{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "9bd55b02",
   "metadata": {},
   "source": [
    "\n",
    "# Sand Box\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "cb936cf9",
   "metadata": {},
   "outputs": [],
   "source": [
    "from gd05 import GenDifS_Map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "29146d75",
   "metadata": {},
   "outputs": [],
   "source": [
    "mm = \"Schnitzel_DE\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "c777f894",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "input dir = /home/dsci/a/l/lib/gendifs_05/mm\n",
      "reading ../mm/Schnitzel_DE.mm: 20 nodes\n",
      "Parsing XML: #1 start nodes\n",
      "ontology node IDs: {'ID_1341768789': 'ONTOLOGY'}\n",
      "RDF: 280 1177\n",
      "output dir = /home/dsci/a/l/lib/gendifs_05/mm\n",
      "updated mindmap with backup to ../mm/Schnitzel_DE.mm_backup_2022-09-07T13-13-05\n"
     ]
    }
   ],
   "source": [
    "o = GenDifS_Map(f\"../mm/{mm}.mm\", verbose = 1, update_mindmap=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "735efc46",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "http://mm2ttl.net/namespace/ex#Kalbschnitzel_ID_1827400828 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://mm2ttl.net/namespace/default#Kalbschnitzel\n",
      "http://mm2ttl.net/namespace/ex#Kalbschnitzel_ID_1953543047 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://mm2ttl.net/namespace/default#Kalbschnitzel\n"
     ]
    }
   ],
   "source": [
    "my_query = \"\"\"\n",
    "SELECT DISTINCT ?s ?p ?o\n",
    "WHERE {\n",
    "    ?s ?p ?o .\n",
    "    ?s rdf:type :Kalbschnitzel \n",
    "}\"\"\"\n",
    "\n",
    "qres = o.rdflib.query(my_query)\n",
    "for row in qres:\n",
    "    print(row.s, row.p, row.o)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "06e6d74c",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>10</th>\n",
       "      <th>11</th>\n",
       "      <th>12</th>\n",
       "      <th>13</th>\n",
       "      <th>14</th>\n",
       "      <th>15</th>\n",
       "      <th>16</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>parseType</th>\n",
       "      <td>object</td>\n",
       "      <td>collection</td>\n",
       "      <td>object</td>\n",
       "      <td>collection</td>\n",
       "      <td>literal</td>\n",
       "      <td>object</td>\n",
       "      <td>object</td>\n",
       "      <td>collection</td>\n",
       "      <td>object</td>\n",
       "      <td>object</td>\n",
       "      <td>object</td>\n",
       "      <td>collection</td>\n",
       "      <td>object</td>\n",
       "      <td>object</td>\n",
       "      <td>collection</td>\n",
       "      <td>object</td>\n",
       "      <td>collection</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TEXT</th>\n",
       "      <td>topConcept</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Milch &lt;pwn:milk#1&gt;</td>\n",
       "      <td>DEF  [Wikipedia -&gt; Milch](https://de.wikipedia...</td>\n",
       "      <td>Eine ''' Emulsion [Wikipedia -&gt; Milch](https:/...</td>\n",
       "      <td>Milch</td>\n",
       "      <td>Rapphengst &lt;http://wiki/Rapphengst&gt;</td>\n",
       "      <td>SUP</td>\n",
       "      <td>Rappe</td>\n",
       "      <td>Hengst</td>\n",
       "      <td>Anna</td>\n",
       "      <td>REV liebt &lt;https://de.wikipedia.org/wiki/Ben_l...</td>\n",
       "      <td>Ben</td>\n",
       "      <td>Russland</td>\n",
       "      <td>BT</td>\n",
       "      <td>Putin</td>\n",
       "      <td>ABC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>parent_object_ID</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>parent_collection_ID</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tag</th>\n",
       "      <td>NaN</td>\n",
       "      <td>BY</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DEF</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SUP</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>REV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>BT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ABC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BY</th>\n",
       "      <td>NaN</td>\n",
       "      <td>topProperty</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SOME</th>\n",
       "      <td>NaN</td>\n",
       "      <td>topConcept</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mm_ID</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ID_792590473</td>\n",
