BA_model.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import networkx as nx\n",
    "import numpy as np\n",
    "import random as rd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Barabási–Albert Network Model\n",
    "#### by Aleksander Molak (2017)\n",
    "#### aleksander.molak@gmail.com\n",
    "\n",
    "**[Barabási–Albert model](https://en.wikipedia.org/wiki/Barab%C3%A1si%E2%80%93Albert_model)** is an algorithm for generating random scale-free networks using a preferential attachment mechanism. \n",
    "\n",
    "The following implementation uses **[Networkx](https://networkx.org/)** library."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "COLOR = '#40a6d1'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Define helper functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Plotting\n",
    "\n",
    "def k_distrib(graph, scale='lin', colour='#40a6d1', alpha=.8, fit_line=False, expct_lo=1, expct_hi=10, expct_const=1):\n",
    "    \n",
    "    plt.close()\n",
    "    num_nodes = graph.number_of_nodes()\n",
    "    max_degree = 0\n",
    "    \n",
    "    # Calculate the maximum degree to know the range of x-axis\n",
    "    for n in graph.nodes():\n",
    "        if graph.degree(n) > max_degree:\n",
    "            max_degree = graph.degree(n)\n",
    "    \n",
    "    # X-axis and y-axis values\n",
    "    x = []\n",
    "    y_tmp = []\n",
    "    \n",
    "    # Loop over all degrees until the maximum to compute the portion of nodes for that degree\n",
    "    for i in range(max_degree + 1):\n",
    "        x.append(i)\n",
    "        y_tmp.append(0)\n",
    "        for n in graph.nodes():\n",
    "            if graph.degree(n) == i:\n",
    "                y_tmp[i] += 1\n",
    "        y = [i / num_nodes for i in y_tmp] \n",
    "    \n",
    "    # Check for the lin / log parameter and set axes scale\n",
    "    if scale == 'log':\n",
    "        plt.xscale('log')\n",
    "        plt.yscale('log')\n",
    "        plt.title('Degree distribution (log-log scale)')\n",
    "        plt.ylabel('log(P(k))')\n",
    "        plt.xlabel('log(k)')\n",
    "        plt.plot(x, y, linewidth = 0, marker = 'o', markersize = 8, color = colour, alpha = alpha)\n",
    "        \n",
    "        if fit_line:\n",
    "            # Add theoretical distribution line k^-3\n",
    "            # Note that you need to parametrize it manually\n",
    "            w = [a for a in range(expct_lo,expct_hi)]\n",
    "            z = []\n",
    "            for i in w:\n",
    "                x = (i**-3) * expct_const # set line's length and fit intercept\n",
    "                z.append(x)\n",
    "\n",
    "            plt.plot(w, z, 'k-', color='#7f7f7f')\n",
    "            \n",
    "    else:\n",
    "        plt.plot(x, y, linewidth = 0, marker = 'o', markersize = 8, color = colour, alpha = alpha)\n",
    "        plt.title('Degree distribution (linear scale)')\n",
    "        plt.ylabel('P(k)')\n",
    "        plt.xlabel('k')\n",
    "\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# BA algo functions\n",
    "\n",
    "def rand_prob_node():\n",
    "    nodes_probs = []\n",
    "    for node in G.nodes():\n",
    "        node_degr = G.degree(node)\n",
    "        #print(node_degr)\n",
    "        node_proba = node_degr / (2 * len(G.edges()))\n",
    "        #print(\"Node proba is: {}\".format(node_proba))\n",
    "        nodes_probs.append(node_proba)\n",
    "        #print(\"Nodes probablities: {}\".format(nodes_probs))\n",
    "    random_proba_node = np.random.choice(G.nodes(),p=nodes_probs)\n",
    "    #print(\"Randomly selected node is: {}\".format(random_proba_node))\n",
    "    return random_proba_node\n",
    "\n",
    "def add_edge():\n",
    "        if len(G.edges()) == 0:\n",
    "            random_proba_node = 0\n",
    "        else:\n",
    "            random_proba_node = rand_prob_node()\n",
