<jupyter_start><jupyter_text>y_ticks = np.linspace(0, 1, num=11)sns.set_style("whitegrid")sns.set()fig, axes = plt.subplots(nrows=2, ncols=1, figsize=(20, 16))ax = axes[0]ax.set(ylim=(0.0,1.0))ax.set(yticks=y_ticks)sns.pointplot(x="ToxField", y="RocAUC", data=results, ax=ax)sns.pointplot(x="ToxField", y="RocAUC", data=cons_results, ax=ax)ax = axes[1]ax.set(ylim=(0.0,1.0))ax.set(yticks=y_ticks)ax.set(ylim=(0.0,1.0))sns.pointplot(x="ToxField", y="BA", data=results, ax=ax)sns.pointplot(x="ToxField", y="BA", data=cons_results, ax=ax)<jupyter_code>results['label'] = 'Best'
cons_results['label'] = 'Consensus'
all_results = pd.concat([results, cons_results], ignore_index=True)

y_ticks = np.linspace(0.5, 1, num=11)
#sns.set_style("whitegrid")
sns.set()
fig, axes = plt.subplots(nrows=2, ncols=1, figsize=(20, 16))
ax = axes[0]
ax.set(ylim=(0.5,1.0))
ax.set(yticks=y_ticks)
sns.pointplot(x="ToxField", y="RocAUC", data=all_results, hue='label', ax=ax)
ax = axes[1]
ax.set(ylim=(0.5,1.0))
ax.set(yticks=y_ticks)
sns.pointplot(x="ToxField", y="BA", data=all_results, hue='label', ax=ax)
challenge_results = pd.read_csv('tox21_challenge_results.csv')
challenge_results.rename(columns={'AUC-ROC': 'RocAUC', 'Balanced Accuracy': 'BA', 'Team Name': 'label'}, inplace=True)
challenge_results['label']='Challenge'

#challenge_results


all_results = pd.concat([results, cons_results, challenge_results], ignore_index=True, sort=False)

y_ticks = np.linspace(0.5, 1, num=11)
#sns.set_style("whitegrid")
sns.set()
fig, axes = plt.subplots(nrows=2, ncols=1, figsize=(20, 16))
ax = axes[0]
ax.set(ylim=(0.5,1.0))
ax.set(yticks=y_ticks)
sns.pointplot(x="ToxField", y="RocAUC", data=all_results, ax=ax, ci='sd', hue='label')
ax = axes[1]
ax.set(ylim=(0.0,1.0))
ax.set(yticks=y_ticks)
ax.set(ylim=(0.5,1.0))
sns.pointplot(x="ToxField", y="BA", data=all_results, hue='label', ci='sd', ax=ax)
fig, axes = plt.subplots(nrows=2, ncols=1, figsize=(20, 16))
ax = axes[0]
ax.set(ylim=(0.5,1.0))
ax.set(yticks=y_ticks)
sns.boxplot(x="ToxField", y="RocAUC", data=all_results, ax=ax, hue='label')
ax = axes[1]
ax.set(ylim=(0.0,1.0))
ax.set(yticks=y_ticks)
ax.set(ylim=(0.5,1.0))
sns.boxplot(x="ToxField", y="BA", data=all_results, hue='label', ax=ax)<jupyter_output><empty_output>
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