{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<center>\n",
    "    <img src=\"xeus-python.png\" width=\"50%\">\n",
    "    <h1>Python kernel based on xeus</h1>\n",
    "</center>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Simple code execution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "b = 89\n",
    "\n",
    "def sq(x):\n",
    "    return x * x\n",
    "\n",
    "sq(b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Redirected streams"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "\n",
    "print(\"Error !!\", file=sys.stderr)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Error handling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "\"Hello\"\n",
    "\n",
    "def dummy_function():\n",
    "    import missing_module"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "dummy_function()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Code completion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### press `tab` to see what is available in `sys` module"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sys import "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Code inspection"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### using the question mark"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "?print"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### by pressing `shift+tab`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print("
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Input support"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "name = input('Enter your name: ')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "'Hello, ' + name"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Rich representation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Person:\n",
    "    def __init__(self, name=\"John Doe\", address=\"Paris\", picture=\"\"):\n",
    "        self.name = name\n",
    "        self.address = address\n",
    "        self.picture = picture\n",
    "\n",
    "    def _repr_mimebundle_(self, include=None, exclude=None):\n",
    "        return {\n",
    "            \"text/html\": \"\"\"<img src=\"{}\">\n",
    "                  <div><i class='fa-user fa'></i>: {}</div>\n",
    "                  <div><i class='fa-map fa'></i>: {}</div>\"\"\".format(self.picture, self.name, self.address) \n",
    "        }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "james = Person(\"James Smith\", \"Boston\")\n",
    "display(james)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "marie = Person(\"Marie Curie\", \"Poland\", \"./marie.png\")\n",
    "display(marie)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Matplotlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "fig = plt.figure()\n",
    "plt.plot(np.sin(np.linspace(0, 20, 100)));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib widget"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig = plt.figure()\n",
    "plt.plot(np.sin(np.linspace(0, 20, 100)));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Widgets support"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Basic widgets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from ipywidgets import IntSlider"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "slider = IntSlider()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "slider"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "slider.value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "slider"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "slider.value = 36"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Widget interacts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from ipywidgets import interact"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "@interact\n",
    "def foo(x = ['a', 'b'], n=(1, 10)):\n",
    "    print(x * n)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Binary buffers support for widgets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from ipywidgets import Video\n",
    "video = Video.from_file(\"Big.Buck.Bunny.mp4\")\n",
    "video"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Higher-level widgets libraries support"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib\n",
    "matplotlib.use(\"agg\")\n",
    "\n",
    "try:\n",
    "    from urllib.request import urlretrieve\n",
    "except ImportError:\n",
    "    from urllib import urlretrieve\n",
    "import os\n",
    "\n",
    "import itk\n",
    "\n",
    "from itkwidgets import view\n",
    "\n",
    "# Download data\n",
    "file_name = '005_32months_T2_RegT1_Reg2Atlas_ManualBrainMask_Stripped.nrrd'\n",
    "if not os.path.exists(file_name):\n",
    "    url = 'https://data.kitware.com/api/v1/file/564a5b078d777f7522dbfaa6/download'\n",
    "    urlretrieve(url, file_name)\n",
    "\n",
    "image = itk.imread(file_name)\n",
    "view(image)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## IPython.display module"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from IPython.display import clear_output, display, update_display\n",
    "from time import sleep"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Update display"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Square:\n",
    "    color = 'PeachPuff'\n",
    "    def _repr_html_(self):\n",
    "        return '''\n",
    "        <div style=\"background: %s; width: 200px; height: 100px; border-radius: 10px;\">\n",
    "        </div>''' % self.color\n",
    "square = Square()\n",
    "\n",
    "display(square, display_id='some-square')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "square.color = 'OliveDrab'\n",
    "update_display(square, display_id='some-square')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Clear output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(\"hello\")\n",
    "sleep(3)\n",
    "clear_output()             # will flicker when replacing \"hello\" with \"goodbye\"\n",
    "print(\"goodbye\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(\"hello\")\n",
    "sleep(3)\n",
    "clear_output(wait=True)   # prevents flickering\n",
    "print(\"goodbye\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Display classes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from IPython.display import HTML\n",
    "HTML('''\n",
    "        <div style=\"background: aliceblue; width: 200px; height: 100px; border-radius: 10px;\">\n",
    "        </div>''')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from IPython.display import Math\n",
    "Math(r'F(k) = \\int_{-\\infty}^{\\infty} f(x) e^{2\\pi i k} dx')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from IPython.display import Latex\n",
    "Latex(r\"\"\"\\begin{eqnarray}\n",
    "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\\n",
    "\\nabla \\cdot \\vec{\\mathbf{E}} & = 4 \\pi \\rho \\\\\n",
    "\\nabla \\times \\vec{\\mathbf{E}}\\, +\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{B}}}{\\partial t} & = \\vec{\\mathbf{0}} \\\\\n",
    "\\nabla \\cdot \\vec{\\mathbf{B}} & = 0 \n",
    "\\end{eqnarray}\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from IPython.display import SVG\n",
    "SVG(url='https://jupyter.org/assets/main-logo.svg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from IPython.display import SVG\n",
    "SVG(filename='./logo.svg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from time import sleep\n",
    "from IPython.display import ProgressBar\n",
    "\n",
    "for i in ProgressBar(10):\n",
    "    sleep(0.1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from IPython.display import JSON\n",
    "JSON(['foo', {'bar': ('baz', None, 1.0, 2)}], metadata={}, expanded=True, root='test')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from IPython.display import GeoJSON\n",
    "GeoJSON(\n",
    "  data={\n",
    "      \"type\": \"Feature\",\n",
    "      \"geometry\": {\n",
    "          \"type\": \"Point\",\n",
    "          \"coordinates\": [11.8, -45.04]\n",
    "      }\n",
    "  }, url_template=\"http://s3-eu-west-1.amazonaws.com/whereonmars.cartodb.net/{basemap_id}/{z}/{x}/{y}.png\",\n",
    "  layer_options={\n",
    "      \"basemap_id\": \"celestia_mars-shaded-16k_global\",\n",
    "      \"attribution\" : \"Celestia/praesepe\",\n",
    "      \"tms\": True,\n",
    "      \"minZoom\" : 0,\n",
    "      \"maxZoom\" : 5\n",
    "  }\n",
    ")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.9 (XPython)",
   "language": "python",
   "name": "xpython"
  },
  "language_info": {
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "version": "3.9.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}