    "        new_edge = (random_proba_node, new_node)\n",
    "        if new_edge in G.edges():\n",
    "            print(\"!ככה לא בונים חומה\")\n",
    "            add_edge()\n",
    "        else:\n",
    "            print(\"!מזל טוב\")\n",
    "            G.add_edge(new_node, random_proba_node)\n",
    "            print(\"Edge added: {} {}\".format(new_node + 1, random_proba_node))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## BA Algorithm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "***\n",
      "Welcome to Barabási–Albert (BA) model simulation\n",
      "Author: Aleksander Molak (2017)\n",
      "!איזה כיף\n",
      "\n",
      "\n",
      "Please type in the initial number of nodes (m_0): 12\n",
      "\n",
      "Please type in the final number of nodes: 250\n",
      "\n",
      "Please type in the value of m parameter (m<=m_0): 7\n",
      "\n",
      "\n",
      "Creating initial graph...\n",
      "Graph created. Number of nodes: 12\n",
      "Adding nodes...\n",
      "----------> Step 0 <----------\n",
      "Node added: 13\n",
      "!מזל טוב\n",
      "Edge added: 13 9\n",
      "!מזל טוב\n",
      "Edge added: 13 10\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 13 2\n",
      "!ככה לא בונים חומה\n",
      "!ככה לא בונים חומה\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 13 3\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 13 11\n",
      "!ככה לא בונים חומה\n",
      "!ככה לא בונים חומה\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 13 4\n",
      "!מזל טוב\n",
      "Edge added: 13 1\n",
      "----------> Step 1 <----------\n",
      "Node added: 14\n",
      "!מזל טוב\n",
      "Edge added: 14 4\n",
      "!מזל טוב\n",
      "Edge added: 14 6\n",
      "!מזל טוב\n",
      "Edge added: 14 10\n",
      "!מזל טוב\n",
      "Edge added: 14 7\n",
      "!מזל טוב\n",
      "Edge added: 14 9\n",
      "!מזל טוב\n",
      "Edge added: 14 1\n",
      "!ככה לא בונים חומה\n",
      "!ככה לא בונים חומה\n",
      "!ככה לא בונים חומה\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 14 3\n",
      "----------> Step 2 <----------\n",
      "Node added: 15\n",
      "!מזל טוב\n",
      "Edge added: 15 7\n",
      "!מזל טוב\n",
      "Edge added: 15 1\n",
      "!מזל טוב\n",
      "Edge added: 15 8\n",
      "!מזל טוב\n",
      "Edge added: 15 3\n",
      "!מזל טוב\n",
      "Edge added: 15 10\n",
      "!מזל טוב\n",
      "Edge added: 15 6\n",
      "!מזל טוב\n",
      "Edge added: 15 11\n",
      "----------> Step 3 <----------\n",
      "Node added: 16\n",
      "!מזל טוב\n",
      "Edge added: 16 0\n",
      "!מזל טוב\n",
      "Edge added: 16 6\n",
      "!מזל טוב\n",
      "Edge added: 16 1\n",
      "!מזל טוב\n",
      "Edge added: 16 10\n",
      "!מזל טוב\n",
      "Edge added: 16 4\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 16 7\n",
      "!ככה לא בונים חומה\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 16 5\n",
      "----------> Step 4 <----------\n",
      "Node added: 17\n",
      "!מזל טוב\n",
      "Edge added: 17 1\n",
      "!מזל טוב\n",
      "Edge added: 17 3\n",
      "!מזל טוב\n",
      "Edge added: 17 5\n",
      "!מזל טוב\n",
      "Edge added: 17 9\n",
      "!מזל טוב\n",
      "Edge added: 17 7\n",
      "!מזל טוב\n",
      "Edge added: 17 11\n",
      "!מזל טוב\n",
      "Edge added: 17 2\n",
      "----------> Step 5 <----------\n",
      "Node added: 18\n",
      "!מזל טוב\n",
      "Edge added: 18 6\n",
      "!מזל טוב\n",
      "Edge added: 18 8\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 18 13\n",
      "!מזל טוב\n",
      "Edge added: 18 2\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 18 1\n",
      "!ככה לא בונים חומה\n",
      "!ככה לא בונים חומה\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 18 3\n",
      "!ככה לא בונים חומה\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 18 9\n",
      "----------> Step 6 <----------\n",
