tutorials/robots_and_marbles/robot-marbles-part-5/robot-marbles-part-5.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/cadCAD-org/demos/blob/master/tutorials/robots_and_marbles/robot-marbles-part-5/robot-marbles-part-5.ipynb)\n",
    "\n",
    "# cadCAD Tutorials: The Robot and the Marbles Part 5 - Networks\n",
    "\n",
    "To expand upon our previous examples, we will introduce the concept of using a graph network object that is updated during each state update. The ability to essential embed a graph 'database' into a state is a game changer for scalability, allowing increased complexity with multiple agents or components is represented, easily updated. Below, building upon our previous examples, we will represent the Robots and Marbles example with n boxes, and a variable number of marbles. \n",
    "\n",
    "## Behavior and Mechanisms:\n",
    "* A network of robotic arms is capable of taking a marble from one of their boxes and dropping it into the other one. \n",
    "* Each robotic arm in the network only controls two boxes and they act by moving a marble from one box to the other.\n",
    "* Each robotic arm is programmed to take one marble at a time from the box containing the most significant number of marbles and drop it in the other box. It repeats that process until the boxes contain an equal number of marbles.\n",
    "* For our analysis of this system, suppose we are only interested in monitoring the number of marbles in their two boxes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: cadcad in /Users/andrewclark/anaconda3/lib/python3.11/site-packages (0.5.3)\n",
      "Requirement already satisfied: matplotlib in /Users/andrewclark/anaconda3/lib/python3.11/site-packages (3.7.2)\n",
      "Requirement already satisfied: pandas in /Users/andrewclark/anaconda3/lib/python3.11/site-packages (2.0.3)\n",
      "Requirement already satisfied: numpy in /Users/andrewclark/anaconda3/lib/python3.11/site-packages (1.24.3)\n",
      "Requirement already satisfied: networkx in /Users/andrewclark/anaconda3/lib/python3.11/site-packages (3.1)\n",
      "Requirement already satisfied: scipy in /Users/andrewclark/anaconda3/lib/python3.11/site-packages (1.11.1)\n",
      "Requirement already satisfied: seaborn in /Users/andrewclark/anaconda3/lib/python3.11/site-packages (0.12.2)\n",
      "Requirement already satisfied: funcy in /Users/andrewclark/anaconda3/lib/python3.11/site-packages (from cadcad) (2.0)\n",
      "Requirement already satisfied: dill in /Users/andrewclark/anaconda3/lib/python3.11/site-packages (from cadcad) (0.3.8)\n",
      "Requirement already satisfied: pathos in /Users/andrewclark/anaconda3/lib/python3.11/site-packages (from cadcad) (0.3.2)\n",
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      "Requirement already satisfied: pillow>=6.2.0 in /Users/andrewclark/anaconda3/lib/python3.11/site-packages (from matplotlib) (10.0.1)\n",
      "Requirement already satisfied: pyparsing<3.1,>=2.3.1 in /Users/andrewclark/anaconda3/lib/python3.11/site-packages (from matplotlib) (3.0.9)\n",
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      "Requirement already satisfied: ppft>=1.7.6.8 in /Users/andrewclark/anaconda3/lib/python3.11/site-packages (from pathos->cadcad) (1.7.6.8)\n",
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     ]
    }
   ],
   "source": [
    "#%%capture\n",
    "# Only run this cell if you need to install the libraries\n",
    "# If running in google colab, this is needed.\n",
    "\n",
    "!pip install cadcad matplotlib pandas numpy networkx scipy seaborn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "# Import dependancies\n",
    "\n",
    "# Data processing and plotting libraries\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from random import normalvariate\n",
