sequential_monte_carlo_test.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "blond-district",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3.7.9 (default, Aug 31 2020, 12:42:55) \n",
      "[GCC 7.3.0]\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "os.environ[\"PATH\"] += os.pathsep + 'C:/Users/anura/anaconda3/Library/bin/graphviz'\n",
    "import sys\n",
    "import networkx as nx\n",
    "import numpy as np\n",
    "import random\n",
    "import pickle\n",
    "import sys\n",
    "from numba import jit\n",
    "import elfi\n",
    "import sklearn as sk\n",
    "import scipy\n",
    "from scipy.spatial import distance\n",
    "import pandas as pd\n",
    "import sys\n",
    "import pickle\n",
    "print(sys.version)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "qualified-evanescence",
   "metadata": {},
   "outputs": [],
   "source": [
    "seed = 20170530  # this will be separately given to ELFI\n",
    "np.random.seed(seed)\n",
    "N = 100 # samples for rejection sampling\n",
    "networktype = 'pref' #pref, smallworld, grid, ER, korea1, korea2, ckm\n",
    "globalThreshold = .95\n",
    "activation_ci = 0.1\n",
    "cascadeParameter = 0.5\n",
    "# nAgents = 4**2\n",
    "# nAgents = 10**2\n",
    "# sidelength = int(nAgents**.5) #10^2 = 100, 32^2 = 1024\n",
    "#haltMin = .6 # minimum % of nodes active\n",
    "#haltMax = .7 # maximum % of nodes active\n",
    "\n",
    "# pRewire = .1 # proportion of edges to rewire\n",
    "# numDatasets = 100 # number of data sets to generate\n",
    "# saveData = True #save the output to file?\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "spare-oxygen",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.5\n",
      "Name: \n",
      "Type: Graph\n",
      "Number of nodes: 23882\n",
      "Number of edges: 132054\n",
      "Average degree:  11.0589\n",
      "23882\n",
      "connected?\tFalse\n",
      "# of connected components:\t57\n"
     ]
    }
   ],
   "source": [
    "print(nx.__version__)\n",
    "#parameters of the script\n",
    "path = '../data/icpsr/DS0001/paluck-edgelist.csv'\n",
    "edgelist = pd.read_csv(path)\n",
    "G = nx.from_pandas_edgelist(edgelist, source='ID', target='PEERID')\n",
    "print(nx.info(G))\n",
    "print(nx.number_of_nodes(G))\n",
    "print(f'connected?\\t{nx.is_connected(G)}')\n",
    "print(f'# of connected components:\\t{nx.number_connected_components(G)}')\n",
    "\n",
    "components = nx.connected_components(G)\n",
    "sglist = [G.subgraph(c) for c in nx.connected_components(G)]\n",
    "\n",
    "gmat = []\n",
    "for g in sglist:\n",
    "    gmat.append(nx.to_numpy_matrix(g, dtype=np.float))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "worth-strain",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "57\n"
     ]
    }
   ],
   "source": [
    "print(len(sglist))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "absolute-willow",
   "metadata": {},
   "outputs": [],
   "source": [
    "#for i in range(len(sglist)):\n",
    "#    print('# of nodes in {i}th component is  - ', str(np.mean(gmat[i])))\n",
    "seeds = pd.read_csv(\"../data/icpsr/DS0001/paluck-seed.csv\")\n",
    "seeds['ID'] = ((seeds['SCHIDW2'] * 1000) + pd.to_numeric(seeds['ID'], errors='coerce'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "possible-tennis",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " /home/gary/.conda/envs/elfi/lib/python3.7/site-packages/IPython/core/interactiveshell.py:3156: DtypeWarning:Columns (238,242,244,245,246,247,248,249,382) have mixed types.Specify dtype option on import or set low_memory=False.\n"
     ]
    }
   ],
   "source": [
    "es = pd.read_csv(\"../data/icpsr/DS0001/paluck-endstate.csv\")\n",
    "es['ID'] = ((es['SCHIDW2'] * 1000) + pd.to_numeric(es['ID'], errors='coerce'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "advised-magnitude",
   "metadata": {},
   "outputs": [],
   "source": [
    "def genNet(n, k=4, pRewire=.1, type='grid'):\n",
    "    # create net\n",
    "    if type == 'grid': #wrap the grid\n",
    "        net = nx.grid_2d_graph(int(n**.5), int(n**.5), periodic=True)\n",
    "        #net = nx.grid_2d_graph(3, 3, periodic=True)\n",
    "        #net = nx.grid_2d_graph(2, 2, periodic=False)\n",
    "        #plotNet(net)\n",
    "        #print(len(net.edges()))\n",
    "        #assert(0)\n",
    "        # rewire\n",
    "        numRewired = 0\n",
    "        #while numRewired < (pRewire * nx.number_of_nodes(net)):\n",
    "        while numRewired < 1:\n",
    "            tries = 0\n",
    "            while tries < 100:\n",
    "                tries = tries + 1\n",
    "                #print([numRewired, pRewire * nx.number_of_nodes(net), tries])\n",
    "                v1 = random.choice(net.nodes())\n",
    "                v2 = random.choice(net.nodes())\n",
    "                if not( net.has_edge(v1,v2) or v1==v2 or len(net.neighbors(v1)) <= 1): #net.neighbors is sometimes (often?) a blank set, changed so v1 needs 2 nb\n",
    "                    #print net.neighbors(v1)\n",
    "                    break\n",
    "            v1Neighbors = net.neighbors(v1)\n",
    "            #print v1Neighbors\n",
    "            #print v1\n",
    "            #print v2\n",
    "            #print(len(net.edges()))\n",
    "            tobeDeleted = random.choice(v1Neighbors)\n",
    "            net.remove_edge(v1, tobeDeleted)\n",
    "            #print(len(net.edges()))\n",
    "            #print([v1, tobeDeleted, v2])\n",
    "            net.add_edge(v1, v2)\n",
    "            numRewired = numRewired + 1\n",
    "            #plotNet(net)\n",
    "            #assert(0)\n",
    "        return net, nx.to_numpy_matrix(net, dtype=np.float)\n",
    "\n",
    "    elif type == 'smallworld':\n",
    "        #net = nx.connected_watts_strogatz_graph(n, k, .15)\n",
    "        net = nx.connected_watts_strogatz_graph(n, k, pRewire)\n",
    "        return net, nx.to_numpy_matrix(net, dtype=np.float)  \n",
    "    elif type == 'pref':\n",
    "        net = nx.barabasi_albert_graph(n, 2)\n",
    "        return net, nx.to_numpy_matrix(net, dtype=np.float)\n",
    "    elif type == 'ER':\n",
    "        #net = nx.erdos_renyi_graph(n, .006)\n",
    "        targetDegree = 4.\n",
    "        nEdgesPossible = ((n*n)-n)/2.\n",
    "        pEdge = (n * targetDegree) / (2. * nEdgesPossible)\n",
    "        assert(pEdge <= 1)\n",
    "\n",
    "        # spare networks will likely be disconnected, so try a bunch\n",
    "        tries = 100\n",
    "        while tries > 0:\n",
    "            net = nx.erdos_renyi_graph(n, pEdge)\n",
    "            if nx.number_connected_components(net) > 1:\n",
    "                tries = tries - 1\n",
    "            else:\n",
    "                break\n",
    "        return net, nx.to_numpy_matrix(net, dtype=np.float)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "substantial-intellectual",
   "metadata": {},
   "outputs": [],
   "source": [
    "def testThresh(agents, agents_ini, mn, mx):\n",
    "    \n",
    "    if np.mean(agents) == 0:\n",
    "        print(\"stopping because no nodes are activated in the initial state\")\n",
    "        return agents, False\n",
    "    \n",
    "    if np.mean(agents) >= mx:\n",
    "        print(\"Bad data discarding the dataset because activation reached \", np.mean(agents))\n",
    "        agents = agents_ini\n",
    "        return agents, False\n",
    "    \n",
    "    if np.mean(agents) <= mn:\n",
    "        return agents, False\n",
    "    \n",
    "    \n",
    "    if np.mean(agents) > mn and np.mean(agents) < mx:\n",
    "        print(\"Achieved stopping condition and stopping diffusion\")\n",
    "        return agents, True\n",
    "        \n",
    "\n",
    "    return False\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "civil-driver",
   "metadata": {},
   "outputs": [],
   "source": [
    "def ltProp(agents, adjMatrix, nAgents, avgDegree=0, haltMin=.49, haltMax=.51, rs = None):\n",
    "    # init some stuff for numba\n",
    "    thresholds = np.zeros_like(nAgents)\n",
    "    inp = np.zeros_like(nAgents)\n",
    "    step = 0\n",
    "    numNeighbors = np.zeros_like(nAgents)\n",
    "    prevMean = 0.\n",
    "    liveEdges = np.zeros_like(adjMatrix)\n",
    "    pInfect = np.zeros_like(adjMatrix)\n",
    "    flips = np.zeros_like(adjMatrix)\n",
    "    \n",
    "\n",
    "    if rs is None:\n",
    "        thresholds = globalThreshold * np.random.random((1, nAgents))\n",
    "        print(\"no seed passed\")\n",
    "    else:\n",
    "        thresholds = globalThreshold * rs.random((1, nAgents))\n",
    "    \n",
    "    numNeighbors = np.sum(adjMatrix, axis=0)\n",
    "    prevMean = -1\n",
    "    step = 1\n",
    "#     print(\"stopping conditions: \", haltMin, haltMax)\n",
    "    print(\"running LT Prop\")\n",
    "\n",
    "    agents_ini = agents\n",
    "    \n",
    "    loop_manager = False\n",
    "    \n",
    "    while not loop_manager  and (np.mean(agents) > prevMean):\n",
    "        \n",
    "        agents, loop_manager = testThresh(agents, agents_ini, haltMin, haltMax)\n",
    "        print(\"state activation: \", prevMean)\n",
    "\n",
    "        #while np.mean(agents) > prevMean:\n",
    "        prevMean = np.mean(agents)\n",
    "        inp = np.true_divide(np.dot(agents, adjMatrix), numNeighbors)\n",
    "        agents = np.logical_or(agents, (inp >= thresholds)).astype(int)\n",
    "\n",
    "        step = step + 1\n",
    "\n",
    "    print(\"state activation: \", prevMean)\n",
    "\n",
    "    #print('LT-proportional stopped at step ' + str(step) + ' '+ str(np.mean(agents)))\n",
    "    return agents"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "discrete-yellow",
   "metadata": {},
   "outputs": [],
   "source": [
    "def ltAbs(agents, adjMatrix, nAgents, avgDegree=0, haltMin=.49, haltMax=.51, rs = None):\n",
    "    # init some stuff for numba\n",
    "    thresholds = np.zeros_like(nAgents)\n",
    "    inp = np.zeros_like(nAgents)\n",
    "    step = 0\n",
    "    numNeighbors = np.zeros_like(nAgents)\n",
    "    prevMean = 0\n",
    "    liveEdges = np.zeros_like(adjMatrix)\n",
    "    pInfect = np.zeros_like(adjMatrix)\n",
    "    flips = np.zeros_like(adjMatrix)\n",
    "\n",
    "    # this controls the thresholds/pInfects for all contagion types\n",
    "    \n",
    "    if rs is None:\n",
    "        thresholds = np.random.randint(low=1, high=round(avgDegree*globalThreshold), size=(1, nAgents))\n",
    "        print(\"no seed passed\")\n",
    "    else:\n",
    "        thresholds = rs.randint(low=1, high=round(avgDegree*globalThreshold), size=(1, nAgents))\n",
    "        print(\"seed passed\")\n",
    "    \n",
    "    numNeighbors = np.sum(adjMatrix, axis=0)\n",
    "    prevMean = -1\n",
    "    step = 1\n",
    "    print(\"running LT Abs\")\n",
    "\n",
    "    agents_ini = agents\n",
    "    loop_manager = False\n",
    "    while not loop_manager and (np.mean(agents) > prevMean):\n",
    "        \n",
    "        agents, loop_manager = testThresh(agents, agents_ini, haltMin, haltMax)\n",
    "        print(\"state activation: \", prevMean)\n",
    "\n",
    "        prevMean = np.mean(agents)\n",
    "        inp = np.dot(agents, adjMatrix)\n",
    "        agents = np.logical_or(agents, (inp >= thresholds)).astype(int)\n",
    "        step = step + 1\n",
    "\n",
    "    print(\"state activation: \", prevMean)\n",
    "\n",
    "    # print('LT-absolute stopped at step ' + str(step) + ' '+ str(np.mean(agents)))\n",
    "\n",
    "    return agents"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "directed-guest",
   "metadata": {},
   "outputs": [],
   "source": [
    "def IC(agents, adjMatrix, nAgents, avgDegree=0, haltMin=.49, haltMax=.51, rs = None):\n",
    "    # init some stuff for numba\n",
    "    thresholds = np.zeros_like(nAgents)\n",
    "    inp = np.zeros_like(nAgents)\n",
    "    step = 0\n",
    "    numNeighbors = np.zeros_like(nAgents)\n",
    "    prevMean = -1\n",
    "    liveEdges = np.zeros_like(adjMatrix)\n",
    "    pInfect = np.zeros_like(adjMatrix)\n",
    "    flips = np.zeros_like(adjMatrix)\n",
    "\n",
    "        \n",
    "    numNeighbors = np.sum(adjMatrix, axis=0)\n",
    "    #prevMean = -1\n",
    "    step = 1\n",
    "    \n",
    "    # calculate each edges probability of allowing infection\n",
    "    \n",
    "    # determine 'live' and 'blocked' edges\n",
    "    \n",
    "    print(\"running IC\")\n",
    "    if rs is None:\n",
    "        pInfect = np.multiply(adjMatrix, np.random.random(adjMatrix.shape))\n",
    "        flips = np.random.random(pInfect.shape)\n",
    "    else:\n",
    "        pInfect = np.multiply(adjMatrix, rs.random(adjMatrix.shape))\n",
    "        flips = rs.random(pInfect.shape)\n",
    "        \n",
    "    pInfect = np.multiply(0.5, pInfect)\n",
    "    liveEdges = flips < pInfect\n",
    "    \n",
    "    agents_ini = agents\n",
    "        \n",
    "    loop_manager = False\n",
    "    print(\"starting loop manager\")\n",
    "    count = 40\n",
    "    while not loop_manager and (np.mean(agents) > prevMean):\n",
    "        agents, loop_manager = testThresh(agents, agents_ini, haltMin, haltMax)\n",
    "        print(\"state activation: \", prevMean)\n",
    "\n",
    "        prevMean = np.mean(agents)\n",
    "        inp = np.dot(agents, liveEdges)\n",
    "        agents = np.logical_or(agents, inp).astype(int)\n",
    "        step = step + 1\n",
    "        \n",
    "        if count >= 40:\n",
    "            loop_manager = True\n",
    "        count += 1\n",
    "        \n",
    "    print(\"state activation: \", prevMean)\n",
    "\n",
    "    # print('LT-absolute stopped at step ' + str(step) + ' '+ str(np.mean(agents)))\n",
    "\n",
    "    return agents"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "respected-distinction",
   "metadata": {},
   "outputs": [],
   "source": [
    "def generateGraph(net, adjMatrix, pp, batch_size = 1, random_state=None):\n",
    "    gg = []\n",
    "\n",
    "    while True:\n",
    "        nAgents = nx.number_of_nodes(net)\n",
    "        agents = np.zeros((1, nAgents))\n",
    "        nodes = nx.nodes(net)\n",
    "        seed_nodes = []\n",
    "        inx = []\n",
    "        count = 0\n",
    "        for n in nodes:\n",
    "            if n in seeds['ID'].tolist():\n",
    "                seed_nodes.append(n)\n",
    "                inx.append(count)\n",
    "            count += 1\n",
    "        \n",
    "        agents[:,inx] = 1\n",
    "\n",
    "        es_nodes = []\n",
    "        es_inx = []\n",
    "        count_es = 0\n",
    "        num_es = 0\n",
    "        for n in nodes:\n",
    "            if n in es['ID'].tolist():\n",
    "                es_nodes.append(n)\n",
    "                es_inx.append(count_es)\n",
    "                num_es += 1\n",
    "            count_es += 1\n",
    "    \n",
    "        p_activation = num_es/count_es\n",
    "        print(\"final_activation: \", p_activation)\n",
    "        print(\"Adjaecency Matrix: \", adjMatrix.shape)\n",
    "        # seed neighbors of seeds\n",
    "        print(\"zero initialized agents: \", agents[agents == 1].shape)\n",
    "#         for i in range(1):\n",
    "#             agents = np.logical_or(agents, np.dot(agents, adjMatrix)).astype(float) #all neighbors\n",
    "\n",
    "        avgDegree = 2*net.number_of_edges() / float(net.number_of_nodes())\n",
    "        print(\"initially activated agents: \", agents[agents == 1].shape)\n",
    "#         if pp >= 0.5:\n",
    "#             agents_type = ltProp(agents, adjMatrix, nAgents, avgDegree=avgDegree, \n",
    "#                                  haltMin = max(0,p_activation-activation_ci), \n",
    "#                                  haltMax = min(p_activation+activation_ci,1), \n",
    "#                                  rs = random_state)\n",
    "\n",
    "#         else:\n",
    "#             agents_type = ltAbs(agents, adjMatrix, nAgents, avgDegree=avgDegree, \n",
    "#                                 haltMin = max(0,p_activation-activation_ci), \n",
    "#                                 haltMax = min(p_activation+activation_ci,1), \n",
    "#                                 rs = random_state)\n",
    "\n",
    "        t = 1/3\n",
    "    \n",
    "        if pp <= t:\n",
    "            agents_type = IC(agents, adjMatrix, nAgents, avgDegree=avgDegree, \n",
    "                                 haltMin = max(0,p_activation-activation_ci), \n",
    "                                 haltMax = min(p_activation+activation_ci,1), \n",
    "                                 rs = random_state)\n",
    "\n",
    "        elif pp > t and pp <= 2*t:\n",
    "            agents_type = ltProp(agents, adjMatrix, nAgents, avgDegree=avgDegree, \n",
    "                                 haltMin = max(0,p_activation-activation_ci), \n",
    "                                 haltMax = min(p_activation+activation_ci,1), \n",
    "                                 rs = random_state)\n",
    "\n",
    "        else:\n",
    "            agents_type = ltAbs(agents, adjMatrix, nAgents, avgDegree=avgDegree, \n",
    "                                haltMin = max(0,p_activation-activation_ci), \n",
    "                                haltMax = min(p_activation+activation_ci,1), \n",
    "                                rs = random_state)\n",
    "\n",
    "            \n",
    "        #if not testThresh(agents_type, haltMin, haltMax):\n",
    "         #   print('bad data, LTabs1:\\t'+str(np.mean(agents_type)))\n",
    "       #     continue\n",
    "        gparam = {}\n",
    "        gparam['init'] = net\n",
    "        gparam['graph'] = agents_type\n",
    "        \n",
    "        gg.append(gparam['graph'])\n",
    "        if len(gg) >= batch_size:\n",
    "            break\n",
    "    \n",
    "    print(\"final graph: \", gg[0])\n",
    "    return gg[0]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "least-terrorist",
   "metadata": {},
   "outputs": [],
   "source": [
    "#n,a = getGraphFromEdgelist(path)\n",
    "net_s = sglist[0]\n",
    "adjMat_s = gmat[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "further-jefferson",
   "metadata": {},
   "outputs": [],
   "source": [
    "def compileG(ll, batch_size = 1, random_state=None):\n",
    "    return generateGraph(net_s, adjMat_s, ll[0], batch_size, random_state)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "ecological-frost",
   "metadata": {},
   "outputs": [],
   "source": [
    "nAgobs = nx.number_of_nodes(net_s)\n",
