{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "af118d77-d87a-4687-be5b-e810a24c403e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2024-07-03 14:30:30 +0000 | io:INFO | Loaded TOML config file successfully.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "A:\\Arbeitsaufgaben\\lang-main\\.venv\\Lib\\site-packages\\transformers\\utils\\generic.py:441: UserWarning: torch.utils._pytree._register_pytree_node is deprecated. Please use torch.utils._pytree.register_pytree_node instead.\n",
      "  _torch_pytree._register_pytree_node(\n",
      "A:\\Arbeitsaufgaben\\lang-main\\.venv\\Lib\\site-packages\\huggingface_hub\\file_download.py:1132: FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.\n",
      "  warnings.warn(\n",
      "A:\\Arbeitsaufgaben\\lang-main\\.venv\\Lib\\site-packages\\transformers\\utils\\generic.py:309: UserWarning: torch.utils._pytree._register_pytree_node is deprecated. Please use torch.utils._pytree.register_pytree_node instead.\n",
      "  _torch_pytree._register_pytree_node(\n",
      "A:\\Arbeitsaufgaben\\lang-main\\.venv\\Lib\\site-packages\\transformers\\utils\\generic.py:309: UserWarning: torch.utils._pytree._register_pytree_node is deprecated. Please use torch.utils._pytree.register_pytree_node instead.\n",
      "  _torch_pytree._register_pytree_node(\n",
      "A:\\Arbeitsaufgaben\\lang-main\\.venv\\Lib\\site-packages\\huggingface_hub\\file_download.py:1132: FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "from lang_main import io\n",
    "from lang_main.analysis.graphs import rescale_edge_weights\n",
    "\n",
    "from pathlib import Path\n",
    "import pickle\n",
    "import base64\n",
    "\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "4256081a-6364-4e8f-8cfd-799912ca6b94",
   "metadata": {},
   "outputs": [],
   "source": [
    "res_path = Path(r'A:\\Arbeitsaufgaben\\lang-main\\scripts\\results\\test_20240619')\n",
    "assert res_path.exists()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e9a92ad6-5e63-49c4-b9e7-9f81da8549fe",
   "metadata": {},
   "outputs": [],
   "source": [
    "#obj = 'TK-GRAPH_POSTPROCESSING.pkl'\n",
    "obj = 'TK-GRAPH_ANALYSIS.pkl'\n",
    "load_pth = res_path / obj\n",
    "assert load_pth.exists()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "c2421d89-ed8c-41dd-b363-ad5b5b716704",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2024-07-03 14:30:35 +0000 | io:INFO | Loaded file successfully.\n"
     ]
    }
   ],
   "source": [
    "ret = io.load_pickle(load_pth)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "ca25a7f2-84af-4b5e-89d6-b139fca35617",
   "metadata": {},
   "outputs": [],
   "source": [
    "tkg = ret[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "ff7e7ab6-67d9-4a2c-b668-cf10740f7542",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "TokenGraph(name: TokenGraph, number of nodes: 143, number of edges: 163)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tkg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "f0df3580-cea5-48cc-bdbc-2927dd446e1b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import networkx as nx\n",
    "from alph import alph, layout\n",
    "import altair as alt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f042b302-fa3c-45b0-8d7a-7a68b66bf595",
   "metadata": {},
   "source": [
    "layout_fn=lambda g: nx.spring_layout(\n",
    "        g,\n",
    "        weight=\"weight\",\n",
    "        k=20,\n",
    "        iterations=5000,\n",
    "        seed=42\n",
    "    ),\n",
    "layout_fn=lambda g: layout.force_atlas_sknet(\n",
    "        g,\n",
    "        n_iter=1000,\n",
    "        gravity_factor=0.01,\n",
    "        repulsive_factor=0.1,\n",
    "        init_seed=42,\n",
    "    ),\n",
    "layout_fn=lambda g: nx.nx_agraph.pygraphviz_layout(\n",
    "        g,\n",
    "        prog=\"fdp\",\n",
    "        args='-GK=5'\n",
    "    ),\n",
    "layout_fn=lambda g: nx.nx_agraph.pygraphviz_layout(\n",
    "        g,\n",
