add life table

notebooks/user/vbui/demo.ipynb

@@ -0,0 +1,145 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import warnings\n",
+    "import pandas as pd\n",
+    "import plotly.graph_objects as go\n",
+    "import plotly.express as px\n",
+    "\n",
+    "from autumn.core.inputs.tb_camau import queries\n",
+    "from autumn.core.inputs import get_death_rates_by_agegroup, get_life_expectancy_by_agegroup, get_crude_birth_rate\n",
+    "import pathlib"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "warnings.filterwarnings(\"ignore\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "age_string_map = {\n",
+    "    0: \"0-4\",\n",
+    "    5: \"5-14\",\n",
+    "    15: \"15-34\",\n",
+    "    35: \"35-49\",\n",
+    "    50: \"50+\",\n",
+    "}\n",
+    "age_breakpoints = [0,5,15,35,50]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def get_death_rates_by_year(year):\n",
+    "    death_rates_from_db =get_death_rates_by_agegroup(age_breakpoints, \"VNM\")\n",
+    "    df = pd.DataFrame(death_rates_from_db[0], index=death_rates_from_db[1])\n",
+    "    if year not in death_rates_from_db[1]:\n",
+    "        print(\"No data for this year!\")\n",
+    "    else:\n",
+    "        return(df.loc[year]) "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "death_series = get_death_rates_by_year(1952.5)\n",
+    "death_series"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "init_pop = 100000"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df = pd.DataFrame({\n",
+    "    'age': death_series.index,\n",
+    "    'qx': death_series.values\n",
+    "})\n",
+    "\n",
+    "# Initialize the 'lx' column with an initial population of 100,000 for age 0\n",
+    "df['lx'] = 100000\n",
+    "\n",
+    "# Calculate population 'lx' for each age group\n",
+    "for i in range(1, len(df)):\n",
+    "    df.loc[i, 'lx'] = df.loc[i - 1, 'lx'] - (df.loc[i - 1, 'qx'] * df.loc[i - 1, 'lx'])\n",
+    "\n",
+    "#calculate number of death\n",
+    "df[\"dx\"] = 0\n",
+    "for x in range(5):\n",
+    "    if x >=4:\n",
+    "        df[\"dx\"][x] = df[\"lx\"][x]\n",
+    "    else:\n",
+    "        df['dx'] =  df['lx'] * df['qx']\n",
+    "\n",
+    "#μx: is the force of mortality, i.e., represents the instantaneous rate at which people are dying.\n",
+    "df[\"μx\"] = 0\n",
+    "df[\"μx\"][0] = 2.0692602739726 * df[\"dx\"][0] /(2*df[\"lx\"][0])\n",
+    "for x in range(1,5):\n",
+    "    df[\"μx\"][x] = (df[\"dx\"][x-1]+df[\"dx\"][x])/(2*df[\"lx\"][x])\n",
+    "#Tx: is the total years of life to be lived by those aged exactly x (not the random variable Tx) until they all die\n",
+    "df[\"Tx\"] = 0\n",
+    "for x in range(5):\n",
+    "    df[\"Tx\"][x] = 0\n",
+    "    for y in range(x,5):\n",
+    "        df[\"Tx\"][x] += df[\"lx\"][y]\n",
+    "df[\"e0x\"] = df[\"Tx\"]/df[\"lx\"] - 0.5\n",
+    "\n",
+    "df[\"Lx\"] = 0.000\n",
+    "for x in range(5):\n",
+    "    df[\"Lx\"][x] = df[\"Tx\"][x]-df[\"lx\"][x]\n",
+    "df"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "autumn310",
+   "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": "3.10.0"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}