    "agobs = np.zeros((1, nAgobs))\n",
    "nodeobs = nx.nodes(net_s)\n",
    "es_nodeobs = []\n",
    "es_inxobs = []\n",
    "count_esobs = 0\n",
    "num_esobs = 0\n",
    "\n",
    "for n in nodeobs:\n",
    "    if n in es['ID'].tolist():\n",
    "        es_nodeobs.append(n)\n",
    "        es_inxobs.append(count_esobs)\n",
    "        num_esobs += 1\n",
    "    count_esobs += 1\n",
    "\n",
    "agobs[:,es_inxobs] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "characteristic-colleague",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0 1 0 0 0 0 0 0 0 1 0 0 0 1 1 1 1 1 0 1 1 0 0 0 0 0 1 0 0 0 1 0 0 0 1 1\n",
      "  0 0 1 0 1 0 0 0 1 1 0 1 1 0 0 1 1 1 0 1 0 0 0 0 0 1 0 1 1 0 1 0 0 1 0 0\n",
      "  0 0 0 0 0 1 0 1 1 0 1 1 0 0 0 0 1 0 0 0 0 1 0 1 0 0 1 1 0 1 1 0 1 0 1 0\n",
      "  1 0 1 0 1 0 0 1 0 0 1 0 1 0 1 0 1 0 1 0 1 1 1 0 1 1 1 1 0 1 1 1 0 1 1 0\n",
      "  0 0 0 1 0 0 1 1 0 1 0 0 0 1 1 0 1 0 0 0 1 0 1 0 1 0 0 1 0 1 1 0 1 0 1 0\n",
      "  1 0 0 1 0 1 0 0 0 1 1 0 1 0 1 1 0 0 0 1 0 0 1 1 1 1 0 1 1 0 0 0 1 0 1 0\n",
      "  1 0 1 1 1 0 1 1 0 1 1 1 1 0 1 1 1 1 1 0 1 0 0 1 1 0 1 0 0 1 0 0 0 0 1 1\n",
      "  0 0 0 0 1 0 1 0 0 1 1 0 0 0 1 1 0 0 0 1]]\n"
     ]
    }
   ],
   "source": [
    "gr_obs = np.matrix(agobs).astype(int)\n",
    "print(gr_obs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "hidden-commitment",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'elfi.model.elfi_model.Prior'>\n"
     ]
    }
   ],
   "source": [
    "prop_prob = elfi.Prior(scipy.stats.uniform, 0, 1)\n",
    "print(type(prop_prob))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "unusual-ending",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "272\n"
     ]
    }
   ],
   "source": [
    "print(gr_obs.shape[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "acceptable-fellow",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Y = elfi.Simulator(generateGraph, prop_prob, observed = gr_obs)\n",
    "Y = elfi.Simulator(compileG, prop_prob, observed = gr_obs, name = \"nodename\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "objective-budget",
   "metadata": {},
   "outputs": [],
   "source": [
    "def yMetric(x, i = 0):\n",
    "    return x[0,i]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "bright-apartment",
   "metadata": {},
   "outputs": [],
   "source": [
    "def eucMultiArgs(X, Y):\n",
    "    dist = np.linalg.norm(X - Y)\n",
    "    print(\"printing the distance between X and Y: \", dist)\n",
    "    return np.array([dist])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "attractive-climate",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n",
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n"
     ]
    }
   ],
   "source": [
    "ret = []\n",
    "for i in range(gr_obs.shape[1]):\n",
    "    st = str(i)\n",
    "    var_s = ''.join(['s',st])\n",
    "    ret.append(var_s)\n",
    "    com = var_s + ' = ' + 'elfi.Summary(yMetric, Y, '+st+')'\n",
    "    exec(com)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "indie-tract",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Automatic name inspection failed, using a random name instead. This may be caused by using an interactive Python shell. You can provide a name parameter e.g. elfi.Prior('uniform', name='nodename') to suppress this warning.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "d=elfi.Distance('euclidean',s0,s1,s2,s3,s4,s5,s6,s7,s8,s9,s10,s11,s12,s13,s14,s15,s16,s17,s18,s19,s20,s21,s22,s23,s24,s25,s26,s27,s28,s29,s30,s31,s32,s33,s34,s35,s36,s37,s38,s39,s40,s41,s42,s43,s44,s45,s46,s47,s48,s49,s50,s51,s52,s53,s54,s55,s56,s57,s58,s59,s60,s61,s62,s63,s64,s65,s66,s67,s68,s69,s70,s71,s72,s73,s74,s75,s76,s77,s78,s79,s80,s81,s82,s83,s84,s85,s86,s87,s88,s89,s90,s91,s92,s93,s94,s95,s96,s97,s98,s99,s100,s101,s102,s103,s104,s105,s106,s107,s108,s109,s110,s111,s112,s113,s114,s115,s116,s117,s118,s119,s120,s121,s122,s123,s124,s125,s126,s127,s128,s129,s130,s131,s132,s133,s134,s135,s136,s137,s138,s139,s140,s141,s142,s143,s144,s145,s146,s147,s148,s149,s150,s151,s152,s153,s154,s155,s156,s157,s158,s159,s160,s161,s162,s163,s164,s165,s166,s167,s168,s169,s170,s171,s172,s173,s174,s175,s176,s177,s178,s179,s180,s181,s182,s183,s184,s185,s186,s187,s188,s189,s190,s191,s192,s193,s194,s195,s196,s197,s198,s199,s200,s201,s202,s203,s204,s205,s206,s207,s208,s209,s210,s211,s212,s213,s214,s215,s216,s217,s218,s219,s220,s221,s222,s223,s224,s225,s226,s227,s228,s229,s230,s231,s232,s233,s234,s235,s236,s237,s238,s239,s240,s241,s242,s243,s244,s245,s246,s247,s248,s249,s250,s251,s252,s253,s254,s255,s256,s257,s258,s259,s260,s261,s262,s263,s264,s265,s266,s267,s268,s269,s270,s271)\n"
     ]
    }
   ],
   "source": [
    "dcom = \"d=elfi.Distance('euclidean'\"\n",
    "# len_run = min(250, gr_obs.shape[1])\n",
    "for i in range(gr_obs.shape[1]):\n",
    "    if i == 0:\n",
    "        dcom = dcom + ',s' + str(i)\n",
    "    else:\n",
    "        dcom = dcom + ',s' + str(i)\n",
    "dcom = dcom + ')'\n",
    "print(dcom)\n",
    "exec(dcom)\n",
    "# d = elfi.Distance('euclidean',s7)\n",
    "# d = elfi.Distance('euclidean',s0, s1, s2, s3, s4, s5, s6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "every-infrastructure",
   "metadata": {},
   "outputs": [],
   "source": [
    "smc = elfi.SMC(d, batch_size=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "based-barrier",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ABC-SMC Round 1 / 4\n",
      "final_activation:  0.45588235294117646\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.14338235294117646\n",
      "state activation:  0.22058823529411764\n",
      "state activation:  0.2610294117647059\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.3014705882352941\n",
      "state activation:  0.35661764705882354\n",
      "final graph:  [[0 1 1 1 0 1 1 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 1 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 1 1 0 1 0 0 1 1 1 1 0 0 0 0 1 1 1 1 1 0 0 1 0 0 1 0 1\n",
      "  1 1 1 0 1 1 1 1 0 1 0 1 1 0 0 0 1 0 1 0 0 0 0 0 0 1 0 0 0 0 1 0 1 0 0 0\n",
      "  0 1 0 0 0 0 0 0 1 0 1 0 0 1 0 1 0 0 0 0 1 0 1 0 1 1 0 1 0 0 0 0 0 0 0 1\n",
      "  0 0 1 0 0 0 0 1 0 0 0 1 1 1 1 1 0 0 1 1 0 1 1 0 0 1 1 1 0 0 0 1 0 1 1 0\n",
      "  1 1 0 0 1 0 0 0 1 0 0 1 1 1 1 0 1 1 1 0 0 1 1 0 0 1 0 1 0 1 0 1 1 1 1 0\n",
      "  0 1 0 1 1 0 0 0 1 1 0 1 0 1 0 0 0 0 0 1 0 1 0 0 1 0 1 0 1 1 0 0 0 0 0 0\n",
      "  0 0 1 0 0 0 1 1 0 1 1 1 0 0 1 0 0 0 0 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 9.1% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 1 0 0 0 0 0 0 1 1 0 0 1 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 1 0 0 1 0 0\n",
      "  0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 0 0 1 0 1 1 1 0\n",
      "  0 0 0 0 1 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 1 0 0 0 1 1 0 0 0 1 0 1 0 0 1 1 1 0 1 0 0 0 1 0 0 0 0\n",
      "  1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 1 0 1 0 0 1\n",
      "  0 1 0 0 1 0 0 0 1 1 1 1 1 0 1 0 0 1 0 0 1 0 0 0 0 0 1 0 0 1 1 1 0 0 1 0\n",
      "  1 0 0 0 1 0 0 0 0 1 1 1 0 0 0 1 0 0 0 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 18.2% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "seed passed\n",
      "running LT Abs\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.17279411764705882\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.3235294117647059\n",
      "state activation:  0.5073529411764706\n",
      "final graph:  [[1 1 0 0 1 0 1 1 1 1 1 0 0 1 1 0 0 1 0 0 1 1 1 1 0 1 0 1 1 1 1 1 1 1 1 1\n",
      "  1 0 1 1 1 1 1 1 1 1 1 0 0 0 0 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 0\n",
      "  1 1 0 1 1 1 1 1 0 1 0 1 0 0 1 1 0 1 1 1 0 0 0 0 0 0 0 0 1 0 0 0 1 1 0 1\n",
      "  0 1 0 1 0 0 0 1 1 1 1 1 1 0 1 1 1 0 0 1 1 1 1 1 1 0 1 1 1 1 0 1 1 1 0 1\n",
      "  0 0 1 1 0 0 0 0 1 1 1 1 1 1 1 0 0 0 1 1 1 1 0 1 1 0 1 1 0 0 1 1 0 0 0 0\n",
      "  1 1 0 0 1 1 0 0 0 0 1 0 0 1 1 1 0 0 1 0 0 1 1 0 1 1 1 1 0 1 0 0 1 1 1 0\n",
      "  1 0 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 0 1 0 1 0 1 1 1 1 0 1 1 1 1 1 1 1 1\n",
      "  1 1 1 1 1 1 0 0 1 1 0 1 1 0 1 1 1 1 1 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 27.3% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "seed passed\n",
      "running LT Abs\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.1213235294117647\n",
      "state activation:  0.17647058823529413\n",
      "state activation:  0.22794117647058823\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.2977941176470588\n",
      "state activation:  0.36764705882352944\n",
      "final graph:  [[1 1 1 0 1 1 1 1 1 1 1 0 0 1 1 0 1 0 0 0 1 1 1 1 0 1 0 1 1 1 1 1 1 1 1 1\n",
      "  0 0 1 0 1 1 0 1 1 1 0 0 0 0 0 0 0 1 0 0 1 0 0 0 1 1 0 1 0 0 1 0 0 1 0 0\n",
      "  0 0 0 0 0 1 0 1 0 1 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 1 0 1 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 1 1 0 0 1 1 0 1 1 0 0 1 0 0 1 0 1 1 0 1 1 0 1 0 1 1 1 0 1 0 0 1 0 0\n",
      "  1 0 0 0 1 1 1 0 0 1 1 1 1 0 1 0 1 1 0 0 1 1 1 1 0 0 1 1 0 1 0 0 1 1 1 1\n",
      "  0 1 1 1 1 0 1 1 1 1 1 1 1 1 1 0 0 1 1 1 0 1 0 1 1 0 1 0 0 1 1 1 1 0 0 0\n",
      "  1 1 1 0 1 0 0 0 1 1 0 1 0 1 1 1 1 1 1 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 36.4% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.12867647058823528\n",
      "state activation:  0.15808823529411764\n",
      "state activation:  0.19117647058823528\n",
      "state activation:  0.2426470588235294\n",
      "state activation:  0.29044117647058826\n",
      "state activation:  0.3125\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.3382352941176471\n",
      "state activation:  0.3713235294117647\n",
      "final graph:  [[0 1 1 0 0 1 1 1 0 1 1 1 0 0 1 1 0 0 0 0 0 1 0 0 1 0 0 0 0 0 1 1 0 1 0 0\n",
      "  1 1 0 0 0 1 1 0 1 1 0 1 0 1 0 1 1 0 0 0 0 0 1 1 0 0 0 0 0 0 1 0 0 1 0 1\n",
      "  1 0 0 0 0 1 0 0 0 1 0 1 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 1 1 1 0 0 1 1 0 1\n",
      "  0 0 0 1 1 0 0 0 0 0 1 0 0 1 1 0 0 0 0 0 1 0 1 0 0 0 1 0 0 1 0 1 0 0 0 0\n",
      "  0 0 1 0 1 0 0 1 0 0 1 1 0 1 1 0 0 0 0 0 1 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1\n",
      "  1 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 1 0 1 1 0 1 1 0 0 0 0 1 0 0 1 0 1 0 1\n",
      "  0 1 0 1 1 1 0 0 1 1 1 1 0 1 1 1 0 1 0 1 0 1 1 1 0 0 1 0 0 1 1 1 0 0 1 1\n",
      "  1 0 1 0 1 1 0 1 0 1 1 1 0 0 0 0 0 1 0 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 45.5% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "seed passed\n",
      "running LT Abs\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.15808823529411764\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.26838235294117646\n",
      "state activation:  0.41544117647058826\n",
      "final graph:  [[1 1 0 0 1 0 1 1 1 1 1 1 0 1 1 0 0 1 0 1 0 0 1 1 0 1 0 1 0 0 1 0 1 1 1 1\n",
      "  0 0 0 0 0 1 0 1 0 1 1 0 1 0 0 1 0 1 0 0 1 1 0 0 0 1 1 1 1 1 1 0 1 1 1 0\n",
      "  0 1 0 1 1 1 1 1 1 0 0 0 0 0 1 1 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 1 0 1 0 0\n",
      "  0 0 0 1 0 1 0 0 1 1 1 0 0 0 1 1 1 1 1 1 0 1 1 1 1 0 0 1 1 1 0 1 1 1 1 1\n",
      "  1 0 0 1 1 0 0 0 0 1 1 0 0 1 1 1 1 0 1 1 0 1 1 1 1 0 1 1 1 0 1 0 0 1 0 0\n",
      "  1 1 0 0 1 1 1 0 0 1 0 1 0 0 1 0 0 1 1 0 1 1 1 1 1 0 1 1 0 1 1 0 0 1 0 0\n",
      "  0 0 1 1 1 1 1 0 0 1 0 1 1 1 0 0 0 1 0 1 0 1 1 1 1 1 1 0 1 1 0 0 1 1 1 1\n",
      "  1 0 1 1 1 0 0 1 1 1 0 1 1 0 1 1 1 1 1 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 54.5% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 1 0 1 1 1 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 0 0 0 1 0 0 0 1 0 0 1 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0\n",
      "  0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 1 0 1 0 0 0 1 0 1 0 0 0 0 0 1 0 0\n",
      "  0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 1 1 1 0 0 0 0 0 0 0 1 0 0 0 0\n",
      "  0 1 0 0 1 1 0 0 0 1 0 1 0 0 0 0 0 1 0 1 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1 0\n",
      "  1 0 1 0 0 0 0 1 0 1 0 1 0 0 1 1 0 0 0 1]]\n",
      "final_activation:  0.45588235294117646===-------------------] 63.6% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 0 0 0 1 0 0 0 1 0 0 0 1 1 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 1 0 0 1 1 0\n",
      "  0 0 0 0 1 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 1 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0\n",
      "  0 0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 1 0 1 0 0 0 1 1 1 1 1 0 1 0 0 0 0 0 0 1 0 1 1 0 1 0 0 1 1 0 0 0 0 0\n",
      "  1 0 0 0 0 0 0 0 1 1 0 1 0 0 0 0 0 1 0 1]]\n",
      "final_activation:  0.45588235294117646========--------------] 72.7% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 0 0 0 0 1 0 0 1 0 0 0 1 1 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 1 1 0 1 0 0\n",
      "  0 0 0 0 1 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0\n",
      "  1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 1 0 0 0 0 0 1 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 1 0 0 0 0\n",
      "  0 1 0 1 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1 0 1 0 0 0 0 1 0 0 1 0 1 0 0 0\n",
      "  1 0 1 0 1 0 0 1 1 1 0 1 1 1 1 0 0 1 0 0 0 0 1 0 0 0 1 0 0 1 0 1 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 1]]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "final_activation:  0.45588235294117646============----------] 81.8% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "seed passed\n",
      "running LT Abs\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.14338235294117646\n",
      "state activation:  0.22426470588235295\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.2977941176470588\n",
      "state activation:  0.38235294117647056\n",
      "final graph:  [[1 1 1 0 1 1 1 0 1 1 1 1 0 1 1 1 1 1 0 1 0 0 1 1 0 1 0 1 1 1 1 1 1 1 1 1\n",
      "  0 1 0 0 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1 0 0 1 0 1 0 1 1 0 0 1 1 1\n",
      "  0 1 0 1 0 1 0 0 0 0 1 0 0 1 1 1 0 0 1 0 0 0 1 0 1 1 0 0 1 1 0 1 0 1 1 0\n",
      "  0 0 1 0 0 0 0 0 0 1 0 0 0 1 0 0 1 0 1 0 0 0 0 1 0 0 1 1 1 0 1 0 1 1 1 0\n",
      "  0 0 1 1 0 0 1 0 0 0 0 1 1 0 0 0 0 1 1 0 1 0 1 0 1 0 1 1 0 0 0 1 0 1 0 0\n",
      "  0 0 0 0 1 0 0 0 1 1 0 1 0 1 1 0 0 1 0 0 0 1 1 0 1 0 1 0 1 1 1 1 0 1 1 1\n",
      "  1 0 1 0 1 1 0 1 1 1 1 1 1 0 0 1 1 1 1 1]]\n",
      "Progress [==================================================] 100.0% Complete\n",
      "\n",
      "ABC-SMC Round 2 / 4\n",
      "final_activation:  0.45588235294117646----------------------] 0.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.12867647058823528\n",
      "state activation:  0.18382352941176472\n",
      "state activation:  0.25\n",
      "state activation:  0.29411764705882354\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.33455882352941174\n",
      "state activation:  0.35661764705882354\n",
      "final graph:  [[0 1 0 1 1 0 1 1 1 1 0 0 1 1 1 1 1 1 0 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 0\n",
      "  1 1 1 1 1 1 1 1 1 1 1 0 1 0 0 1 1 0 1 0 1 0 0 0 1 0 0 1 1 0 1 0 1 1 0 0\n",
      "  0 0 0 1 1 1 1 0 1 1 0 0 0 0 1 0 1 0 0 0 0 0 0 1 0 0 0 1 0 1 0 0 1 0 0 0\n",
      "  0 0 0 0 1 0 0 1 0 0 1 0 1 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0\n",
      "  0 0 0 1 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 1 0 0 0 0 1 0 1 0 0 0 0 0 1 1 1 0 0 1 0 0 0 1 0 0 1 1 1 0 0 1 0\n",
      "  1 0 0 1 1 1 0 1 1 1 0 1 1 1 1 1 1 1 1 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 9.1% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.125\n",
      "state activation:  0.17647058823529413\n",
      "state activation:  0.22794117647058823\n",
      "state activation:  0.2867647058823529\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.3382352941176471\n",
      "state activation:  0.3897058823529412\n",
      "final graph:  [[1 1 1 0 1 1 1 0 1 1 1 0 1 1 1 1 1 1 0 1 1 0 1 1 1 1 0 1 1 1 1 1 1 1 1 1\n",
      "  1 1 0 0 0 1 1 1 1 1 0 1 0 0 0 0 0 0 1 1 1 0 0 1 1 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 1 1 0 1 0 0 0 1 1 0 0 0 0 0 0 1 1 0 0 0 0 0 1 1 0 0 1 1 0\n",
      "  0 0 0 0 1 0 1 1 0 0 0 0 0 1 0 1 0 0 1 1 1 0 0 0 1 1 0 1 0 0 0 1 0 0 0 0\n",
      "  1 0 0 1 0 0 1 0 0 0 1 0 1 1 0 0 0 1 0 0 0 1 1 1 1 0 0 1 0 0 0 0 1 0 0 1\n",
      "  1 1 1 1 1 1 1 0 1 1 0 1 1 1 1 1 0 1 0 1 1 0 0 1 1 0 1 0 0 1 0 0 0 0 0 0\n",
      "  1 1 1 0 0 1 1 1 1 1 0 1 0 0 0 0 0 0 1 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 18.2% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.15073529411764705\n",
      "state activation:  0.22058823529411764\n",
      "state activation:  0.28308823529411764\n",
      "state activation:  0.3272058823529412\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.34558823529411764\n",
      "state activation:  0.3639705882352941\n",
      "final graph:  [[0 1 1 1 1 0 1 1 1 1 0 0 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 0 1 1 1 1 0 1 1\n",
      "  1 0 0 0 0 0 1 0 0 1 1 1 1 1 1 1 1 0 0 0 0 0 0 1 0 1 0 0 0 0 1 0 0 1 0 0\n",
      "  1 0 0 0 0 1 0 0 0 1 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0\n",
      "  0 0 1 0 0 0 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0 1 1 0 0 1 1 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 1 1 0 0 0 0 1 1 1 0 0 0 0 1 0 1 0 0 0 1 0 1 0 0 0 0 0 1 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 1 1 0 0 0 0 0 0 0 1 0 0 0 1\n",
      "  0 1 0 0 1 1 0 1 0 1 0 1 0 0 0 0 0 1 1 1 1 1 1 0 0 0 1 0 1 1 1 0 1 1 0 1\n",
      "  0 0 0 1 0 0 1 1 1 1 1 1 0 0 1 0 0 1 0 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 27.3% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "seed passed\n",
      "running LT Abs\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.11764705882352941\n",
      "state activation:  0.16544117647058823\n",
      "state activation:  0.21323529411764705\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.30514705882352944\n",
      "state activation:  0.40808823529411764\n",
      "final graph:  [[0 1 1 0 0 0 1 0 0 1 1 0 0 1 1 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 1 0 0 0 0 0\n",
      "  0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 1 1 0 0 1 0 1 0 0 0 1 0 1 1 0 1 0 0 1 1 0\n",
      "  1 1 1 1 1 1 0 1 1 1 0 1 0 1 1 1 0 1 1 0 0 0 0 0 0 1 0 1 0 1 1 0 0 1 1 0\n",
      "  0 0 0 1 1 0 0 1 1 1 1 0 1 1 1 1 0 0 0 0 1 1 1 1 1 0 0 0 1 0 0 1 1 1 0 1\n",
      "  0 0 1 0 1 0 1 0 0 1 1 0 1 1 1 0 1 0 1 1 0 0 0 0 1 0 1 1 1 0 0 1 0 0 1 0\n",
      "  1 0 0 0 1 1 1 0 0 1 1 1 1 1 1 1 1 1 1 0 1 1 1 0 0 0 1 1 0 1 1 0 0 1 1 1\n",
      "  1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 0 1 1 0 1 1 1 1 0 1 1 1 1 1 0 0 0\n",