      "Node added: 19\n",
      "!מזל טוב\n",
      "Edge added: 19 4\n",
      "!מזל טוב\n",
      "Edge added: 19 3\n",
      "!מזל טוב\n",
      "Edge added: 19 2\n",
      "!מזל טוב\n",
      "Edge added: 19 0\n",
      "!מזל טוב\n",
      "Edge added: 19 16\n",
      "!מזל טוב\n",
      "Edge added: 19 8\n",
      "!מזל טוב\n",
      "Edge added: 19 11\n",
      "----------> Step 7 <----------\n",
      "Node added: 20\n",
      "!מזל טוב\n",
      "Edge added: 20 7\n",
      "!מזל טוב\n",
      "Edge added: 20 2\n",
      "!מזל טוב\n",
      "Edge added: 20 16\n",
      "!מזל טוב\n",
      "Edge added: 20 14\n",
      "!מזל טוב\n",
      "Edge added: 20 10\n",
      "!מזל טוב\n",
      "Edge added: 20 15\n",
      "!מזל טוב\n",
      "Edge added: 20 4\n",
      "----------> Step 8 <----------\n",
      "Node added: 21\n",
      "!מזל טוב\n",
      "Edge added: 21 9\n",
      "!מזל טוב\n",
      "Edge added: 21 6\n",
      "!מזל טוב\n",
      "Edge added: 21 2\n",
      "!מזל טוב\n",
      "Edge added: 21 13\n",
      "!מזל טוב\n",
      "Edge added: 21 3\n",
      "!ככה לא בונים חומה\n",
      "!ככה לא בונים חומה\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 21 16\n",
      "!מזל טוב\n",
      "Edge added: 21 1\n",
      "----------> Step 9 <----------\n",
      "Node added: 22\n",
      "!מזל טוב\n",
      "Edge added: 22 9\n",
      "!מזל טוב\n",
      "Edge added: 22 5\n",
      "!מזל טוב\n",
      "Edge added: 22 15\n",
      "!מזל טוב\n",
      "Edge added: 22 3\n",
      "!מזל טוב\n",
      "Edge added: 22 13\n",
      "!מזל טוב\n",
      "Edge added: 22 10\n",
      "!מזל טוב\n",
      "Edge added: 22 12\n",
      "----------> Step 10 <----------\n",
      "Node added: 23\n",
      "!מזל טוב\n",
      "Edge added: 23 9\n",
      "!מזל טוב\n",
      "Edge added: 23 8\n",
      "!מזל טוב\n",
      "Edge added: 23 0\n",
      "!מזל טוב\n",
      "Edge added: 23 10\n",
      "!מזל טוב\n",
      "Edge added: 23 16\n",
      "!מזל טוב\n",
      "Edge added: 23 5\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 23 2\n",
      "----------> Step 11 <----------\n",
      "Node added: 24\n",
      "!מזל טוב\n",
      "Edge added: 24 10\n",
      "!מזל טוב\n",
      "Edge added: 24 1\n",
      "!מזל טוב\n",
      "Edge added: 24 15\n",
      "!מזל טוב\n",
      "Edge added: 24 8\n",
      "!מזל טוב\n",
      "Edge added: 24 17\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 24 7\n",
      "!מזל טוב\n",
      "Edge added: 24 19\n",
      "----------> Step 12 <----------\n",
      "Node added: 25\n",
      "!מזל טוב\n",
      "Edge added: 25 4\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 25 24\n",
      "!מזל טוב\n",
      "Edge added: 25 9\n",
      "!מזל טוב\n",
      "Edge added: 25 18\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 25 11\n",
      "!מזל טוב\n",
      "Edge added: 25 8\n",
      "!מזל טוב\n",
      "Edge added: 25 16\n",
      "----------> Step 13 <----------\n",
      "Node added: 26\n",
      "!מזל טוב\n",
      "Edge added: 26 6\n",
      "!מזל טוב\n",
      "Edge added: 26 18\n",
      "!מזל טוב\n",
      "Edge added: 26 8\n",
      "!מזל טוב\n",
      "Edge added: 26 16\n",
      "!מזל טוב\n",
      "Edge added: 26 1\n",
      "!מזל טוב\n",
      "Edge added: 26 3\n",
      "!מזל טוב\n",
      "Edge added: 26 12\n",
      "----------> Step 14 <----------\n",
      "Node added: 27\n",
      "!מזל טוב\n",
      "Edge added: 27 12\n",
      "!מזל טוב\n",
      "Edge added: 27 9\n",
      "!מזל טוב\n",
      "Edge added: 27 1\n",
      "!מזל טוב\n",
      "Edge added: 27 10\n",
      "!מזל טוב\n",
      "Edge added: 27 23\n",
      "!מזל טוב\n",
      "Edge added: 27 8\n",
      "!מזל טוב\n",
      "Edge added: 27 2\n",
      "----------> Step 15 <----------\n",
      "Node added: 28\n",
      "!מזל טוב\n",
      "Edge added: 28 3\n",
      "!מזל טוב\n",
      "Edge added: 28 4\n",
      "!מזל טוב\n",
      "Edge added: 28 13\n",
