Tutorials WIP

tutorials/tutorial2/tutorial.ipynb

@@ -16,7 +16,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "id": "ad0b8dd7",
    "metadata": {},
    "outputs": [],
@@ -32,6 +32,8 @@
     "\n",
     "import torch\n",
     "from torch.nn import Softplus\n",
+    "import matplotlib.pyplot as plt\n",
+    "plt.style.use('tableau-colorblind10')\n",
     "\n",
     "from pina.problem import SpatialProblem\n",
     "from pina.operator import laplacian\n",
@@ -40,7 +42,7 @@
     "from pina.trainer import Trainer\n",
     "from pina.domain import CartesianDomain\n",
     "from pina.equation import Equation, FixedValue\n",
-    "from pina import Condition, LabelTensor#,Plotter\n",
+    "from pina import Condition, LabelTensor\n",
     "from pina.callback import MetricTracker"
    ]
   },
@@ -512,14 +514,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": null,
    "id": "2855cea1",
    "metadata": {},
    "outputs": [],
    "source": [
-    "#plotter.plot_loss(trainer, logy=True, label='Standard')\n",
-    "#plotter.plot_loss(trainer_feat, logy=True,label='Static Features')\n",
-    "#plotter.plot_loss(trainer_learn, logy=True, label='Learnable Features')\n"
+    "trainer_metrics = trainer.callbacks[list_[0]].metrics\n",
+    "\n",
+    "loss = trainer_metrics['val_loss']\n",
+    "epochs = range(len(loss))\n",
+    "plt.plot(epochs, loss.cpu())\n",
+    "# plotting\n",
+    "plt.xlabel('epoch')\n",
+    "plt.ylabel('loss')\n",
+    "plt.yscale('log')\n"
    ]
   },
   {
@@ -557,7 +565,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.3"
+   "version": "3.12.7"
   }
  },
  "nbformat": 4,