    "import matplotlib.pyplot as plt\n",
    "import networkx as nx\n",
    "\n",
    "# cadCAD specific libraries\n",
    "from cadCAD.configuration.utils import config_sim\n",
    "from cadCAD.configuration import Experiment\n",
    "from cadCAD.engine import ExecutionContext, Executor\n",
    "from cadCAD import configs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "# define global variables\n",
    "BOXES=5 #number of boxes in our network\n",
    "m= 2 #for barabasi graph type number of edges is (n-2)*m"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "We create a [Barabási–Albert](https://en.wikipedia.org/wiki/Barab%C3%A1si%E2%80%93Albert_model) graph and then fill the 5 boxes with between 1 and 10 balls. You can create as many different nodes or types of nodes as needed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "# create graph object with the number of boxes as nodes\n",
    "network = nx.barabasi_albert_graph(BOXES, m)\n",
    "\n",
    "# add balls to box nodes\n",
    "for node in network.nodes:\n",
    "    network.nodes[node]['balls'] = np.random.randint(1,10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "Now we will plot the network of boxes and with their labels showing how many balls are in each box."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot of boxes and balls\n",
    "nx.draw_kamada_kawai(network,labels=nx.get_node_attributes(network,'balls'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "# we initialize the cadCAD state as a network object\n",
    "initial_state = {'network':network}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "Behavior: node by edge dimensional operator: input the states of the boxes, output the deltas along the edges\n",
    "\n",
    "Find the difference that each robot sees between their two boxes, ie, find which of the two nodes connected to an edge has the greater value for each edge that exists.\n",
    "\n",
    "We specify the robotic networks logic in a Policy/Behavior function. Unlike previous examples, our policy controls a vector valued action, defined over the edges of our network"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "def p_robotic_network(params, substep, state_history, previous_state):\n",
    "    network = previous_state['network']\n",
    "    delta_balls = {}\n",
    "    for e in network.edges:\n",
    "        src = e[0]\n",
    "        dst = e[1]\n",
    "        #transfer one ball across the edge in the direction of more balls to less\n",
    "        delta_balls[e] = np.sign(network.nodes[src]['balls']-network.nodes[dst]['balls'])\n",
    "    return({'delta': delta_balls})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "Mechanism: edge by node dimensional operator : input the deltas along the edges and update the boxes\n",
    "\n",
    "We make the state update functions less \"intelligent\", ie. they simply add the number of marbles specified in `policy_input` (which, per the policy function definition, may be negative)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "def s_update_network(params, substep, state_history,  previous_state, policy_input):\n",
    "    network = previous_state['network'] \n",
    "    delta_balls = policy_input['delta']\n",
    "    for e in network.edges:\n",
    "        move_ball = delta_balls[e]\n",
    "        src = e[0]\n",
    "        dst = e[1]\n",
    "        if (network.nodes[src]['balls'] >= move_ball) and (network.nodes[dst]['balls'] >= -move_ball):\n",
    "            network.nodes[src]['balls'] = network.nodes[src]['balls']-move_ball\n",
    "            network.nodes[dst]['balls'] = network.nodes[dst]['balls']+move_ball\n",
    "            \n",
    "    return ('network', network)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "# wire up the mechanisms and states\n",