       "      <td>ID_780109244</td>\n",
       "      <td>ID_937861573</td>\n",
       "      <td>ID_250317734</td>\n",
       "      <td>ID_858326988</td>\n",
       "      <td>ID_1403649387</td>\n",
       "      <td>ID_24101473</td>\n",
       "      <td>ID_1221408874</td>\n",
       "      <td>ID_1789270621</td>\n",
       "      <td>ID_840522711</td>\n",
       "      <td>ID_1850018919</td>\n",
       "      <td>ID_1042433107</td>\n",
       "      <td>ID_596082798</td>\n",
       "      <td>ID_575441509</td>\n",
       "      <td>ID_597147113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RESOURCE</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Milch</td>\n",
       "      <td></td>\n",
       "      <td>NaN</td>\n",
       "      <td>Milch</td>\n",
       "      <td>Rapphengst</td>\n",
       "      <td></td>\n",
       "      <td>Rappe</td>\n",
       "      <td>Hengst</td>\n",
       "      <td>Anna</td>\n",
       "      <td>liebt</td>\n",
       "      <td>Ben</td>\n",
       "      <td>Russland</td>\n",
       "      <td></td>\n",
       "      <td>Putin</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LINK</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;pwn:milk#1&gt;</td>\n",
       "      <td></td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td>&lt;http://wiki/Rapphengst&gt;</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>&lt;https://de.wikipedia.org/wiki/Ben_liebt_Anna&gt;</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>object_ID</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>collection_ID</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>md</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>* **Milch &lt;pwn:milk#1&gt;**</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>* **Milch**</td>\n",
       "      <td>* **Rapphengst &lt;http://wiki/Rapphengst&gt;**</td>\n",
       "      <td>NaN</td>\n",
       "      <td>* **Rappe**</td>\n",
       "      <td>* **Hengst**</td>\n",
       "      <td>* **Anna**</td>\n",
       "      <td>* REV *liebt &lt;https://de.wikipedia.org/wiki/...</td>\n",
       "      <td>* **Ben**</td>\n",
       "      <td>* **Russland**</td>\n",
       "      <td>* BT **</td>\n",
       "      <td>* **Putin**</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>REV</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>liebt</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BT</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ERROR</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ID 16: unknown tag ABC</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              0            1                         2   \\\n",
       "parseType                 object   collection                    object   \n",
       "TEXT                  topConcept          NaN        Milch <pwn:milk#1>   \n",
       "parent_object_ID               0            0                         0   \n",
       "parent_collection_ID         1.0          1.0                       NaN   \n",
       "tag                          NaN           BY                       NaN   \n",
       "BY                           NaN  topProperty                       NaN   \n",
       "SOME                         NaN   topConcept                       NaN   \n",
       "ID                           NaN          NaN                       2.0   \n",
       "mm_ID                        NaN          NaN              ID_792590473   \n",
       "RESOURCE                     NaN          NaN                     Milch   \n",
       "LINK                         NaN          NaN              <pwn:milk#1>   \n",
       "object_ID                    NaN          NaN                       2.0   \n",
       "collection_ID                NaN          NaN                       1.0   \n",
       "md                           NaN          NaN  * **Milch <pwn:milk#1>**   \n",
       "REV                          NaN          NaN                       NaN   \n",
       "BT                           NaN          NaN                       NaN   \n",
       "ERROR                        NaN          NaN                       NaN   \n",
       "\n",
       "                                                                     3   \\\n",
       "parseType                                                    collection   \n",
       "TEXT                  DEF  [Wikipedia -> Milch](https://de.wikipedia...   \n",
