diff --git a/notebooks/book1/01/linreg_poly_vs_degree.ipynb b/notebooks/book1/01/linreg_poly_vs_degree.ipynb
index 72494754fd..c2379b32f1 100644
--- a/notebooks/book1/01/linreg_poly_vs_degree.ipynb
+++ b/notebooks/book1/01/linreg_poly_vs_degree.ipynb
@@ -19,12 +19,69 @@
     "import os\n",
     "os.environ[\"FIG_DIR\"] = \"/teamspace/studios/this_studio/pyprobml/notebooks/figures\"\n",
     "os.environ[\"DUAL_SAVE\"] = \"1\"\n",
-    "os.environ[\"LATEXIFY\"] = \"1\""
+    "\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 9,
+   "id": "4b969241",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#https://nipunbatra.github.io/blog/posts/2014-06-02-latexify.html\n",
+    "#https://github.com/probml/probml-utils/blob/main/probml_utils/plotting.py\n",
+    "#os.environ[\"LATEXIFY\"] = \"1\"\n",
+    "\n",
+    "DEFAULT_WIDTH = 6.0\n",
+    "DEFAULT_HEIGHT = 4.0 # 1.5\n",
+    "SIZE_SMALL = 9  # Caption size in the pml book\n",
+    "\n",
+    "def my_latexify(\n",
+    "    width_scale_factor=1,\n",
+    "    height_scale_factor=1,\n",
+    "    fig_width=None,\n",
+    "    fig_height=None,\n",
+    "    font_size=SIZE_SMALL,\n",
+    "):\n",
+    "    f\"\"\"\n",
+    "    width_scale_factor: float, DEFAULT_WIDTH will be divided by this number, DEFAULT_WIDTH is page width: {DEFAULT_WIDTH} inches.\n",
+    "    height_scale_factor: float, DEFAULT_HEIGHT will be divided by this number, DEFAULT_HEIGHT is {DEFAULT_HEIGHT} inches.\n",
+    "    fig_width: float, width of the figure in inches (if this is specified, width_scale_factor is ignored)\n",
+    "    fig_height: float, height of the figure in inches (if this is specified, height_scale_factor is ignored)\n",
+    "    font_size: float, font size\n",
+    "    \"\"\"\n",
+    "    if fig_width is None:\n",
+    "        fig_width = DEFAULT_WIDTH / width_scale_factor\n",
+    "    if fig_height is None:\n",
+    "        fig_height = DEFAULT_HEIGHT / height_scale_factor\n",
+    "\n",
+    "    # use TrueType fonts so they are embedded\n",
+    "    # https://stackoverflow.com/questions/9054884/how-to-embed-fonts-in-pdfs-produced-by-matplotlib\n",
+    "    # https://jdhao.github.io/2018/01/18/mpl-plotting-notes-201801/\n",
+    "    plt.rcParams[\"pdf.fonttype\"] = 42\n",
+    "\n",
+    "    # Font sizes\n",
+    "    # SIZE_MEDIUM = 14\n",
+    "    # SIZE_LARGE = 24\n",
+    "    # https://stackoverflow.com/a/39566040\n",
+    "    plt.rc(\"font\", size=font_size)  # controls default text sizes\n",
+    "    plt.rc(\"axes\", titlesize=font_size)  # fontsize of the axes title\n",
+    "    plt.rc(\"axes\", labelsize=font_size)  # fontsize of the x and y labels\n",
+    "    plt.rc(\"xtick\", labelsize=font_size)  # fontsize of the tick labels\n",
+    "    plt.rc(\"ytick\", labelsize=font_size)  # fontsize of the tick labels\n",
+    "    plt.rc(\"legend\", fontsize=font_size)  # legend fontsize\n",
+    "    plt.rc(\"figure\", titlesize=font_size)  # fontsize of the figure title\n",
+    "\n",
+    "    #plt.rcParams[\"backend\"] = \"ps\"\n",
+    "    #plt.rc(\"text\", usetex=True)\n",
+    "    plt.rc(\"font\", family=\"serif\")\n",
+    "    plt.rc(\"figure\", figsize=(fig_width, fig_height))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
    "id": "ffac3768",
    "metadata": {},
    "outputs": [],
@@ -108,7 +165,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "id": "54da8fe6",
    "metadata": {},
    "outputs": [
@@ -116,7 +173,9 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/probml_utils/plotting.py:70: UserWarning: renaming /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitVsDegree.pdf to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitVsDegree_latexified.pdf because LATEXIFY is True\n",
+      "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/probml_utils/plotting.py:25: UserWarning: LATEXIFY environment variable not set, not latexifying\n",
+      "  warnings.warn(\"LATEXIFY environment variable not set, not latexifying\")\n",
+      "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/probml_utils/plotting.py:70: UserWarning: renaming /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitVsDegree.pdf to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitVsDegree.pdf because LATEXIFY is False\n",
       "  warnings.warn(\n"
      ]
     },
@@ -124,7 +183,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "saving image to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitVsDegree_latexified.pdf\n",
+      "saving image to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitVsDegree.pdf\n",
       "Figure size: [6.4 4.8]\n"
      ]
     },
@@ -141,6 +200,9 @@
    ],
    "source": [
     "# Plot MSE vs degree\n",
+    "#https://nipunbatra.github.io/blog/posts/2014-06-02-latexify.html\n",
+    "pml.latexify()\n",
+    "\n",
     "fig, ax = plt.subplots()\n",
     "mask = degs <= 15\n",
     "ax.plot(degs[mask], mse_test[mask], color=\"r\", marker=\"x\", label=\"test\")\n",
@@ -162,7 +224,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "id": "364d4d58",
    "metadata": {},
    "outputs": [
@@ -170,7 +232,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/probml_utils/plotting.py:70: UserWarning: renaming /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree1.pdf to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree1_latexified.pdf because LATEXIFY is True\n",
+      "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/probml_utils/plotting.py:70: UserWarning: renaming /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree1.pdf to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree1.pdf because LATEXIFY is False\n",
       "  warnings.warn(\n"
      ]
     },
@@ -178,7 +240,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "saving image to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree1_latexified.pdf\n",
+      "saving image to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree1.pdf\n",
       "Figure size: [6.4 4.8]\n"
      ]
     },
@@ -196,7 +258,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/probml_utils/plotting.py:70: UserWarning: renaming /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree2.pdf to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree2_latexified.pdf because LATEXIFY is True\n",
+      "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/probml_utils/plotting.py:70: UserWarning: renaming /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree2.pdf to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree2.pdf because LATEXIFY is False\n",