    "partial_state_update_blocks = [\n",
    "    { \n",
    "        'policies': { # The following policy functions will be evaluated and their returns will be passed to the state update functions\n",
    "            'action': p_robotic_network\n",
    "        },\n",
    "        'variables': { # The following state variables will be updated simultaneously\n",
    "            'network': s_update_network\n",
    "            \n",
    "        }\n",
    "    }\n",
    "]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "Settings of general simulation parameters, unrelated to the system itself\n",
    "* `N` is the number of times the simulation will be run (Monte Carlo runs)\n",
    "* `T` is a range with the number of discrete units of time the simulation will run for"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "MONTE_CARLO_RUNS = 1\n",
    "SIMULATION_TIMESTEPS = 25 # Timesteps / iterations of the simulation\n",
    "\n",
    "sim_config = config_sim(\n",
    "    {\n",
    "        'N': MONTE_CARLO_RUNS,\n",
    "        'T': range(SIMULATION_TIMESTEPS),\n",
    "        #'M': {} # This will be explained in later tutorials\n",
    "    }\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "                  ___________    ____\n",
      "  ________ __ ___/ / ____/   |  / __ \\\n",
      " / ___/ __` / __  / /   / /| | / / / /\n",
      "/ /__/ /_/ / /_/ / /___/ ___ |/ /_/ /\n",
      "\\___/\\__,_/\\__,_/\\____/_/  |_/_____/\n",
      "by cadCAD\n",
      "\n",
      "cadCAD Version: 0.5.3\n",
      "Execution Mode: local_proc\n",
      "Simulation Dimensions:\n",
      "Entire Simulation: (Models, Unique Timesteps, Params, Total Runs, Sub-States) = (1, 25, 0, 1, 1)\n",
      "     Simulation 0: (Timesteps, Params, Runs, Sub-States) = (25, 0, 1, 1)\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "593937a13df44a62ba4585d86a5fb141",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Initializing configurations:   0%|          | 0/1 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Execution Method: single_proc_exec\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "676f6f73985c43148007b0ea5c0fbb49",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Flattening results:   0%|          | 0/26 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total execution time: 0.03s\n"
     ]
    }
   ],
   "source": [
    "del configs[:]\n",
    "\n",
    "experiment = Experiment()\n",
    "\n",
    "experiment.append_configs(\n",
    "    sim_configs=sim_config,\n",
    "    initial_state=initial_state,\n",
    "    partial_state_update_blocks=partial_state_update_blocks,\n",
    ")\n",
    "\n",
    "\n",
    "exec_context = ExecutionContext()\n",
    "run = Executor(exec_context=exec_context, configs=experiment.configs)\n",
    "\n",
    "(system_events, tensor_field, sessions) = run.execute()\n",
    "df = pd.DataFrame(system_events)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "We create a helper functions to extract the networkx graph object from the Pandas dataframe and plot it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "#NetworkX helper function\n",
    "def get_nodes(g):\n",
    "    return [node for node in g.nodes if g.nodes[node]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "Using our helper function get_nodes() we pull out the boxes ball quantity and save it to a new dataframe column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "df['Balls'] = df.network.apply(lambda g: np.array([g.nodes[j]['balls'] for j in get_nodes(g)]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "data = np.stack(df['Balls'].values)\n",