       "parent_object_ID                                                      2   \n",
       "parent_collection_ID                                                1.0   \n",
       "tag                                                                 DEF   \n",
       "BY                                                                  NaN   \n",
       "SOME                                                                NaN   \n",
       "ID                                                                  3.0   \n",
       "mm_ID                                                      ID_780109244   \n",
       "RESOURCE                                                                  \n",
       "LINK                                                                      \n",
       "object_ID                                                           NaN   \n",
       "collection_ID                                                       3.0   \n",
       "md                                                                  NaN   \n",
       "REV                                                                 NaN   \n",
       "BT                                                                  NaN   \n",
       "ERROR                                                               NaN   \n",
       "\n",
       "                                                                     4   \\\n",
       "parseType                                                       literal   \n",
       "TEXT                  Eine ''' Emulsion [Wikipedia -> Milch](https:/...   \n",
       "parent_object_ID                                                      2   \n",
       "parent_collection_ID                                                NaN   \n",
       "tag                                                                 NaN   \n",
       "BY                                                                  NaN   \n",
       "SOME                                                                NaN   \n",
       "ID                                                                  4.0   \n",
       "mm_ID                                                      ID_937861573   \n",
       "RESOURCE                                                            NaN   \n",
       "LINK                                                                NaN   \n",
       "object_ID                                                           4.0   \n",
       "collection_ID                                                       3.0   \n",
       "md                                                                  NaN   \n",
       "REV                                                                 NaN   \n",
       "BT                                                                  NaN   \n",
       "ERROR                                                               NaN   \n",
       "\n",
       "                                5                                          6   \\\n",
       "parseType                   object                                     object   \n",
       "TEXT                         Milch        Rapphengst <http://wiki/Rapphengst>   \n",
       "parent_object_ID                 0                                          0   \n",
       "parent_collection_ID           NaN                                        NaN   \n",
       "tag                            NaN                                        NaN   \n",
       "BY                             NaN                                        NaN   \n",
       "SOME                           NaN                                        NaN   \n",
       "ID                             5.0                                        6.0   \n",
       "mm_ID                 ID_250317734                               ID_858326988   \n",
       "RESOURCE                     Milch                                 Rapphengst   \n",
       "LINK                                                 <http://wiki/Rapphengst>   \n",
       "object_ID                      5.0                                        6.0   \n",
       "collection_ID                  1.0                                        1.0   \n",
       "md                     * **Milch**  * **Rapphengst <http://wiki/Rapphengst>**   \n",
       "REV                            NaN                                        NaN   \n",
       "BT                             NaN                                        NaN   \n",