       "  warnings.warn(\n"
      ]
     },
@@ -204,7 +266,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "saving image to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree2_latexified.pdf\n",
+      "saving image to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree2.pdf\n",
       "Figure size: [6.4 4.8]\n"
      ]
     },
@@ -222,7 +284,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/probml_utils/plotting.py:70: UserWarning: renaming /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree3.pdf to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree3_latexified.pdf because LATEXIFY is True\n",
+      "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/probml_utils/plotting.py:70: UserWarning: renaming /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree3.pdf to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree3.pdf because LATEXIFY is False\n",
       "  warnings.warn(\n"
      ]
     },
@@ -230,7 +292,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "saving image to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree3_latexified.pdf\n",
+      "saving image to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree3.pdf\n",
       "Figure size: [6.4 4.8]\n"
      ]
     },
@@ -248,7 +310,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/probml_utils/plotting.py:70: UserWarning: renaming /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree14.pdf to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree14_latexified.pdf because LATEXIFY is True\n",
+      "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/probml_utils/plotting.py:70: UserWarning: renaming /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree14.pdf to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree14.pdf because LATEXIFY is False\n",
       "  warnings.warn(\n"
      ]
     },
@@ -256,7 +318,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "saving image to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree14_latexified.pdf\n",
+      "saving image to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree14.pdf\n",
       "Figure size: [6.4 4.8]\n"
      ]
     },
@@ -274,7 +336,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/probml_utils/plotting.py:70: UserWarning: renaming /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree20.pdf to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree20_latexified.pdf because LATEXIFY is True\n",
+      "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/probml_utils/plotting.py:70: UserWarning: renaming /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree20.pdf to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree20.pdf because LATEXIFY is False\n",
       "  warnings.warn(\n"
      ]
     },
@@ -282,7 +344,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "saving image to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree20_latexified.pdf\n",
+      "saving image to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree20.pdf\n",
       "Figure size: [6.4 4.8]\n"
      ]
     },
@@ -322,7 +384,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "id": "2cf3971f",
    "metadata": {},
    "outputs": [
@@ -330,7 +392,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/probml_utils/plotting.py:70: UserWarning: renaming /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree1Residuals.pdf to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree1Residuals_latexified.pdf because LATEXIFY is True\n",
+      "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/probml_utils/plotting.py:70: UserWarning: renaming /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree1Residuals.pdf to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree1Residuals.pdf because LATEXIFY is False\n",
       "  warnings.warn(\n"
      ]
     },
@@ -338,7 +400,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "saving image to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree1Residuals_latexified.pdf\n",
+      "saving image to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree1Residuals.pdf\n",
       "Figure size: [6.4 4.8]\n"
      ]
     },
@@ -356,7 +418,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/probml_utils/plotting.py:70: UserWarning: renaming /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree2Residuals.pdf to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree2Residuals_latexified.pdf because LATEXIFY is True\n",
+      "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/probml_utils/plotting.py:70: UserWarning: renaming /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree2Residuals.pdf to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree2Residuals.pdf because LATEXIFY is False\n",
       "  warnings.warn(\n"
      ]
     },
@@ -364,7 +426,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "saving image to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree2Residuals_latexified.pdf\n",
+      "saving image to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree2Residuals.pdf\n",
       "Figure size: [6.4 4.8]\n"
      ]
     },
@@ -408,7 +470,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "id": "ba6ddc7a",
    "metadata": {},
    "outputs": [
@@ -416,7 +478,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/probml_utils/plotting.py:70: UserWarning: renaming /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree1FitVsActualTrain.pdf to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree1FitVsActualTrain_latexified.pdf because LATEXIFY is True\n",
+      "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/probml_utils/plotting.py:70: UserWarning: renaming /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree1FitVsActualTrain.pdf to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree1FitVsActualTrain.pdf because LATEXIFY is False\n",
       "  warnings.warn(\n"
      ]
     },
@@ -424,7 +486,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "saving image to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree1FitVsActualTrain_latexified.pdf\n",
+      "saving image to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree1FitVsActualTrain.pdf\n",
       "Figure size: [6.4 4.8]\n"
      ]
     },
@@ -442,7 +504,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/probml_utils/plotting.py:70: UserWarning: renaming /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree1FitVsActualTest.pdf to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree1FitVsActualTest_latexified.pdf because LATEXIFY is True\n",