    "balls_df=pd.DataFrame(data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "Next we will plot the number of balls in each box over the simulation time period. We can see an oscillation occurs never reaching an equilibrium due to the uneven nature of the boxes and balls."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = balls_df.plot( marker='o', markersize=10, markeredgewidth=2, alpha=0.9, markerfacecolor='black',\n",
    "                linewidth=3, figsize=(12,8),  title=\"Marbles in each box as a function of time\", \n",
    "                ylabel='Number of Marbles', grid=True, fillstyle='none',  \n",
    "                xticks=list(range(SIMULATION_TIMESTEPS)),\n",
    "                yticks=list(range(10)))\n",
    "ax.legend( title='Box #');\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "#T_421cb_row0_col0 {\n",
       "  background-color: #5ec962;\n",
       "  color: #000000;\n",
       "  font-size: 20px;\n",
       "}\n",
       "#T_421cb_row0_col1 {\n",
       "  background-color: #22a884;\n",
       "  color: #f1f1f1;\n",
       "  font-size: 20px;\n",
       "}\n",
       "#T_421cb_row0_col2, #T_421cb_row1_col2, #T_421cb_row2_col4, #T_421cb_row2_col6, #T_421cb_row2_col8, #T_421cb_row2_col10, #T_421cb_row2_col12, #T_421cb_row2_col14, #T_421cb_row2_col16, #T_421cb_row2_col18, #T_421cb_row2_col20, #T_421cb_row2_col22, #T_421cb_row2_col24, #T_421cb_row3_col2 {\n",
       "  background-color: #35b779;\n",
       "  color: #f1f1f1;\n",
       "  font-size: 20px;\n",
       "}\n",
       "#T_421cb_row0_col3, #T_421cb_row3_col3 {\n",
       "  background-color: #21918c;\n",
       "  color: #f1f1f1;\n",
       "  font-size: 20px;\n",
       "}\n",
       "#T_421cb_row0_col4, #T_421cb_row1_col6, #T_421cb_row1_col7, #T_421cb_row1_col8, #T_421cb_row1_col9, #T_421cb_row1_col10, #T_421cb_row1_col11, #T_421cb_row1_col12, #T_421cb_row1_col13, #T_421cb_row1_col14, #T_421cb_row1_col15, #T_421cb_row1_col16, #T_421cb_row1_col17, #T_421cb_row1_col18, #T_421cb_row1_col19, #T_421cb_row1_col20, #T_421cb_row1_col21, #T_421cb_row1_col22, #T_421cb_row1_col23, #T_421cb_row1_col24, #T_421cb_row1_col25 {\n",
       "  background-color: #31688e;\n",
       "  color: #f1f1f1;\n",
       "  font-size: 20px;\n",
       "}\n",
       "#T_421cb_row0_col5, #T_421cb_row0_col7, #T_421cb_row0_col9, #T_421cb_row0_col11, #T_421cb_row0_col13, #T_421cb_row0_col15, #T_421cb_row0_col17, #T_421cb_row0_col19, #T_421cb_row0_col21, #T_421cb_row0_col23, #T_421cb_row0_col25, #T_421cb_row1_col3, #T_421cb_row1_col5, #T_421cb_row3_col0, #T_421cb_row3_col1, #T_421cb_row3_col4, #T_421cb_row3_col6, #T_421cb_row3_col8, #T_421cb_row3_col10, #T_421cb_row3_col12, #T_421cb_row3_col14, #T_421cb_row3_col16, #T_421cb_row3_col18, #T_421cb_row3_col20, #T_421cb_row3_col22, #T_421cb_row3_col24, #T_421cb_row4_col2, #T_421cb_row4_col4, #T_421cb_row4_col6, #T_421cb_row4_col8, #T_421cb_row4_col10, #T_421cb_row4_col12, #T_421cb_row4_col14, #T_421cb_row4_col16, #T_421cb_row4_col18, #T_421cb_row4_col20, #T_421cb_row4_col22, #T_421cb_row4_col24 {\n",
       "  background-color: #fde725;\n",
       "  color: #000000;\n",
       "  font-size: 20px;\n",
       "}\n",
       "#T_421cb_row0_col6, #T_421cb_row0_col8, #T_421cb_row0_col10, #T_421cb_row0_col12, #T_421cb_row0_col14, #T_421cb_row0_col16, #T_421cb_row0_col18, #T_421cb_row0_col20, #T_421cb_row0_col22, #T_421cb_row0_col24, #T_421cb_row1_col4, #T_421cb_row2_col0, #T_421cb_row2_col1, #T_421cb_row2_col2, #T_421cb_row2_col3, #T_421cb_row2_col5, #T_421cb_row2_col7, #T_421cb_row2_col9, #T_421cb_row2_col11, #T_421cb_row2_col13, #T_421cb_row2_col15, #T_421cb_row2_col17, #T_421cb_row2_col19, #T_421cb_row2_col21, #T_421cb_row2_col23, #T_421cb_row2_col25, #T_421cb_row3_col5, #T_421cb_row3_col7, #T_421cb_row3_col9, #T_421cb_row3_col11, #T_421cb_row3_col13, #T_421cb_row3_col15, #T_421cb_row3_col17, #T_421cb_row3_col19, #T_421cb_row3_col21, #T_421cb_row3_col23, #T_421cb_row3_col25, #T_421cb_row4_col3, #T_421cb_row4_col5, #T_421cb_row4_col7, #T_421cb_row4_col9, #T_421cb_row4_col11, #T_421cb_row4_col13, #T_421cb_row4_col15, #T_421cb_row4_col17, #T_421cb_row4_col19, #T_421cb_row4_col21, #T_421cb_row4_col23, #T_421cb_row4_col25 {\n",