      "!מזל טוב\n",
      "Edge added: 28 8\n",
      "!מזל טוב\n",
      "Edge added: 28 16\n",
      "!מזל טוב\n",
      "Edge added: 28 10\n",
      "!מזל טוב\n",
      "Edge added: 28 9\n",
      "----------> Step 16 <----------\n",
      "Node added: 29\n",
      "!מזל טוב\n",
      "Edge added: 29 2\n",
      "!מזל טוב\n",
      "Edge added: 29 7\n",
      "!מזל טוב\n",
      "Edge added: 29 20\n",
      "!מזל טוב\n",
      "Edge added: 29 12\n",
      "!מזל טוב\n",
      "Edge added: 29 1\n",
      "!ככה לא בונים חומה\n",
      "!ככה לא בונים חומה\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 29 19\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 29 16\n",
      "----------> Step 17 <----------\n",
      "Node added: 30\n",
      "!מזל טוב\n",
      "Edge added: 30 0\n",
      "!מזל טוב\n",
      "Edge added: 30 26\n",
      "!מזל טוב\n",
      "Edge added: 30 7\n",
      "!מזל טוב\n",
      "Edge added: 30 6\n",
      "!מזל טוב\n",
      "Edge added: 30 12\n",
      "!מזל טוב\n",
      "Edge added: 30 9\n",
      "!מזל טוב\n",
      "Edge added: 30 19\n",
      "----------> Step 18 <----------\n",
      "Node added: 31\n",
      "!מזל טוב\n",
      "Edge added: 31 13\n",
      "!מזל טוב\n",
      "Edge added: 31 2\n",
      "!מזל טוב\n",
      "Edge added: 31 0\n",
      "!מזל טוב\n",
      "Edge added: 31 24\n",
      "!מזל טוב\n",
      "Edge added: 31 9\n",
      "!מזל טוב\n",
      "Edge added: 31 23\n",
      "!מזל טוב\n",
      "Edge added: 31 17\n",
      "----------> Step 19 <----------\n",
      "Node added: 32\n",
      "!מזל טוב\n",
      "Edge added: 32 8\n",
      "!מזל טוב\n",
      "Edge added: 32 3\n",
      "!מזל טוב\n",
      "Edge added: 32 13\n",
      "!מזל טוב\n",
      "Edge added: 32 2\n",
      "!מזל טוב\n",
      "Edge added: 32 4\n",
      "!מזל טוב\n",
      "Edge added: 32 10\n",
      "!מזל טוב\n",
      "Edge added: 32 1\n",
      "----------> Step 20 <----------\n",
      "Node added: 33\n",
      "!מזל טוב\n",
      "Edge added: 33 1\n",
      "!מזל טוב\n",
      "Edge added: 33 16\n",
      "!מזל טוב\n",
      "Edge added: 33 23\n",
      "!מזל טוב\n",
      "Edge added: 33 11\n",
      "!מזל טוב\n",
      "Edge added: 33 0\n",
      "!מזל טוב\n",
      "Edge added: 33 4\n",
      "!מזל טוב\n",
      "Edge added: 33 10\n",
      "----------> Step 21 <----------\n",
      "Node added: 34\n",
      "!מזל טוב\n",
      "Edge added: 34 30\n",
      "!מזל טוב\n",
      "Edge added: 34 7\n",
      "!מזל טוב\n",
      "Edge added: 34 9\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 34 3\n",
      "!מזל טוב\n",
      "Edge added: 34 20\n",
      "!מזל טוב\n",
      "Edge added: 34 1\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 34 23\n",
      "----------> Step 22 <----------\n",
      "Node added: 35\n",
      "!מזל טוב\n",
      "Edge added: 35 26\n",
      "!מזל טוב\n",
      "Edge added: 35 2\n",
      "!מזל טוב\n",
      "Edge added: 35 19\n",
      "!מזל טוב\n",
      "Edge added: 35 28\n",
      "!מזל טוב\n",
      "Edge added: 35 7\n",
      "!מזל טוב\n",
      "Edge added: 35 27\n",
      "!מזל טוב\n",
      "Edge added: 35 20\n",
      "----------> Step 23 <----------\n",
      "Node added: 36\n",
      "!מזל טוב\n",
      "Edge added: 36 10\n",
      "!מזל טוב\n",
      "Edge added: 36 12\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 36 30\n",
      "!מזל טוב\n",
      "Edge added: 36 7\n",
      "!מזל טוב\n",
      "Edge added: 36 3\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 36 9\n",
      "!מזל טוב\n",
      "Edge added: 36 21\n",
      "----------> Step 24 <----------\n",
      "Node added: 37\n",
      "!מזל טוב\n",
      "Edge added: 37 29\n",
      "!מזל טוב\n",
      "Edge added: 37 27\n",
      "!מזל טוב\n",
      "Edge added: 37 6\n",
      "!מזל טוב\n",
      "Edge added: 37 10\n",
      "!מזל טוב\n",
      "Edge added: 37 11\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 37 13\n",