    "        prog=\"sfdp\",\n",
    "        args='-GK=5 -Gbeautify=true -Goverlap=true'\n",
    "    ),\n",
    "layout_fn=lambda g: nx.nx_agraph.pygraphviz_layout(\n",
    "        g,\n",
    "        prog=\"neato\",\n",
    "        args='-Goverlap=false'\n",
    "    ),"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "04d3d857-37cb-420e-8426-b1465d94efae",
   "metadata": {},
   "outputs": [],
   "source": [
    "alph_params = dict(\n",
    "    weight_attr=\"weight\",\n",
    "    layout_fn=lambda g: nx.nx_agraph.pygraphviz_layout(\n",
    "        g,\n",
    "        prog=\"sfdp\",\n",
    "        args='-GK=5 -Gbeautify=true -Goverlap=true'\n",
    "    ),\n",
    "    node_args=dict(\n",
    "        size=alt.Size(\n",
    "            \"degree_centrality\",\n",
    "            scale=alt.Scale(domain=[0,1], range=[12**2, 40**2]),\n",
    "            legend=None\n",
    "        ),\n",
    "        #fill=alt.Color(\n",
    "        #    \"degree_centrality\",\n",
    "        #    scale=alt.Scale(domain=companies, range=palette),\n",
    "        #),\n",
    "        stroke=\"#333\",\n",
    "        strokeWidth=alt.Size(\n",
    "            \"degree_centrality\",\n",
    "            scale=alt.Scale(domain=[0,1], range=[2, 5]),\n",
    "            legend=None\n",
    "        ),\n",
    "        tooltip_attrs=[\"id\"],\n",
    "        label_attr=\"id\",\n",
    "    ),\n",
    "    edge_args=dict(\n",
    "        color=\"#000\",\n",
    "    ),\n",
    "    width=800,\n",
    "    height=600,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "ae68d7d6-9e95-4a99-ac41-98a294afcca2",
   "metadata": {},
   "outputs": [],
   "source": [
    "tkg = Gtest.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "64e6a5c1-e42d-4ad2-8c32-5cf62bc75852",
   "metadata": {},
   "outputs": [],
   "source": [
    "nx.set_node_attributes(tkg, {\n",
    "    n: {\n",
    "        \"id\": n,\n",
    "    } for n in tkg.nodes\n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "7e895f70-74a2-433c-91c2-a440303ab81a",
   "metadata": {},
   "outputs": [],
   "source": [
    "nx.set_node_attributes(tkg, nx.degree_centrality(tkg), \"degree_centrality\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "a13cc710-01d8-4f52-b066-3796b4609118",
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "decoding to str: need a bytes-like object, NoneType found",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[107], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[43malph\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtkg\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43malph_params\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241m.\u001b[39mconfigure_view(strokeWidth\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0\u001b[39m)\n",
      "File \u001b[1;32mA:\\Arbeitsaufgaben\\lang-main\\.venv\\Lib\\site-packages\\alph\\core.py:195\u001b[0m, in \u001b[0;36malph\u001b[1;34m(G, weight_attr, layout_fn, node_args, edge_args, combo_group_by, combo_node_additional_attrs, combo_layout_fn, combo_node_args, combo_edge_args, combo_empty_attr_action, combo_size_scale_domain, combo_size_scale_range, combo_inner_graph_scale_factor, combo_edge_weight_agg_attr, combo_edge_agg_attrs, combo_edge_weight_threshold, include_edgeless_combo_nodes, non_serializable_datetime_format, width, height, prop_kwargs, padding, nodes_layer_params)\u001b[0m\n\u001b[0;32m    193\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m    194\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m layout_fn:\n\u001b[1;32m--> 195\u001b[0m         pos \u001b[38;5;241m=\u001b[39m \u001b[43mlayout_fn\u001b[49m\u001b[43m(\u001b[49m\u001b[43mG\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    196\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m    197\u001b[0m         pos \u001b[38;5;241m=\u001b[39m layout\u001b[38;5;241m.\u001b[39mdefault_network_layout(G, weight_attr\u001b[38;5;241m=\u001b[39mweight_attr)\n",