       "  background-color: #440154;\n",
       "  color: #f1f1f1;\n",
       "  font-size: 20px;\n",
       "}\n",
       "#T_421cb_row1_col0 {\n",
       "  background-color: #3b528b;\n",
       "  color: #f1f1f1;\n",
       "  font-size: 20px;\n",
       "}\n",
       "#T_421cb_row1_col1 {\n",
       "  background-color: #7ad151;\n",
       "  color: #000000;\n",
       "  font-size: 20px;\n",
       "}\n",
       "#T_421cb_row4_col0 {\n",
       "  background-color: #2c728e;\n",
       "  color: #f1f1f1;\n",
       "  font-size: 20px;\n",
       "}\n",
       "#T_421cb_row4_col1 {\n",
       "  background-color: #2a788e;\n",
       "  color: #f1f1f1;\n",
       "  font-size: 20px;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_421cb\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_421cb_level0_col0\" class=\"col_heading level0 col0\" >0</th>\n",
       "      <th id=\"T_421cb_level0_col1\" class=\"col_heading level0 col1\" >1</th>\n",
       "      <th id=\"T_421cb_level0_col2\" class=\"col_heading level0 col2\" >2</th>\n",
       "      <th id=\"T_421cb_level0_col3\" class=\"col_heading level0 col3\" >3</th>\n",
       "      <th id=\"T_421cb_level0_col4\" class=\"col_heading level0 col4\" >4</th>\n",
       "      <th id=\"T_421cb_level0_col5\" class=\"col_heading level0 col5\" >5</th>\n",
       "      <th id=\"T_421cb_level0_col6\" class=\"col_heading level0 col6\" >6</th>\n",
       "      <th id=\"T_421cb_level0_col7\" class=\"col_heading level0 col7\" >7</th>\n",
       "      <th id=\"T_421cb_level0_col8\" class=\"col_heading level0 col8\" >8</th>\n",
       "      <th id=\"T_421cb_level0_col9\" class=\"col_heading level0 col9\" >9</th>\n",
       "      <th id=\"T_421cb_level0_col10\" class=\"col_heading level0 col10\" >10</th>\n",
       "      <th id=\"T_421cb_level0_col11\" class=\"col_heading level0 col11\" >11</th>\n",
       "      <th id=\"T_421cb_level0_col12\" class=\"col_heading level0 col12\" >12</th>\n",
       "      <th id=\"T_421cb_level0_col13\" class=\"col_heading level0 col13\" >13</th>\n",
       "      <th id=\"T_421cb_level0_col14\" class=\"col_heading level0 col14\" >14</th>\n",
       "      <th id=\"T_421cb_level0_col15\" class=\"col_heading level0 col15\" >15</th>\n",
       "      <th id=\"T_421cb_level0_col16\" class=\"col_heading level0 col16\" >16</th>\n",
       "      <th id=\"T_421cb_level0_col17\" class=\"col_heading level0 col17\" >17</th>\n",
       "      <th id=\"T_421cb_level0_col18\" class=\"col_heading level0 col18\" >18</th>\n",
       "      <th id=\"T_421cb_level0_col19\" class=\"col_heading level0 col19\" >19</th>\n",
       "      <th id=\"T_421cb_level0_col20\" class=\"col_heading level0 col20\" >20</th>\n",
       "      <th id=\"T_421cb_level0_col21\" class=\"col_heading level0 col21\" >21</th>\n",
       "      <th id=\"T_421cb_level0_col22\" class=\"col_heading level0 col22\" >22</th>\n",
       "      <th id=\"T_421cb_level0_col23\" class=\"col_heading level0 col23\" >23</th>\n",
       "      <th id=\"T_421cb_level0_col24\" class=\"col_heading level0 col24\" >24</th>\n",
       "      <th id=\"T_421cb_level0_col25\" class=\"col_heading level0 col25\" >25</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_421cb_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "      <td id=\"T_421cb_row0_col0\" class=\"data row0 col0\" >7</td>\n",
       "      <td id=\"T_421cb_row0_col1\" class=\"data row0 col1\" >5</td>\n",
       "      <td id=\"T_421cb_row0_col2\" class=\"data row0 col2\" >5</td>\n",