      "!מזל טוב\n",
      "Edge added: 37 2\n",
      "----------> Step 25 <----------\n",
      "Node added: 38\n",
      "!מזל טוב\n",
      "Edge added: 38 23\n",
      "!מזל טוב\n",
      "Edge added: 38 6\n",
      "!מזל טוב\n",
      "Edge added: 38 7\n",
      "!מזל טוב\n",
      "Edge added: 38 8\n",
      "!מזל טוב\n",
      "Edge added: 38 20\n",
      "!מזל טוב\n",
      "Edge added: 38 0\n",
      "!מזל טוב\n",
      "Edge added: 38 25\n",
      "----------> Step 26 <----------\n",
      "Node added: 39\n",
      "!מזל טוב\n",
      "Edge added: 39 3\n",
      "!מזל טוב\n",
      "Edge added: 39 1\n",
      "!מזל טוב\n",
      "Edge added: 39 16\n",
      "!מזל טוב\n",
      "Edge added: 39 32\n",
      "!מזל טוב\n",
      "Edge added: 39 24\n",
      "!מזל טוב\n",
      "Edge added: 39 12\n",
      "!מזל טוב\n",
      "Edge added: 39 2\n",
      "----------> Step 27 <----------\n",
      "Node added: 40\n",
      "!מזל טוב\n",
      "Edge added: 40 3\n",
      "!מזל טוב\n",
      "Edge added: 40 7\n",
      "!מזל טוב\n",
      "Edge added: 40 2\n",
      "!מזל טוב\n",
      "Edge added: 40 5\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 40 32\n",
      "!מזל טוב\n",
      "Edge added: 40 9\n",
      "!מזל טוב\n",
      "Edge added: 40 37\n",
      "----------> Step 28 <----------\n",
      "Node added: 41\n",
      "!מזל טוב\n",
      "Edge added: 41 3\n",
      "!מזל טוב\n",
      "Edge added: 41 35\n",
      "!מזל טוב\n",
      "Edge added: 41 18\n",
      "!מזל טוב\n",
      "Edge added: 41 8\n",
      "!מזל טוב\n",
      "Edge added: 41 26\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 41 20\n",
      "!מזל טוב\n",
      "Edge added: 41 19\n",
      "----------> Step 29 <----------\n",
      "Node added: 42\n",
      "!מזל טוב\n",
      "Edge added: 42 8\n",
      "!מזל טוב\n",
      "Edge added: 42 10\n",
      "!מזל טוב\n",
      "Edge added: 42 26\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 42 18\n",
      "!מזל טוב\n",
      "Edge added: 42 21\n",
      "!מזל טוב\n",
      "Edge added: 42 2\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 42 23\n",
      "----------> Step 30 <----------\n",
      "Node added: 43\n",
      "!מזל טוב\n",
      "Edge added: 43 12\n",
      "!מזל טוב\n",
      "Edge added: 43 8\n",
      "!מזל טוב\n",
      "Edge added: 43 37\n",
      "!מזל טוב\n",
      "Edge added: 43 30\n",
      "!מזל טוב\n",
      "Edge added: 43 5\n",
      "!מזל טוב\n",
      "Edge added: 43 18\n",
      "!ככה לא בונים חומה\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 43 28\n",
      "----------> Step 31 <----------\n",
      "Node added: 44\n",
      "!מזל טוב\n",
      "Edge added: 44 16\n",
      "!מזל טוב\n",
      "Edge added: 44 8\n",
      "!מזל טוב\n",
      "Edge added: 44 2\n",
      "!מזל טוב\n",
      "Edge added: 44 26\n",
      "!מזל טוב\n",
      "Edge added: 44 6\n",
      "!מזל טוב\n",
      "Edge added: 44 0\n",
      "!מזל טוב\n",
      "Edge added: 44 18\n",
      "----------> Step 32 <----------\n",
      "Node added: 45\n",
      "!מזל טוב\n",
      "Edge added: 45 1\n",
      "!מזל טוב\n",
      "Edge added: 45 28\n",
      "!מזל טוב\n",
      "Edge added: 45 23\n",
      "!מזל טוב\n",
      "Edge added: 45 2\n",
      "!מזל טוב\n",
      "Edge added: 45 39\n",
      "!מזל טוב\n",
      "Edge added: 45 5\n",
      "!מזל טוב\n",
      "Edge added: 45 20\n",
      "----------> Step 33 <----------\n",
      "Node added: 46\n",
      "!מזל טוב\n",
      "Edge added: 46 33\n",
      "!מזל טוב\n",
      "Edge added: 46 16\n",
      "!מזל טוב\n",
      "Edge added: 46 7\n",
      "!מזל טוב\n",
      "Edge added: 46 3\n",
      "!מזל טוב\n",
      "Edge added: 46 10\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 46 25\n",
      "!ככה לא בונים חומה\n",
      "!ככה לא בונים חומה\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "!ככה לא בונים חומה\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 46 13\n",
