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 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Basic Usage"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook illustrates some of the basic features of `Seagull`. Most of these are just animated outputs found in the Documentation. If you wish to add more examples, please create a Jupyter notebook and open up a Pull Request!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Some settings to show a JS animation\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams[\"animation.html\"] = \"jshtml\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seagull as sg\n",
    "import seagull.lifeforms as lf"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simple Pulsars\n",
    "\n",
    "In this example, we'll create four (4) `Pulsars` in a 40x40 board. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Initialize board\n",
    "board = sg.Board(size=(40,40))\n",
    "\n",
    "# Add three Pulsar lifeforms in various locations\n",
    "board.add(lf.Pulsar(), loc=(1,1))\n",
    "board.add(lf.Pulsar(), loc=(1,22))\n",
    "board.add(lf.Pulsar(), loc=(20,1))\n",
    "board.add(lf.Pulsar(), loc=(20,22))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The view command allows us to see the current state of the `Board`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "board.view()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Running the simulation returns a set of statistics that characterizes your run:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Simulate board\n",
    "sim = sg.Simulator(board)\n",
    "sim.run(sg.rules.conway_classic, iters=100)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The animation command returns a `matplotlib.FuncAnimation` that you can use to show or save your animation. Note that sometimes, saving to GIF or MP4 might require other dependencies such as `ffmpeg` or `ImageMagick`. For more information, please check [this blog post](http://louistiao.me/posts/notebooks/save-matplotlib-animations-as-gifs/)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%capture\n",
    "anim = sim.animate()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "anim"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Small ecosystem\n",
    "\n",
    "In this example, we'll demonstrate the diversity of our `Lifeform`s and see how they interact with one another!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "board = sg.Board(size=(30,30))\n",
    "board.add(lf.Glider(), loc=(4,4))\n",
    "board.add(lf.Glider(), loc=(10,4))\n",
    "board.add(lf.Glider(), loc=(15,4))\n",
    "board.add(lf.Pulsar(), loc=(5,12))\n",
    "board.add(lf.Blinker(length=3), loc=(22,4))\n",
    "board.add(lf.Blinker(length=3), loc=(22,8))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%capture\n",
    "# Simulate board\n",
    "sim = sg.Simulator(board)\n",
    "stats = sim.run(sg.rules.conway_classic, iters=100)\n",
    "anim = sim.animate()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "anim"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Custom lifeform\n",
    "\n",
    "Lastly, we'll create our very first custom lifeform! Defining it is just the same as instantiating any other pre-made lifeform. However in this example, we'll save the instance in a variable `custom_lf` so that we can place it easily without writing the whole matrix again and again."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "board = sg.Board(size=(30,30))\n",
    "\n",
    "# Our custom lifeform\n",
    "custom_lf = lf.Custom([[0, 0, 1, 1, 0],\n",
    "                       [1, 1, 0, 1, 1],\n",
    "                       [1, 1, 1, 1, 0],\n",
    "                       [0, 1, 1, 0, 0]])\n",
    "                      \n",
    "board.add(custom_lf, loc=(1,1))\n",
    "board.add(custom_lf, loc=(10,1))\n",
    "board.add(custom_lf, loc=(20,1))\n",
    "board.add(custom_lf, loc=(5, 10))\n",
    "board.add(custom_lf, loc=(15, 10))\n",
    "board.add(custom_lf, loc=(10, 20))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%capture\n",
    "sim = sg.Simulator(board)\n",
    "stats = sim.run(sg.rules.conway_classic, iters=100)\n",
    "anim = sim.animate()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "anim"
   ]
  }
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