shortcuts/notebooks/deno_tinygo_wasm.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Stats initialized\n",
      "\n",
      "Linear Regression Line:\n",
      "\tEstimated offset is:  -2.258540\n",
      "\tEstimated slope is:  -0.024285\n",
      "\tR^2 is:  0.882633\n"
     ]
    }
   ],
   "source": [
    "import stats from \"../stat/mod.ts\";\n",
    "\n",
    "const xs = [];\n",
    "const ys = [];\n",
    "\n",
    "for (let i = 0; i < 100; i++) {\n",
    "  xs.push(i);\n",
    "  ys.push(1 - Math.log(2 * i + 3 + Math.random() * 10));\n",
    "}\n",
    "\n",
    "const linreg = stats.LinearRegression(xs, ys, [], false);\n",
    "const r = stats.RSquared(xs, ys, [], linreg.alpha, linreg.beta);\n",
    "\n",
    "console.log(\"\\nLinear Regression Line:\");\n",
    "console.log(\"\\tEstimated offset is: \", linreg.alpha.toFixed(6));\n",
    "console.log(\"\\tEstimated slope is: \", linreg.beta.toFixed(6));\n",
    "console.log(\"\\tR^2 is: \", r.toFixed(6));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "![name](data:image/png;base64,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
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import plot from \"../plot/mod.ts?6\";\n",
    "\n",
    "plot.DrawPlot(\n",
    "    { \n",
    "        title: \"Test\", \n",
    "        //XLabel: \"X\", \n",
    "        YLabel: \"Y\", \n",
    "        width: 7.5, \n",
    "        height: 5 \n",
    "    }, \n",
    "    { type: \"scatter\", data: [xs, ys], legend: \"Data\", glyphStyleColor: \"#ff0000\" },\n",
    "    { type: \"line\", data: [xs, ys], legend: \"Line\", lineStyleColor: \"#00ff00\" },\n",
    ");\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{ alpha: \u001b[33m-2.258539916346346\u001b[39m, beta: \u001b[33m-0.02428470043839821\u001b[39m }"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stats.LinearRegression(xs, ys, [], false);"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Deno",
   "language": "typescript",
   "name": "deno"
  },
  "language_info": {
   "codemirror_mode": "typescript",
   "file_extension": ".ts",
   "mimetype": "text/x.typescript",
   "name": "typescript",
   "nbconvert_exporter": "script",
   "pygments_lexer": "typescript",
   "version": "5.6.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}