+      "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/probml_utils/plotting.py:70: UserWarning: renaming /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree1FitVsActualTest.pdf to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree1FitVsActualTest.pdf because LATEXIFY is False\n",
       "  warnings.warn(\n"
      ]
     },
@@ -450,7 +512,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "saving image to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree1FitVsActualTest_latexified.pdf\n",
+      "saving image to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree1FitVsActualTest.pdf\n",
       "Figure size: [6.4 4.8]\n"
      ]
     },
@@ -468,7 +530,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/probml_utils/plotting.py:70: UserWarning: renaming /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree2FitVsActualTrain.pdf to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree2FitVsActualTrain_latexified.pdf because LATEXIFY is True\n",
+      "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/probml_utils/plotting.py:70: UserWarning: renaming /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree2FitVsActualTrain.pdf to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree2FitVsActualTrain.pdf because LATEXIFY is False\n",
       "  warnings.warn(\n"
      ]
     },
@@ -476,7 +538,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "saving image to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree2FitVsActualTrain_latexified.pdf\n",
+      "saving image to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree2FitVsActualTrain.pdf\n",
       "Figure size: [6.4 4.8]\n"
      ]
     },
@@ -494,7 +556,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/probml_utils/plotting.py:70: UserWarning: renaming /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree2FitVsActualTest.pdf to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree2FitVsActualTest_latexified.pdf because LATEXIFY is True\n",
+      "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/probml_utils/plotting.py:70: UserWarning: renaming /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree2FitVsActualTest.pdf to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree2FitVsActualTest.pdf because LATEXIFY is False\n",
       "  warnings.warn(\n"
      ]
     },
@@ -502,7 +564,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "saving image to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree2FitVsActualTest_latexified.pdf\n",
+      "saving image to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree2FitVsActualTest.pdf\n",
       "Figure size: [6.4 4.8]\n"
      ]
     },
@@ -554,7 +616,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 11,
    "id": "51115091",
    "metadata": {},
    "outputs": [
@@ -562,7 +624,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/probml_utils/plotting.py:70: UserWarning: renaming /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree1.pdf to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree1_latexified.pdf because LATEXIFY is True\n",
+      "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/probml_utils/plotting.py:70: UserWarning: renaming /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree1_range21.pdf to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree1_range21.pdf because LATEXIFY is False\n",
       "  warnings.warn(\n"
      ]
     },
@@ -570,15 +632,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "saving image to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree1_latexified.pdf\n",
-      "Figure size: [6.4 4.8]\n"
+      "saving image to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree1_range21.pdf\n",
+      "Figure size: [6. 4.]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
+       "<Figure size 600x400 with 1 Axes>"
       ]
      },
      "metadata": {},
@@ -588,7 +650,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/probml_utils/plotting.py:70: UserWarning: renaming /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree2.pdf to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree2_latexified.pdf because LATEXIFY is True\n",
+      "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/probml_utils/plotting.py:70: UserWarning: renaming /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree2_range21.pdf to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree2_range21.pdf because LATEXIFY is False\n",
       "  warnings.warn(\n"
      ]
     },
@@ -596,15 +658,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "saving image to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree2_latexified.pdf\n",
-      "Figure size: [6.4 4.8]\n"
+      "saving image to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree2_range21.pdf\n",
+      "Figure size: [6. 4.]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
+       "<Figure size 600x400 with 1 Axes>"
       ]
      },
      "metadata": {},
@@ -614,7 +676,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/probml_utils/plotting.py:70: UserWarning: renaming /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree3.pdf to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree3_latexified.pdf because LATEXIFY is True\n",
+      "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/probml_utils/plotting.py:70: UserWarning: renaming /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree3_range21.pdf to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree3_range21.pdf because LATEXIFY is False\n",
       "  warnings.warn(\n"
      ]
     },
@@ -622,15 +684,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "saving image to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree3_latexified.pdf\n",
-      "Figure size: [6.4 4.8]\n"
+      "saving image to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree3_range21.pdf\n",
+      "Figure size: [6. 4.]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
+       "<Figure size 600x400 with 1 Axes>"
       ]
      },
      "metadata": {},
@@ -640,7 +702,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/probml_utils/plotting.py:70: UserWarning: renaming /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree14.pdf to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree14_latexified.pdf because LATEXIFY is True\n",
+      "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/probml_utils/plotting.py:70: UserWarning: renaming /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree14_range21.pdf to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree14_range21.pdf because LATEXIFY is False\n",
