Experiments look good

plotting/compare_runs.py

@@ -10,6 +10,45 @@ from environments.helpers import IGNORED_DF_COLUMNS, MODEL_MAP
 from plotting.plotting import prepare_plot
 
 
+def plot_single_run(run_path: Union[str, PathLike], use_tex: bool = False, column_keys=None):
+    run_path = Path(run_path)
+    df_list = list()
+    if run_path.is_dir():
+        monitor_file = next(run_path.glob('*monitor*.pick'))
+    elif run_path.exists() and run_path.is_file():
+        monitor_file = run_path
+    else:
+        raise ValueError
+
+    with monitor_file.open('rb') as f:
+        monitor_df = pickle.load(f)
+
+        monitor_df = monitor_df.fillna(0)
+        df_list.append(monitor_df)
+
+    df = pd.concat(df_list,  ignore_index=True)
+    df = df.fillna(0).rename(columns={'episode': 'Episode'}).sort_values(['Episode'])
+    if column_keys is not None:
+        columns = [col for col in column_keys if col in df.columns]
+    else:
+        columns = [col for col in df.columns if col not in IGNORED_DF_COLUMNS]
+
+    roll_n = 50
+
+    non_overlapp_window = df.groupby(['Episode']).rolling(roll_n, min_periods=1).mean()
+
+    df_melted = df[columns + ['Episode']].reset_index().melt(id_vars=['Episode'],
+                                                                value_vars=columns, var_name="Measurement",
+                                                                value_name="Score")
+
+    if df_melted['Episode'].max() > 800:
+        skip_n = round(df_melted['Episode'].max() * 0.02)
+        df_melted = df_melted[df_melted['Episode'] % skip_n == 0]
+
+    prepare_plot(run_path.parent / f'{run_path.parent.name}_monitor_lineplot.png', df_melted, use_tex=use_tex)
+    print('Plotting done.')
+
+
 def compare_seed_runs(run_path: Union[str, PathLike], use_tex: bool = False):
     run_path = Path(run_path)
     df_list = list()
@@ -37,7 +76,10 @@ def compare_seed_runs(run_path: Union[str, PathLike], use_tex: bool = False):
         skip_n = round(df_melted['Episode'].max() * 0.02)
         df_melted = df_melted[df_melted['Episode'] % skip_n == 0]
 
-    prepare_plot(run_path / f'{run_path.name}_monitor_lineplot.png', df_melted, use_tex=use_tex)
+    if run_path.is_dir():
+        prepare_plot(run_path / f'{run_path}_monitor_lineplot.png', df_melted, use_tex=use_tex)
+    elif run_path.exists() and run_path.is_file():
+        prepare_plot(run_path.parent / f'{run_path.parent}_monitor_lineplot.png', df_melted, use_tex=use_tex)
     print('Plotting done.')
 
 

plotting/plotting.py

@@ -1,4 +1,5 @@
 import seaborn as sns
+import matplotlib as mpl
 from matplotlib import pyplot as plt
 
 PALETTE = 10 * (
@@ -21,7 +22,14 @@ PALETTE = 10 * (
 def plot(filepath, ext='png'):
     plt.tight_layout()
     figure = plt.gcf()
-    figure.savefig(str(filepath), format=ext)
+    ax = plt.gca()
+    legends = [c for c in ax.get_children() if isinstance(c, mpl.legend.Legend)]
+
+    if legends:
+        figure.savefig(str(filepath), format=ext,  bbox_extra_artists=(*legends,), bbox_inches='tight')
+    else:
+        figure.savefig(str(filepath), format=ext)
+
     plt.show()
     plt.clf()
 
@@ -30,7 +38,7 @@ def prepare_tex(df, hue, style, hue_order):
     sns.set(rc={'text.usetex': True}, style='whitegrid')
     lineplot = sns.lineplot(data=df, x='Episode', y='Score', ci=95, palette=PALETTE,
                             hue_order=hue_order, hue=hue, style=style)
-    # lineplot.set_title(f'{sorted(list(df["Measurement"].unique()))}')
+    lineplot.set_title(f'{sorted(list(df["Measurement"].unique()))}')
     plt.legend(bbox_to_anchor=(1.02, 1), loc='upper left', borderaxespad=0)
     plt.tight_layout()
     return lineplot
@@ -48,6 +56,19 @@ def prepare_plt(df, hue, style, hue_order):
     return lineplot
 
 
+def prepare_center_double_column_legend(df, hue, style, hue_order):
+    print('Struggling to plot Figure using LaTeX - going back to normal.')
+    plt.close('all')
+    sns.set(rc={'text.usetex': False}, style='whitegrid')
+    fig = plt.figure(figsize=(10, 11))
+    lineplot = sns.lineplot(data=df, x='Episode', y='Score', hue=hue, style=style,
+                            ci=95, palette=PALETTE, hue_order=hue_order, legend=False)
+    # plt.legend(bbox_to_anchor=(1.02, 1), loc='upper left', borderaxespad=0)
+    lineplot.legend(hue_order, ncol=3, loc='lower center', title='Parameter Combinations', bbox_to_anchor=(0.5, -0.43))
+    plt.tight_layout()
+    return lineplot
+
+
 def prepare_plot(filepath, results_df, ext='png', hue='Measurement', style=None, use_tex=False):
     df = results_df.copy()
     df[hue] = df[hue].str.replace('_', '-')