      "  0 1 0 0 1 0 1 0 1 1 0 1 0 0 0 0 0 0 0 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 36.4% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "seed passed\n",
      "running LT Abs\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.15808823529411764\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.2536764705882353\n",
      "state activation:  0.3897058823529412\n",
      "final graph:  [[1 1 1 0 1 0 1 0 1 1 0 0 0 1 1 1 1 1 0 1 0 1 1 1 0 1 0 1 1 1 1 1 1 1 1 1\n",
      "  1 0 1 1 1 1 1 1 1 1 1 0 0 0 0 1 1 1 0 1 1 1 1 0 0 0 0 1 0 0 1 0 0 1 1 0\n",
      "  1 1 1 0 1 1 1 1 1 0 0 0 0 0 1 1 1 0 1 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1\n",
      "  1 0 0 0 0 1 0 0 0 0 1 0 1 0 1 1 0 0 0 0 0 0 1 1 1 1 0 0 1 0 0 0 1 0 0 0\n",
      "  1 0 1 1 1 0 0 0 0 1 1 1 1 1 1 1 0 1 1 1 1 1 0 1 1 0 1 1 0 0 0 1 0 1 0 1\n",
      "  1 0 0 0 1 1 1 0 0 1 1 0 1 1 1 1 1 1 0 1 1 1 1 0 1 0 1 1 1 1 1 1 0 1 1 1\n",
      "  1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 0 0 1 0 0 1 1 0 1 0 0 1 1 0 0 1 0 0\n",
      "  1 0 1 0 1 0 0 0 1 1 0 0 0 0 0 1 1 1 1 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 45.5% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "seed passed\n",
      "running LT Abs\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.12867647058823528\n",
      "state activation:  0.1948529411764706\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.3235294117647059\n",
      "state activation:  0.4264705882352941\n",
      "final graph:  [[1 1 1 0 1 1 1 1 1 1 1 0 0 1 1 0 1 1 0 0 0 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1\n",
      "  0 0 1 1 1 1 1 1 0 1 1 1 1 0 0 0 0 1 1 0 0 0 0 0 0 0 1 1 0 0 1 0 0 1 1 0\n",
      "  0 0 0 0 1 1 1 0 0 0 0 1 0 0 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0\n",
      "  0 1 0 1 0 1 0 0 1 0 1 0 1 0 1 1 0 0 0 0 0 1 1 0 1 0 1 1 1 1 0 1 0 0 0 0\n",
      "  1 0 1 1 0 0 0 0 0 1 1 0 0 1 1 0 1 0 1 0 1 0 0 1 1 0 1 1 0 0 0 1 0 1 0 0\n",
      "  1 1 0 1 0 0 1 0 0 1 1 1 1 1 1 0 0 0 1 0 1 1 1 1 1 0 1 1 1 1 0 1 1 1 0 1\n",
      "  1 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 0 0 1 1 0 1 1 1 1 0 1 1 1 0 1 1 1 1\n",
      "  1 0 1 1 1 1 1 0 0 1 0 1 1 0 0 1 1 1 0 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 54.5% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.1323529411764706\n",
      "state activation:  0.1875\n",
      "state activation:  0.21691176470588236\n",
      "state activation:  0.2426470588235294\n",
      "state activation:  0.26838235294117646\n",
      "state activation:  0.2867647058823529\n",
      "state activation:  0.30514705882352944\n",
      "state activation:  0.31985294117647056\n",
      "state activation:  0.3272058823529412\n",
      "state activation:  0.33088235294117646\n",
      "state activation:  0.33455882352941174\n",
      "state activation:  0.3382352941176471\n",
      "state activation:  0.34191176470588236\n",
      "final graph:  [[0 1 1 0 0 1 0 1 1 1 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0\n",
      "  1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0\n",
      "  0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 1 0 1 1 1 0 0 0 1 1 1 1 0 0 1 1 1 1 1 0 0 0 0 0 1 0 1 1 0 0 0 0\n",
      "  1 1 0 0 1 1 1 0 1 0 1 1 1 1 1 1 1 1 1 0 1 1 1 0 1 1 1 1 0 1 1 0 1 0 1 1\n",
      "  1 1 1 1 1 0 1 0 0 1 1 1 1 0 1 0 0 0 0 0 1 1 0 1 0 0 1 0 0 1 0 1 0 0 0 0\n",
      "  0 0 1 1 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 1]]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "final_activation:  0.45588235294117646===-------------------] 63.6% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.12867647058823528\n",
      "state activation:  0.18382352941176472\n",
      "state activation:  0.22794117647058823\n",
      "state activation:  0.26838235294117646\n",
      "state activation:  0.28308823529411764\n",
      "state activation:  0.3014705882352941\n",
      "state activation:  0.3161764705882353\n",
      "state activation:  0.33088235294117646\n",
      "state activation:  0.3382352941176471\n",
      "state activation:  0.34558823529411764\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.35294117647058826\n",
      "state activation:  0.3602941176470588\n",
      "final graph:  [[1 1 1 0 1 1 1 0 0 1 0 0 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 1 0 0\n",
      "  1 0 0 0 0 0 0 0 0 1 0 0 0 1 0 1 0 1 1 0 1 0 1 0 1 0 0 0 1 1 1 1 0 1 0 0\n",
      "  0 0 0 0 1 1 1 1 1 0 0 0 1 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 1 0 1 0 0 0 1 1 0 1 0 1 1 1 0 0 0 1 0 1 0 0 0 0 0 1 1 0 0\n",
      "  0 1 0 0 0 1 0 0 0 0 1 1 1 0 0 0 1 1 0 0 0 1 1 0 0 0 0 1 0 1 1 0 1 0 0 0\n",
      "  0 1 1 1 1 0 1 1 0 1 1 1 1 1 1 0 0 1 0 0 0 0 1 1 0 0 1 0 1 1 1 1 1 0 0 0\n",
      "  1 0 1 1 1 1 0 1 0 1 1 1 1 1 0 0 0 0 1 1]]\n",
      "final_activation:  0.45588235294117646========--------------] 72.7% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.15073529411764705\n",
      "state activation:  0.21691176470588236\n",
      "state activation:  0.2647058823529412\n",
      "state activation:  0.30514705882352944\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.34558823529411764\n",
      "state activation:  0.3713235294117647\n",
      "final graph:  [[0 1 0 0 0 1 0 1 1 1 1 0 0 0 1 1 0 1 0 0 1 1 1 1 1 1 0 1 1 0 1 0 1 0 1 0\n",
      "  1 0 0 1 0 0 1 0 1 1 0 0 0 0 0 1 1 0 1 1 1 0 0 1 0 0 0 0 0 0 1 0 1 1 0 1\n",
      "  1 0 1 1 0 1 1 0 0 1 0 1 0 1 0 0 0 0 1 0 0 0 0 1 0 1 0 1 0 0 0 0 1 0 0 0\n",
      "  0 0 0 1 1 0 0 1 1 1 1 0 0 0 1 0 0 0 0 1 0 0 1 0 1 0 0 0 1 1 0 1 0 1 0 0\n",
      "  0 1 0 1 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 1 0 0 1 0\n",
      "  0 1 0 0 0 0 0 0 0 0 1 0 1 1 0 0 1 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 1 0 1 0 1 1 1 1 0 1 1 1 0 1 0 0 0 0 1 0 1 0 1 1 1 1 1 0 0 0 1 1\n",
      "  0 0 0 1 0 1 1 1 1 1 1 0 1 1 1 0 0 1 0 1]]\n",
      "final_activation:  0.45588235294117646============----------] 81.8% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 1 1 1 0 0 1 1 0 1 1 0 1 1 1\n",
      "  0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0\n",
      "  0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1\n",
      "  1 0 0 0 1 0 0 1 0 1 0 1 1 1 0 0 0 1 0 0 0 0 1 1 0 0 1 0 0 1 1 0 0 0 0 1\n",
      "  0 0 0 0 1 0 1 1 1 1 1 0 0 0 0 1 0 1 1 1]]\n",
      "Progress [==================================================] 100.0% Complete\n",
      "\n",
      "ABC-SMC Round 3 / 4\n",
      "final_activation:  0.45588235294117646----------------------] 0.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "seed passed\n",
      "running LT Abs\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.15441176470588236\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.25735294117647056\n",
      "state activation:  0.375\n",
      "final graph:  [[1 1 1 0 1 1 1 1 1 1 0 0 0 1 1 1 0 0 0 0 0 1 0 1 0 0 0 1 1 0 1 1 0 1 1 1\n",
      "  0 1 0 1 1 0 1 1 0 1 1 0 0 0 0 1 0 1 0 1 1 1 1 0 0 1 0 1 0 1 1 0 1 1 1 0\n",
      "  1 0 1 0 1 1 0 0 1 0 0 0 1 0 1 1 0 1 0 1 1 0 1 1 0 0 0 0 1 0 1 0 1 1 0 0\n",
      "  0 0 0 1 0 1 0 1 0 0 1 0 0 0 1 1 1 0 0 1 0 1 1 0 1 0 1 1 0 0 0 0 0 0 0 1\n",
      "  1 0 0 0 1 0 0 0 0 1 1 0 0 1 1 0 0 0 1 1 0 0 0 1 0 0 0 1 1 0 1 0 0 1 1 1\n",
      "  0 0 0 0 1 0 1 0 0 1 0 1 1 0 1 1 1 1 1 0 1 1 1 1 1 0 1 1 0 1 0 0 0 0 0 1\n",
      "  0 0 1 1 1 0 1 1 1 1 0 1 0 1 1 1 0 1 0 1 1 1 0 1 1 0 1 0 1 1 0 0 0 1 1 1\n",
      "  1 0 1 0 1 0 1 0 1 1 0 1 1 0 1 1 1 1 1 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 50.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "seed passed\n",
      "running LT Abs\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.1323529411764706\n",
      "state activation:  0.19852941176470587\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.26838235294117646\n",
      "state activation:  0.3639705882352941\n",
      "final graph:  [[1 1 0 1 1 1 1 1 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 1 1\n",
      "  0 0 0 0 0 1 0 0 1 1 1 0 0 0 0 1 0 1 0 1 1 1 0 0 0 1 0 1 0 1 1 0 1 1 1 0\n",
      "  1 1 1 1 1 1 0 1 0 0 1 1 0 1 0 1 0 0 1 1 1 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1\n",
      "  0 0 0 1 0 0 0 0 0 1 1 1 0 0 0 1 1 0 0 0 0 0 1 1 1 0 1 1 1 0 0 0 0 1 0 0\n",
      "  1 0 1 0 1 0 0 0 0 1 1 0 0 1 1 0 1 1 1 1 1 1 1 1 0 1 1 1 0 0 0 1 0 0 0 0\n",
      "  1 0 0 0 1 1 1 0 1 1 0 0 1 0 1 0 1 0 0 1 1 1 1 1 1 0 1 1 1 1 0 0 0 1 1 1\n",
      "  1 1 0 0 1 1 1 1 0 1 1 1 1 1 0 0 0 0 0 0 0 1 1 1 1 1 1 0 1 1 1 0 0 1 1 0\n",
      "  1 1 0 1 1 1 1 0 1 1 0 1 1 0 1 1 1 1 1 1]]\n",
      "final_activation:  0.45588235294117646=====-----------------] 66.7% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.15441176470588236\n",
      "state activation:  0.22794117647058823\n",
      "state activation:  0.30514705882352944\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.33455882352941174\n",
      "state activation:  0.3713235294117647\n",
      "final graph:  [[0 1 1 1 1 1 1 0 0 1 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 1 0 1\n",
      "  0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 1 1 0 0 1 0 0 1 0 0 0 0 0 0 0 1 0 0 1 1 0\n",
      "  0 0 0 0 0 1 1 0 0 0 0 1 0 1 0 1 1 0 1 1 0 1 1 1 0 1 0 0 1 0 1 1 1 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 1 0 0 0 0 0\n",
      "  1 1 0 0 1 0 1 1 0 0 1 0 1 1 1 1 0 1 0 1 1 1 1 0 0 1 0 1 1 0 0 1 0 1 0 0\n",
      "  0 1 0 0 1 0 1 0 1 1 1 0 1 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 1 0 0 0 0 1\n",
      "  1 1 0 0 1 1 0 1 1 1 1 1 0 1 0 1 0 0 1 0 1 1 0 0 0 0 1 1 0 1 0 0 0 1 0 0\n",
      "  1 1 1 0 1 1 0 0 0 1 0 0 0 0 0 0 0 1 1 1]]\n",
      "final_activation:  0.45588235294117646=========-------------] 75.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.15808823529411764\n",
      "state activation:  0.21323529411764705\n",
      "state activation:  0.2647058823529412\n",
      "state activation:  0.3125\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.35294117647058826\n",
      "state activation:  0.3897058823529412\n",
      "final graph:  [[1 1 1 0 0 1 0 0 1 1 0 0 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 1 1\n",
      "  0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 1 1 0 1 0 1 0 0 0 0 1 0 0 0 0 1 0 0 1 1 0\n",
      "  0 0 0 0 1 1 1 0 1 0 0 1 0 0 1 0 1 0 0 1 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0 0\n",
      "  1 1 0 0 0 0 0 0 1 0 1 0 1 0 1 0 1 0 1 0 0 1 1 0 0 0 1 0 1 1 1 1 1 0 0 1\n",
      "  1 1 0 0 1 0 1 0 0 1 0 0 0 1 1 1 1 1 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0\n",
      "  0 1 0 0 1 0 1 0 0 1 0 1 0 1 1 1 1 0 0 1 0 1 1 1 1 0 1 0 0 1 1 1 0 0 0 1\n",
      "  0 0 0 1 1 0 1 0 1 1 0 1 0 1 0 0 0 0 0 0 0 0 1 0 0 0 1 1 1 1 1 1 1 1 0 0\n",
      "  1 1 0 0 1 0 1 0 1 1 1 1 1 1 0 1 0 0 1 1]]\n",
      "final_activation:  0.45588235294117646============----------] 80.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "seed passed\n",
      "running LT Abs\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.11764705882352941\n",
      "state activation:  0.1801470588235294\n",
      "state activation:  0.24632352941176472\n",
      "state activation:  0.2977941176470588\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.34558823529411764\n",
      "state activation:  0.4375\n",
      "final graph:  [[1 1 0 0 1 0 0 1 1 1 1 0 0 1 1 1 1 1 0 0 1 1 1 1 0 1 0 1 1 1 1 1 1 1 1 1\n",
      "  0 0 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 1 1 1 1 1 0 0 1 1 1 1 1 1 1 0 1 1 1 0\n",
      "  0 1 1 1 0 1 0 1 1 0 0 0 1 0 1 1 0 0 0 1 1 0 1 1 0 0 0 0 0 0 0 0 1 1 0 0\n",
      "  1 1 0 0 1 0 0 1 0 1 1 0 0 0 1 1 1 0 0 1 0 0 1 1 1 0 0 0 1 0 0 0 0 1 0 1\n",
      "  1 0 0 0 1 0 0 1 0 1 1 0 1 1 1 0 1 0 1 1 1 1 0 0 1 1 1 1 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 1 1 1 0 1 1 1 0 0 0 1 0 0 1 0 0 1 1 1 1 1 0 1 1 0 1 0 0 0 1 0 0\n",
      "  0 0 0 1 1 1 1 0 0 1 1 1 0 1 0 1 0 1 0 1 0 1 1 1 1 1 1 0 1 1 1 0 1 1 1 1\n",
      "  1 0 1 0 1 0 0 0 1 1 1 1 1 0 1 1 1 1 1 1]]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "final_activation:  0.45588235294117646=============---------] 83.3% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "seed passed\n",
      "running LT Abs\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.15808823529411764\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.27941176470588236\n",
      "state activation:  0.4227941176470588\n",
      "final graph:  [[1 1 1 1 1 1 1 1 1 1 0 1 0 1 1 1 0 1 0 0 0 1 1 1 1 0 0 1 1 1 1 1 1 1 0 1\n",
      "  1 0 1 1 1 1 1 1 0 1 1 0 1 0 0 1 0 1 0 1 1 1 0 0 0 1 0 1 0 0 1 0 1 1 0 1\n",
      "  1 0 0 1 1 1 1 0 0 1 0 1 1 0 1 1 0 0 0 0 0 0 1 1 0 0 0 1 1 0 0 0 0 0 0 0\n",
      "  0 1 0 0 0 0 0 0 1 0 1 0 0 1 1 1 1 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 1 0 0\n",
      "  1 0 0 0 1 0 0 0 1 1 1 0 1 1 1 1 1 0 1 1 1 1 0 0 1 1 1 1 1 1 0 1 1 0 0 0\n",
      "  1 0 0 0 1 1 1 0 1 1 0 1 0 0 1 1 0 1 0 0 1 1 1 0 0 0 1 1 1 1 0 0 0 1 1 1\n",
      "  0 0 1 1 1 1 1 1 0 1 0 1 1 1 0 0 0 1 0 1 0 1 0 1 1 0 1 0 1 1 1 1 0 1 1 1\n",
      "  1 1 1 1 1 0 1 0 1 1 0 1 1 1 0 1 1 1 0 1]]\n",
      "final_activation:  0.45588235294117646==============--------] 85.7% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 0 0 0 1 1 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 1 0 0 1 1\n",
      "  0 0 0 0 0 1 1 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0\n",
      "  0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0\n",
      "  0 0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0\n",
      "  0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 1 0 1 0 1 0 0 1 0 1 0 0\n",
      "  0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 0 0 1\n",
      "  0 0 0 0 1 1 0 0 1 1 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 0 0 1\n",
      "  0 0 0 0 1 0 1 0 1 1 0 1 0 0 1 1 0 0 0 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 9.9% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.15808823529411764\n",
      "state activation:  0.21691176470588236\n",
      "state activation:  0.2610294117647059\n",
      "state activation:  0.2867647058823529\n",
      "state activation:  0.3125\n",
      "state activation:  0.3235294117647059\n",
      "state activation:  0.33455882352941174\n",
      "state activation:  0.34191176470588236\n",
      "final graph:  [[0 1 1 0 0 1 1 1 0 1 0 0 0 0 1 1 0 0 0 1 1 1 0 1 1 0 0 1 1 1 1 0 0 0 0 1\n",
      "  1 0 1 0 1 0 1 1 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  1 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 1 0\n",
      "  0 0 0 0 0 0 1 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1\n",
      "  0 0 0 0 0 0 0 1 0 0 0 1 0 1 1 0 0 0 0 1 1 1 0 0 0 1 0 1 0 0 0 1 0 1 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0 1 0 1 0 0 1 1 0 1 1 0 0 0 0 1 1 0 0 1 1\n",
      "  1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 0 1 0 0 0 1 0 0 1 1 0 0 0 1 1\n",
      "  0 0 0 0 0 0 0 1 0 1 1 0 0 0 1 0 1 0 0 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 19.5% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.15808823529411764\n",
      "state activation:  0.22426470588235295\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.30514705882352944\n",
      "state activation:  0.3897058823529412\n",
      "final graph:  [[1 1 1 1 1 1 1 1 1 1 1 0 0 1 1 1 1 0 0 1 1 1 0 0 1 1 0 1 0 0 1 1 0 1 0 1\n",
      "  1 1 0 1 0 1 1 0 0 1 0 0 1 0 0 1 1 1 1 0 0 0 0 1 0 1 0 0 0 0 1 0 0 1 1 0\n",
      "  1 1 1 0 0 1 0 1 1 0 0 1 0 0 0 1 0 0 1 0 0 1 0 1 0 1 0 0 0 0 0 0 1 0 0 0\n",
      "  0 1 0 1 1 0 0 0 1 0 1 0 1 0 0 0 1 0 0 0 0 1 1 1 1 0 0 0 1 0 0 0 0 0 0 0\n",
      "  0 0 1 0 0 1 0 1 1 0 0 0 0 1 1 1 0 0 0 0 0 0 0 1 0 0 0 1 1 1 1 1 1 0 1 1\n",
      "  1 1 1 1 0 0 0 1 0 1 1 0 1 0 0 1 1 0 1 0 0 0 1 0 0 1 0 0 0 0 1 0 0 0 0 0\n",
      "  1 0 0 1 1 0 1 1 1 1 0 1 1 0 0 0 0 1 0 1 1 1 1 0 1 1 1 0 1 1 0 0 0 1 0 1\n",
      "  1 0 1 0 0 0 1 1 1 1 0 1 0 1 0 1 0 1 0 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 29.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.15808823529411764\n",
      "state activation:  0.2426470588235294\n",
      "state activation:  0.3088235294117647\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.3492647058823529\n",
      "state activation:  0.38235294117647056\n",
      "final graph:  [[0 1 0 1 1 0 1 1 0 1 0 1 0 0 1 0 0 0 0 0 0 1 0 1 0 0 0 0 1 1 1 1 0 1 0 0\n",
      "  0 0 0 1 1 0 1 0 0 1 1 0 0 1 0 0 0 0 1 0 1 0 0 0 0 0 0 1 0 0 1 1 1 1 0 0\n",
      "  1 0 1 1 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 1 0 0 1 0 1 1 1 0 1 1 0 0\n",
      "  0 1 1 0 1 0 0 0 1 0 1 0 1 0 0 0 0 0 1 1 1 1 1 0 0 1 0 0 0 0 0 1 0 0 0 1\n",
      "  0 1 0 0 0 0 1 0 0 0 1 0 0 1 1 0 0 1 0 0 0 1 0 0 1 0 0 1 1 0 0 0 0 1 0 0\n",
      "  0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 1 0 1 0 0 1 0 1 0 0 0 0 1 1 1 0 0 0 0\n",
      "  0 0 0 1 1 0 1 1 1 1 0 1 0 0 1 0 0 0 1 1 1 0 1 1 0 0 1 1 1 1 1 0 0 1 1 1\n",
      "  1 1 0 0 1 0 1 1 1 1 1 1 1 1 0 1 1 0 1 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 29.4% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.13970588235294118\n",
      "state activation:  0.21691176470588236\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.3088235294117647\n",
      "state activation:  0.375\n",
      "final graph:  [[0 1 1 1 0 1 1 0 0 1 0 0 0 0 1 0 0 0 1 0 0 0 0 0 1 0 1 0 0 1 1 0 0 0 0 1\n",
      "  0 0 0 0 1 0 0 0 1 1 0 0 0 0 1 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 1 0 0 1 0 0 1 0 0 0 1 1 0 0\n",
      "  1 0 0 1 0 1 1 1 0 1 1 0 0 0 0 0 1 1 0 1 0 1 1 0 1 1 0 0 0 0 1 0 0 1 0 1\n",
      "  0 0 0 0 0 0 0 1 0 0 0 0 1 1 0 0 0 0 1 0 0 1 1 0 0 1 0 0 1 0 1 1 0 0 0 0\n",
      "  1 0 0 0 0 0 0 0 1 0 1 1 1 1 0 0 1 1 1 0 1 1 1 1 1 1 0 1 0 1 1 1 1 0 1 1\n",
      "  1 1 1 1 1 1 1 1 1 1 1 1 0 1 0 1 1 1 1 1 0 1 1 0 0 0 1 0 0 1 1 0 1 1 0 0\n",
      "  0 0 0 0 1 0 1 1 1 1 1 0 0 1 1 0 0 0 0 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 39.3% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.13602941176470587\n",
      "state activation:  0.1801470588235294\n",
      "state activation:  0.22058823529411764\n",
      "state activation:  0.2610294117647059\n",
      "state activation:  0.29411764705882354\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.33088235294117646\n",
      "state activation:  0.36764705882352944\n",
      "final graph:  [[1 1 1 0 0 0 1 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 1 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 0 0\n",
      "  1 0 1 0 0 1 0 0 0 1 0 0 0 1 0 0 1 1 1 0 0 1 1 1 1 1 1 1 0 1 0 1 1 1 1 1\n",
      "  0 0 1 0 0 1 0 0 1 0 1 0 0 1 1 0 1 0 1 0 1 0 1 0 0 0 1 1 0 0 0 1 1 0 0 0\n",
      "  0 1 1 0 0 1 0 1 0 1 0 0 1 1 1 0 1 0 1 1 0 1 1 1 1 1 1 1 0 0 1 1 1 1 0 1\n",
      "  1 0 0 0 0 1 0 0 0 1 0 0 0 0 1 0 1 0 0 0 1 1 1 0 0 0 0 1 0 1 1 1 0 1 0 1\n",
      "  0 0 0 0 1 0 0 1 1 1 1 1 1 0 0 0 0 1 0 0 0 0 1 0 0 0 1 1 0 1 1 0 0 0 0 1\n",
