{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "execution": {},
    "id": "view-in-github"
   },
   "source": [
    "<a href=\"https://colab.research.google.com/github/NeuromatchAcademy/course-content/blob/main/tutorials/W1D1_ModelTypes/W1D1_Outro.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a> &nbsp; <a href=\"https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/NeuromatchAcademy/course-content/main/tutorials/W1D1_ModelTypes/W1D1_Outro.ipynb\" target=\"_parent\"><img src=\"https://kaggle.com/static/images/open-in-kaggle.svg\" alt=\"Open in Kaggle\"/></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "execution": {},
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "# Outro\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "cellView": "form",
    "execution": {}
   },
   "outputs": [],
   "source": [
    "# @title Install and import feedback gadget\n",
    "\n",
    "!pip3 install vibecheck datatops --quiet\n",
    "\n",
    "from vibecheck import DatatopsContentReviewContainer\n",
    "def content_review(notebook_section: str):\n",
    "    return DatatopsContentReviewContainer(\n",
    "        \"\",  # No text prompt\n",
    "        notebook_section,\n",
    "        {\n",
    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
    "            \"name\": \"neuromatch_cn\",\n",
    "            \"user_key\": \"y1x3mpx5\",\n",
    "        },\n",
    "    ).render()\n",
    "\n",
    "\n",
    "feedback_prefix = \"W1D1_Outro\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "execution": {},
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## Video"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "cellView": "form",
    "execution": {},
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "# @markdown\n",
    "from ipywidgets import widgets\n",
    "from IPython.display import YouTubeVideo\n",
    "from IPython.display import IFrame\n",
    "from IPython.display import display\n",
    "\n",
    "\n",
    "class PlayVideo(IFrame):\n",
    "  def __init__(self, id, source, page=1, width=400, height=300, **kwargs):\n",
    "    self.id = id\n",
    "    if source == 'Bilibili':\n",
    "      src = f'https://player.bilibili.com/player.html?bvid={id}&page={page}'\n",
    "    elif source == 'Osf':\n",
    "      src = f'https://mfr.ca-1.osf.io/render?url=https://osf.io/download/{id}/?direct%26mode=render'\n",
    "    super(PlayVideo, self).__init__(src, width, height, **kwargs)\n",
    "\n",
    "\n",
    "def display_videos(video_ids, W=400, H=300, fs=1):\n",
    "  tab_contents = []\n",
    "  for i, video_id in enumerate(video_ids):\n",
    "    out = widgets.Output()\n",
    "    with out:\n",
    "      if video_ids[i][0] == 'Youtube':\n",
    "        video = YouTubeVideo(id=video_ids[i][1], width=W,\n",
    "                             height=H, fs=fs, rel=0)\n",
    "        print(f'Video available at https://youtube.com/watch?v={video.id}')\n",
    "      else:\n",
    "        video = PlayVideo(id=video_ids[i][1], source=video_ids[i][0], width=W,\n",
    "                          height=H, fs=fs, autoplay=False)\n",
    "        if video_ids[i][0] == 'Bilibili':\n",
    "          print(f'Video available at https://www.bilibili.com/video/{video.id}')\n",
    "        elif video_ids[i][0] == 'Osf':\n",
    "          print(f'Video available at https://osf.io/{video.id}')\n",
    "      display(video)\n",
    "    tab_contents.append(out)\n",
    "  return tab_contents\n",
    "\n",
    "\n",
    "video_ids = [('Youtube', 'KUdKlJxtjQw'), ('Bilibili', 'BV1bg411u7we')]\n",
    "tab_contents = display_videos(video_ids, W=854, H=480)\n",
    "tabs = widgets.Tab()\n",
    "tabs.children = tab_contents\n",
    "for i in range(len(tab_contents)):\n",
    "  tabs.set_title(i, video_ids[i][0])\n",
    "display(tabs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "execution": {},
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## Slides"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "cellView": "form",
    "execution": {},
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "# @markdown\n",
    "from IPython.display import IFrame\n",
    "link_id = \"9hkg2\"\n",
    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "cellView": "form",
    "execution": {}
   },
   "outputs": [],
   "source": [
    "# @title Submit your feedback\n",
    "content_review(f\"{feedback_prefix}_Outro_Video\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "execution": {}
   },
   "source": [
    "---\n",
    "## Daily survey\n",
    "\n",
    "Don't forget to complete your reflections and content check in the daily survey! Please be patient after logging in as there is a small delay before you will be redirected to the survey.\n",
    "\n",
    "<a href=\"https://portal.neuromatchacademy.org/api/redirect/to/48f385bc-3cd4-4516-96bb-46bdbdccbe9a\"><img src=\"https://github.com/NeuromatchAcademy/course-content/blob/main/tutorials/static/button.png?raw=1\" alt=\"button link to survey\" style=\"width:410px\"></a>"
   ]
  }
 ],
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  "colab": {
   "collapsed_sections": [],
   "include_colab_link": true,
   "name": "W1D1_Outro",
   "provenance": [],
   "toc_visible": true
  },
  "kernel": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "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": "3.9.17"
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