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cc-ats · Oct 28, 2023 · 2416c05 · 2416c05
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diff --git a/Lesson1_FNN.ipynb b/Lesson1_FNN.ipynb
@@ -87,7 +87,7 @@
         "mueller_brown_potential_vectorized = np.vectorize(mueller_brown_potential, otypes=[np.float32])\n",
         "Z = mueller_brown_potential_vectorized(X, Y)\n",
         "\n",
-        "# keep only low-energy points for training.\n",
+        "# keep only low-energy points for training\n",
         "train_mask = Z < 10\n",
         "X_train, Y_train, Z_train = X[train_mask], Y[train_mask], Z[train_mask]\n",
         "\n",
@@ -126,8 +126,7 @@
         "fig.update_layout(title='Mueller-Brown Potential', width=500, height=500,\n",
         "                  scene = dict(\n",
         "                      zaxis = dict(dtick=3, range=[-15, 15]),\n",
-        "                      camera_eye = dict(x=-1.2, y=-1.2, z=1.2)))\n",
-        "fig.show()"
+        "                      camera_eye = dict(x=-1.2, y=-1.2, z=1.2)))"
       ]
     },
     {
@@ -149,21 +148,23 @@
       "source": [
         "import matplotlib.pyplot as plt\n",
         "\n",
-        "def plot_contour_map(X, Y, Z, title, colorscale='rainbow', levels=[-12, -8, -4, 0, 4, 8, 10], vmin=-15, vmax=10):\n",
-        "    fig = plt.figure(figsize=(3, 2.5), dpi=150)\n",
-        "    ct = plt.contour(X, Y, Z, levels, colors='k')\n",
-        "    plt.clabel(ct, inline=True, fmt='%3.0f', fontsize=8)\n",
-        "    ct = plt.contourf(X, Y, Z, levels, cmap=colorscale, extend='both', vmin=vmin, vmax=vmax)\n",
-        "    plt.xlabel(\"x\", labelpad=-0.75)\n",
-        "    plt.ylabel(\"y\", labelpad=2.5)\n",
-        "    plt.tick_params(axis='both', pad=2, labelsize=8)\n",
-        "    cbar = plt.colorbar()\n",
+        "def plot_contour_map(X, Y, Z, ax, title, colorscale='rainbow', levels=None):\n",
+        "    if levels is None:\n",
+        "        levels = [-12, -8, -4, 0, 4, 8, 10]\n",
+        "    ct = ax.contour(X, Y, Z, levels, colors='k')\n",
+        "    ax.clabel(ct, inline=True, fmt='%3.0f', fontsize=8)\n",
+        "    ct = ax.contourf(X, Y, Z, levels, cmap=colorscale, extend='both', vmin=levels[0], vmax=levels[-1])\n",
+        "    ax.set_xlabel(\"x\", labelpad=-0.75)\n",
+        "    ax.set_ylabel(\"y\", labelpad=2.5)\n",
+        "    ax.tick_params(axis='both', pad=2, labelsize=8)\n",
+        "    cbar = plt.colorbar(ct)\n",
         "    cbar.ax.tick_params(labelsize=8)\n",
-        "    plt.title(title, fontsize=8)\n",
-        "    plt.tight_layout()\n",
-        "    plt.show()\n",
+        "    ax.set_title(title, fontsize=8)\n",
+        "\n",
         "\n",
-        "plot_contour_map(X, Y, Z, 'Mueller-Brown Potential')"
+        "fig, ax = plt.subplots(figsize=(3, 2.5), dpi=150)\n",
+        "plot_contour_map(X, Y, Z, ax=ax, title='Mueller-Brown Potential')\n",
+        "fig.tight_layout()"
       ]
     },
     {
@@ -353,9 +354,11 @@
         "Z_pred = model(torch.from_numpy(np.column_stack((X.flatten(), Y.flatten())))).detach().numpy().reshape(Z.shape)\n",
         "Z_diff = Z_pred - Z\n",
         "\n",
-        "plot_contour_map(X, Y, Z, title='(a) Reference')\n",
-        "plot_contour_map(X, Y, Z_pred, title='(b) Predicted')\n",
-        "plot_contour_map(X, Y, Z_diff, title='(c) Difference', levels=[-4, -2, 0, 2, 4])"
+        "fig, ax = plt.subplots(3, figsize=(3, 7.5), dpi=150)\n",
+        "plot_contour_map(X, Y, Z, ax=ax[0], title='(a) Reference')\n",
+        "plot_contour_map(X, Y, Z_pred, ax=ax[1], title='(b) Predicted')\n",
+        "plot_contour_map(X, Y, Z_diff, ax=ax[2], title='(c) Difference', levels=[-4, -2, 0, 2, 4])\n",
+        "fig.tight_layout()"
       ]
     },
     {
@@ -556,9 +559,11 @@
         "Z_pred = model(torch.from_numpy(np.column_stack((X.flatten(), Y.flatten())))).detach().numpy().reshape(Z.shape)\n",
         "Z_diff = Z_pred - Z\n",
         "\n",
-        "plot_contour_map(X, Y, Z, title='(a) Reference')\n",
-        "plot_contour_map(X, Y, Z_pred, title='(b) Predicted')\n",
-        "plot_contour_map(X, Y, Z_diff, title='(c) Difference', levels=[-4, -2, 0, 2, 4])"
+        "fig, ax = plt.subplots(3, figsize=(3, 7.5), dpi=150)\n",
+        "plot_contour_map(X, Y, Z, ax=ax[0], title='(a) Reference')\n",
+        "plot_contour_map(X, Y, Z_pred, ax=ax[1], title='(b) Predicted')\n",
+        "plot_contour_map(X, Y, Z_diff, ax=ax[2], title='(c) Difference', levels=[-4, -2, 0, 2, 4])\n",
+        "fig.tight_layout()"
       ]
     },
     {
@@ -681,9 +686,11 @@
         "Z_pred = model(torch.from_numpy(np.column_stack((X.flatten(), Y.flatten())))).detach().numpy().reshape(Z.shape)\n",
         "Z_diff = Z_pred - Z\n",
         "\n",
-        "plot_contour_map(X, Y, Z, title='(a) Reference')\n",
-        "plot_contour_map(X, Y, Z_pred, title='(b) Predicted')\n",
-        "plot_contour_map(X, Y, Z_diff, title='(c) Difference', levels=[-4, -2, 0, 2, 4])"
+        "fig, ax = plt.subplots(3, figsize=(3, 7.5), dpi=150)\n",
+        "plot_contour_map(X, Y, Z, ax=ax[0], title='(a) Reference')\n",
+        "plot_contour_map(X, Y, Z_pred, ax=ax[1], title='(b) Predicted')\n",
+        "plot_contour_map(X, Y, Z_diff, ax=ax[2], title='(c) Difference', levels=[-4, -2, 0, 2, 4])\n",
+        "fig.tight_layout()"
       ]
     }
   ],
@@ -707,7 +714,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.10.12"
+      "version": "3.10.13"
     },
     "vscode": {
       "interpreter": {

diff --git a/Lesson2_GPR.ipynb b/Lesson2_GPR.ipynb