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" \n",
" 
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"
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" "
],
"text/plain": [
"Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%matplotlib widget\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"\n",
"fig = plt.figure(figsize=(10, 5))\n",
"ax = fig.add_subplot(projection='3d')\n",
"cmap = plt.get_cmap(\"tab20\")\n",
"\n",
"# Plot each sample category individually such that we can set label name.\n",
"for i, cat in enumerate(categories):\n",
" sub_matrix = np.array(samples[samples[\"category\"] == cat][\"embed_vis\"].to_list())\n",
" x=sub_matrix[:, 0]\n",
" y=sub_matrix[:, 1]\n",
" z=sub_matrix[:, 2]\n",
" colors = [cmap(i/len(categories))] * len(sub_matrix)\n",
" ax.scatter(x, y, zs=z, zdir='z', c=colors, label=cat)\n",
"\n",
"ax.set_xlabel('x')\n",
"ax.set_ylabel('y')\n",
"ax.set_zlabel('z')\n",
"ax.legend(bbox_to_anchor=(1.1, 1))\n"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3.9.9 ('openai')",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.9"
},
"vscode": {
"interpreter": {
"hash": "365536dcbde60510dc9073d6b991cd35db2d9bac356a11f5b64279a5e6708b97"
}
}
},
"nbformat": 4,
"nbformat_minor": 5
}
\n",
"