       "ERROR                          NaN                                        NaN   \n",
       "\n",
       "                                 7                8                 9   \\\n",
       "parseType                collection           object            object   \n",
       "TEXT                            SUP            Rappe            Hengst   \n",
       "parent_object_ID                  6                6                 6   \n",
       "parent_collection_ID            1.0              NaN               NaN   \n",
       "tag                             SUP              NaN               NaN   \n",
       "BY                              NaN              NaN               NaN   \n",
       "SOME                            NaN              NaN               NaN   \n",
       "ID                              7.0              8.0               9.0   \n",
       "mm_ID                 ID_1403649387      ID_24101473     ID_1221408874   \n",
       "RESOURCE                                       Rappe            Hengst   \n",
       "LINK                                                                     \n",
       "object_ID                       NaN              8.0               9.0   \n",
       "collection_ID                   7.0              7.0               7.0   \n",
       "md                              NaN      * **Rappe**      * **Hengst**   \n",
       "REV                             NaN              NaN               NaN   \n",
       "BT                              NaN              NaN               NaN   \n",
       "ERROR                           NaN              NaN               NaN   \n",
       "\n",
       "                                 10  \\\n",
       "parseType                    object   \n",
       "TEXT                           Anna   \n",
       "parent_object_ID                  0   \n",
       "parent_collection_ID            NaN   \n",
       "tag                             NaN   \n",
       "BY                              NaN   \n",
       "SOME                            NaN   \n",
       "ID                             10.0   \n",
       "mm_ID                 ID_1789270621   \n",
       "RESOURCE                       Anna   \n",
       "LINK                                  \n",
       "object_ID                      10.0   \n",
       "collection_ID                   1.0   \n",
       "md                       * **Anna**   \n",
       "REV                             NaN   \n",
       "BT                              NaN   \n",
       "ERROR                           NaN   \n",
       "\n",
       "                                                                     11  \\\n",
       "parseType                                                    collection   \n",
       "TEXT                  REV liebt <https://de.wikipedia.org/wiki/Ben_l...   \n",
       "parent_object_ID                                                     10   \n",
       "parent_collection_ID                                                1.0   \n",
       "tag                                                                 REV   \n",
       "BY                                                                  NaN   \n",
       "SOME                                                                NaN   \n",
       "ID                                                                 11.0   \n",
       "mm_ID                                                      ID_840522711   \n",
       "RESOURCE                                                          liebt   \n",
       "LINK                     <https://de.wikipedia.org/wiki/Ben_liebt_Anna>   \n",
       "object_ID                                                           NaN   \n",
       "collection_ID                                                      11.0   \n",
       "md                      * REV *liebt <https://de.wikipedia.org/wiki/...   \n",
       "REV                                                               liebt   \n",
       "BT                                                                  NaN   \n",
       "ERROR                                                               NaN   \n",
       "\n",
       "                                 12              13            14  \\\n",
       "parseType                    object          object    collection   \n",
       "TEXT                            Ben        Russland            BT   \n",