       "  warnings.warn(\n"
      ]
     },
@@ -648,15 +710,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "saving image to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree14_latexified.pdf\n",
-      "Figure size: [6.4 4.8]\n"
+      "saving image to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree14_range21.pdf\n",
+      "Figure size: [6. 4.]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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",
+      "image/png": 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",
       "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
+       "<Figure size 600x400 with 1 Axes>"
       ]
      },
      "metadata": {},
@@ -666,7 +728,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/probml_utils/plotting.py:70: UserWarning: renaming /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree20.pdf to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree20_latexified.pdf because LATEXIFY is True\n",
+      "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/probml_utils/plotting.py:70: UserWarning: renaming /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree20_range21.pdf to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree20_range21.pdf because LATEXIFY is False\n",
       "  warnings.warn(\n"
      ]
     },
@@ -674,15 +736,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "saving image to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree20_latexified.pdf\n",
-      "Figure size: [6.4 4.8]\n"
+      "saving image to /teamspace/studios/this_studio/pyprobml/notebooks/figures/polyfitDegree20_range21.pdf\n",
+      "Figure size: [6. 4.]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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",
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QmKY0EgM2E7E3DRER+UP0GjabTdGX5Ujvxcb1P0IwYLMA3oUQEVFnVFXVq0SjBPVhA9psT8WLUEBgwGYi3nQQEVF3XG6vfmMvakoUaLM9laQ1bIwDxWLAZgFGlj4TEVFgqXO59T+L2poKaF3HJntKlLkJMRiwmYhvYiIi6o62y4Ez3NauurOv7JKnRJmKEEtqwLZ//35MmjQJ8+fPP+NnTz31FCZMmICJEyfi0UcfDentmUL4n05ERN3QArZogdOhABBmN2YDeC7/EUNawPbZZ5/hkUceQXJy8hk/W7FiBd5//31s3LgRmzdvxvr16/Hiiy/KGoplKXwXExFRN+pbCg4iBVWIamSvYfO2ZCNO1TVh46Fy+dWoQU5awDZy5EisXr0aaWlpZ/xs6dKlWLBgARwOB8LCwnDXXXdh6dKlsoZCREQUsGRl2GSuYVubV4RfvbcDAFBQXo+b/rwJM575HGvzioQ/V6iQFrANGjSowwxSU1MTtm3bhpycHP1748aNw8GDB1FRUdHhsVwuF6qrq9t9BRPecxARUWe0gE1Whk30Gra1eUVYuGorTtU3t/t+cVUjFq7ayqCtlwwvOigrK4PH40FCQoL+Pe3PJSUlHf7OkiVLEB8fr39lZGQYMFIfmbOWnBAlIqLuaFOi0QJ7sHm8qr7DwfbCSmFZNo9XxeI1uztMRGjfW7xmt7DnC6UG9AFRJfrYY4+hqqpK/yosLDR7SEKFcsEFERF1Tc+whYuZEl2bV4QZz3yOkmoXAGDRh7uETVfm5legqKqx05+rAIqqGpGb3/GMGnXO8IAtOTkZdrsdlZWV+ve0P6empnb4Ow6HA3Fxce2+gkLo3BgQEVEv6WvYBGTYtOnK04MqUdOVpTWdB2u9eRy1MjxgczgcGD9+PHbt2qV/b+fOnRg2bBiSkpKMHo4lML9GRESdqW9pnNvXfUSNmK7sH+sU+jhqZcqU6P3334/XXnsNLpcLbrcbr7zyCu6//34zhmIqJtiIiKg79c3axu99mxI1YrpyclYS0uOdnV7fFADp8U5MzgrNBE1fSAvYDh48iFmzZmHt2rVYu3YtZs2ahd27dwMA5s+fj2uuuQbTpk3Deeedh+nTp+PBBx+UNRTL4xI2IiLqjKgMmxHTlXabgkVzszv8mRbELZqbLWTHBo9XRVWDrxL1QElN0Pd5E9vUpY3hw4dj3bp1nf78ySefxJNPPinr6QMCG+cSEVF3tDVsfc2wGTVdOScnHcvnTcCv3t+JyjatPdLinVg0NxtzctL7dHzAtxZv8Zrdesbwxc8P4t0tx4Qd34qkBWzUE8F9V0BERL3XGrD1LcOmTVcWVzV2eNVR4AuqRExXzslJh9cL3Pd/WzE0JRq/vmYsJmclCcmsaYUTp/8btMKJ5fMmBGXQFhBtPYIVE2xERNQdrQ9bXwO2ttOVp19+RE9XAq3XuOSYCEwdlixsGtTIPm9WwoCNiIjIwuoETYkCrdOVafHtpz3T4p3SMlMim9uGcp83TolaAIsOiIioMw1awCZop4M5OemYnZ2GK5d+jV0nqnH/hcPx89lnCcusyRTKfd6YYeuEEUGU9U8NIiIyW502JRoubmsqu01BYlQEAGBY/2gpwZqMy2go93ljwGYBTLAREVFnahu1vUTFTorZWoK0li1F5REYC4ZynzcGbCZiWw8iIupObUsftjhnuNDjakk1j6QpJRmHNbpwwkoYsFkA17AREVFH3B6v3tYj1ik2w2ZvSRqoki9CokMnMwonrIBFByYKvvifiIhE0rJrABAjOGDTZnk8sqdEJdAKJ+b+4WvsLqrGAz8YjgcvDozCid5ihs0CVK5iIyKiDtS0rF9zhtsQbhd7ydYO55U1JSr52ma3KYiP9E0Tj0iNDepgDWDAZiouYSMioq5oAVus4PVrAGBruQjJCtg0vNaJwYDNAriGjYiIOlLT6NuLM1ZwhSjQtkqUF6FAwIDNVLztICKizmlr2EQXHABtM2zCDw2AyQjRGLARERFZlNwpUd9/pU+JMjkhBAM2CzDrLuQPnx3Axb/7EscrG8wZABERdUmbEo2RMCVql7yGjQk2sRiwmcjshZhvbDqCg6W1eH1DgbkDISKiDtVInBI1qq2H2de6YMGArRtGvM/MaOtRWtOI0hoXAOC9LcfQ5A7ARjxEREFO5pSo7LYeJBYDNhOZedOx60S1/ufyuiZ8tqfExNEQEVFH9ClRmUUHkqoOZO+gEGoYsFmAGe/pXcerALQuOn37u0LjB0FERF3SNn6PkxGw2eRWiWo4JSoGAzYTmfkm1jJsN04eDAD4cv9JnGDxARGRpbROicrIsPn+K2vzdxKLAVuIyjvhy7BdMTYdU4YmQVWBd5hlIyKyFC1gi3FIWMNm2ObvTLGJwIDNRGa9iasamlFY4cumZQ+Iw48mDALgy7IREZF1GFMlygxbIGDAFoJ2t0yHDkqMREJUBLIHxAEAjpTXmzksIiI6jcyiA7vkNWycaRWLAZsFGP2m3tUyHTqmJVDLTI4GAFTUNaGqodnYwRARWZyqqmhs9pjy3DUyiw6M2umAM6JCiH8HkN/MehNrBQdjBsQD8HXQTolxoKzWhaPl9Rg7KN6cgRERWYzXq+Khd7bh79tOYHR6HKYOTcaC6UOQkRQl/blVVW2zl6iEram4+XtAYcBmAUY3zs1raemRMzBO/15WShTKal3IL69jwEZE1OK3n+zD37edAADsKarGnqJqfLK7GL++eiwqG5rQP9aJyVlJ+vSiSA3NHn19mYytqbQ+bLKqRM1oCh/MGLCZyIwEW0OTB4dO1gJozbABvmnRbwtO4UhZnQmjIiKynne/K8SydYcAAP9z1RgkREXgib/n4dipBtz2Wq7+uPR4JxbNzcacnHShz69Nh9ptCqIi7EKPDbStEhV+aJKAa9gswMiTZX9JDbwqkBITgf6xDv37Q5J96f0CFh4QEeFoeT0e/2AnAOD+C4fj1qlDEG5XOlznW1zViIWrtmJtXpHQMbS29AjTKzpF0vuwSdvpQMphQxYDNhPJOAG7U17n2z80PT6y3fNrhQdHyplhIyJ6Y1MBmj0qpg5NxkOzz4LHq2Lxmt0dPlaLSxav2S00+NErRCVMhwJtdzqQXXTAqgMRGLBZgJE3IdUNHff0yUrxBWwFDNiIKMQ1NHnwznfHAAB3nZ8Fm01Bbn4FiqoaO/0dFUBRVSNy8yuEjUPmLgdAm71EmQoLCAzYQox2xxZ3WsXR4JYp0bLaJv0xREShaM32E6hqaMagxEhccFZ/AEBpTefBWlv+Ps4fWoXo6Z/Xouh92LxSDs8pUcEYsHXCyOoW2duCtFXdyR1bnDMcydERANhAl4hCl6qqWLmpAAAwb0qmHtT0j3X69fv+Ps4fMpvmAq2tpWTvJcoJUTEYsJnIjGn9ai3DFnnmHduQFG0dGwM2IgpN2workXe8GhFhNtxwbob+/clZSUiPd3YafCjwVYtOzkoSNhbZU6J2yVOiTLCJxYAtxHS2hg0AMvVKUa5jI6LQ9FZuIQDginHpSGqZdQB804eL5mYD6DxjtGhuttB+bIatYZPcOJc1B2IwYLMAI+9COlvDBgBDWipFC9iLjYhCkNer4rO9JQCAH00YdMbP5+SkY/m8CUiLbz/t6QyzYfm8CdL6sMU45Kxhs0neS5TEYuNcE5kzJdp9ho1TokQUirYdq0RZbRNiHWGYNKTjqc05OemYnZ2G3PwKfHekAs99sh92m4ILR/UXPp5al+8GW16GzfdfaTsdsOpAKGbYLMDI93RNF2vY2NqDiELZ53tKAQDnj+yHiLDOL492m4Kpw5LxH7OGIzXOgbomDzYdFtfOQyNz43egtUpUdmDFGVExGLCZSDHhbVzd0PmUaGaSL2ArrXGhrqWcnIgoVHy6xzcdepGf2TKbTcFFo1N9v7u7RPh49ClRaVWictt6kFgM2CzBuBRbV4tY46PCkRjlC+Q4LUpEoeTYqXrsLa6BTQEuHOn/9OYFZ/UDAKENczU1LTfOsZLWsNmlb/5OIjFgM5GZbT3iO5gSBYCBiZEAgKKqBsPGRERkts/3+qZDJ2YmIrFNdWh3zhmcAADYX1ojvOm47D5s2ho26VOiLBMVggFbN4x4nxm1hq3J7UVjsy/33dki1vR4X8B2oostWIiIgs1nLevXfjAqtUe/1z/WiUGJkVBVYMexKqFjkt7WoyVik7X5u5EptlDI5jFgM5HR9xxt7/4620w4vaVcvaiSGTYiCg31TW5sPFQOALh4dM+rPc8ZnAgA+P7oKaHjqm2UuzVV616iUg6vY35NDAZsIUS7W4uOsCPM3vFLr2XYiplhI6IQ8V3BKTR5vBiYEInh/WN6/PvnZCQAAL4/WilsTM0eLxqaPQA6v8HuK21KlJu/BwYGbBZg1KnS1bZUmgEJvgzbCa5hI6IQsfGwL7s2ZWhyr9ZbaevYvi+sFLYerKqhdUYk70SVlGlLffN3aUUHDARFYsBmIqMXYvqzHkLLsBUxw0ZEIWKTHrD1bh/Q7AFxiLDbUFHXhKMVfa+wX5tXhMte+Er/+62v5mLGM59jbV5Rn4/dlnYNkraGTX8eqYcPGQzYLMCobHRXPdg0+hq2qkZ2qSaioFfrcuvFAlOGJvfqGI4wO8YMjAPQ92nRtXlFWLhqK07WNLX7fnFVIxau2io0aLNLXsPGS4hYDNhMZHzRQfcZttQ4JxTFV1FaXtfU6eOIiILBdwUV8HhVDEqMREZSVK+Pc05G3wsPPF4Vi9fs7nAiUfve4jW7hWXE9DVs0jcTZYpNBAZsFmBUJsufNWwRYTakxDgAAEWVnBYlouCmrV+b2svsmqbtOrbeys2v6HI5igrf7IeoJr02yWvYSCwGbGYy+Kajq43f2xqgT4uy8ICIgpu2B+jUYX0L2Ma3VIruPlGNxpbqzp4qrfHvJtnfx3XHpu90IORwZ2AYKBYDNgswrErUjzVsAAsPiCg01DQ2I+9439avaQYlRiIlJgJur4o9RdW9Okb/WKfQx3VH6+4kf6cDqYcPGQzYTGTeGrZuAja29iCiEPBty/q1zOQoDEiI7NOxFEXB6HRf4cGeoppeHWNyVhLS452dXhsU+ArDJmf1rpr1jOMZVCVKYjBgswDDqkT1NWxdT4m27nbADBsRBa/NLdOhU7L6ll3TZOsBW+8ybHabgkVzszv8mRbELZqbrfdP6ytWiQYWBmwmMr4Pmy9g6zbDFs8N4Iko+H1b4AvYzutl/7XTje5jwAYAc3LSsXzeBDjC2l+e0+KdWD5vAubkpPdpjG3pW1PJ7sMm9eihQ85+F2RJ1Q3avnTdFB0ktPZiIyIKRo3NHuxsWb82aYjYgG1vcQ28XlWvwuypOTnpOCv1EHYer8JdM7Pwg1GpmJyVJCyzprG1xITc6SAwMMNmAUa9qWtcPcuwlVQ3GtCfh4jIeNsLK9HsUZEa58CgxL6tX9MM7ReNCLsNtS43jp3q2wxFRUsfzMvGpmPqsGThwRrQtkqURQeBgAGbiYx+D2sZtvhu1rD1j3XApgDNHhVltS4jhkZEZKjvjvga3J47JEnY8pRwuw0jUn2bx+/uw7Qo0BqwJUdH9HlcndGCQK41CwwM2KzAgJNFVVW/17CF2W1IjdMqRTktSkTBR1u/NikzUehxRaxja2jyoKGll1uSxIBNS9rJqhJlICgWAzYTGZkmrmvy6JVA3fVhA3wLXAGgqJKFB0QUXDxeFVvaZNhEEhGwldf5ZjYi7DbEOOQtNdeLDmRPibLsQAgGbBZgxE2Ill0Lsylwhnf/sg9g81wiClL7S2pQ0+hGjCMMo9JihR57dLrveHuKex+wadOhSdERUrsJyK4SZYJNLAZsnTAilWvkXYdeIRoZ7tcHQDq3pyKiIPVdy3ToOYMTEGYXexnUerEVVjToN8o9Vd4mYJPJbpPbh03DogMxGLBZgBHBYev6Nf/S6+ktXb+5ho2Igs23Bb7pUFHtPNpKiIrQb3j3Fvdux4OK2paCgxi5AZsWSHHz98BgWh+2+fPno6CgoN33li1bhuzsjrs8ByMj7zr0XQ78WL8GtNkAnmvYiCjIaBm2c4eILTjQjE6PQ1FVI/YUVfcqKKwwPMPGrQ4CgamNc9etW2fm04eU1n1E/XvJ9aIDZtiIKIgcr2zAiapGhNkUjM9IkPIco9Nj8fne0l4XHpS1FB3IDthskrem0nBKVAxOiVqAEY1zqxt6mGFLaG2e6/Z4pY2LiMhIWnZtzMB4REXIyVmMSmvd8aA39ClRgwI2bv4eGEwN2O677z7MnDkTs2fPxrvvvtvp41wuF6qrq9t9GSVYypGre5hhS4lxIMymwKsCJ9k8l4iChKz+a22NbKk83d+yRVVPtU6JOoSO63Q2yWvYGAaKZVrAlp2djZtuugnr16/HsmXL8NOf/rTToG3JkiWIj4/XvzIyMgwerVxGTPPra9gi/cuw2W1Ka/PcSk6LElFw+K5ATv+1trJSohFuV1DX5MHxXqwDNrxKVPrm7/ISH6E03WpawPboo49i5syZAIARI0bg9ttvx/PPP9/hYx977DFUVVXpX4WFhQaOVB6Z/XVO19M1bEDbTeBZeEBEga+qvhn7SnzTlLIKDgDfFlXD+vm2qOrNtKi+LZXkKlHZa9hYcyCWZdawZWZmnlE1qnE4HIiLi2v3FUyMeE/3dA0b0LoJfBEzbEQUBLYePQVVBYamRCMlRu50o9aQd18vGugaVSVqsxmz+XuQrCwynWkB2yOPPNLu7yUlJRg4cKBJozGHke/hOpcvw9aTbU60XkInmGEjoiDwreR2Hm2N7GXhgcvtQW3L57X8ogPff1WmwgKCaQHbSy+9hH379gEAKioqsHLlSsyfP9+s4ZjKiJPF5fZVejr82JZKowVsxWztQURBwIj1axotw7a/pGcBm5Zds9uUHs2I9IZdcpUoA0GxTOvD9vTTT+O2226Dw+FAfX097r77btx7771mDccURi6W1AO2MLvfv8PdDogoWLjcHmw7VglAzg4Hp9MqRQ+frEOT24uIMP9ulstbWnokRkXoU5ayKEb1YZN7+JBhWsD28MMP4+GHHzbr6S3FiHuQxmYPAPi18btG3wCeux0QUYDbeawKTW4vUmIiMCQ5Svrzpcc7EesMQ02jG4dO1mJ0un9rr/WCA8nToUDrlCjgqxQVHSAyvyaWZYoOQpH1M2y+KdGTtS40udk8l4gCV27L+rWJmYmGVOgrioKRqVrhgf/TokYVHACtbT0AufuJGtkRIZgxYAsRLrcvw9aTNWxJURGIsNugqr4dD4iIAtXmw76A7bysZMOeU5sW7Unhgd6DTXJLD6B9ICW9UpT6jAGbFRhwnriatQyb/y+5zaboe4oWM2AjogDl9nj1LammDDUuYOtNa4+Kln1EjZgSbZthkxGvMQYUiwGbiYzc9qo3U6JAm9YeXMdGRAEq70Q16po8iI8M14MoI2itPaw6Jdp2yZrM/UQ5ISoGAzYLMGLzd31KtAcZNqB1E/giVooSUYDadLgcADA5K0l65WVb2pToiapGVLU0L+9OuUEbvwOtOx0ActewkRgM2Exk1DpMVVV71YcNaM2wsVKUiAKVFrAZOR0KAPGR4RjYctO7+4R/06Ina1umRCXvxACcFrBJqCtjCCgWAzYLkH1j0+Tx6s/hDO/hlCh7sRFRAPOtX/M1zD0vS37/tdPlDPRNi+46UeXX44+W1wMABifJbz1iXJWotEOHFAZsJjLqPexq05Kjp1Oi6XHcAJ6IAteuE9WodbkR5wzzuxeaSGMGxAMA8o53H7BVNzbrVaKZBvSKa7eGTULAxp0OxGLAZgGy39NahSgARNh7GLAlcHsqIgpcbdev2Q1cv6ZpzbB1PyV6pMyXXUuJiUCs5G2pAF9bDy37JTXDJu3IoYUBWye0N29DswcbD5XLqaAxKE/ctuCgpw0Mtd0Oymqb9OMQEQWKzfnGt/NoK6clw3boZC0amrr+DC0orwMAZCZHSx+XRlvHJmMNG4nFgK0Da/OKcPuKbwEAVQ3NuOnPmzDjmc+xNq/I5JH1TmtLj56/3AlR4YhsWfd2/BSnRYkocDR7vMjNN75hblv945xIiXHAqwJ7uunHVlDmC9iGGBiw2fX9RDl9aXUM2E6zNq8IC1dtRVlLabWmuKoRC1dtlRK0yT5N9Ka5PSw4AHwpc23xayEDNiIKIFuPnEKty42k6AiMGWD8+jWNPi3azTq2gpaCAyP2OtUYMiXKqgMhGLC14fGqWLxmd4cBlPa9xWt2C5seNa7ooOcbv7eV0RKwHa2oFzYmIiLZvjpwEgAwc0SKof3XTpejFx50nWE70jIlOiTFwAybTd6UKJN2YjFgayM3v6LLBrEqfA1ktRS7KLIraRqbe7fLgUbPsDFgI6IA8uV+X8B2/oh+po5Dy+7tKuouw2b8lKjNgClR5tfEYMDWRmmNf5WQ/j6uO0ZliXu7y4FmcJKv8EDrD0REZGUer4q1ecV6Rmv68BRTx5Mz0Jdh21dcgyZ3x6msmsZmfSlOZopxU6Ja4pGbv1sfA7Y2+sc6hT7OX9LXsPWh6AAABidzSpSIAsPavCLMeOZz3Ltqi/69a5Z9Y2rR2KDESMQ5w9DsUXGgtON9RY+03BAnR0cgzoCWHhptqljGTI8R2y6GEgZsbUzOSkJ6vLPT9K0C31ZNkwV1yza6ca6IKVE2QiQiq9KKxk5f2iKzaMwfiqLoDXR3dbKOrbWlh3HZNaC1StQjs60H50SFYMDWht2mYNHcbABnvr+0vy+amy28+aL8xrktU6K9LDoYlOj7AKlxuVFZ798GxkRERjK6aKynxg3yBWzfFnS8BlrLsBlZcAC0VnCyrYf1MWA7zZycdCyfNwFp8e2nPdPinVg+bwLm5KQLey6jSp37OiXqDLcjNc63ETGnRYnIiswqGvOXto7u64NlHc5U5JvQgw0AtM1vZASyjAHFCjN7AFY0Jycds7PTkJtfgdKaRvSPdUre1kTuu1oL2Hq68XtbmUnRKKl24WhFPc7OSBA0MiIiMYwuGuupyVlJiAizoaiqEYdO1mJ4/9h2PzejpQfQWiUqM7hSOCcqBDNsnbDbFEwdloyrxg/E1GHJUoI1o97Cjc19qxIF2IuNiKzNrKIxfznD7TivZf3zV/vLzvh5fpnxTXOB1oBNyubvwo8Y2hiwhYC+Fh0ArYUHbO1BRFakFY11RnTRWG/MHOGbFl3f0tBXU+tyo6zWBcDYfUQBwNYSBcjd6UDaoUMKAzYLkF500Mc+bAAwOLmlFxszbERkQW2Lxk4ns2isJ84/y9fAd9PhCv1zGQD2tewxmhQdgfhI41p6AG32EjWpGIP8x4DNRIY1ztX3Eu1DwMYpUSKyuDk56R1m2WQUjfXGyNRY9It1oKHZgy0Fp/Tvv7f1OABzGvy27nQg/tgsOhCLRQcWYFzj3N5PiWpr2IqqGtDk9iKiD9k6IiIZDpTUoKiqEeF2BctvmYi6JrcBRWP+UxQFM0ek4P2tx/HVgTJMG56COpcbq7/3BWw3Tx5s+Ji0xrky252Y/38+OPCqayKjKmf6uvk7APSLccAZboNXBU5UNogaGhGRMP/c6WuMO2N4Ci7OTpVaNNZb2r6mX+wthcerYs32E6hr8iArJRpThhq/vk77X8OdDqyPAZsFyG+c2/cMm6IonBYlIsvyelV8uO0EAODyseZOfXZl5ogUOMJs2FdSgydX5+GvuUcBADdOyjCsN2dbMqtENSw6EIMBm5kCZPN3DQM2IrKqbw6V4XBZHWIcYbjMwgFbcowDz91wNhQFeHPzUWw/VoVwu4IfTRxkynhkrmEjsRiwWYDstLG+hq0PU6JA6zo2rcEjEZFVrNx4BADwowkDEeOw9vLsK8YNwFNX5eh/v2RMGlJiHKaMRW/rEeA7HYTCPtfWflcHOcM2fxcwJQoAI1o6c+8rqe3zmIiIRCmsqMdne0oAALdOHWLuYPx065RMNDZ5sGrzEdw3a5hp47AbsJcodzoQgwGbBQRCHzYAGJXuC9j2FFX3eUxERKK8ufkovKqv2GB4/xizh+O3u84firvOH2rqGLR1czKrREkMTomayLA+bALaegC+HkKKApyscelduYmIzNTY7MHb3/oW7v9kaqbJowk8WgUt4zXrY8AWAlo3f+/byx3tCENmyzq2fcU1fR4XEVFfvb6hAKfqmzEwIRIXjU41ezgBR2vrwa2prI8BmwXIvrFp3fy9bxk2ABiVFgeA06JEZL6TNS784fODAICfzz7LUv3WAoVN4hq2UCgEMBIDNhMZ1zhXTJUo0HYdGzNsRGSu3368D7UuN84eFI9rzxlo9nACkhFtPZhhE4MBmwXIvgtxNYspOgBaM2x7i5lhIyLz7DxWhXe2FAIAnpw7Rt9iiXpGX8PGRWyWxypREwVa0QEAZKf7ArYDJbVwe7wIszPmJyL/ebwqcvMrUFrT2Ot9Pqvqm/Hzd7ZBVYGrxw/AxMxESaMNforENWycERWLAVuQc3u8cLfcOYnIsA1KjER0hB11TR7kl9VhRGpsn49JRKFhbV4RFq/ZjaKqRv176fFOLJqbjTk5/u1O0NjswV1vfIeDpbVIi3Pi8ctHyxpuSLAbsPk7t38Xg+kRExmRYWvyePU/O8P7nmGz2RSMTPMFabtZeEBEflqbV4SFq7a2C9YAoLiqEQtXbcXavKJuj1Hf5MZD72xDbn4FYh1hWHH7JPSPc8oackjQ1rDJyIYxwSYWAzYLkJk21nY5AIAIARk2ABiVrq1jY+EBEXXP41WxeM3uDi/gasvXf3+4q8sszxd7SzH7d1/hXzuLEW5X8KdbJ+praqn3uPl74OCUqImMqBJtbNnlINyuCCt5H92SYdvLDBsR+WHz4fIzMmunK652YcYzn2NUWiwykqIQFRGGCLuCoxX1+O7IKRw71QAAGJgQiSXXjsW04SlGDD3oGdGHjcRgwBbkRO0j2hYzbETkr82Hy/Gr93f69diiqsZOA7swm4LbZ2ThwYtGINrim7sHEplVoowBxeK73gJUiTP9rRWi4ma/R6XFwm5TUFTViMKKemS07H5ARKRRVRWvrM/Hko/2+N3j6z8vH41oRxiOnaqHy+1Fk9uLpOgInDskEecMTkQMAzXhDOnDJu/QIYXvfhMZMa8vauP3tmKd4Zg4OBG5BRX4Yl8pfjJ1iLBjE1Hgc7k9+MW7