{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 実験支援ワークフロー\n",
    "\n",
    "実験中のワークフローを支援します。  \n",
    "実験記録と実験ワークフローの概要を確認後、最後のセルを実行してワークフロー図を作成してください。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 実験記録の概要 "
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 実験記録の管理方法について\n",
    "\n",
    "データガバナンス機能では、以下のパッケージによって実験記録の再現性を確保します。  \n",
    "パッケージには、実験に必要な入力データ、実行コード、実行環境構築情報、実験のメタデータから構成され、実験実施後は実験の出力データも追加されます。\n",
    " ![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 以下のセルを実行して、実験記録管理のための注意点をご確認ください。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from IPython.display import Markdown\n",
    "import os\n",
    "Markdown(\"・実験の実行コードは、sourceフォルダ内の[main.ipynb](./source/main.ipynb) に記述してください。<br>\"\\\n",
    "+ \"・入力データは[input_data](\" + os.environ[\"JUPYTERHUB_SERVICE_PREFIX\"] + \"tree/input_data)に配置してください。<br>\"\\\n",
    "+ \"・実行コードは、実験の出力データを[output_data](\" + os.environ[\"JUPYTERHUB_SERVICE_PREFIX\"] + \"tree/output_data)に出力するように記載してください。\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 実験ワークフローの概要"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 0. 実験ワークフロー実行準備\n",
    "\n",
    "実験中のワークフローを実行する前に実行する必要があります。  \n",
    "同じ実験実行環境であれば2回目以降は実行する必要がありませんが、実行環境を再構築した場合は実行してください。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. 実験ワークフロー\n",
    "\n",
    "実験中のワークフローを支援します。  \n",
    "この実験環境でデータが維持されるのは最後に利用した日から30日間なので、実験終了後は必ず「実験を終了する」でデータガバナンス機能にデータを反映させてください。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ワークフロー図を作成する\n",
    "\n",
    "以下のセルを実行してワークフロー図を作成できます。\n",
    "各ワークフローを実行するにはそれぞれのリンクをクリックしてください。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
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       "      <feGaussianBlur id=\"feGaussianBlur3780\" inkspace:collect=\"always\" stdDeviation=\"4.2\"/>\n",
       "    </filter>\n",
       "  </defs>\n",
       "  <title>blockdiag</title>\n",
       "  <desc>\n",
       "   blockdiag {\n",
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       "    node_height = 145;\n",
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       "\n",
       "            group {\n",
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       "                orientation = portrait;\n",
       "                group {\n",
       "                    orientation = portrait;\n",
       "                    color = &quot;#ffeed9&quot;;\n",
       "                    &quot;0. 実験ワークフロー実行準備&quot;[label = &quot;0. 実験ワークフロー実行準備&quot;, fontsize = 14];\n",
       "                    &quot;required_every_time&quot;;\n",
       "                }\n",
       "            }\n",
       "\n",
       "            group {\n",
       "                shape = line;\n",
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       "                group {\n",
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       "                    &quot;1. 実験ワークフロー&quot;[label = &quot;1. 実験ワークフロー&quot;, fontsize = 14];\n",
       "                    &quot;enter_metadata&quot;;\n",
       "                    &quot;save&quot;;\n",
       "                    &quot;finish&quot;;\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "\n",
       "        &quot;0. 実験ワークフロー実行準備&quot; -&gt; &quot;1. 実験ワークフロー&quot;;\n",
       "        &quot;enter_metadata&quot;,&quot;save&quot; -&gt; &quot;finish&quot;;\n",
       "\n",
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       "</svg>"
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      "text/plain": [
       "<IPython.core.display.SVG object>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import SVG\n",
    "import os\n",
    "\n",
    "nb_utils_path   = os.path.join(os.environ['HOME'], 'WORKFLOW/util/scripts/nb_utils.py')\n",
    "basic_path      = os.path.join(os.environ['HOME'], 'WORKFLOW/images')\n",
    "basic_path_svg  = os.path.join(basic_path, 'notebooks.svg')\n",
    "basic_path_diag = os.path.join(basic_path, 'notebooks.diag')\n",
    "os.chdir(os.environ['HOME'])\n",
    "!python3 $nb_utils_path $basic_path_diag\n",
    "\n",
    "SVG(filename=basic_path_svg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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