       "parent_object_ID                 10               0            13   \n",
       "parent_collection_ID            NaN             NaN           1.0   \n",
       "tag                             NaN             NaN            BT   \n",
       "BY                              NaN             NaN           NaN   \n",
       "SOME                            NaN             NaN           NaN   \n",
       "ID                             12.0            13.0          14.0   \n",
       "mm_ID                 ID_1850018919   ID_1042433107  ID_596082798   \n",
       "RESOURCE                        Ben        Russland                 \n",
       "LINK                                                                \n",
       "object_ID                      12.0            13.0           NaN   \n",
       "collection_ID                  11.0             1.0          14.0   \n",
       "md                        * **Ben**  * **Russland**      * BT **    \n",
       "REV                             NaN             NaN           NaN   \n",
       "BT                              NaN             NaN                 \n",
       "ERROR                           NaN             NaN           NaN   \n",
       "\n",
       "                                   15                      16  \n",
       "parseType                      object              collection  \n",
       "TEXT                            Putin                     ABC  \n",
       "parent_object_ID                   13                      15  \n",
       "parent_collection_ID              NaN                    14.0  \n",
       "tag                               NaN                     ABC  \n",
       "BY                                NaN                     NaN  \n",
       "SOME                              NaN                     NaN  \n",
       "ID                               15.0                    16.0  \n",
       "mm_ID                    ID_575441509            ID_597147113  \n",
       "RESOURCE                        Putin                          \n",
       "LINK                                                           \n",
       "object_ID                        15.0                     NaN  \n",
       "collection_ID                    14.0                    16.0  \n",
       "md                        * **Putin**                     NaN  \n",
       "REV                               NaN                     NaN  \n",
       "BT                                NaN                     NaN  \n",
       "ERROR                             NaN  ID 16: unknown tag ABC  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "pd.DataFrame.from_dict(o.node_dict, orient='index').sort_index().T\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "fb25d795",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'start': ['# ONTOLOGY',\n",
       "  '\\n',\n",
       "  'Milch <pwn:milk#1>',\n",
       "  '* DEF  [Wikipedia -> Milch](https://de.wikipedia.org/wiki/Milch)',\n",
       "  \"  * Eine ''' Emulsion [Wikipedia -> Milch](https://de.wikipedia.org/wiki/Milch)\",\n",
       "  '\\n',\n",
       "  'Milch',\n",
       "  '\\n',\n",
       "  'Rapphengst <http://wiki/Rapphengst>',\n",
       "  '* SUP',\n",
       "  '  * Rappe',\n",
       "  '  * Hengst',\n",
       "  '\\n',\n",
       "  'Anna',\n",
       "  '* REV liebt <https://de.wikipedia.org/wiki/Ben_liebt_Anna>',\n",
       "  '  * Ben',\n",
       "  '\\n',\n",
       "  'Russland',\n",
       "  '* BT',\n",
       "  '  * Putin',\n",
       "  '    * ABC',\n",
       "  '      * War']}"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "o.result_dict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "2aceafc2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "\n",
       "\n",
       "* **Milch <pwn:milk#1>**\n",
       "\n",
       "\n",
       "* **Milch**\n",
       "* **Rapphengst <http://wiki/Rapphengst>**\n",
       "\n",
       "    * **Rappe**\n",
       "    * **Hengst**\n",
       "* **Anna**\n",
       "  * REV *liebt <https://de.wikipedia.org/wiki/Ben_liebt_Anna>* <https://de.wikipedia.org/wiki/Ben_liebt_Anna>\n",
       "    * **Ben**\n",
       "* **Russland**\n",
       "  * BT ** \n",
       "    * **Putin**\n"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "o.parser_markdown()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "36e1a992",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Graph identifier=Ncbe7cfe673ac4af4959f410a31d35c7a (<class 'rdflib.graph.Graph'>)>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "o.rdflib.serialize(destination=f\"../ttl/{mm}.ttl\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "24646bad",
