{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "A example of plotting not quite right\n",
    "======================================\n",
    "\n",
    "An \"ugly\" example of plotting.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib\n",
    "#matplotlib.use('Agg')\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "matplotlib.rc('grid', color='black', linestyle='-', linewidth=1)\n",
    "\n",
    "fig = plt.figure(figsize=(5,4),dpi=72)\n",
    "axes = fig.add_axes([0.01, 0.01, .98, 0.98], facecolor='.75')\n",
    "X = np.linspace(0, 2, 40)\n",
    "Y = np.sin(2 * np.pi * X)\n",
    "plt.plot(X, Y, lw=.05, c='b', antialiased=False)\n",
    "\n",
    "plt.xticks([])\n",
    "plt.yticks(np.arange(-1., 1., 0.2))\n",
    "plt.grid()\n",
    "ax = plt.gca()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}