       "      <td id=\"T_421cb_row0_col3\" class=\"data row0 col3\" >5</td>\n",
       "      <td id=\"T_421cb_row0_col4\" class=\"data row0 col4\" >4</td>\n",
       "      <td id=\"T_421cb_row0_col5\" class=\"data row0 col5\" >6</td>\n",
       "      <td id=\"T_421cb_row0_col6\" class=\"data row0 col6\" >3</td>\n",
       "      <td id=\"T_421cb_row0_col7\" class=\"data row0 col7\" >7</td>\n",
       "      <td id=\"T_421cb_row0_col8\" class=\"data row0 col8\" >3</td>\n",
       "      <td id=\"T_421cb_row0_col9\" class=\"data row0 col9\" >7</td>\n",
       "      <td id=\"T_421cb_row0_col10\" class=\"data row0 col10\" >3</td>\n",
       "      <td id=\"T_421cb_row0_col11\" class=\"data row0 col11\" >7</td>\n",
       "      <td id=\"T_421cb_row0_col12\" class=\"data row0 col12\" >3</td>\n",
       "      <td id=\"T_421cb_row0_col13\" class=\"data row0 col13\" >7</td>\n",
       "      <td id=\"T_421cb_row0_col14\" class=\"data row0 col14\" >3</td>\n",
       "      <td id=\"T_421cb_row0_col15\" class=\"data row0 col15\" >7</td>\n",
       "      <td id=\"T_421cb_row0_col16\" class=\"data row0 col16\" >3</td>\n",
       "      <td id=\"T_421cb_row0_col17\" class=\"data row0 col17\" >7</td>\n",
       "      <td id=\"T_421cb_row0_col18\" class=\"data row0 col18\" >3</td>\n",
       "      <td id=\"T_421cb_row0_col19\" class=\"data row0 col19\" >7</td>\n",
       "      <td id=\"T_421cb_row0_col20\" class=\"data row0 col20\" >3</td>\n",
       "      <td id=\"T_421cb_row0_col21\" class=\"data row0 col21\" >7</td>\n",
       "      <td id=\"T_421cb_row0_col22\" class=\"data row0 col22\" >3</td>\n",
       "      <td id=\"T_421cb_row0_col23\" class=\"data row0 col23\" >7</td>\n",
       "      <td id=\"T_421cb_row0_col24\" class=\"data row0 col24\" >3</td>\n",
       "      <td id=\"T_421cb_row0_col25\" class=\"data row0 col25\" >7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_421cb_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "      <td id=\"T_421cb_row1_col0\" class=\"data row1 col0\" >3</td>\n",
       "      <td id=\"T_421cb_row1_col1\" class=\"data row1 col1\" >6</td>\n",
       "      <td id=\"T_421cb_row1_col2\" class=\"data row1 col2\" >5</td>\n",
       "      <td id=\"T_421cb_row1_col3\" class=\"data row1 col3\" >6</td>\n",
       "      <td id=\"T_421cb_row1_col4\" class=\"data row1 col4\" >3</td>\n",
       "      <td id=\"T_421cb_row1_col5\" class=\"data row1 col5\" >6</td>\n",
       "      <td id=\"T_421cb_row1_col6\" class=\"data row1 col6\" >4</td>\n",
       "      <td id=\"T_421cb_row1_col7\" class=\"data row1 col7\" >5</td>\n",
       "      <td id=\"T_421cb_row1_col8\" class=\"data row1 col8\" >4</td>\n",
       "      <td id=\"T_421cb_row1_col9\" class=\"data row1 col9\" >5</td>\n",
       "      <td id=\"T_421cb_row1_col10\" class=\"data row1 col10\" >4</td>\n",
       "      <td id=\"T_421cb_row1_col11\" class=\"data row1 col11\" >5</td>\n",
       "      <td id=\"T_421cb_row1_col12\" class=\"data row1 col12\" >4</td>\n",
       "      <td id=\"T_421cb_row1_col13\" class=\"data row1 col13\" >5</td>\n",
       "      <td id=\"T_421cb_row1_col14\" class=\"data row1 col14\" >4</td>\n",
       "      <td id=\"T_421cb_row1_col15\" class=\"data row1 col15\" >5</td>\n",
       "      <td id=\"T_421cb_row1_col16\" class=\"data row1 col16\" >4</td>\n",
       "      <td id=\"T_421cb_row1_col17\" class=\"data row1 col17\" >5</td>\n",
       "      <td id=\"T_421cb_row1_col18\" class=\"data row1 col18\" >4</td>\n",
       "      <td id=\"T_421cb_row1_col19\" class=\"data row1 col19\" >5</td>\n",
       "      <td id=\"T_421cb_row1_col20\" class=\"data row1 col20\" >4</td>\n",
       "      <td id=\"T_421cb_row1_col21\" class=\"data row1 col21\" >5</td>\n",