   "metadata": {},
   "outputs": [],
   "source": [
    "import rdflib\n",
    "from rdflib.extras.external_graph_libs import rdflib_to_networkx_multidigraph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "8eee1e7a",
   "metadata": {},
   "outputs": [],
   "source": [
    "#!pip install networkx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "3e7050d4",
   "metadata": {},
   "outputs": [],
   "source": [
    "import networkx as nx\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "b2d0e30e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "url = 'https://www.w3.org/TeamSubmission/turtle/tests/test-30.ttl'\n",
    "\n",
    "g = rdflib.Graph()\n",
    "result = g.parse(url, format='turtle')\n",
    "\n",
    "#G = rdflib_to_networkx_multidigraph(result)\n",
    "\n",
    "G = rdflib_to_networkx_multidigraph(o.rdflib)\n",
    "\n",
    "\n",
    "# Plot Networkx instance of RDF Graph\n",
    "pos = nx.shell_layout(G, scale=1000)\n",
    "edge_labels = nx.get_edge_attributes(G, 'r')\n",
    "#nx.draw_networkx_edge_labels(G, pos, edge_labels=edge_labels)\n",
    "nx.draw(G, with_labels=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "16d2e811",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Graph identifier=N7e7daad5fdfe42af9b424caf40bbebc4 (<class 'rdflib.graph.Graph'>)>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "o.owlrl"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5f2b408c",
   "metadata": {},
   "source": [
    "The parser will read the mindmap file, parse the content, and store the result in the dictionary `o.node_dict`.\n",
    "\n",
    "This dict is acessable from outside, e.g. like this:"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "58264735",
   "metadata": {},
   "source": [
    "Then raw turtle code will be generated. It's stored in the list `o.turtle_list`. To conveniently inspect distinct entries, use the method `o.show_turtle([ <list of IDs > ])`, e.g.:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "95945b5b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "# 1\n",
      "# COLLECTION.a, context\n",
      "#   None: None\n",
      "#     None: None\n",
      "#       None: None\n",
      "\n",
      "\n",
      "\n",
      "# 1\n",
      "# BY.a, owl\n",
      ":topProperty\n",
      "   rdf:type owl:ObjectProperty .\n",
      "\n",
      "\n",
      "# 1\n",
      "# BY.b, owl\n",
      ":topConcept\n",
      "   a owl:Class .\n",
      "\n",
      "\n",
      "# 1\n",
      "# BY.c, owl-test\n",
      "ex:topConcept_None\n",
      "   a :topConcept .\n",
      "\n",
      "\n",
      "\n",
      "# 1\n",
      "# BY.g, owl-classification\n",
      ":BY_1_restriction\n",
      "   a owl:Class ;\n",
      "   rdfs:label \"BY topProperty SOME topConcept\" ;\n",
      "   owl:equivalentClass [ a owl:Restriction ;\n",
      "      owl:onProperty :topProperty ;\n",
      "      owl:someValuesFrom :topConcept ] .\n",
      "\n",
      "\n",
      "\n",
      "# 1\n",
      "# BY.h, owl-classification\n",
      ":BY_1_intersection\n",
      "   a owl:Class ;\n",
      "   rdfs:label \"(BY topProperty SOME topConcept) INTERSECT None_None\" ;\n",
      "   rdfs:subClassOf :None ;\n",
      "   owl:equivalentClass [ a owl:Class ;\n",
      "      owl:intersectionOf (\n",
      "         :BY_1_restriction\n",
      "         :None ) ] .\n",
      "\n",
      "\n",
      "\n",
      "# 2\n",
      "# OBJECT_BY.a, owl\n",
      ":Milch\n",
      "   a owl:Class ; # <pwn:milk#1>\n",
      "   rdfs:subClassOf :None .\n",
      "\n",
      "\n",
      "# 2\n",
      "# OBJECT_BY.b, owl-test\n",
      "ex:Milch_ID_792590473\n",
      "   a :Milch .\n",
      "\n",
      "\n",
      "\n",
      "# 2\n",
      "# OBJECT_BY.c, skos\n",
      "cpt:Milch\n",
      "   a skos:Concept ;\n",
      "   skos:broaderTransitive cpt:None .\n",
      "\n",
      "\n",
      "# 3\n",
      "# COLLECTION.a, context\n",
      "#   None: None\n",
      "#     2: Milch\n",
      "#       3: \n",
      "\n",
      "\n",
      "\n",
      "# 4\n",
      "# LITERAL.a, owl\n",
      ":Milch \n",
      "    rdfs:comment '''Eine \\'\\'\\' Emulsion [Wikipedia -> Milch](https://de.wikipedia.org/wiki/Milch)''' .  # None\n",
      "\n",
      "\n",
      "# 4\n",