      "Cell \u001b[1;32mIn[66], line 3\u001b[0m, in \u001b[0;36m<lambda>\u001b[1;34m(g)\u001b[0m\n\u001b[0;32m      1\u001b[0m alph_params \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mdict\u001b[39m(\n\u001b[0;32m      2\u001b[0m     weight_attr\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mweight\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m----> 3\u001b[0m     layout_fn\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mlambda\u001b[39;00m g: \u001b[43mnx\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mnx_agraph\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpygraphviz_layout\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m      4\u001b[0m \u001b[43m        \u001b[49m\u001b[43mg\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m      5\u001b[0m \u001b[43m        \u001b[49m\u001b[43mprog\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43msfdp\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[0;32m      6\u001b[0m \u001b[43m        \u001b[49m\u001b[43margs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m-GK=5 -Gbeautify=true -Goverlap=true\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\n\u001b[0;32m      7\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m,\n\u001b[0;32m      8\u001b[0m     node_args\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mdict\u001b[39m(\n\u001b[0;32m      9\u001b[0m         size\u001b[38;5;241m=\u001b[39malt\u001b[38;5;241m.\u001b[39mSize(\n\u001b[0;32m     10\u001b[0m             \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdegree_centrality\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m     11\u001b[0m             scale\u001b[38;5;241m=\u001b[39malt\u001b[38;5;241m.\u001b[39mScale(domain\u001b[38;5;241m=\u001b[39m[\u001b[38;5;241m0\u001b[39m,\u001b[38;5;241m1\u001b[39m], \u001b[38;5;28mrange\u001b[39m\u001b[38;5;241m=\u001b[39m[\u001b[38;5;241m12\u001b[39m\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m2\u001b[39m, \u001b[38;5;241m40\u001b[39m\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m2\u001b[39m]),\n\u001b[0;32m     12\u001b[0m             legend\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m     13\u001b[0m         ),\n\u001b[0;32m     14\u001b[0m         \u001b[38;5;66;03m#fill=alt.Color(\u001b[39;00m\n\u001b[0;32m     15\u001b[0m         \u001b[38;5;66;03m#    \"degree_centrality\",\u001b[39;00m\n\u001b[0;32m     16\u001b[0m         \u001b[38;5;66;03m#    scale=alt.Scale(domain=companies, range=palette),\u001b[39;00m\n\u001b[0;32m     17\u001b[0m         \u001b[38;5;66;03m#),\u001b[39;00m\n\u001b[0;32m     18\u001b[0m         stroke\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m#333\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m     19\u001b[0m         strokeWidth\u001b[38;5;241m=\u001b[39malt\u001b[38;5;241m.\u001b[39mSize(\n\u001b[0;32m     20\u001b[0m             \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdegree_centrality\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m     21\u001b[0m             scale\u001b[38;5;241m=\u001b[39malt\u001b[38;5;241m.\u001b[39mScale(domain\u001b[38;5;241m=\u001b[39m[\u001b[38;5;241m0\u001b[39m,\u001b[38;5;241m1\u001b[39m], \u001b[38;5;28mrange\u001b[39m\u001b[38;5;241m=\u001b[39m[\u001b[38;5;241m2\u001b[39m, \u001b[38;5;241m5\u001b[39m]),\n\u001b[0;32m     22\u001b[0m             legend\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m     23\u001b[0m         ),\n\u001b[0;32m     24\u001b[0m         tooltip_attrs\u001b[38;5;241m=\u001b[39m[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mid\u001b[39m\u001b[38;5;124m\"\u001b[39m],\n\u001b[0;32m     25\u001b[0m         label_attr\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mid\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m     26\u001b[0m     ),\n\u001b[0;32m     27\u001b[0m     edge_args\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mdict\u001b[39m(\n\u001b[0;32m     28\u001b[0m         color\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m#000\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m     29\u001b[0m     ),\n\u001b[0;32m     30\u001b[0m     width\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m800\u001b[39m,\n\u001b[0;32m     31\u001b[0m     height\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m600\u001b[39m,\n\u001b[0;32m     32\u001b[0m )\n",