      "  0 0 0 0 0 1 1 1 0 1 1 0 1 1 0 0 1 1 0 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 38.7% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "seed passed\n",
      "running LT Abs\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.14338235294117646\n",
      "state activation:  0.21323529411764705\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.3014705882352941\n",
      "state activation:  0.36764705882352944\n",
      "final graph:  [[1 1 0 0 1 0 0 1 1 1 0 0 0 1 1 0 0 1 0 0 0 1 1 1 0 1 0 1 1 1 1 1 1 1 1 1\n",
      "  0 1 0 1 1 1 1 1 1 1 1 0 1 0 0 0 0 1 1 0 1 1 1 0 0 1 1 1 1 1 1 0 0 1 1 0\n",
      "  1 0 0 1 1 1 1 1 1 0 1 1 0 1 1 1 1 0 0 1 0 0 0 1 0 0 1 1 1 0 0 1 0 1 0 1\n",
      "  0 1 1 1 0 0 0 0 0 0 1 0 1 0 1 0 1 0 1 0 0 0 1 0 1 0 1 0 0 0 0 0 1 0 0 1\n",
      "  0 1 1 0 1 0 0 0 0 0 1 0 0 1 0 1 0 0 1 0 0 0 1 1 0 0 1 0 0 0 0 0 0 0 0 0\n",
      "  0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  1 0 0 0 1 1 0 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 1 0 0 0 1 1 1\n",
      "  1 0 1 1 1 0 1 0 1 1 1 0 1 0 0 1 1 1 1 1]]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "final_activation:  0.45588235294117646----------------------] 39.4% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "seed passed\n",
      "running LT Abs\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.1323529411764706\n",
      "state activation:  0.22058823529411764\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.3235294117647059\n",
      "state activation:  0.43014705882352944\n",
      "final graph:  [[1 1 0 0 1 0 1 0 1 1 1 1 0 1 1 1 1 1 0 0 0 0 1 1 0 1 0 1 1 1 1 1 0 1 1 1\n",
      "  1 0 0 0 1 1 1 1 1 1 1 0 0 0 0 0 0 1 0 1 0 1 0 0 0 1 1 1 1 1 1 0 1 1 1 0\n",
      "  0 1 1 0 0 1 0 1 0 0 0 0 0 1 1 1 0 0 0 1 1 0 0 1 0 0 0 0 0 0 0 1 0 1 0 0\n",
      "  1 1 0 1 0 0 0 0 0 1 1 0 1 0 1 1 1 0 1 1 1 1 1 1 1 0 0 1 1 1 0 0 0 1 1 0\n",
      "  1 0 0 1 0 0 1 1 0 1 1 0 1 1 1 1 1 0 1 1 1 1 1 1 1 0 1 1 1 0 1 1 0 0 0 1\n",
      "  1 0 0 0 1 1 1 0 1 1 0 1 1 0 1 0 1 0 1 0 1 1 1 0 0 0 1 1 0 1 0 0 0 1 0 1\n",
      "  0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 0 0 0 1 0 1 1 1 1 0 0 1 1 1 0 1 1 1\n",
      "  1 0 1 0 1 1 0 0 1 1 0 1 1 1 0 1 1 1 1 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 38.9% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.14338235294117646\n",
      "state activation:  0.20588235294117646\n",
      "state activation:  0.2757352941176471\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.3235294117647059\n",
      "state activation:  0.3602941176470588\n",
      "final graph:  [[0 1 0 0 0 1 1 1 1 1 0 0 1 1 1 1 0 1 0 1 1 0 0 1 0 0 0 1 1 1 1 0 0 1 0 1\n",
      "  1 1 0 1 0 1 1 0 0 1 1 1 0 1 0 1 0 0 0 0 0 0 1 0 1 0 0 0 1 0 1 1 1 1 1 0\n",
      "  0 0 0 0 1 1 1 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 1 0 0 0 0 0 0 0 1 1 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 1 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 1 0 0 1 1 1 0 0 0 1 1 0 0 0\n",
      "  0 0 0 0 0 1 0 0 0 0 0 1 1 1 1 0 1 0 1 0 1 1 1 0 1 1 1 0 1 0 1 1 1 1 0 0\n",
      "  1 0 0 0 1 0 0 1 1 1 1 1 1 0 1 0 0 1 0 1 0 0 1 0 0 0 1 0 0 1 1 0 0 0 1 1\n",
      "  0 0 1 1 1 1 0 1 0 1 0 0 0 1 0 0 0 0 0 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 48.4% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 0 0 0 0 1 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 1 0 0 1 1 1\n",
      "  0 0 0 0 0 1 0 0 0 1 0 0 1 0 0 1 0 0 1 0 0 0 0 1 0 0 0 0 0 0 1 0 0 1 1 0\n",
      "  0 0 0 0 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0\n",
      "  0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 1 0 0 1 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 1 0 0 1 1 1 0 0 0 1 0 0 1 0 1 0 0 1 1 0 0 0 1 0 0 0 0\n",
      "  1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 1 0 0 0 0 0 1\n",
      "  0 1 0 0 1 1 0 0 1 1 1 1 0 0 1 0 0 0 0 1 0 0 0 0 0 0 1 0 0 1 0 1 0 1 0 1\n",
      "  0 0 0 0 1 0 0 0 1 1 0 1 0 0 1 0 0 0 1 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 48.5% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.15073529411764705\n",
      "state activation:  0.21323529411764705\n",
      "state activation:  0.27941176470588236\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.34558823529411764\n",
      "state activation:  0.39705882352941174\n",
      "final graph:  [[0 1 1 0 0 1 0 1 1 1 1 0 0 1 1 0 0 1 0 0 1 1 1 1 0 1 0 0 1 1 1 0 1 1 1 0\n",
      "  0 0 1 1 1 1 0 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 0 0 1 1 1 0 0 1 0 0 1 0 0 1 0 1 0 0 0 0 0 0 1 1 1 1 1 1 0 0 1 1 1 0\n",
      "  0 1 0 0 0 1 0 0 0 0 1 1 0 1 1 0 1 1 0 0 0 0 1 0 0 0 1 0 1 1 0 0 0 0 0 0\n",
      "  0 0 1 0 0 0 0 0 0 1 0 0 1 1 1 1 1 0 1 0 0 0 1 1 1 1 1 1 1 0 0 1 1 1 0 0\n",
      "  1 0 0 0 0 1 1 0 0 0 0 1 0 0 1 0 0 0 0 0 1 1 1 0 0 0 1 0 0 1 1 1 0 0 0 1\n",
      "  0 1 0 0 1 0 0 1 0 1 1 1 0 0 0 1 0 1 1 0 1 0 1 1 1 0 1 0 1 1 1 0 0 0 1 0\n",
      "  0 0 0 1 1 1 1 1 0 1 0 1 0 0 0 0 0 1 0 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 48.6% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 1 0 1 1 0 0 0 1 0 0 0 1 1 0 0 0 0 0 0 0 0 1 1 0 0 1 0 0 1 0 0 0 0 1\n",
      "  0 0 0 0 0 1 1 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 1\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 1 1 0 0 1 0 0 0 0\n",
      "  0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 0 0 0 1 0 0 0 0\n",
      "  0 0 0 0 1 0 0 0 1 1 1 1 0 1 0 0 0 1 0 0 0 0 1 0 0 0 1 0 0 1 1 0 1 0 1 0\n",
      "  0 0 1 0 1 0 0 0 1 1 0 0 0 0 1 1 0 0 0 1]]\n",
      "final_activation:  0.45588235294117646=---------------------] 58.1% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[1 1 1 0 0 0 1 0 0 1 0 0 0 1 1 0 0 0 0 0 0 0 1 1 1 1 0 0 0 0 1 0 0 0 1 0\n",
      "  0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0\n",
      "  0 0 0 0 0 1 1 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 1 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 1 0 0 0 0 0 0 1 0 1 0 0 1 0 0 0 0\n",
      "  1 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 1 1 1 0 0 0 0 0 0 0 1 0 1 0 0 0\n",
      "  0 0 0 0 1 1 1 0 1 1 0 1 0 0 0 0 0 1 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0 0 1 0\n",
      "  1 0 1 0 1 0 0 0 0 1 0 0 0 0 1 0 0 1 0 1]]\n",
      "final_activation:  0.45588235294117646=====-----------------] 67.9% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.1213235294117647\n",
      "state activation:  0.16544117647058823\n",
      "state activation:  0.20588235294117646\n",
      "state activation:  0.2426470588235294\n",
      "state activation:  0.27941176470588236\n",
      "state activation:  0.30514705882352944\n",
      "state activation:  0.3235294117647059\n",
      "state activation:  0.3382352941176471\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.3492647058823529\n",
      "state activation:  0.35661764705882354\n",
      "final graph:  [[0 1 1 0 1 1 1 0 0 1 1 0 0 1 1 1 0 0 1 0 0 0 0 1 1 0 1 0 0 0 1 0 1 0 1 1\n",
      "  1 0 0 0 0 0 0 0 0 1 0 0 1 1 1 1 0 0 1 0 1 0 1 0 1 0 1 0 0 0 1 1 0 1 0 0\n",
      "  1 0 1 1 0 1 1 0 1 0 1 0 0 0 0 0 0 0 0 0 0 1 0 1 1 1 1 0 0 0 0 0 0 0 0 1\n",
      "  0 0 1 1 0 0 0 0 1 0 1 1 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 1 1 0 0 0\n",
      "  0 0 1 0 1 1 1 0 1 0 0 1 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 0 0 0 1 1\n",
      "  0 1 1 0 0 0 0 1 0 0 1 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 1 0 1 0 0 1\n",
      "  1 1 0 1 1 1 0 1 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 0 0 1 1 0 1 1 1 1\n",
      "  1 0 1 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 1]]\n",
      "final_activation:  0.45588235294117646======----------------] 69.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 1 0 1 1 0 1 0 1 1 0 0 1 1 0 0 0 0 0 0 0 0 0 1 1 0 1 0 1 1 1 0 1 0 0\n",
      "  0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0\n",
      "  1 0 1 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 1 0 0 0 1 0 0 1 0 0 0 1 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 1 0 0 1 1 1 0 0 0 1 0 0 0 0 0 0 0 0 0\n",
      "  0 1 0 0 1 0 0 0 1 1 1 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 1 0 1 0 0\n",
      "  0 0 0 0 1 0 1 1 0 1 1 0 0 0 0 0 0 0 0 1]]\n",
      "final_activation:  0.45588235294117646==========------------] 77.8% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "seed passed\n",
      "running LT Abs\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.15808823529411764\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.2757352941176471\n",
      "state activation:  0.3713235294117647\n",
      "final graph:  [[1 1 0 0 1 0 1 1 1 1 0 0 1 1 1 0 1 1 0 0 0 0 1 1 0 1 0 1 1 1 1 1 1 1 1 1\n",
      "  0 1 0 1 1 1 1 1 1 1 1 0 1 1 0 1 1 1 0 1 1 0 0 0 1 1 0 1 1 1 1 0 1 1 0 0\n",
      "  0 0 0 0 0 1 1 1 0 1 0 0 1 1 1 1 0 0 0 1 1 0 0 0 0 0 0 1 1 0 0 0 0 0 1 0\n",
      "  0 1 0 0 0 0 0 0 0 1 1 0 0 1 1 0 1 1 0 0 0 0 1 1 1 0 0 0 1 0 1 0 0 1 0 1\n",
      "  0 0 0 0 1 0 1 0 0 0 1 0 1 1 0 1 0 0 0 1 1 1 0 0 1 1 0 1 1 0 1 0 0 0 1 0\n",
      "  0 1 0 0 1 0 0 0 1 1 0 0 1 0 0 0 1 1 0 0 0 1 1 1 1 0 0 1 0 0 0 1 0 1 0 1\n",
      "  0 0 0 1 1 1 0 1 1 1 0 1 0 1 1 0 0 1 0 1 0 0 0 0 1 1 1 0 0 1 1 0 0 1 1 0\n",
      "  1 0 1 1 1 1 0 0 1 1 0 0 1 0 1 1 1 1 1 1]]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "final_activation:  0.45588235294117646===========-----------] 78.6% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 1 0 0 0 1 0 1 1 0 0 0 1 1 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 1 0 0 1 0 1\n",
      "  0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 1 0 0 1 1 1 0 1 0 1 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 0 0 1 1 0 1 1 0 1 0 0\n",
      "  1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 1 1 1 0 0 0 0 1 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 0 0 1\n",
      "  1 0 0 0 1 0 0 0 0 1 1 0 0 0 0 1 0 0 0 1]]\n",
      "final_activation:  0.45588235294117646================------] 88.5% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 0 0 0 0 0 0 0 1 0 0 0 1 1 0 0 0 0 0 0 0 1 0 0 1 0 0 0 1 1 0 0 1 0 0\n",
      "  0 0 0 0 1 0 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 1 0 0 1 1 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 1 0 0 0 0 0 1 0 0 0 0 1 1 0 0 0 0\n",
      "  0 1 0 0 0 0 0 0 0 0 1 0 0 1 1 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0\n",
      "  0 0 0 0 1 1 1 1 0 1 0 1 0 0 1 0 0 1 0 1 1 1 0 0 0 0 1 0 1 1 1 1 0 1 0 0\n",
      "  1 0 0 0 0 0 0 0 0 1 0 1 0 0 1 0 0 1 0 1]]\n",
      "Progress [==================================================] 100.0% Complete\n",
      "\n",
      "ABC-SMC Round 4 / 4\n",
      "final_activation:  0.45588235294117646----------------------] 0.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[1 1 0 0 0 1 0 1 0 1 0 0 0 1 1 0 0 0 0 0 0 0 1 0 1 0 0 0 1 0 1 0 0 1 0 0\n",
      "  0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 1 0 1 0 0 0 0 0 0 0 1 0 0 1 1 0\n",
      "  0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0\n",
      "  0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 1 1 0 0 0 0 0 1 0 0 0 0\n",
      "  1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1\n",
      "  0 0 1 0 1 0 0 1 0 1 0 1 0 1 0 0 0 0 0 1 1 0 0 0 0 0 1 0 0 1 1 1 1 1 0 1\n",
      "  1 0 0 0 1 0 0 0 0 1 0 1 0 0 0 0 0 1 0 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 50.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.13602941176470587\n",
      "state activation:  0.20220588235294118\n",
      "state activation:  0.2647058823529412\n",
      "state activation:  0.3125\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.35294117647058826\n",
      "state activation:  0.3786764705882353\n",
      "final graph:  [[0 1 0 0 0 1 0 1 1 1 0 0 0 1 1 1 0 1 1 0 1 0 1 0 1 1 1 1 1 1 1 0 0 1 1 0\n",
      "  0 0 0 1 0 0 1 0 0 1 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 1 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 1 0 1 1 0 0 1 0 1 1 0 1 1 1 1 1 1 1 0 1 1 1 1 1 0 1 1 0 0 0 0\n",
      "  1 1 1 1 1 0 0 1 0 1 1 1 1 0 1 1 0 1 0 1 1 1 1 0 1 0 1 1 0 1 1 0 1 0 0 0\n",
      "  0 1 1 1 1 1 1 0 0 1 1 1 1 1 1 0 0 0 0 0 1 1 1 1 0 0 1 0 1 1 1 0 0 1 0 0\n",
      "  1 0 1 0 0 1 0 0 1 1 0 0 1 0 1 1 0 0 1 1]]\n",
      "final_activation:  0.45588235294117646=====-----------------] 66.7% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.12867647058823528\n",
      "state activation:  0.18382352941176472\n",
      "state activation:  0.23897058823529413\n",
      "state activation:  0.26838235294117646\n",
      "state activation:  0.28308823529411764\n",
      "state activation:  0.29411764705882354\n",
      "state activation:  0.3014705882352941\n",
      "final graph:  [[0 1 0 0 0 1 1 0 1 1 1 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 1 0 0 0 1 0\n",
      "  0 0 1 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 1 0 0 0 1 0 0 1 0 0\n",
      "  0 0 1 0 0 1 1 1 0 0 0 0 0 0 1 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 1 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 1\n",
      "  0 1 0 1 1 0 0 0 0 0 1 1 1 1 0 0 1 0 1 0 1 1 1 0 1 1 1 1 0 0 1 0 1 0 0 1\n",
      "  0 1 0 1 1 0 1 0 0 1 0 1 1 1 1 0 0 0 0 0 0 1 0 0 0 1 1 0 1 1 0 0 0 1 0 1\n",
      "  1 0 0 0 1 0 1 0 0 1 0 1 1 0 1 0 1 1 1 1]]\n",
      "final_activation:  0.45588235294117646=========-------------] 75.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.12867647058823528\n",
      "state activation:  0.18382352941176472\n",
      "state activation:  0.23529411764705882\n",
      "state activation:  0.27205882352941174\n",
      "state activation:  0.3088235294117647\n",
      "state activation:  0.33455882352941174\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.3492647058823529\n",
      "state activation:  0.36764705882352944\n",
      "final graph:  [[0 1 1 1 1 1 1 0 1 1 0 0 1 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 1 0 0 0\n",
      "  0 0 1 1 1 1 0 0 0 1 1 1 0 0 0 0 0 0 1 1 0 0 0 1 1 0 0 0 1 1 1 0 0 1 0 1\n",
      "  1 0 1 0 0 1 1 0 0 1 0 0 0 1 0 0 0 0 0 1 0 1 0 0 1 0 0 1 1 1 0 0 0 0 0 1\n",
      "  0 0 0 1 0 0 1 1 0 0 1 1 0 0 0 0 1 0 0 1 0 0 1 1 0 0 0 0 1 0 0 1 0 0 0 1\n",
      "  0 0 1 0 0 1 0 1 0 0 0 0 1 1 0 0 0 1 0 1 0 1 0 1 0 1 0 0 0 1 0 0 0 0 0 1\n",
      "  0 0 0 0 1 0 0 1 1 0 0 0 0 0 0 0 0 1 0 1 0 0 1 1 0 0 1 0 1 0 0 0 1 1 0 1\n",
      "  0 1 0 0 1 0 1 0 0 1 0 1 0 1 0 0 1 1 0 1 0 0 1 0 1 0 1 0 1 1 0 0 0 0 0 0\n",
      "  1 1 1 0 0 0 1 1 0 1 0 1 1 1 0 1 0 0 0 1]]\n",
      "final_activation:  0.45588235294117646============----------] 80.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.14705882352941177\n",
      "state activation:  0.22058823529411764\n",
      "state activation:  0.26838235294117646\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.3088235294117647\n",
      "state activation:  0.3639705882352941\n",
      "final graph:  [[0 1 0 1 0 0 1 1 0 1 0 1 1 0 1 1 1 0 1 0 0 1 0 0 1 0 1 0 0 0 1 1 0 0 0 1\n",
      "  0 1 0 0 0 1 0 0 0 1 0 1 0 1 1 1 1 0 1 1 1 1 0 1 1 1 1 0 0 0 1 0 0 1 0 0\n",
      "  1 0 1 1 0 1 0 1 0 1 0 1 0 0 1 1 0 0 0 1 1 1 1 1 0 0 1 0 1 1 0 1 1 0 0 0\n",
      "  0 1 0 1 0 1 0 0 1 1 1 0 1 0 0 0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 1 1 0 0 1\n",
      "  1 0 1 0 0 0 0 0 0 0 1 1 1 1 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 1 0 0\n",
      "  0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 1 0 1 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0\n",
      "  0 0 0 0 1 0 0 0 1 1 0 1 0 0 0 0 0 1 0 1 0 1 1 0 0 1 1 0 0 1 1 1 0 0 1 0\n",
      "  0 0 0 1 1 1 0 1 1 1 1 0 0 1 1 0 1 1 0 1]]\n",
      "final_activation:  0.45588235294117646=============---------] 83.3% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.13970588235294118\n",
      "state activation:  0.20588235294117646\n",
      "state activation:  0.26838235294117646\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.3161764705882353\n",
      "state activation:  0.35661764705882354\n",
      "final graph:  [[1 1 1 0 0 1 1 1 1 1 0 0 0 1 1 1 1 1 0 1 1 0 1 1 1 1 0 1 1 1 1 1 0 1 0 1\n",
      "  0 0 0 1 1 0 1 0 1 1 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 1 0 0 1 0 1 1 0 0\n",
      "  1 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 1 0 1 1 1 0 0 0 0 1 1 0 0 0\n",
      "  0 0 0 1 1 0 0 0 1 0 1 0 1 0 1 0 0 1 1 0 0 1 1 0 0 0 1 0 1 0 0 0 0 1 0 0\n",
      "  1 1 0 1 1 0 0 1 0 0 1 0 0 1 0 0 0 0 0 0 1 1 0 0 0 1 0 1 0 0 0 1 0 1 0 0\n",
      "  1 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 1 0 0 0 0 1 0 1 1 0 0 0 0\n",
      "  0 1 0 0 1 0 0 0 0 1 0 1 0 1 0 0 0 1 0 0 0 1 1 0 1 0 1 1 0 1 1 0 1 0 0 0\n",
      "  0 0 1 1 1 1 0 1 1 1 1 1 0 1 1 1 0 0 0 1]]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "final_activation:  0.45588235294117646==============--------] 85.7% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 0 0 0 1 1 1 0 1 0 0 0 1 1 0 1 0 0 0 0 0 0 1 1 1 0 0 0 1 1 0 0 1 1 0\n",
      "  0 0 1 0 1 0 0 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  1 0 0 0 0 1 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0\n",
      "  0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 1 0 0 1 0 0 0 0 0 1 0\n",
      "  0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 0 0 0 0 1 0 0 1 0 0 0 1 0 0 1 0 0 1 0 0\n",
      "  0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 1 0 0 1 1 1 0 1 1 0 1 0 0 0 0 1 1 0 1 0 0 0 1 0 0 1 0 0 0 0 0 0\n",
      "  1 0 0 0 0 0 0 0 1 1 0 1 0 0 0 0 0 1 0 1]]\n",
      "final_activation:  0.45588235294117646===============-------] 87.5% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.12867647058823528\n",
      "state activation:  0.19117647058823528\n",
      "state activation:  0.23529411764705882\n",
      "state activation:  0.25735294117647056\n",
      "state activation:  0.2867647058823529\n",
      "state activation:  0.2977941176470588\n",
      "state activation:  0.3014705882352941\n",
      "state activation:  0.30514705882352944\n",
      "final graph:  [[0 1 0 0 1 0 0 0 1 1 1 0 1 1 1 1 1 1 0 1 1 0 1 1 1 1 0 1 1 1 1 1 1 1 1 1\n",
      "  0 1 1 0 1 1 1 1 1 1 0 1 1 1 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 1 0 1 1 0 1\n",
      "  0 0 1 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1 0 1 0 1 0 0 0 0 0 0 0 0 1 0 0 0 1\n",
      "  0 1 0 0 1 0 0 0 1 1 0 1 0 0 0 1 0 0 0 0 0 0 1 0 1 0 1 0 0 1 1 1 0 0 0 0\n",
      "  0 0 0 1 1 1 0 1 1 1 1 0 0 0 1 0 1 0 0 1]]\n",
      "final_activation:  0.45588235294117646================------] 88.9% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.15441176470588236\n",
      "state activation:  0.22058823529411764\n",
      "state activation:  0.2757352941176471\n",
      "state activation:  0.3161764705882353\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.34558823529411764\n",
      "state activation:  0.3786764705882353\n",
