included markov chain example weather simulation

notebooks/MCMC/markov_chain_weather.ipynb

+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "0938a32d-af05-440e-a207-b1af52425e98",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import random\n",
+    "# List with sunny and rainy\n",
+    "d = ['S', 'R']\n",
+    "# Define empty list\n",
+    "w = []\n",
+    "# Initialize first entry: Chooses randomly a value of list # d and adds (append) it to the empty list w\n",
+    "w.append(random.choice(d))\n",
+    "# Number of days\n",
+    "n = 1000"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "fd5f38eb-b522-4859-805b-d9cd4b0bd3b2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['S']"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "w"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "e98e5870-9f9e-446c-9714-e25d8585ff87",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'S S S S S S S R S S S S S S S S S S S S S S S S S S S R S S S S S S S R R S S S S S S S S S S S S R R R R S S S S S S S S R S S S R R R S R R S S R R S S S S S S S S R S S S S S S S S S S S S S S S S S R S R R S S S S S S S R R S R R R R R S S S S S S S S R S S S S S S S S S S S S S S R S S S R R R R R R S S S S S S S S S S S S S S S R S S S S R R S S S S S S S S S S S S S S S S S R S S S S S S S S S S S R R S S S S R S S S S S S S S S S S S S S S S S S S S S S R R R S S R R S S S S S S S S S S S S S S S S S S R R R R S S S S S S S S S S S S S R R R R R R R S S S S S S S S S R R S S S S S S S S S S S S S S S S S S S S S R S S S S S S S S S S S S S S S S S S S S S R R S S R S S S S S S S S S S S S S S S S S S S S S S S S R R R R S S S S S R R S R S S S R R S S S S S S S S S S R S S S S S S S S S S S S S S S S R R R R S S S S S R S S R R S S S S S S R S S R S S S S S S S S S S S S R R S S S S S S S S S S S S S S S S S R S S S S S S S S S S S S S S R S S S S S S S S S S S S S S R S S R S S S S S S S S S S S S S S S R R S S S S S S S S S R S S S S S S S S S S S S S S S S S S S S S R S S S S S S S S S S S S S S S S R R R R R S S S S S S R S S R R R R S S S S S S S S S R R R S S S S S R R R S S S S S S S S S S S S S S S S S S S S S S S S S S S R S S S S S S S S S R S S S R R R R R S S S R S S S S S R R R R S S S S S S S S S S S S S S S S S S S S S S S S R S S S S S S R R R R S R S S R R R R R R R S S S S S S S S S S R R R R R S S S S S S S S S S S S S R S S S S S S S S S S S S S S S S S R S S S S S S R R S S S S S S S S S S S S R S S S R S S S S S S S S S S S S S S S S S S S S S S S R S S S R R S S S S S S S S S S S S S R R R R S S R S S S S S S S S S S S S S S S S S S S S S S S S R S S S S S R S S R S S S S S S S S S R S S S S S S S S S S S S S S S S S S S R R S S S R S S S S S S S S S S S S S R R R R R S S S S R S S S S S S S S S S S S S S S S S S S S R R S S S S S R R S S S S S S S R R S S S S S R S S S S S S S S S R R S S S S S S S S S S S S S S S S S R R S S S S S S S'"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Markov chain\n",
+    "for i in range(n):\n",
+    "# If it's sunny on day i add randomly 'S' from d with\n",
+    "# absweight .9 or 'R' with weight 0.1\n",
+    "    if w[i] == 'S':\n",
+    "        w.append(random.choices(d, weights=[0.9, 0.1])[0])\n",
+    "    # If it's rainy on day i add randomly 'S' with weight .5\n",
+    "    # or 'R' with weight 0.5\n",
+    "    else:\n",
+    "        w.append(random.choices(d, weights=[0.5, 0.5])[0])\n",
+    "        # Removes quotes ' ' in list w\n",
+    "w_1 = ' '.join(w)\n",
+    "w_1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "6c8e96be-29f4-4ac7-a230-38fbccdcaa71",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.8231768231768232"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Probability of sunny days\n",
+    "w.count('S') / len(w)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
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+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.12"
+  }
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+}