      "File \u001b[1;32mA:\\Arbeitsaufgaben\\lang-main\\.venv\\Lib\\site-packages\\networkx\\drawing\\nx_agraph.py:307\u001b[0m, in \u001b[0;36mpygraphviz_layout\u001b[1;34m(G, prog, root, args)\u001b[0m\n\u001b[0;32m    305\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m root \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m    306\u001b[0m     args \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m-Groot=\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mroot\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m--> 307\u001b[0m A \u001b[38;5;241m=\u001b[39m \u001b[43mto_agraph\u001b[49m\u001b[43m(\u001b[49m\u001b[43mG\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    308\u001b[0m A\u001b[38;5;241m.\u001b[39mlayout(prog\u001b[38;5;241m=\u001b[39mprog, args\u001b[38;5;241m=\u001b[39margs)\n\u001b[0;32m    309\u001b[0m node_pos \u001b[38;5;241m=\u001b[39m {}\n",
      "File \u001b[1;32mA:\\Arbeitsaufgaben\\lang-main\\.venv\\Lib\\site-packages\\networkx\\drawing\\nx_agraph.py:159\u001b[0m, in \u001b[0;36mto_agraph\u001b[1;34m(N)\u001b[0m\n\u001b[0;32m    157\u001b[0m \u001b[38;5;66;03m# add nodes\u001b[39;00m\n\u001b[0;32m    158\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m n, nodedata \u001b[38;5;129;01min\u001b[39;00m N\u001b[38;5;241m.\u001b[39mnodes(data\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m):\n\u001b[1;32m--> 159\u001b[0m     \u001b[43mA\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43madd_node\u001b[49m\u001b[43m(\u001b[49m\u001b[43mn\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    160\u001b[0m     \u001b[38;5;66;03m# Add node data\u001b[39;00m\n\u001b[0;32m    161\u001b[0m     a \u001b[38;5;241m=\u001b[39m A\u001b[38;5;241m.\u001b[39mget_node(n)\n",
      "File \u001b[1;32mA:\\Arbeitsaufgaben\\lang-main\\.venv\\Lib\\site-packages\\pygraphviz\\agraph.py:338\u001b[0m, in \u001b[0;36mAGraph.add_node\u001b[1;34m(self, n, **attr)\u001b[0m\n\u001b[0;32m    336\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m:\n\u001b[0;32m    337\u001b[0m     nh \u001b[38;5;241m=\u001b[39m gv\u001b[38;5;241m.\u001b[39magnode(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandle, n, _Action\u001b[38;5;241m.\u001b[39mcreate)\n\u001b[1;32m--> 338\u001b[0m node \u001b[38;5;241m=\u001b[39m \u001b[43mNode\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnh\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mnh\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    339\u001b[0m node\u001b[38;5;241m.\u001b[39mattr\u001b[38;5;241m.\u001b[39mupdate(\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mattr)\n",
      "File \u001b[1;32mA:\\Arbeitsaufgaben\\lang-main\\.venv\\Lib\\site-packages\\pygraphviz\\agraph.py:1861\u001b[0m, in \u001b[0;36mNode.__new__\u001b[1;34m(self, graph, name, nh)\u001b[0m\n\u001b[0;32m   1859\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__new__\u001b[39m(\u001b[38;5;28mself\u001b[39m, graph, name\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, nh\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m):\n\u001b[0;32m   1860\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m nh \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m-> 1861\u001b[0m         n \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[38;5;21;43m__new__\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mgv\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43magnameof\u001b[49m\u001b[43m(\u001b[49m\u001b[43mnh\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mgraph\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mencoding\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m   1862\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m   1863\u001b[0m         n \u001b[38;5;241m=\u001b[39m \u001b[38;5;28msuper\u001b[39m()\u001b[38;5;241m.\u001b[39m\u001b[38;5;21m__new__\u001b[39m(\u001b[38;5;28mself\u001b[39m, name)\n",