      "final graph:  [[0 1 1 1 1 1 1 0 0 1 0 0 1 0 1 1 0 0 1 0 0 1 0 0 1 0 1 0 0 1 1 0 0 0 0 0\n",
      "  0 0 1 1 1 1 0 0 0 1 0 1 1 1 1 1 1 1 0 0 0 0 1 0 1 1 0 0 1 0 1 1 1 1 0 0\n",
      "  1 0 0 0 1 1 0 0 0 0 1 1 1 0 0 0 0 0 0 1 0 0 0 0 0 1 0 1 1 0 0 1 0 0 0 0\n",
      "  0 1 1 0 1 1 0 0 0 0 1 1 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0\n",
      "  0 1 0 0 1 0 1 0 1 0 0 0 0 1 1 1 0 0 0 1 0 1 0 1 0 0 0 1 0 1 0 1 0 0 0 0\n",
      "  0 0 1 1 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 1 1 1 0 1 1 0 0 0 1 0 0 0 0 0 1\n",
      "  1 0 0 1 1 0 0 1 0 1 1 1 1 0 1 1 1 0 0 1 1 0 1 0 0 0 1 1 0 1 1 0 1 1 0 1\n",
      "  0 0 1 0 1 0 1 1 0 1 1 1 0 0 1 0 0 0 0 1]]\n",
      "final_activation:  0.45588235294117646=================-----] 90.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 1 0 1 1 1 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 1 1 1 1 0 0 0 1 1 0 0 0 0 0\n",
      "  0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  1 0 0 0 0 1 1 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0\n",
      "  0 0 0 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 1 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0\n",
      "  0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0\n",
      "  0 0 0 0 1 0 0 0 1 1 0 1 0 0 0 0 0 1 0 0 0 0 1 0 0 0 1 0 0 1 1 1 0 0 0 0\n",
      "  1 0 0 0 1 0 0 0 1 1 0 0 0 0 0 0 0 0 0 1]]\n",
      "final_activation:  0.45588235294117646=================-----] 90.9% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 0 0 1 0 0 0 0 1 0 0 0 1 1 0 0 0 0 0 0 0 0 1 1 0 0 1 1 0 1 0 0 1 1 0\n",
      "  0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0\n",
      "  1 0 0 0 0 1 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0\n",
      "  0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 1 1 0 1 0 0 1 0 1 0 0 1 0 0 0 0 1 0 0 0 0 1 0 1 0 0 1 0 0 0 0 0 1\n",
      "  0 0 0 0 1 0 1 0 1 1 0 0 0 0 0 0 0 0 0 1]]\n",
      "final_activation:  0.45588235294117646=================-----] 91.7% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[1 1 0 0 0 1 1 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0 1 1 1 1 0 0 1 1 1 0 0 0 0 0\n",
      "  0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 0 0 1 1 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0\n",
      "  0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0 0 0 1 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  1 0 0 0 1 0 0 0 0 1 1 1 0 0 1 0 0 1 0 0 1 0 0 0 0 0 1 0 0 1 1 0 0 1 1 1\n",
      "  0 0 0 0 1 0 0 0 0 1 0 1 0 0 1 1 0 1 0 1]]\n",
      "final_activation:  0.45588235294117646==================----] 92.3% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 0 0 0 0 1 0 0 1 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 1 0 1 1 0 0 0 1 1\n",
      "  0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 1 1 0\n",
      "  0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0\n",
      "  0 0 0 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0\n",
      "  1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 1 0 0 0 1 1 0 0 1 0 0 0 0 1\n",
      "  0 0 0 0 1 0 0 0 1 1 1 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 1 0 0\n",
      "  1 0 1 0 1 0 0 0 1 1 1 0 0 0 0 0 0 1 0 1]]\n",
      "final_activation:  0.45588235294117646==================----] 92.9% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.16176470588235295\n",
      "state activation:  0.22426470588235295\n",
      "state activation:  0.27205882352941174\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.31985294117647056\n",
      "state activation:  0.35661764705882354\n",
      "final graph:  [[0 1 0 0 1 1 1 1 1 1 0 0 1 0 1 0 1 0 0 0 0 0 0 1 1 0 1 0 0 0 1 1 0 1 0 0\n",
      "  0 1 0 1 0 0 1 1 1 1 0 0 1 0 0 1 1 1 1 0 0 1 1 1 1 1 0 0 0 1 1 0 1 1 0 0\n",
      "  0 0 1 0 1 1 1 1 0 1 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 1 0 0 0\n",
      "  0 0 0 0 0 0 0 0 1 0 1 0 1 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 0\n",
      "  0 0 1 0 1 1 0 1 0 1 0 1 1 1 0 0 0 1 1 0 1 1 0 0 0 1 1 0 0 1 0 1 0 0 0 0\n",
      "  1 0 1 0 1 1 0 1 0 1 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 1 1 0 0 0 1 1 0 1 1 0 0 0 0 1 0 1 0 0 1 0 0 0 1 0 0 1 1 1 1 1 0 0\n",
      "  0 0 0 1 1 1 0 1 0 1 1 1 1 1 1 1 0 0 1 1]]\n",
      "final_activation:  0.45588235294117646==================----] 93.3% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[1 1 1 0 0 1 0 0 0 1 0 0 0 1 1 0 0 0 0 0 0 0 0 1 1 0 0 0 1 0 1 0 0 1 0 0\n",
      "  0 0 0 0 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0\n",
      "  0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0\n",
      "  0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 1 1 1 0 0 0 1 0 0 0 0 0\n",
      "  1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 1 0 0 0 0 1 0 0 1\n",
      "  0 0 0 0 1 1 1 1 0 1 1 1 0 0 1 0 0 0 0 1 0 0 1 0 1 0 1 0 0 1 0 1 1 0 0 0\n",
      "  1 0 0 0 0 0 0 1 0 1 0 0 0 0 1 0 0 0 1 1]]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "final_activation:  0.45588235294117646==================----] 93.8% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.11397058823529412\n",
      "state activation:  0.14705882352941177\n",
      "state activation:  0.18382352941176472\n",
      "state activation:  0.24632352941176472\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.3088235294117647\n",
      "state activation:  0.3602941176470588\n",
      "final graph:  [[0 1 0 0 0 1 0 0 0 1 0 0 0 0 1 0 0 0 0 1 1 0 1 0 0 0 0 0 1 1 1 0 0 0 0 0\n",
      "  0 0 1 1 1 0 0 1 0 1 0 0 0 1 0 0 0 0 0 1 0 1 0 0 1 0 0 0 1 0 1 0 0 1 0 1\n",
      "  0 0 0 0 0 1 0 0 0 0 0 1 0 0 1 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 1\n",
      "  0 0 0 1 0 0 0 1 0 1 1 0 1 0 0 1 0 0 1 1 0 1 1 0 1 0 0 0 1 0 0 1 1 1 0 1\n",
      "  0 0 0 0 0 0 0 1 0 1 1 0 1 1 1 0 1 0 1 0 1 1 1 0 1 1 1 0 0 0 0 1 0 1 0 0\n",
      "  1 0 0 1 0 1 0 0 1 1 1 1 0 1 1 1 1 0 0 0 1 1 1 0 0 0 1 1 0 1 1 1 1 1 0 0\n",
      "  1 1 1 0 1 0 1 1 0 1 1 1 1 1 1 0 0 0 0 0 0 1 0 1 0 0 1 0 0 1 1 0 0 0 1 0\n",
      "  1 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 1]]\n",
      "final_activation:  0.45588235294117646===================---] 94.1% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 0 0 0 0 1 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 1 0 0 1 1 0\n",
      "  0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0\n",
      "  0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 1 0 0 0 0 1 0 0 0 1 1 0 0 0 0 0 0 0 1\n",
      "  0 0 0 0 1 0 1 1 0 1 1 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 1 1 1 0 1 0 0\n",
      "  1 0 0 0 0 0 0 0 1 1 0 0 0 0 1 1 0 1 1 1]]\n",
      "final_activation:  0.45588235294117646===================---] 94.4% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.14705882352941177\n",
      "state activation:  0.21323529411764705\n",
      "state activation:  0.2867647058823529\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.3382352941176471\n",
      "state activation:  0.4007352941176471\n",
      "final graph:  [[0 1 0 0 0 1 1 0 1 1 1 0 0 0 1 0 0 1 0 1 1 0 1 0 0 1 0 0 1 1 1 0 1 1 1 0\n",
      "  0 0 0 0 0 1 1 1 1 1 0 0 1 0 0 1 0 1 1 0 0 0 0 0 0 1 0 0 0 0 1 0 1 1 1 0\n",
      "  0 1 1 1 0 1 0 1 0 0 0 0 0 0 1 0 0 0 1 0 0 1 0 1 1 0 0 1 0 0 1 0 1 0 0 0\n",
      "  0 0 0 1 1 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 0 0 1 0 1 0 0 0 0 1 0 1 0\n",
      "  1 0 0 0 1 0 1 0 0 0 1 0 1 1 0 1 0 0 1 1 0 0 0 0 1 0 1 1 1 0 1 0 1 0 0 0\n",
      "  0 0 0 1 1 1 1 0 1 0 1 1 1 1 0 1 1 1 1 1 1 0 1 1 1 1 0 1 1 0 1 1 1 1 1 1\n",
      "  1 0 1 1 1 1 1 1 1 1 1 1 1 1 0 1 0 0 0 0 1 1 1 1 0 1 1 0 0 1 0 0 0 0 0 1\n",
      "  0 1 1 1 1 1 1 0 0 1 0 0 0 1 1 0 1 0 0 1]]\n",
      "final_activation:  0.45588235294117646===================---] 94.7% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 1 0 1 0 0 0 0 1 1 0 0 0 1 0 1 0 0 0 0 0 0 1 0 0 0 0 1 0 1 0 0 1 0 1\n",
      "  0 0 1 0 0 1 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 1 1 0 1 0 0 0 0 1 0 0 1 0 0 0 0\n",
      "  0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 1 0 0 0 0 1 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 1 0 1 1 0 1 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 1 1 0 0 0 0 1 0\n",
      "  1 0 1 0 1 0 0 0 1 1 0 0 0 0 0 0 0 1 0 1]]\n",
      "final_activation:  0.45588235294117646===================---] 95.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "seed passed\n",
      "running LT Abs\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.16544117647058823\n",
      "state activation:  0.25735294117647056\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.34191176470588236\n",
      "state activation:  0.47794117647058826\n",
      "final graph:  [[0 1 0 1 1 1 1 0 1 1 1 0 0 1 1 0 0 1 0 0 1 1 1 1 1 1 0 1 1 0 1 1 0 1 1 1\n",
      "  0 0 1 0 1 1 1 1 0 1 1 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 1 1 0 0 1 0 0 1 1 0\n",
      "  1 1 1 0 1 1 0 1 0 1 0 1 0 1 1 1 0 1 1 1 1 1 1 1 0 0 1 0 1 0 0 0 1 1 0 1\n",
      "  1 1 1 1 1 1 0 1 0 1 1 0 0 1 1 1 0 1 0 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1\n",
      "  1 0 1 1 1 0 0 0 0 1 1 0 1 1 1 0 1 1 1 1 0 1 0 1 1 0 1 1 1 0 0 0 0 1 0 0\n",
      "  1 0 0 0 1 1 1 0 1 1 1 1 1 1 1 0 1 1 1 0 1 1 1 0 1 0 1 1 0 1 0 1 1 1 1 1\n",
      "  0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 1 1 0 1 0 1 1 1 1 0 0 1 0 0 1 1 0 1\n",
      "  0 1 0 0 1 0 1 0 1 1 0 1 0 0 0 1 1 1 1 1]]\n",
      "final_activation:  0.45588235294117646===================---] 95.2% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.1213235294117647\n",
      "state activation:  0.15808823529411764\n",
      "state activation:  0.16911764705882354\n",
      "state activation:  0.17279411764705882\n",
      "final graph:  [[0 1 1 0 0 0 1 1 0 1 0 0 1 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0\n",
      "  0 0 0 0 0 0 1 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 1 1 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0\n",
      "  1 0 0 0 1 0 0 1 1 1 0 1 0 0 0 1 0 0 0 0 0 0 1 0 0 0 1 0 0 1 1 0 0 0 0 0\n",
      "  0 0 0 0 1 0 0 0 0 1 0 0 0 0 1 0 0 0 0 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 10.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 0 0 0 0 1 0 1 1 1 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 0 0 0 0 0\n",
      "  0 0 1 0 1 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 1 0 0 1 0 0 0 0 0 0 1 0 1 1 0 0\n",
      "  0 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0\n",
      "  0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0\n",
      "  0 0 0 0 0 0 0 0 0 1 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 1 1 0 0 0 0 1 0 0 1 1 0 0 0 1\n",
      "  0 0 1 0 1 0 0 1 0 1 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 1 0 1 1 0 0 0 1 0 0\n",
      "  1 0 0 0 0 0 0 0 1 1 1 1 0 0 1 0 0 0 0 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 10.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "seed passed\n",
      "running LT Abs\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.16544117647058823\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.29044117647058826\n",
      "state activation:  0.4375\n",
      "final graph:  [[1 1 1 1 1 0 1 0 1 1 1 0 0 1 1 0 1 1 0 0 1 1 1 1 0 1 0 1 1 1 1 1 1 1 1 1\n",
      "  1 1 0 0 1 1 0 1 1 1 1 1 0 0 0 1 0 1 0 1 1 1 0 0 1 1 1 1 1 1 1 0 1 1 1 0\n",
      "  1 1 0 1 1 1 1 1 1 0 0 0 0 0 1 1 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 1 0 1 0 1 1 0 0 0 0 1 1 0 0 0 1 0 1 1 0 0 0 1 0 0 0 0 0 1 0 1\n",
      "  1 0 0 0 0 0 1 1 0 1 1 0 0 1 0 0 1 1 1 0 0 0 1 0 1 1 1 1 1 0 1 1 0 0 0 0\n",
      "  1 1 0 0 1 1 0 0 1 1 0 0 1 0 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 0 1\n",
      "  0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 0 0 0 1 0 1 1 1 1 0 1 1 0 0 1 1 1 0\n",
      "  1 1 1 0 1 1 1 1 1 1 0 1 1 0 1 1 1 1 1 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 10.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[1 1 0 0 0 1 1 0 0 1 1 0 0 0 1 0 0 0 0 0 0 0 1 1 0 0 0 1 0 0 1 0 0 0 1 1\n",
      "  0 0 0 0 1 1 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 1 0 0 0 1 1 0 0 0 1 1 0 0 0 0\n",
      "  0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 1 0 1 0 0 0 0 1 0 0 0 1 1 0 0 0 0 1 0 0 0\n",
      "  1 0 0 0 1 1 0 0 0 1 0 1 1 0 0 0 0 1 0 0 0 0 0 0 1 0 1 0 0 1 1 1 0 0 0 0\n",
      "  1 0 1 0 0 0 0 0 1 1 0 1 0 0 0 0 0 1 0 1]]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "final_activation:  0.45588235294117646----------------------] 10.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 0 0 0 1 1 0 0 1 0 0 0 1 1 0 0 0 0 0 0 0 1 0 1 0 0 0 0 1 1 0 0 1 0 0\n",
      "  0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 0 0 1 1 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 1 0 0\n",
      "  0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 1 0 0 1 0 0 1 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0\n",
      "  1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 1 1 0 0 0\n",
      "  0 0 0 1 1 0 0 0 0 1 0 1 1 1 0 0 0 1 0 1 1 0 0 0 0 0 1 0 0 1 1 1 1 1 0 0\n",
      "  0 0 1 0 1 0 0 1 0 1 0 0 0 0 1 0 0 0 0 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 10.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.15073529411764705\n",
      "state activation:  0.20955882352941177\n",
      "state activation:  0.2426470588235294\n",
      "state activation:  0.2757352941176471\n",
      "state activation:  0.3014705882352941\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.3272058823529412\n",
      "state activation:  0.35661764705882354\n",
      "final graph:  [[0 1 1 0 1 1 1 0 1 1 0 0 0 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 1 1 0 1 0 1 0 0 0 0 1 0 0 1 0 1 0 0 1 0 0\n",
      "  1 0 1 1 0 1 0 0 0 1 0 0 0 0 0 1 1 0 1 0 1 1 1 1 1 1 1 0 1 0 1 1 1 0 0 0\n",
      "  1 1 0 0 1 1 1 1 0 0 1 0 0 1 0 1 0 1 0 1 1 1 1 1 0 1 1 1 0 0 0 0 0 0 1 1\n",
      "  0 1 0 1 0 0 0 0 0 1 0 0 1 1 1 1 1 0 0 1 0 0 0 1 0 0 0 1 1 1 0 0 1 0 0 0\n",
      "  0 0 0 0 0 0 1 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 1 0 0 0 1 0 0 0 1 0 0 0 0 0\n",
      "  0 1 0 0 1 0 1 0 0 1 0 1 1 0 1 0 1 1 0 0 0 0 1 0 0 1 1 0 0 1 1 0 1 0 0 0\n",
      "  1 0 0 0 1 0 0 1 0 1 1 0 1 1 0 1 0 0 1 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 10.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 0 0 0 1 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 1 1 0 0 1 0 1 1 1 0 0 0 1\n",
      "  0 0 1 0 1 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 1 1 0 0\n",
      "  0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 1 1 0 0 0 0 0 0 1 0 0 0 0 1\n",
      "  0 1 0 0 1 0 0 0 0 1 0 1 0 0 1 0 0 0 0 0 0 0 1 0 0 0 1 0 1 1 0 0 0 0 0 0\n",
      "  1 0 0 0 0 0 0 1 1 1 0 0 0 0 1 0 0 0 0 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 10.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 1 0 0 0 1 0 1 1 1 0 0 0 1 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 0 0 1 0 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 1 1 1 0\n",
      "  0 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 1 0 0 0 0 0 1 0\n",
      "  0 0 0 0 0 0 0 1 0 0 0 0 1 1 1 0 0 0 0 1 0 1 0 0 1 0 1 0 0 0 0 1 0 1 0 0\n",
      "  1 0 0 0 0 0 0 0 0 1 0 0 0 1 0 1 0 1 0 0 0 0 1 1 0 0 0 1 0 1 1 0 0 0 0 1\n",
      "  0 0 0 1 1 0 1 1 0 1 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 0 1 0\n",
      "  0 0 1 0 1 0 0 1 1 1 0 1 0 0 0 0 0 1 1 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 10.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 0 0 0 0 0 1 1 1 0 0 0 0 1 0 1 0 0 0 0 0 1 1 1 1 0 0 0 0 1 0 0 0 1 0\n",
      "  0 0 0 0 0 1 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  1 0 0 1 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 1 0 0 1 0 0 1 0 0 0 0 0 1 0\n",
      "  0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 1 0 0 0 1 0 0 0 0\n",
      "  0 0 1 1 1 0 0 0 1 1 0 1 1 1 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 1 1 0 1 0 0 0\n",
      "  1 0 0 0 0 0 1 0 0 1 1 1 0 0 0 1 0 1 0 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 10.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "seed passed\n",
      "running LT Abs\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.13602941176470587\n",
      "state activation:  0.23161764705882354\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.3272058823529412\n",
      "state activation:  0.4411764705882353\n",
      "final graph:  [[0 1 0 0 0 0 1 0 1 1 1 1 0 1 1 1 1 1 0 0 0 0 0 1 1 1 0 1 1 1 1 0 0 1 1 1\n",
      "  1 0 1 0 0 1 1 0 0 1 0 0 0 0 0 0 0 1 0 1 0 1 0 1 1 1 1 1 0 1 1 0 0 1 1 0\n",
      "  1 1 0 1 1 1 1 1 0 1 1 1 0 0 1 1 0 1 0 1 0 0 0 1 0 0 0 0 1 0 0 0 0 1 0 0\n",
      "  1 1 1 1 0 1 0 1 0 1 1 0 0 0 1 1 1 0 1 1 0 1 1 1 1 0 1 1 1 0 0 1 0 1 0 0\n",
      "  1 0 1 1 1 0 1 0 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 0 1 1 1 1 1 0 0 1 0 0\n",
      "  1 0 0 0 1 1 1 0 1 1 0 1 1 0 1 0 0 1 0 0 1 1 1 0 0 0 1 1 0 1 1 1 0 1 0 1\n",
      "  0 0 0 0 1 1 1 1 0 1 1 1 1 1 1 0 1 1 0 0 1 1 0 0 1 1 1 0 0 1 1 0 1 0 1 1\n",
      "  0 0 1 1 0 1 0 0 0 1 0 0 0 1 1 0 1 1 0 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 10.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "seed passed\n",
      "running LT Abs\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.14338235294117646\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.24632352941176472\n",
      "state activation:  0.375\n",
      "final graph:  [[0 1 0 0 1 0 0 1 1 1 1 1 0 1 1 0 0 0 0 0 0 1 0 1 0 1 0 0 0 1 1 1 1 1 0 1\n",
      "  0 0 0 0 0 1 0 1 1 1 1 0 0 0 0 1 1 1 0 1 1 1 0 0 1 1 1 1 1 1 1 0 1 1 1 0\n",
      "  0 1 0 1 1 1 1 1 1 0 0 1 1 1 1 1 0 0 0 0 1 0 1 1 0 0 0 0 0 0 0 1 0 1 0 0\n",
      "  0 1 0 1 0 1 0 0 0 0 1 0 0 1 0 1 1 0 1 1 1 1 1 1 0 0 1 1 1 0 0 1 0 1 1 1\n",
      "  1 0 0 1 1 0 0 0 0 1 1 0 1 1 0 0 0 0 1 0 0 0 0 0 1 0 1 0 1 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 1 0 1 0 0 1 0 0 0 1 1 1 1 0 0 0 1 1 1 0 1 1 1 0 0 0 1 1 0 0\n",
      "  0 1 1 0 1 1 1 1 1 1 0 1 1 1 0 0 1 0 0 1 0 0 1 0 1 1 1 0 0 1 1 1 1 1 1 1\n",
      "  0 0 0 1 1 1 0 0 1 1 1 0 1 0 1 0 1 1 1 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 10.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.16176470588235295\n",
      "state activation:  0.25\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.34558823529411764\n",
      "state activation:  0.4227941176470588\n",
      "final graph:  [[1 1 1 0 0 1 1 1 1 1 1 0 1 0 1 0 0 0 0 1 1 0 0 1 1 1 0 0 0 1 1 1 0 1 0 0\n",
      "  0 1 1 0 0 0 0 1 0 1 0 0 1 0 0 1 0 0 0 0 1 0 1 0 0 0 0 0 1 0 1 1 0 1 1 0\n",
      "  0 0 0 1 1 1 1 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 1 1 0 0 0 0 1 0 0 0 0 1 0 0\n",
      "  0 0 1 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 1 1 0\n",
      "  0 1 0 1 1 0 1 1 0 1 0 0 0 1 1 1 1 0 1 1 1 0 1 0 1 1 1 0 1 1 0 1 1 0 0 0\n",