      "# LITERAL.c, skos\n",
      "cpt:Milch \n",
      "    skos:definition '''Eine \\'\\'\\' Emulsion [Wikipedia -> Milch](https://de.wikipedia.org/wiki/Milch)''' . # None \n",
      "\n",
      "\n",
      "# 5\n",
      "# OBJECT_BY.a, owl\n",
      ":Milch\n",
      "   a owl:Class ; # \n",
      "   rdfs:subClassOf :None .\n",
      "\n",
      "\n",
      "# 5\n",
      "# OBJECT_BY.b, owl-test\n",
      "ex:Milch_ID_250317734\n",
      "   a :Milch .\n",
      "\n",
      "\n",
      "\n",
      "# 5\n",
      "# OBJECT_BY.c, skos\n",
      "cpt:Milch\n",
      "   a skos:Concept ;\n",
      "   skos:broaderTransitive cpt:None .\n",
      "\n",
      "\n",
      "# 6\n",
      "# OBJECT_BY.a, owl\n",
      ":Rapphengst\n",
      "   a owl:Class ; # <http://wiki/Rapphengst>\n",
      "   rdfs:subClassOf :None .\n",
      "\n",
      "\n",
      "# 6\n",
      "# OBJECT_BY.b, owl-test\n",
      "ex:Rapphengst_ID_858326988\n",
      "   a :Rapphengst .\n",
      "\n",
      "\n",
      "\n",
      "# 6\n",
      "# OBJECT_BY.c, skos\n",
      "cpt:Rapphengst\n",
      "   a skos:Concept ;\n",
      "   skos:broaderTransitive cpt:None .\n",
      "\n",
      "\n",
      "# 7\n",
      "# COLLECTION.a, context\n",
      "#   None: None\n",
      "#     6: Rapphengst\n",
      "#       7: \n",
      "\n",
      "\n",
      "\n",
      "# 7\n",
      "# SUP.b, owl\n",
      ":SUP_7\n",
      "   a owl:Class ;\n",
      "   rdfs:label \"Rappe(8) AND Hengst(9)\" ;\n",
      "   rdfs:subClassOf :Rapphengst ;\n",
      "   owl:equivalentClass [ a owl:Class ;\n",
      "      owl:intersectionOf (\n",
      "          :Rappe :Hengst ) ] .\n",
      "\n",
      "\n",
      "\n",
      "# 7\n",
      "# SUP.d, owl-test\n",
      "ex:SUP_7_ID_1403649387\n",
      "   a :Rappe .\n",
      "\n",
      "\n",
      "\n",
      "# 7\n",
      "# SUP.d, owl-test\n",
      "ex:SUP_7_ID_1403649387\n",
      "   a :Hengst .\n",
      "\n",
      "\n",
      "\n",
      "# 7\n",
      "# SUP.c, owl-test\n",
      "ex:Rapphengst_ID_858326988\n",
      "   a :Rapphengst .\n",
      "ex:SUP_7_ID_1403649387\n",
      "   ex:classifyLike ex:Rapphengst_ID_858326988 .\n",
      "\n",
      "\n",
      "\n",
      "# 8\n",
      "# OBJECT_SUP.a, owl\n",
      ":Rappe\n",
      "   a owl:Class . # \n",
      ":Rapphengst\n",
      "    rdfs:subClassOf :Rappe .\n",
      "\n",
      "\n",
      "# 8\n",
      "# OBJECT_SUP.b, owl-test\n",
      "ex:Rappe_ID_24101473\n",
      "   a :Rappe .\n",
      "\n",
      "\n",
      "\n",
      "# 8\n",
      "# OBJECT_SUP.c, skos\n",
      "cpt:Rappe\n",
      "   a skos:Concept . # \n",
      "cpt:Rapphengst\n",
      "    skos:broaderTransitive cpt:Rappe .\n",
      "\n",
      "\n",
      "# 9\n",
      "# OBJECT_SUP.a, owl\n",
      ":Hengst\n",
      "   a owl:Class . # \n",
      ":Rapphengst\n",
      "    rdfs:subClassOf :Hengst .\n",
      "\n",
      "\n",
      "# 9\n",
      "# OBJECT_SUP.b, owl-test\n",
      "ex:Hengst_ID_1221408874\n",
      "   a :Hengst .\n",
      "\n",
      "\n",
      "\n",
      "# 9\n",
      "# OBJECT_SUP.c, skos\n",
      "cpt:Hengst\n",
      "   a skos:Concept . # \n",
      "cpt:Rapphengst\n",
      "    skos:broaderTransitive cpt:Hengst .\n",
      "\n",
      "\n",
      "# 10\n",
      "# OBJECT_BY.a, owl\n",
      ":Anna\n",
      "   a owl:Class ; # \n",
      "   rdfs:subClassOf :None .\n",
      "\n",
      "\n",
      "# 10\n",
      "# OBJECT_BY.b, owl-test\n",
      "ex:Anna_ID_1789270621\n",
      "   a :Anna .\n",
      "\n",
      "\n",
      "\n",
      "# 10\n",
      "# OBJECT_BY.c, skos\n",
      "cpt:Anna\n",
      "   a skos:Concept ;\n",
      "   skos:broaderTransitive cpt:None .\n",
      "\n",
      "\n",
      "# 11\n",
      "# COLLECTION.a, context\n",
      "#   None: None\n",
      "#     10: Anna\n",
      "#       11: liebt\n",
      "\n",
      "\n",
      "\n",
      "# 13\n",
      "# OBJECT_BY.a, owl\n",
      ":Russland\n",
      "   a owl:Class ; # \n",
      "   rdfs:subClassOf :None .\n",
      "\n",
      "\n",
      "# 13\n",
      "# OBJECT_BY.b, owl-test\n",
      "ex:Russland_ID_1042433107\n",
      "   a :Russland .\n",
      "\n",
      "\n",
      "\n",
      "# 13\n",
      "# OBJECT_BY.c, skos\n",
      "cpt:Russland\n",
      "   a skos:Concept ;\n",
      "   skos:broaderTransitive cpt:None .\n",
      "\n",
      "\n",
      "# 14\n",
      "# COLLECTION.a, context\n",