      "\u001b[1;31mTypeError\u001b[0m: decoding to str: need a bytes-like object, NoneType found"
     ]
    }
   ],
   "source": [
    "alph(tkg, **alph_params).configure_view(strokeWidth=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "842e01fa-29cd-4028-9461-c7af24e01c33",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'id': 'Wartungstätigkeit', 'degree_centrality': 0.04225352112676056}"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tkg.nodes['Wartungstätigkeit']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8d36d22e-73fd-44fe-ab08-98f8186bc6b2",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "14efa0e8-0937-44da-a76c-160829a7e9bf",
   "metadata": {},
   "source": [
    "**additional info:**\n",
    "- overlap removal for sfdp Graphviz algorithm not available because of missing triangulation library (only available on Linux)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bfc0f3a7-8865-4b44-bd9c-2c3f4ff9e70e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "1e61aca3-efea-4e38-8174-5ca4b2585256",
   "metadata": {},
   "outputs": [],
   "source": [
    "obj = 'TK-GRAPH_POSTPROCESSING.pkl'\n",
    "# obj = 'TK-GRAPH_ANALYSIS.pkl'\n",
    "load_pth = res_path / obj\n",
    "assert load_pth.exists()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "5d83c04c-03ab-4086-a4e9-ae430e4c6090",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2024-07-03 14:30:35 +0000 | io:INFO | Loaded file successfully.\n"
     ]
    }
   ],
   "source": [
    "ret = io.load_pickle(load_pth)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "4718b54e-0891-4f70-8c67-90c439bc8bfd",
   "metadata": {},
   "outputs": [],
   "source": [
    "tkg = ret[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "ddcb4ff0-eac4-45ba-9c6e-83ada4b0276c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "TokenGraph(name: TokenGraph, number of nodes: 6028, number of edges: 17950)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tkg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "97c46ca7-ca9f-4d11-8d86-cfbd819b7573",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "f6fc2c6a-2171-411d-92f1-4ab694adda7b",
   "metadata": {},
   "outputs": [],
   "source": [
    "Gtest = rescale_edge_weights(tkg)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "859be6a3-a919-433a-a0a7-f4d74cdc6bf7",
   "metadata": {},
   "source": [
    "break_early = False\n",
    "i = 0\n",
    "for idx, (node1, node2) in enumerate(list(Gtest.edges)):\n",
    "    if break_early and i == 10:\n",
    "        break\n",
    "    Gtest[node1][node2]['weight'] = adjusted_weights[idx]\n",
    "    \n",
    "    i += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "f381b25a-6149-4a2a-876c-4cbd8bb9bd04",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wartungstätigkeit Vorgabe 1.0\n",
      "Wartungstätigkeit Maschinenhersteller 1.0\n",
      "Wartungstätigkeit Maschinenbediener 0.8215\n",
      "Wartungstätigkeit Laserabteilung 0.8215\n",
      "Wartungstätigkeit Arbeitsplan 0.8219\n",
      "Wartungstätigkeit abarbeiten 0.8215\n",
      "Wartungstätigkeit Webmaschinenkontrollliste 0.2534\n",
      "Wartungstätigkeit sehen 0.2534\n",
      "Vorgabe Maschinenhersteller 1.0\n",
      "Vorgabe Wartungsplan 0.9181\n"
     ]
    }
   ],
   "source": [
    "break_early = True\n",
    "i = 0\n",
    "for n1, n2, w in Gtest.edges.data('weight'):\n",
    "    if break_early and i == 10:\n",
    "        break\n",
    "    print(n1, n2, w)\n",
    "\n",
    "    i += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "c45a8136-2a81-4ede-a087-cf86ce85d939",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2024-07-03 14:30:39 +0000 | graphs:INFO | Successfully converted graph to one with undirected edges.\n",
