{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "b936cb30",
   "metadata": {},
   "source": [
    "# Enzymatic\n",
    "\n",
    "For slightly more complex example,\n",
    "`SimBio` contains compound reactions,\n",
    "consisting of many single or compound reactions.\n",
    "For instance,\n",
    "from `simbio.reactions.enzymatic`\n",
    "we can import a `MichaelisMenten` reaction,\n",
    "which binds a substrate $S$ to an enzyme $E$\n",
    "creating an intermediate bound species $E:S$,\n",
    "before converting to the product $P$ species:\n",
    "\n",
    "$$ S + E ↔ E:S → P + E $$\n",
    "\n",
    "It consists of a `ReversibleSynthesis` ($ S + E ↔ E:S$)\n",
    "and a `Dissociation` ($E:S → P + E$) reaction.\n",
    "In turn,\n",
    "`ReversibleSynthesis` is also a compound reaction,\n",
    "consisting of a `Synthesis` ($ S + E → E:S$)\n",
    "and `Dissociation` ($ E:S → S + E$) reactions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "4382e3e9",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "from simbio.components import EmptyCompartment, Species\n",
    "from simbio.reactions.enzymatic import MichaelisMenten\n",
    "from simbio.simulator import Simulator"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "342a6873",
   "metadata": {},
   "source": [
    "When defining a model,\n",
    "we do not need to explicitly create every species.\n",
    "For instance,\n",
    "the intermediate species `ES`,\n",
    "is created inside the reaction\n",
    "by assigning it to a number."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c7c5d961",
   "metadata": {},
   "outputs": [],
   "source": [
    "class Model(EmptyCompartment):\n",
    "    enzyme: Species = 1\n",
    "    subtrate: Species = 1\n",
    "    product: Species = 0\n",
    "\n",
    "    catalyze = MichaelisMenten(\n",
    "        E=enzyme,\n",
    "        S=subtrate,\n",
    "        ES=0,  # \"nameless\" intermediate species\n",
    "        P=product,\n",
    "        forward_rate=1,\n",
    "        reverse_rate=1,\n",
    "        catalytic_rate=1,\n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "09ea7bf1",
   "metadata": {},
   "source": [
    "To simulate it,\n",
    "we feed the model into `Simulator`,\n",
    "and use the `.run()` method.\n",
    "It will compile and integrate an `ODE`-based simulation,\n",
    "returning a `pandas.DataFrame` with the result:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "44b4b71b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>enzyme</th>\n",
       "      <th>subtrate</th>\n",
       "      <th>catalyze.ES</th>\n",
       "      <th>product</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>time</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0.00000</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.10101</th>\n",
       "      <td>0.916804</td>\n",
       "      <td>0.912323</td>\n",
       "      <td>0.083196</td>\n",
       "      <td>0.004481</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.20202</th>\n",
       "      <td>0.860984</td>\n",
       "      <td>0.845092</td>\n",
       "      <td>0.139016</td>\n",
       "      <td>0.015891</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.30303</th>\n",
       "      <td>0.823633</td>\n",
       "      <td>0.791686</td>\n",
       "      <td>0.176367</td>\n",
       "      <td>0.031947</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.40404</th>\n",
       "      <td>0.798962</td>\n",
       "      <td>0.747866</td>\n",
       "      <td>0.201038</td>\n",
       "      <td>0.051096</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           enzyme  subtrate  catalyze.ES   product\n",
       "time                                              \n",
       "0.00000  1.000000  1.000000     0.000000  0.000000\n",
       "0.10101  0.916804  0.912323     0.083196  0.004481\n",
       "0.20202  0.860984  0.845092     0.139016  0.015891\n",
       "0.30303  0.823633  0.791686     0.176367  0.031947\n",
       "0.40404  0.798962  0.747866     0.201038  0.051096"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "simulator = Simulator(Model)\n",
    "\n",
    "t = np.linspace(0, 10, 100)\n",
    "df = simulator.run(t)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7c25bdb3",
   "metadata": {},
   "source": [
    "To visualize the time evolution,\n",
    "we can use the `DataFrame.plot` method:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "475f4f35",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot: xlabel='time'>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
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