src/apply/flowchart/mermaid/quadratic_formula.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "cca11c7c",
   "metadata": {},
   "source": [
    "# quadratic_formula\n",
    "+ url https://ouhammmourachid.github.io/mermaid-py/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# install memraid-py\n",
    "%pip install mermaid-py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import mermaid as md"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ccfc4302",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%mermaidjs --img\n",
    "graph LR\n",
    "    B --> I --> P1 --> P2a & P2b --> O --> E\n",
    "    B([\"Begin\"])\n",
    "    I[\"a, b, c\"]\n",
    "    P1[\"D = b^2 - 4*a*c\"]\n",
    "    P2a[\"x1 = (-b - D^0.5) / (2a)\"]\n",
    "    P2b[\"x2 = (-b + D^0.5) / (2a)\"]\n",
    "    O[\"x1, x2\"]\n",
    "    E([\"End\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fce427fe",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "authors": [
   {
    "name": "Sparisoma Viridi"
   }
  ],
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.10.8"
  },
  "title": "quadratic_formula"
 },
 "nbformat": 4,
 "nbformat_minor": 5
}