performance mode plot updated

pni-lab · Nov 7, 2024 · 519cf72 · 519cf72
1 parent 6bf60f6
commit 519cf72
Showing 1 changed file with 14 additions and 7 deletions.
diff --git a/notebooks/results.ipynb b/notebooks/results.ipynb
@@ -494,7 +494,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": null,
    "metadata": {},
    "outputs": [
     {
@@ -511,7 +511,7 @@
    "source": [
     "import numpy as np\n",
     "import pandas as pd\n",
-    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
     "import warnings\n",
     "import ast\n",
     "\n",
@@ -543,6 +543,9 @@
     "# Initialize warnings filter;\n",
     "warnings.filterwarnings(\"ignore\")\n",
     "\n",
+    "# Set Seaborn style;\n",
+    "sns.set(style=\"whitegrid\")\n",
+    "\n",
     "# Prepare the plot;\n",
     "fig, ax = plt.subplots(1, 3, figsize=(12, 3))\n",
     "\n",
@@ -573,17 +576,21 @@
     "    lc_mean = lc_mean[valid_indices]\n",
     "    lc_std = lc_std[valid_indices]\n",
     "\n",
-    "    # Plot the mean learning curve with standard deviation shading;\n",
-    "    ax[i].plot(x_values, lc_mean, c='b', linewidth=1.5)\n",
-    "    ax[i].fill_between(x_values, lc_mean - lc_std, lc_mean + lc_std, edgecolor='b', facecolor='b', alpha=0.1)\n",
+    "    # Plot the mean learning curve with Seaborn's lineplot;\n",
+    "    sns.lineplot(x=x_values, y=lc_mean, ax=ax[i], color='b', linewidth=1.5)\n",
+    "\n",
+    "    # Add shading (standard deviation) using fill_between;\n",
+    "    ax[i].fill_between(x_values, lc_mean - lc_std, lc_mean + lc_std, color='b', alpha=0.1)\n",
+    "    \n",
+    "    # Add a vertical line at the stopping point;\n",
     "    ax[i].axvline(x=stop_adj, c='b')\n",
     "    \n",
     "    # Dynamically position the text label for the stop point;\n",
     "    text_x = min(stop_adj, len(lc_mean) - 1)\n",
-    "    ax[i].text(text_x, 0.8, f\"{(stop_adj / len(lc_mean)) * 100:.2f}%\", rotation=0)\n",
+    "    ax[i].text(text_x, 0.8, f\"{(stop_adj / len(lc_mean)) * 100:.2f}%\", rotation=0, color='k')\n",
     "    \n",
     "    # Set the subplot title\n",
-    "    ax[i].set_title(f'Performance with MRS = {mrs}')\n",
+    "    ax[i].set_title(f'Performance with $s_{{min}}$ = {mrs}')\n",
     "\n",
     "# Adjust layout and show plot\n",
     "plt.tight_layout()\n",