       "      <td id=\"T_421cb_row1_col22\" class=\"data row1 col22\" >4</td>\n",
       "      <td id=\"T_421cb_row1_col23\" class=\"data row1 col23\" >5</td>\n",
       "      <td id=\"T_421cb_row1_col24\" class=\"data row1 col24\" >4</td>\n",
       "      <td id=\"T_421cb_row1_col25\" class=\"data row1 col25\" >5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_421cb_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "      <td id=\"T_421cb_row2_col0\" class=\"data row2 col0\" >1</td>\n",
       "      <td id=\"T_421cb_row2_col1\" class=\"data row2 col1\" >2</td>\n",
       "      <td id=\"T_421cb_row2_col2\" class=\"data row2 col2\" >3</td>\n",
       "      <td id=\"T_421cb_row2_col3\" class=\"data row2 col3\" >4</td>\n",
       "      <td id=\"T_421cb_row2_col4\" class=\"data row2 col4\" >5</td>\n",
       "      <td id=\"T_421cb_row2_col5\" class=\"data row2 col5\" >4</td>\n",
       "      <td id=\"T_421cb_row2_col6\" class=\"data row2 col6\" >5</td>\n",
       "      <td id=\"T_421cb_row2_col7\" class=\"data row2 col7\" >4</td>\n",
       "      <td id=\"T_421cb_row2_col8\" class=\"data row2 col8\" >5</td>\n",
       "      <td id=\"T_421cb_row2_col9\" class=\"data row2 col9\" >4</td>\n",
       "      <td id=\"T_421cb_row2_col10\" class=\"data row2 col10\" >5</td>\n",
       "      <td id=\"T_421cb_row2_col11\" class=\"data row2 col11\" >4</td>\n",
       "      <td id=\"T_421cb_row2_col12\" class=\"data row2 col12\" >5</td>\n",
       "      <td id=\"T_421cb_row2_col13\" class=\"data row2 col13\" >4</td>\n",
       "      <td id=\"T_421cb_row2_col14\" class=\"data row2 col14\" >5</td>\n",
       "      <td id=\"T_421cb_row2_col15\" class=\"data row2 col15\" >4</td>\n",
       "      <td id=\"T_421cb_row2_col16\" class=\"data row2 col16\" >5</td>\n",
       "      <td id=\"T_421cb_row2_col17\" class=\"data row2 col17\" >4</td>\n",
       "      <td id=\"T_421cb_row2_col18\" class=\"data row2 col18\" >5</td>\n",
       "      <td id=\"T_421cb_row2_col19\" class=\"data row2 col19\" >4</td>\n",
       "      <td id=\"T_421cb_row2_col20\" class=\"data row2 col20\" >5</td>\n",
       "      <td id=\"T_421cb_row2_col21\" class=\"data row2 col21\" >4</td>\n",
       "      <td id=\"T_421cb_row2_col22\" class=\"data row2 col22\" >5</td>\n",
       "      <td id=\"T_421cb_row2_col23\" class=\"data row2 col23\" >4</td>\n",
       "      <td id=\"T_421cb_row2_col24\" class=\"data row2 col24\" >5</td>\n",
       "      <td id=\"T_421cb_row2_col25\" class=\"data row2 col25\" >4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_421cb_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "      <td id=\"T_421cb_row3_col0\" class=\"data row3 col0\" >9</td>\n",
       "      <td id=\"T_421cb_row3_col1\" class=\"data row3 col1\" >7</td>\n",
       "      <td id=\"T_421cb_row3_col2\" class=\"data row3 col2\" >5</td>\n",
       "      <td id=\"T_421cb_row3_col3\" class=\"data row3 col3\" >5</td>\n",
       "      <td id=\"T_421cb_row3_col4\" class=\"data row3 col4\" >6</td>\n",
       "      <td id=\"T_421cb_row3_col5\" class=\"data row3 col5\" >4</td>\n",
       "      <td id=\"T_421cb_row3_col6\" class=\"data row3 col6\" >6</td>\n",
       "      <td id=\"T_421cb_row3_col7\" class=\"data row3 col7\" >4</td>\n",
       "      <td id=\"T_421cb_row3_col8\" class=\"data row3 col8\" >6</td>\n",
       "      <td id=\"T_421cb_row3_col9\" class=\"data row3 col9\" >4</td>\n",
       "      <td id=\"T_421cb_row3_col10\" class=\"data row3 col10\" >6</td>\n",
       "      <td id=\"T_421cb_row3_col11\" class=\"data row3 col11\" >4</td>\n",
       "      <td id=\"T_421cb_row3_col12\" class=\"data row3 col12\" >6</td>\n",
       "      <td id=\"T_421cb_row3_col13\" class=\"data row3 col13\" >4</td>\n",
       "      <td id=\"T_421cb_row3_col14\" class=\"data row3 col14\" >6</td>\n",