      "  0 1 0 1 0 0 1 0 0 0 0 0 0 1 0 0 0 1 0 0 0 1 1 0 1 1 1 1 0 1 1 1 1 1 1 1\n",
      "  1 1 1 1 1 1 0 0 0 1 1 1 1 1 0 1 0 1 0 1 1 0 1 1 1 0 1 1 1 1 1 0 1 0 1 1\n",
      "  1 1 1 0 0 1 1 1 1 1 1 1 1 1 1 1 0 0 1 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 10.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 1 0 1 0 0 1 0 1 1 0 0 1 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 1 0 0 0 1 0\n",
      "  0 0 1 0 0 1 1 0 0 1 0 0 0 0 0 0 0 0 1 0 1 0 1 0 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  1 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 1 0 0 0\n",
      "  0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 1\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 0 0 0 0 0 1 1 1 0 0 1 1 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 1 0 0 0 1 1 0 1 0 0 0 0 1 1 1 0 0 1 0 0 0 0 0 1 0 0 1\n",
      "  1 0 0 1 1 0 0 0 0 1 0 1 1 0 0 0 0 1 0 0 0 0 1 0 0 0 1 0 0 1 1 0 0 1 1 0\n",
      "  1 0 1 0 1 0 0 0 1 1 0 0 0 0 0 0 0 0 1 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 10.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.1323529411764706\n",
      "state activation:  0.1948529411764706\n",
      "state activation:  0.2536764705882353\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.30514705882352944\n",
      "state activation:  0.375\n",
      "final graph:  [[0 1 1 0 0 1 0 1 1 1 0 0 1 0 1 1 1 0 0 0 1 0 1 1 1 1 0 1 0 0 1 0 1 1 0 0\n",
      "  0 0 0 0 0 1 0 0 1 1 1 1 1 1 0 1 0 0 1 0 1 1 1 1 0 0 1 0 1 0 1 0 0 1 1 1\n",
      "  0 1 0 0 1 1 1 1 0 0 0 0 0 1 1 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0\n",
      "  1 0 0 1 0 1 1 0 0 0 1 0 0 0 1 1 0 0 0 0 0 0 1 0 1 0 0 0 0 0 1 0 0 0 0 0\n",
      "  0 1 1 0 0 0 1 0 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0\n",
      "  1 0 0 1 1 0 1 0 0 1 1 1 1 1 0 0 1 0 1 0 0 0 1 0 1 1 0 0 0 0 1 1 0 0 0 0\n",
      "  0 0 1 0 1 1 0 1 1 1 0 1 0 1 0 1 1 0 1 0 0 0 1 0 0 0 1 1 1 1 1 0 1 1 1 0\n",
      "  0 1 1 1 0 0 1 0 0 1 0 1 1 0 1 1 1 1 1 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 10.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 1 0 1 1 0 1 0 1 0 0 0 0 1 0 0 0 0 0 0 0 1 1 0 0 0 1 0 0 1 0 0 1 0 0\n",
      "  0 0 1 0 1 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 1 0 1 1 1 0\n",
      "  0 0 0 0 0 1 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0\n",
      "  0 1 0 0 0 0 1 0 0 0 1 0 0 1 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 1\n",
      "  0 1 0 1 1 0 0 0 0 1 1 1 0 0 0 0 0 1 0 1 0 0 0 1 0 0 1 0 1 1 1 0 0 0 0 0\n",
      "  0 0 1 0 1 0 1 1 1 1 0 0 0 0 0 1 0 0 0 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 10.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 1 0 1 0 1 0 0 1 0 0 0 1 1 0 0 0 0 0 0 0 0 1 1 0 0 1 0 0 1 0 0 1 0 0\n",
      "  0 0 1 0 1 1 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 1 0 0\n",
      "  0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0\n",
      "  0 0 0 0 0 0 0 0 0 1 0 0 1 1 1 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1\n",
      "  0 1 0 1 1 0 0 0 1 1 0 1 0 0 0 0 0 1 0 0 0 1 0 0 0 0 1 0 1 1 1 1 0 0 0 0\n",
      "  1 0 1 0 1 0 0 0 0 1 0 0 0 0 1 0 0 0 0 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 10.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.13970588235294118\n",
      "state activation:  0.16911764705882354\n",
      "state activation:  0.19852941176470587\n",
      "state activation:  0.22058823529411764\n",
      "state activation:  0.23529411764705882\n",
      "state activation:  0.27205882352941174\n",
      "state activation:  0.3235294117647059\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.34558823529411764\n",
      "state activation:  0.3639705882352941\n",
      "final graph:  [[1 1 1 1 1 1 0 0 1 1 1 1 1 0 1 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 1 1 0 1 1 0 0 1 0 1 0 0 0 0 0 1 1 0 0 1 1 0 0 0 1 0 0 0 1 0 0 1 0 0\n",
      "  0 0 1 0 0 1 0 1 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 1\n",
      "  0 0 0 1 1 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 1 0 0 0 0 0 0\n",
      "  1 0 0 0 1 0 0 0 0 0 1 0 1 1 0 1 0 1 0 0 0 0 0 0 0 1 0 1 1 0 0 1 1 1 0 0\n",
      "  1 0 0 0 1 1 0 0 1 0 0 0 0 0 1 0 0 1 0 1 1 0 1 1 0 0 0 0 1 1 0 0 0 1 0 0\n",
      "  0 1 0 0 1 0 1 0 1 1 0 1 0 0 0 0 0 0 1 0 0 1 0 1 0 0 1 0 1 1 0 1 0 1 1 1\n",
      "  0 1 0 1 0 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 10.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[1 1 1 0 0 0 1 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 1 1 0 0 1 0 1 1 0 0 0 1 0\n",
      "  0 0 1 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 1 0 1 1 0 0\n",
      "  0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 1 0 1 0 0\n",
      "  1 0 0 1 0 0 1 0 0 1 0 0 0 0 0 0 1 0 0 0 0 1 1 0 0 0 0 0 0 0 0 1 0 0 0 0\n",
      "  0 0 1 0 1 0 1 0 1 1 0 1 0 0 1 0 0 1 0 1 0 1 0 0 1 0 1 0 0 1 1 0 0 1 0 1\n",
      "  1 0 1 0 0 0 0 0 0 1 0 0 0 0 1 1 0 0 0 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 10.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 0 0 0 0 0 1 1 1 0 0 0 0 1 1 1 0 1 0 0\n",
      "  0 0 0 0 0 1 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0\n",
      "  0 0 0 0 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 1 1 0 0 0 0 0 1 1 1 0 0 1 0 0 0 0\n",
      "  0 1 0 1 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1 1 0 0 0 0 0 0 1 1 0 1 0 0 1\n",
      "  0 0 1 1 1 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 1 0 1 0 1 0 1 0 1 1 1 0 1 1 0 0\n",
      "  0 0 0 0 1 0 1 0 0 1 0 1 0 0 1 0 0 1 1 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 10.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.16176470588235295\n",
      "state activation:  0.1948529411764706\n",
      "state activation:  0.21323529411764705\n",
      "state activation:  0.22426470588235295\n",
      "state activation:  0.23897058823529413\n",
      "state activation:  0.2536764705882353\n",
      "state activation:  0.2610294117647059\n",
      "final graph:  [[0 1 1 0 0 1 1 1 0 1 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 1 0 0 1 0 0\n",
      "  0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 1 0 1 1 0 0 0 1 1 1 1 0 0 0 0 0 0 1 0 0 1 0 0 1 0 0 1 0 0 0 0\n",
      "  0 0 0 1 1 0 0 0 0 0 1 0 1 1 0 0 0 1 0 0 0 1 1 0 0 1 0 1 0 1 1 0 1 0 0 0\n",
      "  1 1 1 1 1 0 0 0 1 1 1 1 0 0 1 1 0 1 0 0 1 1 1 0 0 0 1 0 0 1 1 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 1 1 1 1 0 0 0 1 0 0 0 1 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 10.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[1 1 0 0 0 1 0 0 1 1 0 0 0 1 1 0 1 0 0 0 0 0 1 0 0 1 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  1 0 0 0 0 1 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 1 0 0 1 1 0 1 1 0 0 0 0 0 0 0\n",
      "  0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 1 0 1 0 0 0 0\n",
      "  0 0 1 0 1 0 0 0 0 1 1 1 0 1 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 1 1 1 0 0 0 0\n",
      "  0 0 1 0 1 0 0 0 0 1 0 1 0 0 0 0 0 0 1 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 10.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "seed passed\n",
      "running LT Abs\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.13602941176470587\n",
      "state activation:  0.21691176470588236\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.3125\n",
      "state activation:  0.4007352941176471\n",
      "final graph:  [[1 1 0 0 1 0 1 0 1 1 0 0 0 1 1 1 0 1 0 0 1 0 1 1 0 1 0 1 1 1 1 1 1 1 1 1\n",
      "  1 0 1 1 1 1 1 1 1 1 1 1 0 0 0 1 0 1 1 0 1 1 0 0 0 1 1 1 1 1 1 0 1 1 1 0\n",
      "  1 1 0 0 1 1 0 1 0 1 0 1 0 0 1 1 0 0 0 0 0 0 1 1 0 0 0 1 1 0 1 0 0 0 0 1\n",
      "  1 1 0 1 0 0 0 1 1 0 1 0 1 0 1 1 1 0 0 0 0 1 1 1 1 0 0 1 0 0 0 0 1 1 0 0\n",
      "  1 0 0 0 0 0 0 0 0 1 0 0 1 1 1 0 0 0 0 0 0 0 1 1 0 1 0 0 0 0 0 1 1 0 1 1\n",
      "  1 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 1 0 0 0 1 1 1 0 0 1 1 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 1 0 1 0 0 1 0 1 0 1 1 0 0 1 0 0 0 1 0 1 1 1 1 0 1 1 0 0 0 1 1 0\n",
      "  1 1 1 0 1 1 1 1 1 1 0 1 1 0 0 1 1 1 1 1]]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "final_activation:  0.45588235294117646----------------------] 10.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "seed passed\n",
      "running LT Abs\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.16176470588235295\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.2757352941176471\n",
      "state activation:  0.3860294117647059\n",
      "final graph:  [[0 1 1 0 1 0 0 0 1 1 1 0 0 1 1 0 1 1 0 0 0 1 0 1 1 1 1 1 1 0 1 1 0 1 1 1\n",
      "  1 0 1 0 0 1 1 0 1 1 1 0 0 0 0 1 0 1 0 1 0 1 1 1 0 1 1 1 0 1 1 0 1 1 1 0\n",
      "  0 1 0 0 1 1 0 1 1 1 1 1 0 0 1 1 0 0 0 1 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0\n",
      "  1 1 0 0 0 1 0 0 0 0 1 1 0 0 1 1 0 1 1 1 1 1 1 1 0 1 0 1 1 0 0 0 0 1 1 0\n",
      "  1 0 0 1 1 0 0 0 0 1 1 0 0 1 1 0 1 0 1 1 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 1 0 0 1 1 1 1 0 1 1 1 1 0 0 0 1 1 0 1 0 1 1 0 0 1 0 0 1 0 1\n",
      "  1 0 1 1 1 1 1 1 0 1 1 1 1 1 1 0 0 1 1 0 1 1 1 1 1 1 1 0 1 1 1 0 1 1 1 0\n",
      "  1 0 1 1 1 1 1 1 1 1 0 1 0 1 1 1 1 1 1 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 10.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 1 0 0 0 0 0 0 1 1 0 0 0 1 0 0 0 0 0 0 0 1 1 0 0 0 1 1 0 1 0 0 1 1 1\n",
      "  0 0 0 0 1 0 1 0 0 1 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 0 0 0 1 1 1 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 1 0 0 0 1 1 0 0 0 0 1 0 1 0 0 1 1 0 1 1 0 0 1 0 1 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 0 1 0 0 0 0 0 0\n",
      "  1 0 0 0 1 0 0 0 1 1 1 1 1 0 1 0 0 1 0 0 0 0 0 0 1 0 1 0 0 1 1 0 0 0 0 0\n",
      "  0 0 1 0 0 0 0 1 1 1 0 1 0 0 0 1 0 0 0 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 10.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 1 0 1 1 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 1 1 0 0\n",
      "  0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 1 1 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 1 0 0 1 0 0 0\n",
      "  1 0 0 1 1 0 1 1 1 1 1 1 1 1 0 0 0 1 0 0 0 1 1 0 0 0 1 0 0 1 1 0 0 0 0 1\n",
      "  0 0 0 0 0 0 1 1 1 1 0 1 0 0 1 1 0 0 0 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 10.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.125\n",
      "state activation:  0.16544117647058823\n",
      "state activation:  0.22426470588235295\n",
      "state activation:  0.29044117647058826\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.35294117647058826\n",
      "state activation:  0.40441176470588236\n",
      "final graph:  [[0 1 0 1 0 1 0 1 1 1 1 0 1 0 1 1 1 1 0 0 0 0 1 0 1 1 0 1 0 1 1 0 1 0 1 1\n",
      "  0 0 1 0 0 1 1 1 0 1 0 0 1 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 1 1 0 0 0 0 0 0 1 0 0 0 0 0\n",
      "  0 0 0 1 1 0 1 1 0 1 1 1 1 1 0 1 0 1 0 1 1 1 1 0 1 1 1 1 1 0 1 1 0 1 1 0\n",
      "  1 1 0 1 1 0 1 0 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 0 1 1 0 1 0 1 0 1 1 0 1 1\n",
      "  1 0 1 1 1 0 1 0 1 1 1 1 1 1 1 1 1 0 1 1 0 0 0 1 0 0 1 0 0 1 1 0 0 1 1 1\n",
      "  1 0 0 0 1 1 1 0 0 1 1 1 1 1 0 1 0 1 1 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 10.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 0 0 0 1 0 1 1 1 0 0 0 1 1 0 0 0 0 0 0 0 1 1 1 1 0 0 0 0 1 0 0 0 1 0\n",
      "  0 0 0 0 1 1 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 1 0 1 1 0 0\n",
      "  0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0\n",
      "  0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 1 0 0 1 0 0 1 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 1 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 1 1 0 0 0 0 1 0 1 1 0 0 0 0 1\n",
      "  0 0 0 0 1 0 1 0 0 1 0 1 0 0 0 0 0 0 0 1 1 0 0 0 0 0 1 0 1 1 1 0 1 0 0 0\n",
      "  0 0 1 0 1 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 10.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 0 0 0 0 0 1 0 1 0 0 0 1 1 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1 1 1 0 1 1 1\n",
      "  0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 0 0 0 1 1 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 1 0 1 0 0 0 1 0 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 0 1 0 1 0 0\n",
      "  0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 1 0 1 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0\n",
      "  1 1 1 1 1 1 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1 0\n",
      "  1 0 1 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 1 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 10.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.15073529411764705\n",
      "state activation:  0.20955882352941177\n",
      "state activation:  0.24632352941176472\n",
      "state activation:  0.27205882352941174\n",
      "state activation:  0.3014705882352941\n",
      "state activation:  0.33455882352941174\n",
      "state activation:  0.34191176470588236\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.35294117647058826\n",
      "state activation:  0.36764705882352944\n",
      "final graph:  [[0 1 1 0 0 0 1 0 1 1 0 0 1 1 1 1 0 1 0 0 0 0 0 1 1 1 0 1 0 1 1 0 0 1 0 1\n",
      "  1 0 0 1 0 0 1 0 0 1 0 1 1 1 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0\n",
      "  1 1 1 0 1 1 1 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1 1 1 0 0 0 0 0 0 1 1 1 0 1 1\n",
      "  0 1 0 0 0 0 0 0 1 0 1 0 1 1 1 0 1 0 0 0 0 1 1 0 0 0 0 1 1 0 1 0 0 1 1 1\n",
      "  0 0 0 1 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1\n",
      "  0 1 0 1 0 0 0 0 0 1 1 0 0 1 0 0 1 0 1 0 0 0 1 1 0 1 0 0 0 0 0 0 0 0 1 0\n",
      "  1 0 0 0 1 0 0 0 0 1 0 1 1 0 0 0 0 1 1 0 1 0 1 0 1 0 1 0 1 1 1 0 0 0 0 1\n",
      "  0 0 1 0 1 0 0 1 1 1 1 0 0 1 0 1 0 1 1 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 10.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[1 1 0 0 0 1 1 0 1 1 1 0 0 0 1 0 1 0 0 0 0 0 0 0 1 0 0 1 1 0 1 0 0 1 1 0\n",
      "  0 0 0 0 0 1 1 0 0 1 0 0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 0 0 1 0 1 1 1 0\n",
      "  0 0 0 1 0 1 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 1 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0\n",
      "  0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 1 1 1 0 0 0 0 1 0 0 0 0\n",
      "  0 1 0 0 0 0 1 0 0 0 0 0 0 0 1 1 0 0 0 0 0 1 1 1 0 0 1 0 0 0 0 0 0 0 0 1\n",
      "  0 1 0 0 1 0 1 1 1 1 0 1 0 0 0 0 0 1 0 1 0 0 0 0 0 0 1 0 0 1 1 1 0 0 0 0\n",
      "  0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 1 0 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 10.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 1 0 0 1 1 0 0 1 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0\n",
      "  0 0 0 0 1 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0\n",
      "  0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 1 0 0 1 0 0 1 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 1 0 0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 0\n",
      "  0 0 0 0 1 0 1 0 0 1 1 1 1 0 0 0 0 0 0 1 1 0 1 0 0 0 1 0 0 1 0 0 0 1 0 0\n",
      "  1 0 1 0 1 0 1 0 1 1 0 1 0 0 1 0 0 1 0 1]]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "final_activation:  0.45588235294117646----------------------] 10.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 0 0 0 1 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 1 0 1 0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0 1 0 0 0 0 0 0 0 1 0 1 1 0 0\n",
      "  0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 1 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 1 1 0 0 0 0 1 0 1 0 0 0 0 0 1 0 0 1 1 0 0 0 0 1 0 1 1 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 1 0 0 1 0 1 0 0 0 0 0 0 0 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 10.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[1 1 0 0 0 0 1 0 0 1 1 0 0 0 1 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 1 0 0 1 0 1\n",
      "  0 0 0 0 0 1 0 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 1\n",
      "  0 0 0 0 0 0 0 1 0 1 0 0 0 1 1 0 0 0 0 0 0 0 0 1 0 1 0 1 0 0 1 1 0 0 0 0\n",
      "  1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 1 1 0 0 0 0 0 0 0 1 0 0 0 0\n",
      "  0 0 0 0 1 1 0 0 0 1 0 1 0 0 0 0 0 0 0 1 1 0 0 0 1 0 1 0 0 1 0 0 0 0 0 0\n",
      "  1 0 0 0 0 0 0 1 0 1 0 1 0 0 0 0 0 0 0 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 10.0% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[1 1 1 0 0 0 0 1 0 1 0 0 0 0 1 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 1 0 1 1 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 1 1 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0\n",
      "  0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 1 0 0 0 0 1 1 0 1 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 1 1 1 0 0 0 1 0 0 0 0 1 0 0 0 0\n",
      "  1 0 0 1 1 0 0 1 0 1 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 1 0 0\n",
      "  0 0 0 0 1 0 0 1 1 1 1 1 0 0 0 0 0 1 0 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 19.9% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 0 0 0 1 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 1 0 0 0 1 0\n",
      "  0 0 0 0 0 1 0 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0\n",
      "  0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0\n",
      "  0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 1 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0\n",
      "  1 1 0 1 0 0 1 0 0 0 0 0 0 0 1 0 1 0 0 0 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 1\n",
      "  0 0 0 1 1 0 0 1 1 1 1 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 1 1 0\n",
      "  0 0 0 0 0 0 0 0 0 1 0 1 0 0 1 0 0 0 1 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 19.9% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 0 0 1 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 1 1 0 0 0 0\n",
      "  0 0 1 0 0 1 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0\n",
      "  0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 1 0 1 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1\n",
      "  0 0 0 1 1 0 1 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 0 0 1\n",
      "  1 0 0 0 1 0 1 1 1 1 0 1 0 0 0 1 0 0 1 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 19.9% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 0 0 0 0 0 0 0 1 0 0 0 1 1 0 0 0 0 0 0 0 1 1 0 0 0 0 1 0 1 0 0 1 1 0\n",
      "  0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 1 0 0 1 0 0 0 0 1 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 0 0 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 1 0 1 0 0 0 1 1 0 0 0 0 1 1 1 0 0 0 1 0 0 0 0 0 1 0 1 0 0\n",
      "  0 1 0 0 0 0 0 0 0 1 1 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 1\n",