      "#   None: None\n",
      "#     13: Russland\n",
      "#       14: \n",
      "\n",
      "\n",
      "\n",
      "# 14\n",
      "# BT.a, skos\n",
      "# BT or ISA\n",
      "\n",
      "\n",
      "\n",
      "# 15\n",
      "# BT/ISA_OBJECT.a, owl\n",
      ":Putin\n",
      "   a owl:Class . #  \n",
      "\n",
      "\n",
      "\n",
      "# 15\n",
      "# BT/ISA_OBJECT.c, owl-test\n",
      "ex:Putin_ID_575441509\n",
      "   a :Putin .\n",
      "\n",
      "\n",
      "\n",
      "# 15\n",
      "# BT/ISA_OBJECT.d, skos\n",
      "cpt:Putin\n",
      "   a skos:Concept .\n",
      "\n",
      "\n",
      "\n",
      "# 15\n",
      "# BT_OBJECT.f, skos\n",
      "cpt:Putin \n",
      "   skos:broader cpt:Russland \n",
      ".\n",
      "\n",
      "\n",
      "# 16\n",
      "# COLLECTION.a, context\n",
      "#   14: \n",
      "#     15: Putin\n",
      "#       16: \n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(o.show_turtle([]))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "45cde82b",
   "metadata": {},
   "source": [
    "`focus_map` prints a subset of the mindmap focused on a set of nodes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "d401fd66",
   "metadata": {},
   "outputs": [],
   "source": [
    "from rdflib import Graph, URIRef, Literal\n",
    "import owlrl\n",
    "graph = Graph()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "80ad2f1c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "# 2\n",
      "# OBJECT_BY.a, owl\n",
      ":Milch\n",
      "   a owl:Class ; # <pwn:milk#1>\n",
      "   rdfs:subClassOf :None .\n",
      "\n",
      "\n",
      "# 2\n",
      "# OBJECT_BY.b, owl-test\n",
      "ex:Milch_ID_792590473\n",
      "   a :Milch .\n",
      "\n",
      "\n",
      "\n",
      "# 2\n",
      "# OBJECT_BY.c, skos\n",
      "cpt:Milch\n",
      "   a skos:Concept ;\n",
      "   skos:broaderTransitive cpt:None .\n"
     ]
    }
   ],
   "source": [
    "ttl = o.show_turtle([2])\n",
    "print(ttl)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "46387e25",
   "metadata": {},
   "outputs": [],
   "source": [
    "namespaces = \"\"\"\n",
    "# namespaces to be aligned by the user \n",
    "@prefix ex: <http://mm2ttl.net/namespace/ex#> .\n",
    "@prefix cpt: <http://mm2ttl.net/namespace/x#> .\n",
    "@prefix : <http://mm2ttl.net/namespace/default#> .\n",
    "\n",
    "# standard namespaces, c.f. https://www.w3.org/TR/owl2-quick-reference/\n",
    "@prefix owl: <http://www.w3.org/2002/07/owl#> .\n",
    "@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .\n",
    "@prefix xml: <http://www.w3.org/XML/1998/namespace> .\n",
    "@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .\n",
    "@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .\n",
    "@prefix skos: <http://www.w3.org/2004/02/skos/core#> .\n",
    "\n",
    "ex:classifyLike a owl:ObjectProperty .\n",
    "[ rdf:type owl:Ontology ; owl:imports <http://www.w3.org/2004/02/skos/core> ] .\n",
    "\"\"\"\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "e0225e21",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Graph identifier=Ne6d86911e3d94a29bfff6c5579156317 (<class 'rdflib.graph.Graph'>)>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "graph.parse(data = namespaces+ttl, format='ttl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "a7df85bf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "43"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(o.turtle_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "3ec660be",
   "metadata": {},
   "outputs": [],
   "source": [
    "from IPython.display import display, Markdown\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "2cfe3aa8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "# Hallo <span style='color:red'>ROT</span> und <span style='color:blue'>BLAU</span>"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(Markdown(\"# Hallo <span style='color:red'>ROT</span> und <span style='color:blue'>BLAU</span>\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "bbd6a010",
   "metadata": {},
   "outputs": [],
   "source": [
    "txt = \"\"\"text mit 3 '''!\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "2674aa9c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"'''\" in txt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "c2b29525",
   "metadata": {},
   "outputs": [],
   "source": [
    "import re"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}