dashboard.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# scroll down and click on show widget \n",
    "### (and refresh if the simulation doesn't work)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>.container { width:100% !important; }</style>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from IPython.core.display import display, HTML\n",
    "display(HTML(\"<style>.container { width:100% !important; }</style>\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "import ipywidgets as widgets\n",
    "from ipywidgets import Layout\n",
    "import matplotlib.pyplot as plt\n",
    "#from PIL import Image\n",
    "from io import BytesIO\n",
    "import numpy as np\n",
    "\n",
    "import colorsys\n",
    "import pickle # package use to save data\n",
    "\n",
    "from IPython.display import display, Image\n",
    "\n",
    "#from scipy import interpolate\n",
    "#import scipy.stats as st"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from dynamic import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import nbinteract as nbi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [],
   "source": [
    "Model = [\"complete\", \"simplified\"]\n",
    "Plot = [\"time series\", \"histogram\"] # \"phase portrait\", "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "class Select_box(widgets.VBox):\n",
    "    def __init__(self, dashboard):\n",
    "        \n",
    "        import numpy as np\n",
    "        \n",
    "        self.dashboard = dashboard\n",
    "\n",
    "        self.selection_model = widgets.Dropdown(options=Model, description = \"model\")\n",
    "        self.selection_model.observe(dashboard.on_model_selected, names = \"value\")\n",
    "\n",
    "        self.selection_alpha = widgets.FloatSlider(min = 0, max = 1, description = \"alpha\", value = 0.5)\n",
    "        self.selection_alpha.observe(dashboard.on_alpha_selected, names = \"value\")\n",
    "\n",
    "        self.selection_c = widgets.FloatLogSlider(min = np.log10(0.1), max = np.log10(10), description = \"c\")\n",
    "        self.selection_c.observe(dashboard.on_c_selected, names = \"value\")\n",
    "\n",
    "        self.selection_h = widgets.FloatLogSlider(min = np.log10(0.1), max = np.log10(10), description = \"h\")\n",
    "        self.selection_h.observe(dashboard.on_h_selected, names = \"value\")\n",
    "\n",
    "        self.selection_l = widgets.FloatLogSlider(min = np.log10(0.1), max = np.log10(10), description = \"l\")\n",
    "        self.selection_l.observe(dashboard.on_l_selected, names = \"value\")\n",
    "\n",
    "        self.selection_plot = widgets.Dropdown(options=Plot, description = \"plot\")\n",
    "        self.selection_plot.observe(dashboard.on_plot_selected, names = \"value\")\n",
    "\n",
    "        \n",
    "        children = [\n",
    "        self.selection_model,\n",
    "        self.selection_alpha,\n",
    "        self.selection_c,\n",
    "        self.selection_h,\n",
    "        self.selection_l,\n",
    "        self.selection_plot,\n",
    "        ]\n",
    "        super().__init__(children, layout=Layout(width=\"100%\"))   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Image_box(widgets.Box):\n",
    "    def __init__(self, dashboard):\n",
    "        %pip install matplotlib\n",
    "        import matplotlib.pyplot as plt\n",
    "        #from dynamic import *\n",
    "        import dynamic\n",
    "        self.image = widgets.Image()\n",
    "        self.dashboard = dashboard\n",
    "        \n",
    "        self.model = self.dashboard.model\n",
    "        self.alpha = self.dashboard.alpha\n",
    "        self.c = self.dashboard.c\n",
    "        self.h = self.dashboard.h\n",
    "        self.l = self.dashboard.l\n",
    "        self.plot = self.dashboard.plot\n",
    "  \n",
    "        self.print_image()\n",
    "        \n",
    "        image_container = widgets.Box([self.image], layout=Layout(width=\"100%\"))\n",
    "        \n",
    "        children = [\n",
    "   #     image_container,\n",
    "        self.image,   \n",
    "        ]\n",
    "        super().__init__(children, layout=Layout(width=\"100%\"))\n",
    "        \n",
    "    def print_image(self):\n",
    "        try:\n",
    "            import matplotlib.pyplot as plt\n",
    "        except:\n",
    "            %pip install matplotlib -qqq\n",
    "            import matplotlib.pyplot as plt\n",
    "        import dynamic\n",
    "        fig = plt.figure(figsize=(10, 6))\n",
    "        #fig = nbi.plotting.Figure()\n",
    "        h = self.h\n",
    "        l = self.l\n",
    "        alpha = self.alpha\n",
    "        c = self.c\n",
    "\n",
    "        #fig = fonction_plot(alpha, c, h, l)\n",
    "        \n",
    "        D = Dynamic(h=h, l=l, alpha=alpha, c=c, model=self.model, tFinal=50)\n",
    "        D.initialisation()\n",
    "        if(self.plot == \"time series\"):\n",
    "            D.eulerEx()\n",
    "            D.plot(show=False)\n",
    "            plt.legend(fontsize = 20) # duplicate ...\n",