O/Dh9hMAfK03Nhwqx8kaV4e3pwqAtHgnbp+Rxd0KDGYzpEqURGDRgQVILTrQdzkQNyUKAD8Y3R8A8PneUqHHJaLA5vWqePid7fhw+wmE2RQsvnIMfv/j8XjqqjEAzsy2aH9fNDebwZoJZK5hkzl7FIoYsAW51jVsYl/qH4zyBWwbD5Wjockj9NhEFJhUVcXiNbvwjx1FCLcreHX+JNw2bQgURcGcnHQsnzcBafHt23CkxTuxfN4Ev/uwkVh2iXuJalglKganRC1AboatZUpUcIZtRP8YDEyIxPHKBvzu3/vwg1GpfnUsV1UVO45VYU9RNY5U1KNfjAPzpmQKazlCROZ5+avDeH3jESgK8NwN43HBWf3a/XxOTjpmZ6f1eacDEkeRuIaNRQdiMWAzkWLAbUejpAzbx7uKcaq+CQDw5/X5+PP6/G47lje5vfivv+fh7e8KzzjWH+dNRGJ0hNAxEpFxthw5hWc/3gcA+K8fZuPKswd0+Di7TcHUYclGDo26oO0uKHMNmxEtrEIB0xoWIPMmREbRgdaxvP60qdCuOpaX1bpwyyub8PZ3hbApwMwRKbhpcgZiHGHYnF+Ba5Z9gyPldcLGSETGqWpoxgN//R4er4orzx6ABdOHmD0k8lPrTgdMh1kdAzYTGXHPIXLjd6D7juUAsHjN7nZ3axV1Tfjxnzbi24JTiHWE4dX5k/DGHedhybXj8N7CaRiYEImC8nr84m87+KFBFGBUVcV/frATxysbkJEUiaevyTFk9oDEaK0SFX9sfpqLxYDNAmQGKa5mbQ2bmJc6N7+iy47lKnzNL3PzKwAAtS435r+Wi0Mn6zAg3okP/mM6LhzZX3/8yLRYvH3PFETYbcjNr8A3B8uFjJOIjLE2rxj/2FGEMJuCF288B3HOcLOHRD1gxE4HjN/FYMBmImP6sPlum5yCMmylNV1vL9P2cfVNbty98jvsOFaFpOgIrLzjPAzvH3PGYwclRuHm8wYDAJ779z5m2YgCRHVjMxZ9uAsAsHDWMJwzONHkEVFPSa0S5We5UAzYglxrHzYxL3X/WGf3DwIAFbh22QZsOFSO6Ag7ViyY1GGwprnvwmFwhtvw/dFKrNt3UshYiUiu5z7eh9IaF4YkR+E/Lhxu9nCoFxQj2npIO3JoYcBmATLvQRqbxRYdTM5KQnq8s8sT0Bluw3+v2YW9xTVIiYnAyjsmY9yghC6P2z/Widtadkxglo3I+rYVVmLlpiMAgF9fMxZOwa2DyBh2iWvYSCwGbCYKxKIDu03BornZADoff2OzF6fqmzF2YDw+vH8GJmYm+XXsey4YhshwO/KOVyPveLWQ8RKReF6vikUf7oKqAteeMxDTh6eYPSTqJW0Nm4ybZN52i8U+bFZgRONcgW09tI7li9fsbleAkBITgcvHpiMzORpREXZcc87AHt11J0VH4Aej+uOfO4vwr7wijB0UL2zMRCTOmh0nsL2wEtERdvzq8lFmD4f6QGvrIbUPG6sOhGDAZiIj3sT61lSC1rBpZHUsn5OThn/uLMJHO4vw6KUjeaITWUxjswfPrvU1yL3vwuH+r2slS9LaenDvd+tjwGYBMjfIFT0l2paMjuUXjuoPR5gNBeX12Ftcg9HpcUKPT0R98+rX+The2YAB8U7cMSPL7OFQH0nd/J1BoFAM2ExkzBo235SoU3CGTZYYRxjOP6sf/r27BB/tLGLARkHD61Xxj51F2HCwDHknqnCishFDU6KRMzAeF49OxfThyZbPKJ+scWHZFwcBAL+8bBQLDYKAEZu/kxgM2CxA7ubv8jJsslw+Ns0XsOUV46FLRpo9HKI+23GsEv+1ehe2F1a2+35FXRO+O3IKKzYUYNqwZPzqslHdVlSb6Xf/3o+6Jg/OzkjA3HEd7xVKgUVmWw+Zs0ehiAGbiYy4mRbd1sMIF41ORbhdwYHSWhwoqcGI1Fizh0TUa3/+6jB+89EeqCoQHWHHvCmZGJ+RgEGJUTh4sga5+afw3pZj2HCoHFe99A0euWQk7ps1zHLZtr3F1Xj726MAgP/64Wh97RMFNiPaeljsrRywTL2KP/XUU5gwYQImTpyIRx99lL23JGjNsAVOwBbnDMeMljYBH+8qNnk0RL23fN0h/PpfvmDt6vED8MUjs/DY5aNx2dh0jB0Uj2vOGYQl147FZw9fgCvPHgBVBf734334+dvb9JstK1BVFb/+5x54VV8G/Nwh/rXqIeuT2daDxDLtKr5ixQq8//772LhxIzZv3oz169fjxRdfNGs4ppJ5mrRWiQbOlCgA/GCUb7/RjYe5tygFDo9XxcZD5Vi97Tgee28Hnlm7FwDw0Oyz8PyN56B/XMcVlRlJUXjxpnPw9NU5sNsU/H3bCcx/LdcyQdu6/Sex/kAZIuw2/HIO23gEk9bN31l0YHWmBWxLly7FggUL4HA4EBYWhrvuugtLly41azgmMaCth4Q+bEY4b6iv+nTLkVNocrMFN1nf2rwizHjmc9z050148K1t+Ou3hQCAK89OxwMXjfDrGPOmZGLl7ZMR6wjDpsMVWLhqi+nvf7fHi1//cw8AYP70IchMjjZ1PCSWTZHf1kPh5lRCmHIVb2pqwrZt25CTk6N/b9y4cTh48CAqKirOeLzL5UJ1dXW7r2BiRNFBoFVzjegfg6ToCDQ2e7HjWKXZwyHq0tq8IixctbVdI2nNmu1FWJtX5Pexpg9PwavzJ8EZbsMX+07i529vk9rUtDt//bYQB0trkRgVzv1Cg5DMKlEm2MQyJWArKyuDx+NBQkKC/j3tzyUlJWc8fsmSJYiPj9e/MjIyDBqpXEYsxAzENWyAr3LpvCzfOplNnBYlC/N4VSxes7vLi9PiNbt7FHRNzkrCH+dNRLhdwT93FuH/fbSn7wPtherGZvz+3/sBAD+ffRbiI8NNGQfJo0jsw3b6cwTasa0mIK7ijz32GKqqqvSvwsJCs4cklNTGuQFYJaqZ0jItujn/zKwrkVXk5ld0mFnTqACKqhqR28P38ayR/fHcDeMBAH9en69XaBrppS8OoqKuCcP6ReOmyYMNf36Szy5xDRuJZUpbj+TkZNjtdlRWVurf0/6cmpp6xuMdDgccDodBozOOETcGje7ALDoAgPOG+jJsufkVeH/rMaTHRwrZ/opIpNKazoO13jyurSvPHoBDpbV44bMD+M8P8jAoMQo2RRG6HdzpPF4VufkVyDteiVfX5wMAHr98NMLtgXfTR93T1rDJSLCx6EAsUwI2h8OB8ePHY9euXbjooosAADt37sSwYcOQlBQa5eIer4qKuiYAwKHSOni8qvAPXrfHqy9Y3nmsCmlxzoAKdg6frIWi+KZ1H3pnOwAgPd6JRXOzMScn3eTREfn4u5dmb/fc/NnFI3DoZC3+saMI817d3O4iKPp8WJtXhMVrdrfLGDrCbGhyW6NalcSTWSWqCZyrjrWZdst0//3347XXXoPL5YLb7cYrr7yC+++/36zhGEqrJvvuyCkAwF++yceMZz7v0cJkf59Dc++qLcKfQ6a1eUX4jze/P+MOrbiqEQtXbQ2YfwcFv8lZSUiOjuj05wp8gdXkrN7djCqKgkuyfTMPMs+HzgonXG4v7nvze55zQUrmXqIklmkB2/z583HNNddg2rRpOO+88zB9+nQ8+OCDZg3HMJ19KMr44C2udkl7Dpm6WsStfa+ni7iJZLEpQHxUx4vxtczCornZvc5ue7wqlny0t8OfiTofZBROUGCQWyXK94tIpi5KePLJJ7FlyxZs2bIFzz77rOW2YhHNiEAkGIIdWYu4iWRYt/8kDp+sQ7hdQf/Y9mtt0+KdWD5vQp+mLI04H3jOhS5D+rAF96XdMNxL1EA9+VCcOizZss8hm8xF3EQiqaqqt72YP20IfnXZaOTmVwgtCjDifOA5F7qkrmGzbl4gIDFgMxA/eP0jexE3kSif7y3FjmNViAy3454LhsFuU4TfCBlxPvCcC11GrGEL9tkzo7BO20D84PXP5KwkpMc7O60s6usibiIRVFXF7z/1Zdd+Mi0TKTFyWg91dz4AQEpMRJ/Oh0lDEuEM7/xywHMueGkZYBYdWB8DNgMZEYgEQ7BjtylYNDcbwJnl4CIWcROJ8PneUuQdr0ZUhB33nD9M2vN0dT60VVnf1OvnWLbuEBqbO96zlOdccNOyX14JW9YyBBSLAZuBjAhE2j7H6QLpg3dOTjqWz5uAtPj2mcDUOEefF3ETifDq176msvOmZCKpi7YeInR6PsQ6kBITgbLaJtz9xhZUNzb3+Ngfbj+B37Wsw7vlvMFIP+05RBROkHVpVaIemVOi0o4cWriGzWDaB+/pzSnTBDbA1J7jPz/IQ3ld6123yOcwwpycdMzOTsPmw+W4643vUOfy4KVbJmJiZqLZQ6MQt7e4GhsOlcNuU3DbtCGGPKd2Ppxe1JBfVotrlm3AliOncMMfN+K1BZOQHh/p1zE/3lWMR971NaW++/yhePzy0fpOBzJ3UyDr0F5aVUZbD06zCsWAzQTaB+8tr2zCpsMVuG1qJp6cO0boh+KcnHREO8Jw66u5SIt34vc3jA/ID167TcG04SmYNCQJ6/adRN7xKgZsZLrXvi4AAMwZk4aBCf4FRyJ0VNQwvH8s/nrXFCxY8S32Ftfgmpc24MWbzuly2YOqqvjTV4fxzNq9UFXfv+OXc0Z1+hwUvIzY6YApNjE4JWoSu03RFylnJkdLCaS08y8pKgJThyUHXLDW1tmDEgAA249VmjoOovJaFz7YdhwAsGD6EHMH0yJnYDw+uG8ahvePQXF1I27400b8/O1tOFHZcMZjtxw5hfmvfYv/95EvWPvJ1EwsvfmcgP58oN4zog8bicEMm4lklzo3t+wjGm4P/A/iszPiAQDbCyvNHQiFvP/bfBRNbi/GDYq3VLZ3UGIU3ls4Df/vo71469uj+OD74/jg++MYmRqL8RkJqHE140h5PXadqAbgu2l88opsw6Z0yZrsLWkbOVOiwg8Z0hiwWYCs97TbqwVsgZ9IHdeSYTtcVoeaxmbEOjveCohIpia3Fys3HQEA3D49y3L9peIjw7Hk2rG4cVIGfv2vPfi2oAL7Smqwr6RGf0y4XcG15wzCPRcMxdB+MSaOlqxAMaTowFrnSaBiwGYi7S0sa2Fms8d33LAgyLClxDgwMCESxysbsPN4FaYNSzF7SBSC/rWzCCdrXOgf68DlY61bvHN2RgLeuWcqKuqasOFQGfYX1yAxOgL9Y52YmJl4RrUphS67xLYeJBYDNhPJvjkPpgwb4JsWPV7ZgB3HGLCR8VRVxV++8bXy+MnUTESEWf+8SoqOwBXjBgDjzB4JWZVN6ubvJJL1P3GCmOy8l55hC5LFxGMG+Nax7SmqNnkkFIq2HDmFHceqEBFmw02TB5s9HCIhjNmaStqhQwoDNhNpawdknSfNHl+GLSxIMmzZA+IAALtPMGAj42nZtWvGD0SypG2oiIwms60Hiw7ECo4reYBTJSWO3S0ZtoggCdjGpPsCtkMna9HY7DF5NBRKjp2qx9q8YgDAghlDzB0MkUA2yYkDgG3YRAmOK3mAai06kHP81gxbcJwu/Vq24fGqwN7imu5/gUiQNzYegVcFpg9Pxqi0OLOHQySMdj8vs0qUxGDAZibpRQfaGrbgeJkVRcHodE6LkrHqXG78NfcoAF8rD6JgokgtOmAQKFJwXMkDlNabRlofNk/wNM7V6OvYiqpMHgmFive3HkN1oxtDkqNw4cj+Zg+HSCgj2nqw6EAMBmwWICsT3RREfdg02cywkYG8XhWvfVMAAJg/bYi+QJsoWEht68EEm1AM2Eyk3XXIKzoIrj5sADCmJcO2t7hG7mbFRAC+PHASh8vqEOsIw3XnZpg9HCLhtBUzMj9PudOBGMFzJQ9AsosOtDVswRSwZaXEwBluQ32TB0fK68weDgW5v3zta+Xx40kZiHGwzzgFH27+HjiC50oegGTP6+tVokE0jWO3KXqV3m420CWJ9pfUYP2BMtgUcIN0Clp2m7wpURKLAVsQc+tr2ILrZWYDXTKCtnbtkuw0ZCRFmTsYIkm400HgCK4reYDRq0Slbf7esoYtiDJsQGvhwS4GbCTJqbomvL/1GABgwfQh5g6GSCJtSpRrgq2PAZuJ9KIDaY1zW9awBcAm1T3R2tqDARvJ8ddvj8Ll9mLMgDhMzkoyezhE0sjc6UBWMiJUBdeVPMDIThO7vcG3hg0ARqXFQlGAkzUulNY0mj0cCjLNHi9WbjgCwNcoV+F8DgUxu8S9RDU8g8RgwGYB8hrnBl+VKABERYQhKyUaALCniFtUkVj/2HECxdWNSIlx4Iqz080eDpFUisQ1bMyviRVcV/KAI3fT3WDbS7QtNtAlGVRVxctf+Vp5zJ+WCUeY3eQREcllSJUos9RCMGAzkezGua1FB8H3Mo8ZEA+A69hIrK8PlmFPUTWiIuyYNyXT7OEQScc+bIEj+K7kAUT2PYfeODcs+O5uWlt7cE9REuflrw4DAG44NwMJUREmj4ZIPplVoqw5EIsBm4nkV4lqRQfB9zJrU6KHy+pQ3+Q2eTQUDHadqML6A2Ww2xTcMSPL7OEQGaJtTZqsqs7gSxmYI/iu5AFIftFB8J0u/WId6BfrgKoC+4pZeEB998cvfdm1y8ems1EuhQx7m4hNdJJN1nKfUMWAzUT6hriyGue2nH3BmGEDAqeBrserYuOhcqzedhwbD5WzQaUFHSipwT92nAAALLxgmMmjITJO27Y1sj6bWHMgBnczNpH0vUTdwVslCvjWsX25/6SlCw/W5hVh8ZrdKKpq7ReXHu/EornZmJPDlhFW8eLnB6GqwJwxafr6SKJQ0D7DxptJKwvO1EuA0E4TaVOiLY1zI4KsD5vG6q091uYVYeGqre2CNQAoqmrEvau24r0thewEbgFts2sPXDTC5NEQGavtGjbRARs/3sQKzit5gJH1pg7Wzd81WiZkb3G15aYZPV4Vi9fs7jIYf/jdHbjiD18j7zgrXc3E7BqFMpsibw2bRmHZgRDBeSUPENraAWl92LzBPSU6JDkaURF2NDZ7kV9WZ/Zw2snNrzgjs9aRXSeqcfVL3+B3n+yDu6Wql4yTd7yK2TUKaTYD1rCRGAzYgpheJRqkRQd2m4JRabEArNdA1989TsdnJMDtVfHi5wexeM1uyaOitlRVxVNrdkNVgavGD2B2jUJS2zVsopdoMPwTKziv5AHCsD5sQZphA9o20LVWwNY/1unX4345ZxSeu/5sKArwxqYjWLmxQO7ASPevncXILaiAM9yGX84ZZfZwiEzRdg0bq0StjVWiFiDrLqQ5iPuwabLTrblF1eSsJCRGheNUfXOHP1cApMU7MTkrCXabgtIaF55ZuxeL1+zGkORonH9WP2MHHAI8XhW5+RUorWlEQmQEfvOvPQCAe84fhgEJkSaPjsgciqJAUXyJA+F92JhiE4oBm4kUyZu/a2uiwoO06ABov0WVqqrtegqZyeNVOy320Ea4aG62Ph1x7wVDcaC0Bu9vPY6H3tmGzx6ahfiocINGG/w6aq8CAIlR4biXfdcoxNkUBR5VldbWwxqfyoEveK/kAUB6HzZvcFeJAsDI1FjYFKCstgkna1xmD0e3cmMBTta4EOcMQ2qco93P0uKdWD5vQrs+bIqiYMm1YzGsXzTKapvwv5/sNXrIppPVYLiz9ioAcKq+GV/uLxXyPESBSpsWZR82a2OGzUStfdjknCR6hs0WvPc3kRF2DO0Xg4OltdhVVI3+cf6tHZPpVF0TXvzsAADgP384GtdNzNCn4vrHtk6Dns4RZsfTV4/FTX/ehDc3H8V1EzMwPiPB4NGbQ1aD4e7aqygAFq/ZjdnZaR2+JkShwFcpqkpYw8YAUKTgTb0EEgnvaY9X1dcjBHOGDbBeA90XPjuA6kY3RqfH4bqJGbDbFEwdloyrxg/E1GHJXQYGU4cl49oJA6GqwH9+sDOoW33UNDajoq4J720pxL0dZMCKqxqxcNVWrM0r6vVzdNdeRYWvkXFufkWvn4Mo0GmtPWQl2CyyUiXgMcNmIr1KVMKxm9tc6IO5ShQAxgyIw4fbT1ii8KC0uhFvbj4CAHjih6N7lbV5/PLR+GxPKXadqMbfthzDjZMHix6mKVRVxYZD5fjHjiLk5pfj0Mmue+ep6HsGzN/2Kv4+jigYaeeW6AwbZ1jFCu7Ui8XJXCDvbnPiBevWVBqt8GCPBTJsb2w6gmaPinMzEzF9eEqvjpES48BPfzAcAPCHzw/C5faIHKIpNh8ux4//tAm3vLIZf8092m2wpulrBszf9ir+Po4oGCmS17BZpRgs0AX3ldzi9DVsEk6StlNpYUG+Nmd0y5Rofnkd6lxu08bR2OzBm5uPAgDumJHVp2PNm5KJ1DgHjlc24O1vC0UMzxRujxe/+dce/PjlTcgtqEBEmA23nDcYf/7Jufj+v2bj9z8+26/j5J3o3fZdWnuVzijwrZWbnJXUq+MTBQMtw8aiA2tjwGYmiY1ztR5sAIJ+MXVKjAOpcQ6oKrC3uMa0cXzw/XFU1DVhYEIkZmen9ulYznA7fvoD31ZJf/j8IBqaAi/LVl7rwk/+kouXvzoMALhpcga++sWF+PU1YzE7OxWJ0RFIi/Ov/9lv/rkHd638Drn5FX7f4Hi9Kv7w+QFUdtELD2jfXoUoFGlr2NiHzdoYsFmAzDVs4XYlJNLRrYUH5mykrqoq/vJ1PgBgwfQhQgo9bjg3A4MSI3GyxoU3NhX0+XhGKq914ccvb8KGQ+WIjrBj+S0TsOTacUiLbz/1ODkrCenxzi77NDnCbFAB/Ht3CW7400ZcvWwDPtx+AvVNHWdTVVXFl/tP4scvb8Tznx6ACuCCs/ohzY/2KkShSAvYuJeotbHowESKxHaC2j6iYUG6j+jpsgfE4Yt9J00rPFh/oAwHSmsRHWHHDZMyhBwzIsyGBy8agV/8bQde/iofP5k6BM5wu5Bjy1TV0IxbX83FwdJapMc7sfL2yRiRGtvhY+02BYvmZmPhqq3wNRZopZ0dL9w4HsP7x+LVr/Px3tZj2F5YiQf++j0i7DZMzkrC6PRYJMc4YFcUHCitwfdHK3GgtBaAL9j79TVjcd3EQe12OuiqvQpRqGEftsDAgM1EMvcSbfa2ZthCgbZFVd5xcwI2bZ3ZjyYOQpxT3A4FV58zEM9/egDHKxvwty3HMG9KprBjy9DY7MGC13Kxu6gaKTERePPO8zC0X0yXvzMnJx3L5004ow9b2ml92JZcOxYPX3IW3th4BO9/fwyFFQ34+mAZvj5YdsYxoyLsuHHSYNw5M0vfdkprr0JE7elr2AR3EZLVYzRUMWAzkczGuW59H9HQyLCNG+QL2PYWV8Pl9sARZlwmqrK+Cf/eXQLAN40pUrjdhrvPH4pFH+7Cn746hBsnZVi2r56qqvivv+dh69FKxEeG4407ug/WNHNy0jE7O63bDFhKjAM/n30WfnbxCBwuq8PXB8pw7FQ9ymub0OTxYmi/GJyVGoMZw1OQEBUh459JFHRa17Bx83crY8BmAXKKDny3SsHeg00zKDFS32x9b1ENzjZwh4DV206gyePF6PQ45AyMF378G87NwAufHUBhRQP+ubMIV40fKPw5RHjr20K8u+UYbAqw7JYJevWuv3qSAVMUBcP6xWCYnwEhEXVOWznjEXwx4gyrWNa8VQ8RMu869IAtRNawKYqiB2nbj1Ua+tzvbvFNh14/cZCU40dG2LFg2hAAwPJ1h6S0gemrHccqsWj1LgDALy4d1esedERkvNadDmRt/h4aiQPZQuNqblFSiw682pRo6Jwo4wYlAAC2FxpXKbqnqBp5x6sRbldw9TnyMl8/mToE0RF27C2uwbr9J6U9T280Nnvws7e3ocnjxSXZqbj3gqFmD4mIesAuqa0HicWAzUStRQfiz5LWth6h8xKf3bKOzcgM27vfHQMAXDQqFUnR8tZMxUeF45aWgoPlXxyS9jy9sfTzgzh8sg79Yh343+vODok2MkTBRDtlhW9NJfRoFDpXcwuT8abW23qEUMCmZdgOnaxFTWPHzVJFcnu8+HD7cQDA9efKmQ5t644ZWYiw25BbUIHvCqyxWfnuE9X445e+APJ/rhqD+C52FSAia5K90wHv4cQInau5BbVuTSX+2O4Qa+sBAP1iHRiYEAlVBXYelz8t+s2hcpTVNiEpOgLnn9VP+vOlxjlx7QTftKsWJJnJ7fHil+/tgNur4rKcNDagJQpQepWo6LYeTLEJxYDNTBJvO5rcWuPc0AnYgNb2HjuOyQ/YVm/zZdd+ODbdsKnnu88fCkUBPt1Tin0mbsMFAH/5Jh87j1chzhmGxVeNMXUsRNR70tt6SDlq6GHAZiKpfdi8WluP0HqJtUrRHZLXsTU2e/BxXjEA4KrxA6Q+V1tD+8Xgspw0AOZm2QrK6vDcJ/sBAE/8MBv9Y53d/AYRWZWsth4kluFX84KCAgwZMgSzZs3Svx599FGjh2EpUqZEW9awRYRYwKZl2GRXin62pxR1TR4MTIjEhMGJUp/rdAsvGA4A+HD7CRRW1Bv63ICvSOZX7++Ay+3F9OHJhqzfIyJ57JLaenCnA7FMaZw7f/58/Pd//7cZT20pepWohGOHWuNczdiB8VAU4HhlA07WuNAv1tH9L/WCVmxw5fgBsBk87Tx2UDxmjkjB+gNleGX9YSy+Kkf6c7bdh3Pn8SpsOlyByHA7llwzjlWhRAFO0Td/l3V8OccNNdzpwEQy+7A1h9jm75pYZziG9YvBwdJabD16CpeOSRP+HFUNzfhir68XmpHToW0tvGAY1h8ow1vfFuKnF41ASoycwBQA1uYVnbHPJwD8cGwaBidHSXteIjKG7CpREsOUq/k333yDiy++GDNmzMA999yDsrIzN29uy+Vyobq6ut1XMJC5+XsoVolqJg1JAgDk5stpffFxXjGaPF6MTI3FqLSebb8kytRhyTh7UDxcbi9WfFMg7XnW5hVh4aqtZwRrAPC3rcexNq9I2nMTkTG0SQKv6M65jP+EMjxgczqdyM7Oxocffoj169cjNjYWF110ETweT6e/s2TJEsTHx+tfGRliN9g2S2soJaNxbuj1YdNMGSo3YFvdZjrULIqiYOGsYQCA1zcWoKpBfN85j1fF4jW7O313KgAWr9ktvNkmERnLJnmnA25NJYbQq/kVV1wBRVE6/SooKEBaWhpeeOEFREVFQVEUPPXUU9i9ezc+//zzTo/72GOPoaqqSv8qLCwUOWzTySk6CN0M2+QsX8C260QVqgU30C2tbsSGQ+UAgCvPNi9gA4BLstMwon8MahrdePmrw9h4qByrtx3HxkPlQoKo3PyKDjNrGhVAUVWjtMCYiIyhBWzCN38XerSOhVIwKHQN2wcffNBlpszhOHOdTVRUFFJSUlBQUNDl73X0u4FO5kJMfS/REFvDBgDp8ZEYnBSFoxX12HLkFC4c2V/YsdfsKIKqAhMzE5GRZO76LZtNwcOXnIV7V23Fsi8O4qUvDuo/S493YtHc7D41sy2t6TxY683jiMiatDVs0jZ/D52YSiqhV/Pw8HA4nc5OvxRFwVtvvYXvvvtO/53m5mZUVFRg4EB5G2dblaKXUos/dpM7NKtENee1ZNk2Hxab/fmwpVmuWcUGp9M+YE9/CxVXNWLhqq19WmPmb2819mAjCmyy9hIlsQxPv+zduxfLly/XLzTLli1Deno6LrzwQqOHYhkyG+eG0ubvbWnTorn55cKOmV9Wh+3HqmC3Kbh8rPnbMHm8Kp76x54Of6a9o/qyxmxyVhJS4zrPbCvwZfK0/9dEFJhaq0TFHldWxi5UGX41v+6661BbW4tp06ZhxowZ+Oijj7B27VpERkYaPRTLkNk4N9S2ptJMGZoMwLdFVX2TW8gxP9x2AgAwY3iK1DYa/pK9xsxuUzAyLbbDn2nvqkVzs/UPeyIKTK17iTLAsjLD+7Dl5OTg7bffNvppLUnmvL5WJRoeFpoZtkGJkRgQ78SJqkZsPVKJGSNS+nQ8VVXx95bpULOLDTSy15h9ursEX+33tdxJig5HRV1rAUeagDVyRGQNeluPACw6CCVsnGsirbpFxptanxIN0eyHoiiYnJWEv287gdz88j4HbFuOnEJ+WR2iIuyYkyO+GW9vyFxjVlrTiEff2wEAuHNGFh67fLS+00H/WN80KDNrRMFBVpWohruhiBGa6ReLkNk4t3VrqtB9ibVp0a8OdN2Y2R9/23IMAHD52HREO6xxnzM5Kwnp8c5Oi9p7u8bM7fHi4Xe2o6KuCaPSYvGLOSNhtymYOiwZV40fiKnDkhmsEQUR2X3YSIzQvZpbiIyig9bGuaF7Yb1wlK+dx7bCSpRU9771RH2TG//Y4au2vH6idTY6t9sULJqbDQAdBm0qerfG7Ol/7sH6A2Vwhtvw4k3nwBFm7/tgiciy9KIDwREbaw7EYsBmIpmhlN44NwT7sGlS45w4Z3ACAODfu0t6fZyPdxWj1uXG4KQoy1VEzslJx/J5E5AWf+a0Z7TDjjED4nt0vNc3FGDFhgIAwPM/Ho+zUjsuOiCi4KFIWsOmH1/KUUNP6F7NLUCf1pcxJao1zg3hDBvg2w0AAD7pQ8CmTYdeN3GQJddizMlJx9e//AH+etcUvHDjeLy+YDLGDIhDncuDe97Y4neV7Ptbj2Hxml0AgEfnjGRBAVGI0DJs7MNmbQzYTCS16IBr2AAAl4xJBQBsPFTWq22qCivq9a2orp1g3ebObdeYXTCyH17+yblIjo7A7qJq3PCnjThR2dDp76qqihc/O4CH3tkOrwr8+NwMLLxgmIGjJyIz2SQ1cTcy/AuF6dfQvppbhIzmgnpbjxDPsA3rF4Nh/aLR7FGxbt/JHv/+6xsKoKrAzBEpGJRo7lZUPTEwIRKv3HYukqIjkHe8Glcu/QZf7Cs9Y43KnqJq3LVyC3737/0AgHsuGIol1461ZCaRiORoLTrg1lRWZo1ytxAltw9bS4YthNewaS4Zk4bl6w7hk13FPeqhVtPYjLe+LQQA3D4jS9bwpDlncCJW/8d03LXyO+wtrsGC177FoMRIXDw6FS63F8dO1WN9SwWtTQEWX5WDW6dkmjxqIjKaVpckfPP3UEh7GYgBmwXImRJllajmkuxULF93COv2nURjswfOcP+qHt/+thC1LjeG94/BBSP6SR6lHBlJUXhv4TQ8u3Yv3t96HMdONehFBYDvpuGHY9PxwEUjWGBAFKJaN3+Xc3xehcRgwGYimZu/h/peom2dPShB3/Xgw+0ncMO5Gd3+jtvjxWvfFAAAbp+eBVsA9x2LdoRh8VU5eOzy0fh4VzF2HKtCrDMMSdERmDYsGcP7M1AjCmXatYhFB9bGgM0CZJwirWvYGLDZbArmTx+C3/xrL17+6jCumzCo2wDs410lOF7ZgMSocEsXG/SEM9yOq8YPxFXjg+PfQ0RiaJcJbk1lbbyam0hmzqZ1p4PAzQyJdNPkwYh1hOFgaS0+31va5WOb3F78/lPfIvx5UzL9nkIlIgpEsjd/ZxGTGAzYTNS6NZX4k0RbwxbKjXPbinWG4+YpgwEAL391uMvHvvL1YRwsrUVKTATunDHUiOEREZlG2tZUTLEJxau5iST2zUWzlxm2090+PQvhdgW5BRXYcuQUAN+ajY2HyrF623FsPFSOI+V1ePGzAwCAxy8fjfiocDOHTEQknfzN36UcNuRwDZuJ9DSxjKID9mE7Q2qcE1eNH4i/bTmGX763AwsvGIrffrIfRVWt+4w6wmxwub04LysJ15zDtV5EFPxkrWEjsZhhC1L6XqIsOmjnkUtGIi3OiYOltXj43R3tgjUAcLl9/98uHZPKdRdEFBJkrWFTOScqFK/mJmpNsIl/Uzdpfdi4hq2dtHgn/jL/3G4LPv68Pp8l7kQUErSqeVkfebz1FYNXcxPpa9ik9mHjqXK6qgZ3tyFyUVUjcvMrDBkPEZGZ9J0OeJNqaQzYzCSzca6+0wFf4tOV1jR2/6AePI6IKJDZ9WuR6K2phB4u5PFqHqRa9xJlhu10/WOdQh9HRBTIFMlVoiwTFYMBm4la23pI6MPWktqOCONLfLrJWUlIj3d2uq5CAZAe78TkrCQjh0VEZAq7pDVszLCJxau5iVob54o9rter6msRmGE7k92mYNHcbABnLobV/r5obrb+IUZEFMy0jzppOx1IOWroYcBmIqXlbSz6FNGa5gJcw9aZOTnpWD5vAtLi2097psU7sXzeBMzJSTdpZERExmqtEmVKzMrYODcIaQUHAKtEuzInJx2zs9OQm1+B0ppG9I/1TYMys0ZEoUTf6cDbzQN7iH3YxGLAZiJZU6JtAzb2Yeua3aZg6rBks4dBRGQaWVWiGtYciMGruYla38NiT5K2U6LMsBERUVe0gEp0lShnWMViwGYiWRm2ti09uL0SERF1RVaVqEZh2YEQDNgsQPQ50to0lycJERF1TdZeoiQWAzYTybrr0DJs4Vy/RkRE3dDbeoieEhV6NOIV3Uz6lKjYt7XWNJcZNiIi6o7sth5cmSMGAzYTte50IJaeYWMPNiIi6oasth4kFq/oJlIkbf7e3LKGjQEbERF1h5u/BwZe0YOQW6sS5ZQoERF1Q1ZbD/34Uo4aehiwmUjelCj3ESUiIv/Ia+vBFJtIDNhMpEgrOuAaNiIi8o/sth4sOhCDV3QTyXoTu7mGjYiI/MTN3wMDr+hBqIlr2IiIyE/a6hmP4Awb4z+xGLCZSGucK2vzdzbOJSKi7tgkdSzQcGsqMXhFN5G+hk3wwkxtDRszbERE1B2bpGsRE2xiMWCzAFl92MK4ho2IiLqh9QSVtpUocwdC8IoehLQ+bBHMsBERUTf0KlEuOrM0BmwmkrfTQcuUKNewERFRN1o3fxd7XNEtq0Idr+gmam2cK/ZN3TolygwbERF1zSZpayoNr0RiMGAzUWvjXLHHZeNcIiLym55hY0bMynhFD0LcmoqIiPzVutOB2OMy/BOLAZuJ9D5sgo+r92EL48tLRERda23rIYfCvamE4BXdRErrIjahtKKDcGbYiIioG7LWsHGGVSwGbCaSVnSgN87ly0tERF1TJK9hY+pADF7RTSR783dWiRIRUXdsshvnkhAM2CxA/F6i2pQoX14iIuqarMa5jP/E4hXdVHKKDpq9zLAREZF/ZLWYOv341DcM2EzUepII3vxd3+mAZwkREXXNJmkNG3c6EIsBm4lkhVMt8RqLDoiIqFuytklsPb6c44YaXtEtQPQ54vEyw0ZERP7h5u+BgQGbiWTd1bhb1rDZGbAREVE3bJLXsJEYDNhMJKlvrn6XxICNiIi6IzvDprATmxAM2Ewkuw8bAzYiIuqO7Ma5JAYDNisQfJJ4tLYeDNiIiKgbWgZMdONcxn9iMWAzkd7WQ/BxW9ew8eUlIqKuaZcKWW04WCUqBq/oJtLuakSfI1pamxk2IiLqjk1SAZzofbJDHQM2M0lew2ZjwEZERN2Q1TiXxJISsHm9Xjz77LNwOBwoKCg44+d79+7F+eefj/PPPx9Tp07F999/L2MYAUP0XQjXsBERkb8Ubv4eEKQEbNdffz3q6urQ1NR0xs+am5sxd+5c3Hffffjqq6/wxBNP4IorrkB9fb2MoVia3tZD8EniYVsPIiLyk7TN3xkACiUlYHv++eexYMGCDn/28ccf49SpU7jhhhsAAD/84Q8RFhaGDz74QMZQLE1241xm2IiIqDuyG+cqrDoQIkzGQTMyMjqcCgWAzZs3Y/To0bC1qWAcO3YsNm/ejFtuuaXD33G5XHC5XPrfq6qqAADV1dXiBm2C+toaeF31aG60C/23NNb5jttQX4vq6khhxyUiouBTV1PvuxapNqHXouaGOnhd9aivrZF2vdaeo662GtXVsVKeQybt/4s/FbpSAraulJSUICEhod33EhISUFJS0unvLFmyBIsXLz7j+xkZGaKHZ4pCAPG/En/cuc+LPyYREQWv+GfFH/Om58Uf83TzDHgOmWpqahAfH9/lY3oUsF1xxRX45z//2enP8/PzMWTIkJ4c0i+PPfYYHnroIf3vXq8XFRUVSE5Olppqra6uRkZGBgoLCxEXFyftechcfJ1DB1/r0MHXOjQE+uusqipqamowYMCAbh/bo4Dtgw8+gMfj6fTnDoej22OkpqZiz5497b5XWVmJoUOHdnnc0499epZOpri4uIB8I1DP8HUOHXytQwdf69AQyK9zd5k1TY+KDsLDw+F0Ojv98ifbdd5552HPnj3t5mt37tyJyZMn92QoRERERCHD8Ma5l156KRITE/Huu+8CAD766CO43W5ce+21Rg+FiIiIKCBIKTp44okn8OmnnwIAbrzxRpx//vl49lnfSsbw8HCsWbMGd999N5YuXYrm5mb84x//QFRUlIyh9InD4cCiRYv8muqlwMXXOXTwtQ4dfK1DQyi9zooqa7dXIiIiIhKCe4kSERERWRwDNiIiIiKLY8BGREREZHEM2IiIiIgsjgFbF5566ilMmDABEydOxKOPPurXXl8UWObPn49Zs2a1+9q9e7fZwyJB9u/fj0mTJmH+/Pln/Iznd/Do7HXm+R083G43/vCHP+iv44QJE7Bq1ap2P//pT3+Kc889FxMmTMBzzz1n4mjlMHwv0UCxYsUKvP/++9i8eTPsdjtmzpyJF198EQ8++KDZQyPB1q1bZ/YQSILPPvsML7zwApKTk8/4Gc/v4NHV6wzw/A4Wx44dw7PPPovt27cjKSkJO3bswKRJk5CVlYXp06fj6aefxqFDh/Dtt9+irq4O48aNw/Dhw3HVVVeZPXRhmGHrxNKlS7FgwQI4HA6EhYXhrrvuwtKlS80eFhH5aeTIkVi9ejXS0tLO+BnP7+DR1etMwSM2NhZPPfUUkpKSAADjxo3D2LFj8cknn8Dr9WLZsmW45557oCgKYmJiMG/evKA7pxmwdaCpqQnbtm1DTk6O/r1x48bh4MGDqKioMHFkJMN9992HmTNnYvbs2foOHBT4Bg0a1OF2eTy/g0tnr7OG53dwSE5OxoIFC9p9r6GhAampqcjPz8fJkyfPOKc3b95s9DCl4pRoB8rKyuDxeNptMK/9uaSkRI/wKfBlZ2dj6tSpWLZsGQ4cOICZM2cCAK6//nqTR0ay8PwOHTy/g9f+/ftx8uRJ3HTTTdizZw8AnHFO19TUoKGhAZGRkSaNUixm2CikPfroo/qH+IgRI3D77bfj+eefN3dQRCQEz+/g5PF4cP/99+OVV15BYmKi2cMxDAO2DiQnJ8Nut6OyslL/nvbn1NRUcwZFhsjMzERBQYHZwyCJeH6HLp7fweFnP/sZrrjiClx55ZUAWs/b08/p2NjYoMmuAQzYOuRwODB+/Hjs2rVL/97OnTsxbNgwTpcEmUceeaTd30tKSjBw4ECTRkNG4PkdOnh+B58nn3wSSUlJeOCBB+ByuXDgwAFkZWWhX79+Z5zTkydPNnGk4jFg68T999+P1157DS6XC263G6+88gruv/9+s4dFgr300kvYt28fAKCiogIrV67ssGcXBRee36GB53dw+f3vf4+jR4/iF7/4BWpra3Ho0CH8+te/hs1mw3333YeXX34Zqqqirq4Oq1atCrpzWlHZLbJTTz31FFavXg0AuOiii/DMM890WY1Egee5557Du+++C4fDgfr6elx//fV45JFHYLPxXibQHTx4EHfeeSf27t0LABg1ahSWLVuG7OxsADy/g0VXrzPP7+Cxf/9+jBo16owG17fddhtWrFgBt9uNn/3sZ9i8eTM8Hg9uueUWPPzwwyaNVg4GbEREREQWx9sMIiIiIotjwEZERERkcQzYiIiIiCyOARsRERGRxTFgIyIiIrI4BmxEREREFseAjYiIiMjiGLARERERWRwDNiIiIiKLY8BGREREZHEM2IiIiIgs7v8Dt8PSNWpkLlwAAAAASUVORK5CYII=",
       "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
+       "<Figure size 600x400 with 1 Axes>"
       ]
      },
      "metadata": {},
@@ -694,6 +756,13 @@
     "# Now replot fitted functions for xtest = 0 to 21 so D=20 interpolates all points\n",
     "# (This messes up the mse vs degree plot, so we don't recompute that)\n",
     "\n",
+    "#https://nipunbatra.github.io/blog/posts/2014-06-02-latexify.html\n",
+    "#os.environ[\"LATEXIFY\"] = \"1\"\n",
+    "#os.environ.pop('LATEXIFY', None)\n",
+    "#pml.latexify()\n",
+    "\n",
+    "my_latexify(fig_width=6, fig_height=4)\n",
+    "\n",
     "xtrain, ytrain, xtest, ytest = make_1dregression_data(n=21, m=21)\n",
     "\n",
     "# Rescaling data\n",
@@ -730,7 +799,7 @@
     "    ax.plot(xtest, ytest_pred_stored[deg - 1])\n",
     "    ax.set_ylim((-10, 15))\n",
     "    plt.title(\"degree {}\".format(deg))\n",
-    "    pml.savefig(\"polyfitDegree{}.pdf\".format(deg))\n",
+    "    pml.savefig(\"polyfitDegree{}_range21.pdf\".format(deg))\n",
     "    plt.show()"
    ]
   }
diff --git a/notebooks/figures/polyfitDegree1.pdf b/notebooks/figures/polyfitDegree1.pdf
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diff --git a/notebooks/figures/polyfitDegree14.pdf b/notebooks/figures/polyfitDegree14.pdf
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diff --git a/notebooks/figures/polyfitDegree1FitVsActualTest.pdf b/notebooks/figures/polyfitDegree1FitVsActualTest.pdf
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diff --git a/notebooks/figures/polyfitDegree1FitVsActualTrain.pdf b/notebooks/figures/polyfitDegree1FitVsActualTrain.pdf
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