      "2024-07-03 14:30:39 +0000 | graphs:INFO | Graph properties: 6028 Nodes, 17554 Edges\n",
      "2024-07-03 14:30:39 +0000 | graphs:INFO | Node memory: 373.36 KB\n",
      "2024-07-03 14:30:39 +0000 | graphs:INFO | Edge memory: 959.98 KB\n",
      "2024-07-03 14:30:39 +0000 | graphs:INFO | Total memory: 1333.34 KB\n"
     ]
    }
   ],
   "source": [
    "Gtest.to_undirected(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "303d8d0c-9320-4739-adf6-ac9ba82731de",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "a7929935-3bd2-4eb8-907c-4d37251f11ea",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wartungstätigkeit Vorgabe 1.0\n",
      "Wartungstätigkeit Maschinenhersteller 1.0\n",
      "Wartungstätigkeit sehen 0.2533999979496002\n",
      "Wartungstätigkeit Maschinenbediener 0.8215000033378601\n",
      "Wartungstätigkeit Laserabteilung 0.8215000033378601\n",
      "Wartungstätigkeit Arbeitsplan 0.8219000101089478\n",
      "Wartungstätigkeit abarbeiten 0.8215000033378601\n",
      "Wartungstätigkeit Webmaschinenkontrollliste 0.2533999979496002\n",
      "Vorgabe Maschinenhersteller 1.0\n",
      "Vorgabe Wartungsplan 0.9180999994277954\n"
     ]
    }
   ],
   "source": [
    "break_early = True\n",
    "i = 0\n",
    "for n1, n2, w in Gtest.undirected.edges.data('weight'):\n",
    "    if break_early and i == 10:\n",
    "        break\n",
    "    print(n1, n2, w)\n",
    "\n",
    "    i += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "4df89d59-3832-4b6d-9eae-b3220b6f7e5b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'num_nodes': 6028,\n",
       " 'num_edges': 17554,\n",
       " 'min_edge_weight': 0.09520000219345093,\n",
       " 'max_edge_weight': 1.7527999877929688,\n",
       " 'node_memory': 382321,\n",
       " 'edge_memory': 983024,\n",
       " 'total_memory': 1365345}"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Gtest.metadata_undirected"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "adf02de4-f22c-499f-91bf-ac1be1b3186f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'num_nodes': 6028,\n",
       " 'num_edges': 17950,\n",
       " 'min_edge_weight': 0.0952,\n",
       " 'max_edge_weight': 1.0,\n",
       " 'node_memory': 382321,\n",
       " 'edge_memory': 1005200,\n",
       " 'total_memory': 1387521}"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Gtest.metadata_directed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9e939c9c-ba9e-4576-9d85-afba8481af93",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "bfafdc8b-418d-4dd8-b986-d36082ba870e",
   "metadata": {},
   "outputs": [],
   "source": [
    "c_comps = nx.connected_components(Gtest.undirected)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "abf5603d-dab9-49a0-8c86-d2429a36d24d",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5714\n",
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      "2\n",
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     ]
    }
   ],
   "source": [
    "for comp in c_comps:\n",
    "    print(len(comp))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "80db8d16-fa48-417d-91b0-37e5b32f3b74",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b2e2cbbe-68ef-4ea0-9ed0-b114be1efd08",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "fcd9247f-c4f9-4f73-9fd3-2ab56700073f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "You are connected to Cytoscape!\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'apiVersion': 'v1',\n",
       " 'cytoscapeVersion': '3.10.2',\n",
       " 'automationAPIVersion': '1.9.0',\n",
       " 'py4cytoscapeVersion': '1.9.0'}"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import py4cytoscape as py4\n",
    "dir(py4)\n",
    "py4.cytoscape_ping()\n",
    "py4.cytoscape_version_info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b9290659-e33c-47fc-8d89-7aa3dd6e843a",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
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