
errwidth=0.,
alpha=0.3,
alpha=0.4,
palette=palette,
estimator=median,
);
axes[0].set(ylabel='Wallclock Time (s)')
axes[1].set_ylim(-0.5, 5.5)
ax1.set(ylabel='Wallclock Time (s)')
ax2.set_ylim(-0.5, 5.5)
sns.stripplot(x="Solver",
y="Gap (%)",
jitter=0.25,
data=results[results["Solver"] != "ml-heuristic"],
ax=axes[1],
ax=ax2,
palette=palette,
size=4.0,
);
axes[2].set_ylim(0.95,1.01)
ax3.set_ylim(0.95,1.05)
sns.stripplot(x="Solver",
y=primal_column,
jitter=0.25,
data=results[results["Solver"] == "ml-heuristic"],
ax=axes[2],
ax=ax3,
palette=palette,
);
sns.scatterplot(x=obj_column,
y=predicted_obj_column,
hue="Solver",
data=results[results["Solver"] == "ml-exact"],
ax=ax4,
palette=palette,
);
xlim, ylim = ax4.get_xlim(), ax4.get_ylim()
ax4.plot([-1e10, 1e10], [-1e10, 1e10], ls='-', color="#cccccc");
ax4.set_xlim(xlim)
ax4.set_ylim(ylim)
ax4.get_legend().remove()
fig.tight_layout()
plt.savefig("%s/performance.png" % basepath,
bbox_inches='tight',