Resolved some warnings and style issues

marl_factory_grid/utils/plotting/plot_compare_runs.py

@@ -7,50 +7,11 @@ from typing import Union, List
 import pandas as pd
 
 from marl_factory_grid.utils.helpers import IGNORED_DF_COLUMNS
-from marl_factory_grid.utils.plotting.plotting import prepare_plot
+from marl_factory_grid.utils.plotting.plotting_utils import prepare_plot
 
 MODEL_MAP = None
 
 
-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()

marl_factory_grid/utils/plotting/plot_single_runs.py

@@ -0,0 +1,48 @@
+import pickle
+from os import PathLike
+from pathlib import Path
+from typing import Union
+
+import pandas as pd
+
+from marl_factory_grid.utils.helpers import IGNORED_DF_COLUMNS
+from marl_factory_grid.utils.plotting.plotting_utils import prepare_plot
+
+
+def plot_single_run(run_path: Union[str, PathLike], use_tex: bool = False, column_keys=None,
+                    file_key: str ='monitor', file_ext: str ='pkl'):
+    run_path = Path(run_path)
+    df_list = list()
+    if run_path.is_dir():
+        monitor_file = next(run_path.glob(f'*{file_key}*.{file_ext}'))
+    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.')

marl_factory_grid/utils/plotting/plotting_utils.py

@@ -60,7 +60,7 @@ 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))
+    _ = 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)