    "        elif(self.plot == \"phase portrait\"):\n",
    "            D.plot_phase_portrait(show=False)\n",
    "        elif(self.plot == \"histogram\"):\n",
    "            D.plot_histogram(show=False)\n",
    "            \n",
    "        image_file = BytesIO()\n",
    "        fig.savefig(fname = image_file)\n",
    "        image_file.seek(0)\n",
    "        image_data = image_file.read()\n",
    "        self.image.value = image_data\n",
    "#            self.image.width = 1500\n",
    "#           self.image.height = 2000\n",
    "        plt.close()\n",
    "\n",
    "#          file = open(nom, \"rb\")\n",
    "#         image = file.read()\n",
    "        #plt.imshow(image)\n",
    "#        self.image.value = image\n",
    " #       self.image.format = 'png'\n",
    "\n",
    "\n",
    "        return\n",
    "        \n",
    "\n",
    "    def change_model(self, change):\n",
    "        self.model = change\n",
    "        self.print_image()\n",
    "\n",
    "    def change_alpha(self, change):\n",
    "        self.alpha = change\n",
    "        self.print_image()\n",
    "\n",
    "    def change_c(self, change):\n",
    "        self.c = change\n",
    "        self.print_image()\n",
    "        \n",
    "    def change_h(self, change):\n",
    "        self.h = change\n",
    "        self.print_image()\n",
    "\n",
    "    def change_l(self, change):\n",
    "        self.l = change\n",
    "        self.print_image()\n",
    "\n",
    "    def change_plot(self, change):\n",
    "        self.plot = change\n",
    "        self.print_image()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Dashboard(widgets.VBox):\n",
    "    def __init__(self):\n",
    "        self.model = Model[0]\n",
    "        self.plot = Plot[0]\n",
    "        self.alpha = 0.5\n",
    "        self.c = 1.\n",
    "        self.h = 2.\n",
    "        self.l = 0.5\n",
    "    \n",
    "        self.select_box = Select_box(self)\n",
    "    #    self.text_box = Text_box(self)\n",
    "        self.image_box = Image_box(self)\n",
    "\n",
    "        C1 = widgets.Box([self.image_box], layout=Layout(width=\"65%\"))\n",
    "        C2 = widgets.Box([self.select_box], layout=Layout(width=\"32%\"))\n",
    "\n",
    "        #rowA = widgets.Box([self.image_box, self.select_box], layout=Layout(width=\"100%\"))\n",
    "        rowA = widgets.Box([C1, C2], layout=Layout(width=\"100%\"))\n",
    "        super().__init__([rowA], layout=Layout(width=\"100%\"))\n",
    "    \n",
    "\n",
    "    \n",
    "    \n",
    "    def on_model_selected(self, change):\n",
    "        #if(change[\"new\"]==\"equilibrium\"):\n",
    "         #   change[\"new\"] = 1.0\n",
    "        self.model = change[\"new\"]\n",
    "        self.image_box.change_model(self.model)\n",
    "\n",
    "    def on_alpha_selected(self, change):\n",
    "        self.alpha = change[\"new\"]\n",
    "        self.image_box.change_alpha(self.alpha)\n",
    "        \n",
    "    def on_c_selected(self, change):\n",
    "        self.c = change[\"new\"]\n",
    "        self.image_box.change_c(self.c)\n",
    "        \n",
    "    def on_h_selected(self, change):\n",
    "        self.h = change[\"new\"]\n",
    "        self.image_box.change_h(self.h)\n",
    "        \n",
    "    def on_l_selected(self, change):\n",
    "        self.l = change[\"new\"]\n",
    "        self.image_box.change_l(self.l)\n",
    "        \n",
    "    def on_plot_selected(self, change):\n",
    "        self.plot = change[\"new\"]\n",
    "        self.image_box.change_plot(self.plot)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Defaulting to user installation because normal site-packages is not writeable\n",
      "Requirement already satisfied: matplotlib in /usr/lib/python3.8/site-packages (3.2.0)\n",
      "Requirement already satisfied: cycler>=0.10 in /usr/lib/python3.8/site-packages (from matplotlib) (0.10.0)\n",
      "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/lib/python3.8/site-packages (from matplotlib) (1.1.0)\n",
      "Requirement already satisfied: numpy>=1.11 in /usr/lib/python3.8/site-packages (from matplotlib) (1.18.1)\n",
      "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /usr/lib/python3.8/site-packages (from matplotlib) (2.4.6)\n",
      "Requirement already satisfied: python-dateutil>=2.1 in /usr/lib/python3.8/site-packages (from matplotlib) (2.8.1)\n",
      "Requirement already satisfied: six in /usr/lib/python3.8/site-packages (from cycler>=0.10->matplotlib) (1.14.0)\n",
      "Requirement already satisfied: setuptools in /usr/lib/python3.8/site-packages (from kiwisolver>=1.0.1->matplotlib) (46.1.1)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
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       "Dashboard(children=(Box(children=(Box(children=(Image_box(children=(Image(value=b'\\x89PNG\\r\\n\\x1a\\n\\x00\\x00\\x0…"
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   ],
   "source": [
    "D=Dashboard()\n",
    "D"
   ]
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