mmpataki/test.ipynb

## test.ipynb
{
 "metadata": {
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5-final"
  },
  "orig_nbformat": 2,
  "kernelspec": {
   "name": "python3",
   "display_name": "Python 3",
   "language": "python"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2,
 "cells": [
  {
   "source": [
    "## This is a sample notebook to test the gists"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# here is some code\n",
    "def sayHelloTo(name):\n",
    "    print(f'hello {name}!')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "hello madhusoodan!\n"
     ]
    }
   ],
   "source": [
    "sayHelloTo('madhusoodan')"
   ]
  },
  {
   "source": [
    "## Image test"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "# if using a jupyter notebook\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = np.arange(0,4*np.pi,0.1)   # start,stop,step\n",
    "y = np.sin(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
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\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "plt.plot(x,y)\n",
    "plt.show()"
   ]
  }
 ]
}