       "      <td id=\"T_421cb_row3_col15\" class=\"data row3 col15\" >4</td>\n",
       "      <td id=\"T_421cb_row3_col16\" class=\"data row3 col16\" >6</td>\n",
       "      <td id=\"T_421cb_row3_col17\" class=\"data row3 col17\" >4</td>\n",
       "      <td id=\"T_421cb_row3_col18\" class=\"data row3 col18\" >6</td>\n",
       "      <td id=\"T_421cb_row3_col19\" class=\"data row3 col19\" >4</td>\n",
       "      <td id=\"T_421cb_row3_col20\" class=\"data row3 col20\" >6</td>\n",
       "      <td id=\"T_421cb_row3_col21\" class=\"data row3 col21\" >4</td>\n",
       "      <td id=\"T_421cb_row3_col22\" class=\"data row3 col22\" >6</td>\n",
       "      <td id=\"T_421cb_row3_col23\" class=\"data row3 col23\" >4</td>\n",
       "      <td id=\"T_421cb_row3_col24\" class=\"data row3 col24\" >6</td>\n",
       "      <td id=\"T_421cb_row3_col25\" class=\"data row3 col25\" >4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_421cb_level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
       "      <td id=\"T_421cb_row4_col0\" class=\"data row4 col0\" >4</td>\n",
       "      <td id=\"T_421cb_row4_col1\" class=\"data row4 col1\" >4</td>\n",
       "      <td id=\"T_421cb_row4_col2\" class=\"data row4 col2\" >6</td>\n",
       "      <td id=\"T_421cb_row4_col3\" class=\"data row4 col3\" >4</td>\n",
       "      <td id=\"T_421cb_row4_col4\" class=\"data row4 col4\" >6</td>\n",
       "      <td id=\"T_421cb_row4_col5\" class=\"data row4 col5\" >4</td>\n",
       "      <td id=\"T_421cb_row4_col6\" class=\"data row4 col6\" >6</td>\n",
       "      <td id=\"T_421cb_row4_col7\" class=\"data row4 col7\" >4</td>\n",
       "      <td id=\"T_421cb_row4_col8\" class=\"data row4 col8\" >6</td>\n",
       "      <td id=\"T_421cb_row4_col9\" class=\"data row4 col9\" >4</td>\n",
       "      <td id=\"T_421cb_row4_col10\" class=\"data row4 col10\" >6</td>\n",
       "      <td id=\"T_421cb_row4_col11\" class=\"data row4 col11\" >4</td>\n",
       "      <td id=\"T_421cb_row4_col12\" class=\"data row4 col12\" >6</td>\n",
       "      <td id=\"T_421cb_row4_col13\" class=\"data row4 col13\" >4</td>\n",
       "      <td id=\"T_421cb_row4_col14\" class=\"data row4 col14\" >6</td>\n",
       "      <td id=\"T_421cb_row4_col15\" class=\"data row4 col15\" >4</td>\n",
       "      <td id=\"T_421cb_row4_col16\" class=\"data row4 col16\" >6</td>\n",
       "      <td id=\"T_421cb_row4_col17\" class=\"data row4 col17\" >4</td>\n",
       "      <td id=\"T_421cb_row4_col18\" class=\"data row4 col18\" >6</td>\n",
       "      <td id=\"T_421cb_row4_col19\" class=\"data row4 col19\" >4</td>\n",
       "      <td id=\"T_421cb_row4_col20\" class=\"data row4 col20\" >6</td>\n",
       "      <td id=\"T_421cb_row4_col21\" class=\"data row4 col21\" >4</td>\n",
       "      <td id=\"T_421cb_row4_col22\" class=\"data row4 col22\" >6</td>\n",
       "      <td id=\"T_421cb_row4_col23\" class=\"data row4 col23\" >4</td>\n",
       "      <td id=\"T_421cb_row4_col24\" class=\"data row4 col24\" >6</td>\n",
       "      <td id=\"T_421cb_row4_col25\" class=\"data row4 col25\" >4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x165790f90>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "balls_df.T.style.background_gradient(cmap ='viridis').set_properties(**{'font-size': '20px'}) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
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    "In summary, we created a graph network of boxes and robotic arms to transfer balls between the boxes, striving for an unachievable equilibrium state. The ability to embed a graph, virtually a graph database, into a cadCAD state allows for tremendous scalability and flexibility as a modeling tool.  "
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