mu_map/random_search/eval/params.py allows the evaluation of multiple params with the same call

mu_map/random_search/eval/params.py

@@ -7,6 +7,7 @@ import itertools
 import os
 from typing import Any, Callable, Dict, List, Optional
 
+import matplotlib as mlp
 import matplotlib.pyplot as plt
 import numpy as np
 from scipy import stats
@@ -121,6 +122,7 @@ def plot_param_groups(
     param_groups: ParameterGroups,
     measure: str = "NMAE",
     colors: ColorList = color_lists["printer_friendly"],
+    ax: mlp.axes.Axes =  None,
 ):
     """
     Create a plot to visually compare all manifestations of a parameter.
@@ -142,10 +144,11 @@ def plot_param_groups(
         a color list object defining which colors to use for different parameter
         manifestations
     """
-    fig_width = 6 + len(param_groups.groups) - 2
-    fig_height = 4
+    if ax is None:
+        fig_width = 6 + len(param_groups.groups) - 2
+        fig_height = 4
 
-    fig, ax = plt.subplots(figsize=(fig_width, fig_height))
+        _, ax = plt.subplots(figsize=(fig_width, fig_height))
 
     y_max = 0
     for i, (label, value) in enumerate(param_groups.groups.items()):
@@ -254,6 +257,7 @@ if __name__ == "__main__":
     parser.add_argument(
         "param",
         choices=list(parameter_groups.keys()),
+        nargs="+",
         help="the parameter to analyse",
     )
     parser.add_argument(
@@ -293,16 +297,38 @@ if __name__ == "__main__":
             data, os.path.join(args.random_search_dir, args.outliers_file)
         )
 
-    param_groups = parameter_groups[args.param]
-    analyse_stats(data, param_groups, measure=args.measure)
-    plot_param_groups(
-        data,
-        param_groups,
-        measure=args.measure,
-        colors=color_lists[args.colors],
-    )
+    axs = [None]
+    if len(args.param) > 1:
+        _, axs = plt.subplots(1, len(args.param), figsize=(1 + len(args.param) * 4, 4))
+        print(type(axs[0]))
+
+    for i, (_param, ax) in enumerate(zip(args.param, axs)):
+        title = " ".join(map(lambda s: s[0].upper() + s[1:], _param.split("_")))
+
+        param_groups = parameter_groups[_param]
+
+        print()
+        print(title)
+        analyse_stats(data, param_groups, measure=args.measure)
+        plot_param_groups(
+            data,
+            param_groups,
+            measure=args.measure,
+            colors=color_lists[args.colors],
+            ax=ax,
+        )
+
+        if len(args.param) > 1:
+            ax.set_title(title)
+
+        if i == 0:
+            continue
+
+        ax.set_ylabel("")
+        ax.set_yticklabels([])
 
     plt.tight_layout()
+    plt.subplots_adjust(wspace=0.15)
     if args.save:
         plt.savefig(args.save, dpi=300)
     plt.show()