      "----------> Step 34 <----------\n",
      "Node added: 47\n",
      "!מזל טוב\n",
      "Edge added: 47 36\n",
      "!מזל טוב\n",
      "Edge added: 47 6\n",
      "!מזל טוב\n",
      "Edge added: 47 24\n",
      "!מזל טוב\n",
      "Edge added: 47 7\n",
      "!מזל טוב\n",
      "Edge added: 47 4\n",
      "!מזל טוב\n",
      "Edge added: 47 31\n",
      "!מזל טוב\n",
      "Edge added: 47 29\n",
      "----------> Step 35 <----------\n",
      "Node added: 48\n",
      "!מזל טוב\n",
      "Edge added: 48 33\n",
      "!מזל טוב\n",
      "Edge added: 48 14\n",
      "!מזל טוב\n",
      "Edge added: 48 2\n",
      "!מזל טוב\n",
      "Edge added: 48 10\n",
      "!מזל טוב\n",
      "Edge added: 48 16\n",
      "!מזל טוב\n",
      "Edge added: 48 28\n",
      "!מזל טוב\n",
      "Edge added: 48 1\n",
      "----------> Step 36 <----------\n",
      "Node added: 49\n",
      "!מזל טוב\n",
      "Edge added: 49 10\n",
      "!מזל טוב\n",
      "Edge added: 49 16\n",
      "!מזל טוב\n",
      "Edge added: 49 12\n",
      "!מזל טוב\n",
      "Edge added: 49 23\n",
      "!מזל טוב\n",
      "Edge added: 49 2\n",
      "!מזל טוב\n",
      "Edge added: 49 41\n",
      "!מזל טוב\n",
      "Edge added: 49 11\n",
      "----------> Step 37 <----------\n",
      "Node added: 50\n",
      "!מזל טוב\n",
      "Edge added: 50 28\n",
      "!מזל טוב\n",
      "Edge added: 50 27\n",
      "!מזל טוב\n",
      "Edge added: 50 6\n",
      "!מזל טוב\n",
      "Edge added: 50 23\n",
      "!מזל טוב\n",
      "Edge added: 50 44\n",
      "!מזל טוב\n",
      "Edge added: 50 45\n",
      "!מזל טוב\n",
      "Edge added: 50 3\n",
      "----------> Step 38 <----------\n",
      "Node added: 51\n",
      "!מזל טוב\n",
      "Edge added: 51 44\n",
      "!מזל טוב\n",
      "Edge added: 51 26\n",
      "!מזל טוב\n",
      "Edge added: 51 17\n",
      "!מזל טוב\n",
      "Edge added: 51 6\n",
      "!מזל טוב\n",
      "Edge added: 51 16\n",
      "!מזל טוב\n",
      "Edge added: 51 10\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 51 3\n",
      "----------> Step 39 <----------\n",
      "Node added: 52\n",
      "!מזל טוב\n",
      "Edge added: 52 47\n",
      "!מזל טוב\n",
      "Edge added: 52 15\n",
      "!מזל טוב\n",
      "Edge added: 52 4\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 52 39\n",
      "!מזל טוב\n",
      "Edge added: 52 3\n",
      "!מזל טוב\n",
      "Edge added: 52 8\n",
      "!מזל טוב\n",
      "Edge added: 52 7\n",
      "----------> Step 40 <----------\n",
      "Node added: 53\n",
      "!מזל טוב\n",
      "Edge added: 53 10\n",
      "!מזל טוב\n",
      "Edge added: 53 6\n",
      "!מזל טוב\n",
      "Edge added: 53 23\n",
      "!מזל טוב\n",
      "Edge added: 53 19\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 53 1\n",
      "!מזל טוב\n",
      "Edge added: 53 2\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 53 41\n",
      "----------> Step 41 <----------\n",
      "Node added: 54\n",
      "!מזל טוב\n",
      "Edge added: 54 36\n",
      "!מזל טוב\n",
      "Edge added: 54 16\n",
      "!מזל טוב\n",
      "Edge added: 54 22\n",
      "!מזל טוב\n",
      "Edge added: 54 2\n",
      "!מזל טוב\n",
      "Edge added: 54 20\n",
      "!מזל טוב\n",
      "Edge added: 54 42\n",
      "!מזל טוב\n",
      "Edge added: 54 30\n",
      "----------> Step 42 <----------\n",
      "Node added: 55\n",
      "!מזל טוב\n",
      "Edge added: 55 10\n",
      "!מזל טוב\n",
      "Edge added: 55 45\n",
      "!מזל טוב\n",
      "Edge added: 55 28\n",
      "!מזל טוב\n",
      "Edge added: 55 24\n",
      "!מזל טוב\n",
      "Edge added: 55 23\n",
      "!מזל טוב\n",
      "Edge added: 55 6\n",
      "!מזל טוב\n",
      "Edge added: 55 2\n",
      "----------> Step 43 <----------\n",
      "Node added: 56\n",
      "!מזל טוב\n",
      "Edge added: 56 22\n",
      "!מזל טוב\n",