      "  0 1 1 1 1 0 1 1 0 1 1 1 0 0 0 0 0 1 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0 0 1 0\n",
      "  0 0 1 0 0 0 1 1 0 1 0 0 0 0 0 0 0 0 1 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 29.8% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.12867647058823528\n",
      "state activation:  0.17647058823529413\n",
      "state activation:  0.24632352941176472\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.3088235294117647\n",
      "state activation:  0.3713235294117647\n",
      "final graph:  [[0 1 1 1 0 0 1 0 0 1 1 1 0 1 1 1 1 1 0 1 1 1 1 1 1 1 0 0 1 1 1 1 0 1 1 0\n",
      "  1 1 1 1 1 0 1 1 1 1 1 0 1 1 0 0 0 0 0 1 1 0 0 1 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 0 0 0 1 0 0 0 1 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0\n",
      "  0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 1 1 0 0 1 0 1 0 1 1 1 0 1 0 0 1 1 1 1 0 1\n",
      "  0 0 0 0 1 0 1 1 0 0 0 0 1 0 0 0 1 0 0 0 1 1 1 1 1 1 1 0 0 0 1 1 0 1 1 1\n",
      "  0 0 0 1 1 1 1 0 1 1 0 1 0 1 1 0 1 1 1 0 0 0 1 0 0 0 1 0 0 1 1 0 1 1 1 1\n",
      "  0 0 0 1 0 1 1 1 0 1 1 1 0 1 1 0 0 1 0 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 29.9% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 0 0 0 1 1 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 1 0 0 0 1 0\n",
      "  0 0 1 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 1 0 1 1 0 0\n",
      "  1 0 0 0 0 1 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 1 1 1 1 1 0 0 1 0 0 0 0 0\n",
      "  0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 0 0 0 1 0 0 0 0 1 0 0 1\n",
      "  0 0 1 1 1 0 0 1 0 1 0 1 1 0 1 0 0 1 0 0 1 0 0 0 1 0 1 0 1 1 0 0 1 1 1 1\n",
      "  1 0 0 0 1 0 1 0 1 1 0 0 0 0 1 1 0 1 0 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 39.9% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 0 0 1 1 1 0 0 1 0 0 0 1 1 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 1 0 0 1 1 0\n",
      "  0 0 0 0 1 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 0 1 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 1 0 0\n",
      "  0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 1 1 0 0 0 0 1 0 0 0 0 1 1 0 0 0 0\n",
      "  0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 1 0 0 0\n",
      "  0 0 0 1 1 1 0 1 0 1 0 1 1 0 0 0 0 1 0 1 0 1 1 0 1 0 1 0 0 1 1 0 0 0 0 0\n",
      "  0 0 1 0 0 0 0 1 1 1 0 0 0 0 1 0 0 1 0 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 39.7% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 0 0 1 0 1 1 0 1 1 0 0 1 1 0 0 0 0 0 0 0 1 1 0 1 0 0 0 0 1 0 0 1 1 1\n",
      "  0 0 1 0 1 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 1 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1\n",
      "  0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 1 0 0 0 1 0 0 0 1 0 1 0 0 0\n",
      "  0 0 0 0 1 0 0 1 1 1 1 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 0 1 0\n",
      "  0 0 0 0 0 0 1 0 1 1 0 0 0 0 0 0 0 1 1 1]]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "final_activation:  0.45588235294117646----------------------] 39.9% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 0 0 0 1 1 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 1 1 1 0 1 0 0 1 0 0 1 0 0\n",
      "  0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 1 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 0 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 1 0 0 0 0\n",
      "  0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 1 1 0 0 0 0 1 0 0 0 1 1 0 0 0 0 0 0 0 1\n",
      "  0 0 0 0 1 0 0 0 0 1 0 1 0 1 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 1 1 0 0 0 0\n",
      "  1 0 1 0 1 0 1 0 1 1 0 0 0 0 1 0 0 1 0 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 39.7% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 1 0 1 0 1 1 0 1 0 0 0 1 1 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 0 0 1 0 1\n",
      "  0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0\n",
      "  1 0 1 1 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 1 1 0 0 0 0\n",
      "  1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 1 1 0 0 0 1 1 1 0 0 0 0 1 0 0 1 0 0 0 0 0\n",
      "  1 0 0 0 1 0 0 0 1 1 1 1 1 0 0 0 0 1 0 0 0 1 0 0 0 0 1 0 0 1 1 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 1 1 0 1 0 0 0 0 0 1 0 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 39.9% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 0 0 1 0 0 1 0 1 0 0 0 0 1 0 1 0 0 0 0 0 0 1 1 0 0 0 0 0 1 0 0 0 1 1\n",
      "  0 0 1 0 1 1 1 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 1 1 1 0\n",
      "  0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0\n",
      "  0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 1 0 0 0 0 0\n",
      "  0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 1 0 0 0 1 0 0 0 0 1 0 0 0\n",
      "  0 0 0 0 1 0 0 1 1 1 1 1 0 0 0 0 0 1 0 1 0 0 0 0 0 0 1 0 0 1 1 0 1 0 1 0\n",
      "  0 0 0 0 0 0 0 0 0 1 0 1 0 0 1 0 0 1 0 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 49.6% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.14705882352941177\n",
      "state activation:  0.1801470588235294\n",
      "state activation:  0.21323529411764705\n",
      "state activation:  0.26838235294117646\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.33088235294117646\n",
      "state activation:  0.3860294117647059\n",
      "final graph:  [[0 1 1 0 0 1 1 1 0 1 0 1 1 1 1 1 0 1 0 1 1 1 0 1 1 1 0 0 0 1 1 0 0 0 1 1\n",
      "  1 1 1 1 1 0 1 0 1 1 1 1 1 1 0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 0 1 0 1 1 0 0\n",
      "  0 0 1 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 1 0 1 0 0 0 0 1 1 1 0 1 0\n",
      "  1 0 0 0 1 1 0 0 0 1 1 0 1 1 1 0 0 1 1 1 1 1 1 0 1 0 1 1 1 1 1 0 0 0 0 1\n",
      "  1 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 1 0 0 0 0 0 1 0 0 0 0 1 0 0 0 1 1\n",
      "  0 1 1 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 1 0 0 1 1 0 0 0 0 1 1 0 0 0 1 0 1\n",
      "  0 1 0 0 1 0 0 0 0 1 0 1 0 0 0 0 0 1 0 0 0 0 0 1 1 0 1 0 0 1 1 1 0 0 1 1\n",
      "  0 1 1 0 0 0 0 0 1 1 1 1 0 0 0 0 0 1 1 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 49.6% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.12867647058823528\n",
      "state activation:  0.1875\n",
      "state activation:  0.2426470588235294\n",
      "state activation:  0.28308823529411764\n",
      "state activation:  0.3161764705882353\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.34191176470588236\n",
      "state activation:  0.35661764705882354\n",
      "final graph:  [[0 1 1 0 0 0 1 1 0 1 0 1 1 1 1 1 0 1 0 1 0 0 0 1 1 0 0 0 1 1 1 1 1 1 1 1\n",
      "  1 1 0 1 1 1 1 0 1 1 1 1 1 0 0 1 1 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0\n",
      "  1 0 0 0 1 1 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 1 0 1 0 0 0 1 0 0 0 0 0 0 0 1 0 0 1 1 0 0 0 0 0 0 0 1 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 1 1 1 0 0 1 0 1 1 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0\n",
      "  0 0 0 0 0 0 1 0 1 1 0 0 0 0 0 0 1 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 1\n",
      "  0 0 0 1 1 0 0 1 1 1 0 1 0 0 0 0 1 1 0 0 0 0 1 1 0 0 1 0 1 1 0 1 0 1 0 1\n",
      "  0 0 1 0 0 1 1 1 1 1 0 1 0 1 0 1 1 1 0 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 49.6% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 1 0 0 1 1 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 1 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 1 0 1 1 0 0\n",
      "  1 0 1 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 1 1 0 0 0 0 0 0 0 0 1 1 0 0 0\n",
      "  0 1 0 0 1 0 0 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 1 1 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 1 0 1 1 1 0 0 0 1 0 0 0 1]]\n",
      "final_activation:  0.45588235294117646----------------------] 49.6% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 0 0 0 0 0 1 0 1 0 0 0 0 0 1 0 0 1 0 1\n",
      "  0 0 0 0 1 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0\n",
      "  0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 0 0 0 1 1 0 0 0 0 0 0 1 0 0 1 0 0 0\n",
      "  0 0 0 1 1 0 0 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 0 0 0\n",
      "  0 0 1 0 1 0 1 0 0 1 0 0 0 0 1 0 0 0 0 1]]\n",
      "final_activation:  0.45588235294117646=---------------------] 59.6% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "seed passed\n",
      "running LT Abs\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.16176470588235295\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.25\n",
      "state activation:  0.3602941176470588\n",
      "final graph:  [[1 1 1 0 1 1 1 1 1 1 0 0 0 1 1 0 1 1 0 0 0 0 1 0 1 1 0 1 0 0 1 1 1 0 0 0\n",
      "  0 0 0 0 0 0 0 1 0 1 0 0 1 0 0 1 0 1 0 0 0 1 0 1 1 1 0 1 1 0 1 0 0 1 1 1\n",
      "  1 0 0 1 0 1 1 1 0 0 0 0 0 0 1 1 0 1 0 1 0 0 0 1 0 0 1 1 0 0 0 0 0 0 1 0\n",
      "  0 0 0 0 1 1 0 0 0 1 1 0 0 0 1 1 1 1 0 0 1 0 1 1 1 0 1 0 1 0 0 0 0 1 0 1\n",
      "  1 1 0 0 0 0 0 1 0 1 1 0 0 1 1 0 1 0 1 1 0 1 0 0 0 0 1 1 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 1 1 1 0 1 1 0 0 0 0 1 1 1 0 0 0 1 1 1 0 0 0 1 1 0 0 0 1 0 1 0 0\n",
      "  0 0 0 1 1 1 1 1 1 1 0 1 1 1 0 0 0 1 1 1 0 1 1 1 1 1 1 0 1 1 1 0 0 1 0 1\n",
      "  1 0 1 0 0 0 1 1 1 1 0 1 1 0 1 1 1 0 0 1]]\n",
      "final_activation:  0.45588235294117646=---------------------] 59.5% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 0 0 0 0 0 0 0 1 0 0 0 1 1 0 0 0 0 0 0 0 1 1 1 1 0 1 1 1 1 0 0 1 0 0\n",
      "  0 0 1 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 1 1 1 0\n",
      "  0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 1 0 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 1\n",
      "  1 0 1 0 1 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 1 1 0 0 0 0 0\n",
      "  1 0 0 0 0 0 1 1 1 1 0 0 0 0 0 0 0 1 1 1]]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "final_activation:  0.45588235294117646=---------------------] 59.8% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[1 1 1 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 1 1 1 0 0 1 0 0\n",
      "  0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 1 1 0 0\n",
      "  1 0 0 0 0 1 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0\n",
      "  0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 1 0 0 0 1 0 0 0 0\n",
      "  1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0\n",
      "  1 0 0 1 1 0 0 0 1 1 0 1 0 0 0 0 0 1 0 1 0 1 0 0 0 0 1 0 0 1 0 0 1 0 0 0\n",
      "  1 0 0 0 0 0 1 0 1 1 0 0 0 0 0 1 0 0 0 1]]\n",
      "final_activation:  0.45588235294117646=---------------------] 59.7% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[1 1 0 0 0 1 0 1 0 1 0 0 0 1 1 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 1 0 0 0 0\n",
      "  0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 1 0 1 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 1 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 1 1 0 0 1 0 1 0 1 0 0 0 1 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 0 0 0 1 0 1 1 0 0 0 1 0 1 0 0 0 0 0 1\n",
      "  1 0 0 0 1 0 0 1 1 1 0 1 0 1 1 0 0 1 0 0 0 0 0 0 0 0 1 0 1 1 1 0 0 0 0 0\n",
      "  1 0 1 0 0 0 0 0 1 1 0 1 0 0 0 0 0 0 1 1]]\n",
      "final_activation:  0.45588235294117646=---------------------] 59.5% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.14705882352941177\n",
      "state activation:  0.20955882352941177\n",
      "state activation:  0.25735294117647056\n",
      "state activation:  0.2867647058823529\n",
      "state activation:  0.3235294117647059\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.3492647058823529\n",
      "state activation:  0.36764705882352944\n",
      "final graph:  [[1 1 0 0 0 1 0 0 0 1 0 0 0 1 1 0 1 1 0 0 0 0 1 0 1 0 0 0 0 0 1 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 1 1 1 1 1 0 1 0 0 1 0 0 0 1 0 1 1 0 0\n",
      "  1 0 1 1 0 1 0 0 0 1 0 1 0 1 0 1 0 0 1 1 1 1 0 0 1 0 1 0 1 0 0 1 0 0 0 1\n",
      "  1 1 0 0 0 1 0 1 1 1 1 0 1 0 1 1 0 0 0 0 0 0 1 1 0 0 0 0 0 0 1 1 1 1 0 1\n",
      "  0 1 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 1 0 1 1 1 1 0 0 1 0 1 1 1 0 0\n",
      "  0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 1 0 0 0 1 1 1 1 0 1 0 0 0 0 0 0 1 0 1 0 1 0 1 1 1 1 1 1 0 1 0 0\n",
      "  1 0 1 0 0 0 1 0 1 1 0 0 1 1 1 1 1 0 1 1]]\n",
      "final_activation:  0.45588235294117646=---------------------] 59.8% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[1 1 0 0 1 1 1 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 1 1 1 0 0 0 1 1 1 0 0 0 0\n",
      "  0 0 0 0 0 1 1 0 0 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0\n",
      "  0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1\n",
      "  0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 1 0 0 0 1 1 1 0 0 0 1 0 0 0 0 0 0 0 0 0\n",
      "  0 1 0 0 1 0 0 1 1 1 0 1 0 0 0 0 0 1 0 0 0 1 0 0 1 0 1 0 1 1 1 0 0 1 1 0\n",
      "  0 0 0 0 0 0 1 0 0 1 0 1 0 0 1 0 0 1 0 1]]\n",
      "final_activation:  0.45588235294117646=---------------------] 59.7% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 1 0 0 1 1 1 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 1 0 0 1 0 0\n",
      "  0 0 1 0 1 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0\n",
      "  0 0 0 1 0 1 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0\n",
      "  0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 1 0 0 0 0 1 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  1 0 0 0 1 0 0 1 0 1 0 1 1 1 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 1 1 0\n",
      "  0 0 1 0 0 0 0 0 0 1 0 0 0 0 1 0 0 1 0 1]]\n",
      "final_activation:  0.45588235294117646=---------------------] 59.5% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 0 0 0 0 1 0 1 1 1 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 1 0 1 0 1\n",
      "  0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0 1 1 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  1 0 0 0 1 1 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 1 1 0 1 1 1 0 0 1 0 0 1 0 1 0 0\n",
      "  0 1 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 0 1 1 0 0 0\n",
      "  0 0 0 1 1 1 0 1 1 1 0 1 1 0 0 0 0 0 0 1 0 0 0 0 1 0 1 0 0 1 0 0 0 1 0 0\n",
      "  0 0 0 0 1 0 0 0 1 1 1 1 0 0 0 0 0 1 0 1]]\n",
      "final_activation:  0.45588235294117646=---------------------] 59.8% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[1 1 1 0 0 1 0 0 1 1 0 0 0 0 1 0 1 0 0 0 0 0 0 1 0 1 0 0 0 0 1 0 0 1 1 0\n",
      "  0 0 1 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 1 0 1 0 1 0 0 0 0 0 0 0 1 0 1 1 0 0\n",
      "  1 0 0 1 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 1 0 0\n",
      "  0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 1 0 0 0 0 1 1 1 0 0 0 0 1 0 0 0 0\n",
      "  1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 1 0 0 0 0 0\n",
      "  1 0 0 0 1 0 0 0 1 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 1 1 0 0 0 0 1\n",
      "  0 0 1 0 0 0 0 0 1 1 0 0 0 0 1 0 0 1 0 1]]\n",
      "final_activation:  0.45588235294117646=---------------------] 59.7% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[1 1 1 0 0 0 1 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 1 1 1 1 0 1 0 1 1 0 0 0 0 0\n",
      "  0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 1 1 0 0 0 1 1 0 0 0 0 1 0 0 0 0\n",
      "  0 1 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 1 1 1 1 0 1 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 1 1 0 1 0 0 0\n",
      "  1 0 0 0 1 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1]]\n",
      "final_activation:  0.45588235294117646=---------------------] 59.5% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 0 0 1 1 1 1 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 0\n",
      "  0 0 0 0 0 1 1 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1\n",
      "  0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 1 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0\n",
      "  1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0\n",
      "  0 0 1 0 1 0 0 1 0 1 0 1 1 0 1 0 0 1 0 0 0 1 1 1 0 0 1 0 1 1 1 1 0 0 0 0\n",
      "  1 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 1]]\n",
      "final_activation:  0.45588235294117646=---------------------] 59.8% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "seed passed\n",
      "running LT Abs\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.14705882352941177\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.2647058823529412\n",
      "state activation:  0.39338235294117646\n",
      "final graph:  [[1 1 1 0 1 0 0 0 1 1 1 0 0 1 1 0 0 1 0 1 0 0 1 1 0 1 0 1 1 0 1 1 1 1 0 1\n",
      "  1 0 1 1 1 1 1 1 1 1 1 0 1 0 0 0 0 1 0 1 1 0 0 0 0 1 0 1 1 1 1 0 1 1 1 0\n",
      "  1 1 0 1 0 1 0 0 1 0 0 0 1 0 0 1 0 0 0 0 1 0 0 0 0 1 0 1 0 1 0 0 0 1 0 0\n",
      "  1 1 0 1 0 1 0 0 0 0 1 0 1 0 1 1 1 0 1 1 1 0 1 0 1 0 0 0 1 0 0 1 1 1 0 1\n",
      "  1 0 1 0 0 0 0 0 1 1 1 0 0 1 1 0 1 0 1 1 0 1 0 0 1 0 1 1 1 0 0 0 0 1 0 0\n",
      "  0 0 0 1 1 1 1 0 0 1 0 1 0 0 1 0 1 1 1 0 1 1 1 1 1 0 1 1 0 1 0 0 1 1 0 1\n",
      "  0 1 0 1 1 0 1 0 0 1 1 1 1 1 1 0 0 1 0 1 1 1 0 1 0 0 1 0 0 1 0 1 1 1 0 1\n",
      "  0 0 1 1 0 0 0 1 1 1 0 0 0 0 1 1 1 1 0 1]]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "final_activation:  0.45588235294117646=---------------------] 59.7% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 0 0 0 1 0 0 0 1 0 0 0 1 1 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 1 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1\n",
      "  0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0\n",
      "  0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0\n",
      "  1 0 0 0 1 0 1 1 1 1 0 1 1 1 1 0 0 0 0 1 1 0 0 0 1 0 1 0 0 1 1 0 0 0 0 0\n",
      "  1 0 0 0 1 0 0 0 0 1 0 0 0 0 1 0 0 0 0 1]]\n",
      "final_activation:  0.45588235294117646======----------------] 69.8% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.1323529411764706\n",
      "state activation:  0.1948529411764706\n",
      "state activation:  0.2536764705882353\n",
      "state activation:  0.30514705882352944\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.35294117647058826\n",
      "state activation:  0.3786764705882353\n",
      "final graph:  [[0 1 1 1 1 0 0 0 0 1 0 0 0 1 1 0 1 0 0 1 0 1 0 1 0 1 0 1 1 1 1 1 1 0 1 0\n",
      "  1 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0 1 0 0\n",
      "  0 0 0 1 0 1 0 0 0 0 0 1 0 0 1 1 0 0 0 0 1 0 1 1 0 1 0 1 0 0 0 0 1 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 1 0 0 0 0 0 0 1 0\n",
      "  0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 1 1 0 1 1 0 0 1 1 0 0 1 1\n",
      "  0 1 0 1 0 0 0 0 0 1 1 0 1 0 0 0 1 0 1 0 1 1 1 0 0 1 1 0 0 0 1 1 0 0 1 0\n",
      "  1 0 0 0 1 1 0 1 1 1 1 1 1 1 1 1 0 0 1 0 1 1 1 1 0 1 1 0 1 1 1 0 0 1 1 0\n",
