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Update tutorials 1 through 12 to current version 0.2

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This commit is contained in:
Matteo Bertocchi
2025-02-26 16:21:12 +01:00
committed by Nicola Demo
parent 10ea59e15a
commit 14a6008437
4 changed files with 70 additions and 62 deletions
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60
tutorials/tutorial4/tutorial.ipynb vendored
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@@ -869,16 +869,16 @@
"output = net(input_data).detach()\n",
"\n",
"# visualize data\n",
"fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(8, 3))\n",
"pic1 = axes[0].scatter(grid[:, 0], grid[:, 1], c=input_data[0, 0, :, -1])\n",
"axes[0].set_title(\"Real\")\n",
"fig.colorbar(pic1)\n",
"plt.subplot(1, 2, 2)\n",
"pic2 = axes[1].scatter(grid[:, 0], grid[:, 1], c=output[0, 0, :, -1])\n",
"axes[1].set_title(\"Autoencoder\")\n",
"fig.colorbar(pic2)\n",
"plt.tight_layout()\n",
"plt.show()\n"
"#fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(8, 3))\n",
"#pic1 = axes[0].scatter(grid[:, 0], grid[:, 1], c=input_data[0, 0, :, -1])\n",
"#axes[0].set_title(\"Real\")\n",
"#fig.colorbar(pic1)\n",
"#plt.subplot(1, 2, 2)\n",
"#pic2 = axes[1].scatter(grid[:, 0], grid[:, 1], c=output[0, 0, :, -1])\n",
"#axes[1].set_title(\"Autoencoder\")\n",
"#fig.colorbar(pic2)\n",
"#plt.tight_layout()\n",
"#plt.show()\n"
]
},
{
@@ -963,16 +963,16 @@
"output = net.decoder(latent, input_data2).detach()\n",
"\n",
"# show the picture\n",
"fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(8, 3))\n",
"pic1 = axes[0].scatter(grid2[:, 0], grid2[:, 1], c=input_data2[0, 0, :, -1])\n",
"axes[0].set_title(\"Real\")\n",
"fig.colorbar(pic1)\n",
"plt.subplot(1, 2, 2)\n",
"pic2 = axes[1].scatter(grid2[:, 0], grid2[:, 1], c=output[0, 0, :, -1])\n",
"axes[1].set_title(\"Up-sampling\")\n",
"fig.colorbar(pic2)\n",
"plt.tight_layout()\n",
"plt.show()\n"
"#fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(8, 3))\n",
"#pic1 = axes[0].scatter(grid2[:, 0], grid2[:, 1], c=input_data2[0, 0, :, -1])\n",
"#axes[0].set_title(\"Real\")\n",
"#fig.colorbar(pic1)\n",
"#plt.subplot(1, 2, 2)\n",
"#pic2 = axes[1].scatter(grid2[:, 0], grid2[:, 1], c=output[0, 0, :, -1])\n",
"# axes[1].set_title(\"Up-sampling\")\n",
"#fig.colorbar(pic2)\n",
"#plt.tight_layout()\n",
"#plt.show()\n"
]
},
{
@@ -1051,16 +1051,16 @@
"output = net.decoder(latent, input_data2).detach()\n",
"\n",
"# show the picture\n",
"fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(8, 3))\n",
"pic1 = axes[0].scatter(grid2[:, 0], grid2[:, 1], c=input_data2[0, 0, :, -1])\n",
"axes[0].set_title(\"Real\")\n",
"fig.colorbar(pic1)\n",
"plt.subplot(1, 2, 2)\n",
"pic2 = axes[1].scatter(grid2[:, 0], grid2[:, 1], c=output[0, 0, :, -1])\n",
"axes[1].set_title(\"Autoencoder not re-trained\")\n",
"fig.colorbar(pic2)\n",
"plt.tight_layout()\n",
"plt.show()\n",
"#fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(8, 3))\n",
"#pic1 = axes[0].scatter(grid2[:, 0], grid2[:, 1], c=input_data2[0, 0, :, -1])\n",
"#axes[0].set_title(\"Real\")\n",
"#fig.colorbar(pic1)\n",
"#plt.subplot(1, 2, 2)\n",
"#pic2 = axes[1].scatter(grid2[:, 0], grid2[:, 1], c=output[0, 0, :, -1])\n",
"#axes[1].set_title(\"Autoencoder not re-trained\")\n",
"#fig.colorbar(pic2)\n",
"#plt.tight_layout()\n",
"#plt.show()\n",
"\n",
"# calculate l2 error\n",
"print(f'l2 error: {l2_error(input_data2[0, 0, :, -1], output[0, 0, :, -1]):.2%}')"