      "Edge added: 56 33\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 56 45\n",
      "!מזל טוב\n",
      "Edge added: 56 6\n",
      "!מזל טוב\n",
      "Edge added: 56 1\n",
      "!מזל טוב\n",
      "Edge added: 56 23\n",
      "!מזל טוב\n",
      "Edge added: 56 28\n",
      "----------> Step 44 <----------\n",
      "Node added: 57\n",
      "!מזל טוב\n",
      "Edge added: 57 23\n",
      "!מזל טוב\n",
      "Edge added: 57 9\n",
      "!מזל טוב\n",
      "Edge added: 57 2\n",
      "!מזל טוב\n",
      "Edge added: 57 17\n",
      "!מזל טוב\n",
      "Edge added: 57 3\n",
      "!מזל טוב\n",
      "Edge added: 57 15\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 57 30\n",
      "----------> Step 45 <----------\n",
      "Node added: 58\n",
      "!מזל טוב\n",
      "Edge added: 58 12\n",
      "!מזל טוב\n",
      "Edge added: 58 43\n",
      "!מזל טוב\n",
      "Edge added: 58 50\n",
      "!מזל טוב\n",
      "Edge added: 58 11\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 58 17\n",
      "!מזל טוב\n",
      "Edge added: 58 26\n",
      "!מזל טוב\n",
      "Edge added: 58 19\n",
      "----------> Step 46 <----------\n",
      "Node added: 59\n",
      "!מזל טוב\n",
      "Edge added: 59 3\n",
      "!מזל טוב\n",
      "Edge added: 59 9\n",
      "!מזל טוב\n",
      "Edge added: 59 2\n",
      "!מזל טוב\n",
      "Edge added: 59 26\n",
      "!מזל טוב\n",
      "Edge added: 59 10\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 59 0\n",
      "!מזל טוב\n",
      "Edge added: 59 8\n",
      "----------> Step 47 <----------\n",
      "Node added: 60\n",
      "!מזל טוב\n",
      "Edge added: 60 13\n",
      "!מזל טוב\n",
      "Edge added: 60 54\n",
      "!מזל טוב\n",
      "Edge added: 60 21\n",
      "!מזל טוב\n",
      "Edge added: 60 58\n",
      "!מזל טוב\n",
      "Edge added: 60 33\n",
      "!מזל טוב\n",
      "Edge added: 60 6\n",
      "!מזל טוב\n",
      "Edge added: 60 22\n",
      "----------> Step 48 <----------\n",
      "Node added: 61\n",
      "!מזל טוב\n",
      "Edge added: 61 5\n",
      "!מזל טוב\n",
      "Edge added: 61 10\n",
      "!מזל טוב\n",
      "Edge added: 61 30\n",
      "!מזל טוב\n",
      "Edge added: 61 9\n",
      "!מזל טוב\n",
      "Edge added: 61 32\n",
      "!מזל טוב\n",
      "Edge added: 61 16\n",
      "!מזל טוב\n",
      "Edge added: 61 24\n",
      "----------> Step 49 <----------\n",
      "Node added: 62\n",
      "!מזל טוב\n",
      "Edge added: 62 15\n",
      "!מזל טוב\n",
      "Edge added: 62 2\n",
      "!מזל טוב\n",
      "Edge added: 62 41\n",
      "!מזל טוב\n",
      "Edge added: 62 43\n",
      "!מזל טוב\n",
      "Edge added: 62 54\n",
      "!מזל טוב\n",
      "Edge added: 62 17\n",
      "!מזל טוב\n",
      "Edge added: 62 40\n",
      "----------> Step 50 <----------\n",
      "Node added: 63\n",
      "!מזל טוב\n",
      "Edge added: 63 28\n",
      "!מזל טוב\n",
      "Edge added: 63 21\n",
      "!מזל טוב\n",
      "Edge added: 63 8\n",
      "!מזל טוב\n",
      "Edge added: 63 4\n",
      "!מזל טוב\n",
      "Edge added: 63 35\n",
      "!מזל טוב\n",
      "Edge added: 63 2\n",
      "!מזל טוב\n",
      "Edge added: 63 56\n",
      "----------> Step 51 <----------\n",
      "Node added: 64\n",
      "!מזל טוב\n",
      "Edge added: 64 12\n",
      "!מזל טוב\n",
      "Edge added: 64 49\n",
      "!מזל טוב\n",
      "Edge added: 64 8\n",
      "!מזל טוב\n",
      "Edge added: 64 0\n",
      "!מזל טוב\n",
      "Edge added: 64 57\n",
      "!מזל טוב\n",
      "Edge added: 64 54\n",
      "!מזל טוב\n",
      "Edge added: 64 2\n",
      "----------> Step 52 <----------\n",
      "Node added: 65\n",
      "!מזל טוב\n",
      "Edge added: 65 50\n",
      "!מזל טוב\n",
      "Edge added: 65 30\n",
      "!מזל טוב\n",
      "Edge added: 65 21\n",
      "!מזל טוב\n",
      "Edge added: 65 9\n",
      "!מזל טוב\n",
      "Edge added: 65 16\n",
      "!מזל טוב\n",
      "Edge added: 65 7\n",