      "  1 1 0 1 1 1 1 1 0 1 0 1 1 1 0 1 1 1 0 1]]\n",
      "final_activation:  0.45588235294117646======----------------] 69.5% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.11764705882352941\n",
      "state activation:  0.13970588235294118\n",
      "state activation:  0.15441176470588236\n",
      "state activation:  0.15808823529411764\n",
      "final graph:  [[0 1 0 0 0 1 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 1 0 0 0 0 0 1 0 0 0\n",
      "  0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 1 0 0 1 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 1 1 0 0 0 0 0 1 0 1 0 0 0 0 0 1 1 0 0 0 0\n",
      "  1 1 0 0 1 0 0 1 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1]]\n",
      "final_activation:  0.45588235294117646===========-----------] 79.8% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 0 0 0 1 1 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 1 0 0 0 0 1\n",
      "  0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 0 1 0 1 0 0 1 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 1 1 0 0 0 0 0 1 1 0 0 0 0 1\n",
      "  0 0 0 0 1 0 0 1 0 1 0 1 0 0 1 0 0 0 0 0 0 0 0 0 1 0 1 0 1 1 1 1 0 1 0 0\n",
      "  0 0 0 0 1 0 1 0 1 1 0 0 0 0 1 1 0 0 0 1]]\n",
      "final_activation:  0.45588235294117646===========-----------] 79.2% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[1 1 0 0 1 0 0 1 1 1 1 0 0 1 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 1 0 0 0 0 1\n",
      "  0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 1 0 1 1 0 0\n",
      "  1 0 1 0 0 1 1 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0\n",
      "  0 0 0 0 1 1 0 0 0 0 1 0 0 1 0 0 0 0 0 0 1 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0\n",
      "  0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 1 0 0 0 1 0 1 0 1 0 0 0 1 0 1 0 0\n",
      "  0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 1 0 0 1 0 1 0 1 1 0 0 0 0 1 0 0 0 1 1 0 1 0 1 0 0 1 0 0 0 0 1 0\n",
      "  1 0 1 0 0 0 0 0 1 1 1 0 0 0 0 1 0 1 1 1]]\n",
      "final_activation:  0.45588235294117646===========-----------] 79.4% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 0 0 0 1 1 1 0 1 0 0 0 1 1 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 1 1 0 0 0 0\n",
      "  0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  1 0 1 1 1 1 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 1 1 0 0 0 0 1 0 0 1 0 0 0 0 0 0 1 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 1 1 0 1 0 0 0 1 0 1 0 0\n",
      "  0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 1 0 0 0 1 0 1 1 0 0 1 0 0 0 0 0 0 0 0 0\n",
      "  0 1 0 0 1 0 1 1 0 1 0 1 1 1 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 1 0 0 1\n",
      "  1 0 1 0 1 0 0 0 0 1 0 1 0 0 1 0 0 0 1 1]]\n",
      "final_activation:  0.45588235294117646===========-----------] 79.6% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.17279411764705882\n",
      "state activation:  0.2647058823529412\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.3235294117647059\n",
      "state activation:  0.3713235294117647\n",
      "final graph:  [[1 1 1 0 1 1 1 1 1 1 0 1 1 0 1 1 1 1 1 0 0 0 1 0 1 1 1 1 1 1 1 1 0 1 1 0\n",
      "  1 1 1 1 1 1 1 0 1 1 1 0 1 1 1 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 1 0 0 0\n",
      "  0 0 0 0 0 1 0 0 0 0 1 0 0 1 1 0 0 0 1 0 1 0 1 0 0 0 1 0 0 0 0 0 0 0 1 0\n",
      "  0 0 0 0 1 0 1 0 0 0 0 0 1 1 0 0 0 1 0 1 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 1\n",
      "  0 0 0 1 0 0 1 0 1 0 0 0 0 0 0 0 1 0 1 0 1 0 1 0 0 0 0 1 0 0 1 0 0 0 0 1\n",
      "  0 1 0 1 1 0 0 1 1 1 1 1 0 0 0 0 0 1 0 0 1 0 1 1 0 0 1 0 1 1 1 1 1 1 1 1\n",
      "  1 1 1 1 0 1 1 1 0 1 1 1 1 1 0 1 1 1 1 1]]\n",
      "final_activation:  0.45588235294117646===========-----------] 79.8% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 0 0 0 1 0 0 0 1 1 0 0 1 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 1 1 0 1 0 0\n",
      "  0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 1 0 0 0 0 1 1 1 0 0 0 1 1 0 0 0 0 0 1 0 1 1 0 1 0 0 1 0 0\n",
      "  0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1\n",
      "  0 0 0 0 1 1 0 0 0 1 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 1 1 1 0 0 0 0 0\n",
      "  0 0 0 0 0 0 1 0 0 1 0 1 0 0 1 0 0 1 0 1]]\n",
      "final_activation:  0.45588235294117646===========-----------] 79.3% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.125\n",
      "state activation:  0.17279411764705882\n",
      "state activation:  0.21691176470588236\n",
      "state activation:  0.23897058823529413\n",
      "state activation:  0.2647058823529412\n",
      "state activation:  0.29411764705882354\n",
      "state activation:  0.3014705882352941\n",
      "state activation:  0.30514705882352944\n",
      "state activation:  0.3088235294117647\n",
      "final graph:  [[1 1 1 0 0 0 0 0 0 1 0 0 0 0 1 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0\n",
      "  0 1 0 0 0 0 1 0 0 1 0 0 1 0 0 1 0 0 0 0 0 0 1 1 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0\n",
      "  0 0 0 0 0 0 1 0 1 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 1 0 0 1 0 0 1 0 1 1 1 0 0 0 1 1 1 0 0 0 0 0 1 0 1 0 1 0 1 0 0\n",
      "  1 0 1 1 0 0 0 1 0 1 1 1 1 0 0 0 1 0 0 0 0 1 1 0 0 1 1 0 0 0 1 1 0 0 0 1\n",
      "  1 0 0 0 1 0 1 1 1 1 0 1 1 1 1 0 1 0 0 0 1 1 0 0 0 0 1 0 0 1 0 1 0 1 1 0\n",
      "  0 0 1 0 1 0 0 0 1 1 0 1 1 0 1 0 0 0 1 1]]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "final_activation:  0.45588235294117646===========-----------] 79.5% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[1 1 0 0 0 0 1 0 0 1 0 0 0 1 1 0 0 0 0 0 0 0 0 1 1 1 0 0 0 1 1 1 0 1 1 0\n",
      "  0 0 0 0 1 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 1 1 0 0\n",
      "  0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0\n",
      "  0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 0 0 0 0 1 0 0 0 1\n",
      "  0 1 0 0 1 0 0 0 1 1 0 1 0 0 1 0 0 0 0 1 0 0 1 0 0 0 1 0 0 1 1 0 0 0 0 0\n",
      "  1 0 1 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 1]]\n",
      "final_activation:  0.45588235294117646===========-----------] 79.6% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[1 1 0 0 0 1 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 1 1 1 1 0 1 0 0 1 0 0 0 0 0\n",
      "  0 0 0 0 0 1 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 1 1 0 0\n",
      "  0 0 0 0 0 1 1 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0\n",
      "  0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0\n",
      "  0 1 0 1 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1\n",
      "  0 0 0 1 1 1 1 1 1 1 0 1 1 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 1 1 1 0 0 0 0 0\n",
      "  1 0 1 0 1 0 0 0 0 1 0 0 0 0 1 0 0 1 0 1]]\n",
      "final_activation:  0.45588235294117646===========-----------] 79.8% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.14705882352941177\n",
      "state activation:  0.19117647058823528\n",
      "state activation:  0.25\n",
      "state activation:  0.28308823529411764\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.3272058823529412\n",
      "state activation:  0.36764705882352944\n",
      "final graph:  [[0 1 1 0 0 0 1 1 0 1 0 0 0 1 1 1 1 1 1 0 1 0 0 1 1 0 1 1 1 1 1 1 0 1 1 1\n",
      "  1 1 1 1 1 0 0 1 1 1 1 0 0 0 1 0 0 0 0 0 0 0 1 0 0 1 0 1 0 0 1 0 0 1 1 0\n",
      "  0 1 0 0 1 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 1 0 0 0 1 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0\n",
      "  1 0 0 0 0 0 0 1 0 1 0 0 1 1 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 1 1 0 0 1 1 1\n",
      "  0 0 0 1 0 0 1 0 1 1 1 1 0 1 0 0 1 1 0 1 0 1 1 1 0 0 1 1 1 1 1 1 1 0 1 1\n",
      "  0 1 1 1 1 0 1 1 0 1 1 1 1 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 0 1 0\n",
      "  0 0 0 0 1 0 0 1 0 1 1 0 0 0 1 0 0 1 1 1]]\n",
      "final_activation:  0.45588235294117646================------] 89.3% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 1 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 1 0 0 1 0\n",
      "  0 0 1 0 1 1 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 1 1 0 0\n",
      "  0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 1 0 0 1 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 1 0 0 0 0 0 1 0 0 1 0 0 1 0 0 0 0 0 0 1\n",
      "  0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 1 1 0 0 1 0 0 0 0 1\n",
      "  0 0 1 0 1 1 0 1 0 1 0 1 1 0 1 0 0 0 0 1 1 0 0 0 1 0 1 0 1 1 1 0 1 0 0 0\n",
      "  1 0 0 0 0 0 1 0 1 1 0 0 0 0 0 1 0 0 0 1]]\n",
      "final_activation:  0.45588235294117646================------] 89.4% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.10661764705882353\n",
      "state activation:  0.12867647058823528\n",
      "state activation:  0.13602941176470587\n",
      "state activation:  0.15441176470588236\n",
      "state activation:  0.17647058823529413\n",
      "state activation:  0.19852941176470587\n",
      "state activation:  0.21691176470588236\n",
      "state activation:  0.22426470588235295\n",
      "state activation:  0.2426470588235294\n",
      "state activation:  0.27205882352941174\n",
      "state activation:  0.3014705882352941\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.35294117647058826\n",
      "state activation:  0.39338235294117646\n",
      "final graph:  [[1 1 1 0 1 1 1 1 1 1 1 0 1 1 1 1 1 1 0 0 1 1 1 1 1 1 0 1 1 1 1 1 0 1 1 1\n",
      "  1 1 1 1 1 0 1 1 1 1 1 1 1 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 1 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 1 1 0 0 1 0 0 0 1 0 0 0 0\n",
      "  0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 1 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 1 1\n",
      "  0 1 0 0 0 1 0 0 1 0 0 0 0 0 1 1 0 1 0 1 0 0 1 1 0 0 0 0 0 0 1 0 1 1 0 0\n",
      "  0 1 0 0 1 0 0 0 0 1 0 1 1 0 0 0 0 1 0 0 0 0 1 0 0 0 1 0 1 1 1 1 0 1 1 1\n",
      "  1 1 1 1 1 1 1 1 0 1 0 1 1 1 1 1 1 1 1 1]]\n",
      "final_activation:  0.45588235294117646================------] 89.5% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[0 1 1 0 0 1 1 0 0 1 1 0 0 0 1 0 0 0 0 0 0 0 1 0 1 1 0 0 1 0 1 1 0 0 1 1\n",
      "  0 0 0 0 0 1 0 0 0 1 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 1 1 1 0\n",
      "  1 0 0 1 0 1 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0 0 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 1 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0 0 1 1 0 0 0 0 0 0 0 0 1 0 0 0 1\n",
      "  0 0 0 0 1 0 1 0 1 1 1 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 1 0 0 0 0\n",
      "  1 0 0 0 0 0 0 1 0 1 0 1 0 0 1 0 0 0 0 1]]\n",
      "final_activation:  0.45588235294117646================------] 89.6% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running IC\n",
      "starting loop manager\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "final graph:  [[1 1 1 0 0 1 1 1 0 1 1 0 0 0 1 0 1 0 0 0 0 0 1 1 0 0 0 0 0 0 1 1 0 1 0 0\n",
      "  0 0 0 0 1 1 1 0 0 1 0 0 0 0 0 0 0 0 1 0 1 0 0 1 0 0 0 0 0 0 1 0 1 1 0 0\n",
      "  0 0 0 1 0 1 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 1 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      "  0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1\n",
      "  0 0 1 0 1 1 0 0 1 1 0 1 1 0 1 0 0 1 0 0 0 0 1 0 1 0 1 0 0 1 0 0 1 1 1 0\n",
      "  1 0 1 0 0 0 1 0 1 1 1 0 0 0 1 1 0 1 1 1]]\n",
      "final_activation:  0.45588235294117646================------] 89.7% Complete\n",
      "Adjaecency Matrix:  (272, 272)\n",
      "zero initialized agents:  (19,)\n",
      "initially activated agents:  (19,)\n",
      "running LT Prop\n",
      "state activation:  -1\n",
      "state activation:  0.06985294117647059\n",
      "state activation:  0.16176470588235295\n",
      "state activation:  0.24632352941176472\n",
      "Achieved stopping condition and stopping diffusion\n",
      "state activation:  0.33455882352941174\n",
      "state activation:  0.3897058823529412\n",
      "final graph:  [[0 1 1 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 1 1 0 0 1 1 0 1 0 0 0 0 1\n",
      "  0 0 0 0 0 0 0 0 1 1 0 0 0 1 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0\n",
      "  0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 1 1 1 1 0 1 1 1 1\n",
      "  0 0 0 1 1 0 1 0 0 0 1 0 0 1 0 0 1 0 0 0 1 0 1 0 0 1 1 0 1 0 0 0 0 1 1 1\n",
      "  0 0 0 0 1 0 0 1 0 1 1 0 1 1 1 1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 0 1 0 0\n",
      "  0 1 0 0 1 0 1 0 1 1 0 0 1 0 1 0 1 1 1 1 0 1 1 1 0 1 0 0 1 1 0 0 1 0 1 1\n",
      "  1 1 1 0 1 1 1 0 1 1 1 1 1 0 1 0 1 1 0 0 0 1 1 0 1 0 1 0 0 1 1 1 1 0 0 0\n",
      "  1 0 0 0 1 0 0 0 0 1 1 0 0 0 0 1 1 0 0 1]]\n",
      "Progress [==================================================] 100.0% Complete\n",
      "CPU times: user 2min 10s, sys: 3.48 s, total: 2min 13s\n",
      "Wall time: 35.6 s\n"
     ]
    }
   ],
   "source": [
    "N = 10\n",
    "# You can give the sample method a `vis` keyword to see an animation how the prior transforms towards the\n",
    "# posterior with a decreasing threshold.\n",
    "schedule = [16, 13, 11, 10.5]\n",
    "# schedule = [16, 15, 14]\n",
    "\n",
    "%time result = smc.sample(N, schedule)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "greater-reunion",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.26298877361581496"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result.samples['prop_prob'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "detailed-language",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Method: SMC\n",
      "Number of samples: 10\n",
      "Number of simulations: 141\n",
      "Threshold: 10.5\n",
      "Sample means: prop_prob: 0.34\n",
      "\n",
      "Population 0:\n",
      "Method: Rejection within SMC-ABC\n",
      "Number of samples: 10\n",
      "Number of simulations: 10\n",
      "Threshold: 11.8\n",
      "Sample means: prop_prob: 0.505\n",
      "\n",
      "Population 1:\n",
      "Method: Rejection within SMC-ABC\n",
      "Number of samples: 10\n",
      "Number of simulations: 10\n",
      "Threshold: 11.4\n",
      "Sample means: prop_prob: 0.59\n",
      "\n",
      "Population 2:\n",
      "Method: Rejection within SMC-ABC\n",
      "Number of samples: 10\n",
      "Number of simulations: 24\n",
      "Threshold: 11\n",
      "Sample means: prop_prob: 0.194\n",
      "\n",
      "Population 3:\n",
      "Method: Rejection within SMC-ABC\n",
      "Number of samples: 10\n",
      "Number of simulations: 97\n",
      "Threshold: 10.5\n",
      "Sample means: prop_prob: 0.34\n"
     ]
    }
   ],
   "source": [
    "result.summary(all=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "pressed-connection",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['__class__',\n",
       " '__delattr__',\n",
       " '__dict__',\n",
       " '__dir__',\n",
       " '__doc__',\n",
       " '__eq__',\n",
       " '__format__',\n",
       " '__ge__',\n",
       " '__getattr__',\n",
       " '__getattribute__',\n",
       " '__getstate__',\n",
       " '__gt__',\n",
       " '__hash__',\n",
       " '__init__',\n",
       " '__init_subclass__',\n",
       " '__le__',\n",
       " '__lt__',\n",
       " '__module__',\n",
       " '__ne__',\n",
       " '__new__',\n",
       " '__reduce__',\n",
       " '__reduce_ex__',\n",
       " '__repr__',\n",
       " '__setattr__',\n",
       " '__setstate__',\n",
       " '__sizeof__',\n",
       " '__str__',\n",
       " '__subclasshook__',\n",
       " '__weakref__',\n",
       " 'dim',\n",
       " 'discrepancies',\n",
       " 'discrepancy_name',\n",
       " 'is_multivariate',\n",
       " 'meta',\n",
       " 'method_name',\n",
       " 'n_batches',\n",
       " 'n_populations',\n",
       " 'n_samples',\n",
       " 'n_sim',\n",
       " 'outputs',\n",
       " 'parameter_names',\n",
       " 'plot_marginals',\n",
       " 'plot_pairs',\n",
       " 'populations',\n",
       " 'sample_means',\n",
       " 'sample_means_array',\n",
       " 'sample_means_summary',\n",
       " 'samples',\n",
       " 'samples_array',\n",
       " 'save',\n",
       " 'seed',\n",
       " 'summary',\n",
       " 'threshold',\n",
       " 'weights']"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dir(result)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "radical-therapy",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Method: SMC\n",
      "Number of samples: 10\n",
      "Number of simulations: 141\n",
      "Threshold: 10.5\n",
      "Sample means: prop_prob: 0.34\n",
      "\n",
      "Population 0:\n",
      "Method: Rejection within SMC-ABC\n",
      "Number of samples: 10\n",
      "Number of simulations: 10\n",
      "Threshold: 11.8\n",
      "Sample means: prop_prob: 0.505\n",
      "\n",
      "Population 1:\n",
      "Method: Rejection within SMC-ABC\n",
      "Number of samples: 10\n",
      "Number of simulations: 10\n",
      "Threshold: 11.4\n",
      "Sample means: prop_prob: 0.59\n",
      "\n",
      "Population 2:\n",
      "Method: Rejection within SMC-ABC\n",
      "Number of samples: 10\n",
      "Number of simulations: 24\n",
      "Threshold: 11\n",
      "Sample means: prop_prob: 0.194\n",
      "\n",
      "Population 3:\n",
      "Method: Rejection within SMC-ABC\n",
      "Number of samples: 10\n",
      "Number of simulations: 97\n",
      "Threshold: 10.5\n",
      "Sample means: prop_prob: 0.34\n"
     ]
    }
   ],
   "source": [
    "res = result.summary(all = True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "hungarian-ozone",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "elfi.methods.results.SmcSample"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(result)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "secret-supervisor",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.15697714, 0.32005939, 0.40497832, 0.13299753, 0.10826478,\n",
       "       0.06212582, 0.36028866, 0.34275362, 0.66382729, 0.07761518])"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result.samples['prop_prob']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "affected-peter",
   "metadata": {},
   "outputs": [],
   "source": [
    "filename = \"../results/sequential_monte_carlo/LT_IC/graph_trial.pkl\"\n",
    "filehandler = open(filename, 'wb')\n",
    "pickle.dump(result, filehandler)\n",
    "filehandler.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "postal-producer",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[22.0, 34.0]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = [10,20,30,40,50,60,70]\n",
    "x = np.percentile(np.array(a), [20,40])\n",
    "list(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "operating-suspension",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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