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steffen-illium
2021-06-14 11:55:11 +02:00
parent e156540e2c
commit 0ba109c083
3 changed files with 154 additions and 14 deletions
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journal_robustness.py
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@@ -126,7 +126,8 @@ class RobustnessComparisonExperiment:
# This checks wether to use synthetic setting with multiple seeds
# or multi network settings with a singlee seed
df = pd.DataFrame(columns=['setting', 'noise_level', 'steps', 'absolute_loss', 'time_to_vergence', 'time_as_fixpoint'])
df = pd.DataFrame(columns=['setting', 'Noise Level', 'steps', 'absolute_loss',
'time_to_vergence', 'time_as_fixpoint'])
with tqdm(total=max(len(self.id_functions), seeds)) as pbar:
for i, fixpoint in enumerate(self.id_functions): # 1 / n
row_headers.append(fixpoint.name)
@@ -160,21 +161,22 @@ class RobustnessComparisonExperiment:
# When this raises a Type Error, we found a second order fixpoint!
steps += 1
df.loc[df.shape[0]] = [setting, noise_level, steps, absolute_loss,
df.loc[df.shape[0]] = [setting, f'10e-{noise_level}', steps, absolute_loss,
time_to_vergence[setting][noise_level],
time_as_fixpoint[setting][noise_level]]
pbar.update(1)
# Get the measuremts at the highest time_time_to_vergence
df_sorted = df.sort_values('steps', ascending=False).drop_duplicates(['setting', 'noise_level'])
df_melted = df_sorted.reset_index().melt(id_vars=['setting', 'noise_level', 'steps'],
value_vars=['time_to_vergence', 'time_as_fixpoint'],
df_sorted = df.sort_values('Steps', ascending=False).drop_duplicates(['setting', 'Noise Level'])
df_melted = df_sorted.reset_index().melt(id_vars=['setting', 'Noise Level', 'Steps'],
value_vars=['Time to vergence', 'Time as fixpoint'],
var_name="Measurement",
value_name="Steps")
# Plotting
sns.set(style='whitegrid')
bf = sns.boxplot(data=df_melted, y='Steps', x='noise_level', hue='Measurement', palette=PALETTE)
bf.set_title('Robustness as self application steps per noise level')
sns.set(style='whitegrid', font_scale=2)
bf = sns.boxplot(data=df_melted, y='Steps', x='Noise Level', hue='Measurement', palette=PALETTE)
synthetic = 'synthetic' if self.is_synthetic else 'natural'
bf.set_title(f'Robustness as self application steps per noise level for {synthetic} fixpoints.')
plt.tight_layout()
# sns.set(rc={'figure.figsize': (10, 50)})
@@ -221,9 +223,9 @@ if __name__ == "__main__":
ST_steps = 1000
ST_epochs = 5
ST_log_step_size = 10
ST_population_size = 100
ST_population_size = 2
ST_net_hidden_size = 2
ST_net_learning_rate = 0.04
ST_net_learning_rate = 0.004
ST_name_hash = random.getrandbits(32)
ST_synthetic = True