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+{
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+ {
+ "cell_type": "markdown",
+ "id": "dcddb3be-940b-4416-aec5-7159354c7cc0",
+ "metadata": {},
+ "source": [
+ "
Markov Chain Monte Carlo for fun and profit
\n",
+ " ๐ฒ โ๏ธ ๐ ๐งช
"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "6e51fe6c-a8b8-48ed-9e7f-70e18945e597",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import numpy as np\n",
+ "import matplotlib.pyplot as plt\n",
+ "\n",
+ "# This loads some custom styles for matplotlib\n",
+ "import json, matplotlib\n",
+ "with open(\"assets/matplotlibrc.json\") as f: matplotlib.rcParams.update(json.load(f))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "6327bffe-5a27-4643-929e-a9d41672cd2c",
+ "metadata": {},
+ "source": [
+ "## Packaging\n",
+ "\n",
+ "Now that we have some code, we're going to factor it out into a little python package, this has a few benefits:\n",
+ " - foo\n",
+ " - bah"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "58bef986-9d69-4ef6-8a64-9eaf29c3424e",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python [conda env:jupyter3.9] *",
+ "language": "python",
+ "name": "conda-env-jupyter3.9-py"
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+ "nbformat_minor": 5
+}