      "!מזל טוב\n",
      "Edge added: 65 6\n",
      "----------> Step 53 <----------\n",
      "Node added: 66\n",
      "!מזל טוב\n",
      "Edge added: 66 58\n",
      "!מזל טוב\n",
      "Edge added: 66 21\n",
      "!מזל טוב\n",
      "Edge added: 66 10\n",
      "!מזל טוב\n",
      "Edge added: 66 56\n",
      "!מזל טוב\n",
      "Edge added: 66 8\n",
      "!מזל טוב\n",
      "Edge added: 66 11\n",
      "!מזל טוב\n",
      "Edge added: 66 1\n",
      "----------> Step 54 <----------\n",
      "Node added: 67\n",
      "!מזל טוב\n",
      "Edge added: 67 0\n",
      "!מזל טוב\n",
      "Edge added: 67 46\n",
      "!מזל טוב\n",
      "Edge added: 67 19\n",
      "!מזל טוב\n",
      "Edge added: 67 20\n",
      "!מזל טוב\n",
      "Edge added: 67 31\n",
      "!מזל טוב\n",
      "Edge added: 67 13\n",
      "!מזל טוב\n",
      "Edge added: 67 58\n",
      "----------> Step 55 <----------\n",
      "Node added: 68\n",
      "!מזל טוב\n",
      "Edge added: 68 8\n",
      "!מזל טוב\n",
      "Edge added: 68 6\n",
      "!מזל טוב\n",
      "Edge added: 68 16\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 68 52\n",
      "!מזל טוב\n",
      "Edge added: 68 2\n",
      "!מזל טוב\n",
      "Edge added: 68 44\n",
      "!מזל טוב\n",
      "Edge added: 68 5\n",
      "----------> Step 56 <----------\n",
      "Node added: 69\n",
      "!מזל טוב\n",
      "Edge added: 69 41\n",
      "!מזל טוב\n",
      "Edge added: 69 14\n",
      "!מזל טוב\n",
      "Edge added: 69 20\n",
      "!מזל טוב\n",
      "Edge added: 69 65\n",
      "!מזל טוב\n",
      "Edge added: 69 1\n",
      "!מזל טוב\n",
      "Edge added: 69 30\n",
      "!מזל טוב\n",
      "Edge added: 69 34\n",
      "----------> Step 57 <----------\n",
      "Node added: 70\n",
      "!מזל טוב\n",
      "Edge added: 70 9\n",
      "!מזל טוב\n",
      "Edge added: 70 18\n",
      "!מזל טוב\n",
      "Edge added: 70 43\n",
      "!מזל טוב\n",
      "Edge added: 70 13\n",
      "!מזל טוב\n",
      "Edge added: 70 23\n",
      "!מזל טוב\n",
      "Edge added: 70 39\n",
      "!מזל טוב\n",
      "Edge added: 70 8\n",
      "----------> Step 58 <----------\n",
      "Node added: 71\n",
      "!מזל טוב\n",
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      "Edge added: 71 53\n",
      "----------> Step 59 <----------\n",
      "Node added: 72\n",
      "!מזל טוב\n",
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      "Edge added: 72 1\n",
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      "!ככה לא בונים חומה\n",
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      "!ככה לא בונים חומה\n",
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      "Edge added: 72 7\n",
      "----------> Step 60 <----------\n",
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      "Edge added: 73 2\n",
      "----------> Step 61 <----------\n",
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      "Edge added: 74 60\n",
      "!ככה לא בונים חומה\n",
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      "Edge added: 74 28\n",
      "!מזל טוב\n",
      "Edge added: 74 0\n",
      "----------> Step 62 <----------\n",
      "Node added: 75\n",
      "!מזל טוב\n",
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      "Edge added: 75 7\n",
      "----------> Step 63 <----------\n",
      "Node added: 76\n",
      "!מזל טוב\n",
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      "Edge added: 76 15\n",
      "!ככה לא בונים חומה\n",
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      "Edge added: 76 9\n",
      "!מזל טוב\n",
      "Edge added: 76 40\n",
      "----------> Step 64 <----------\n",
      "Node added: 77\n",
      "!מזל טוב\n",
      "Edge added: 77 26\n",
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      "Edge added: 77 28\n",
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      "!מזל טוב\n",
      "Edge added: 77 66\n",
      "!מזל טוב\n",
      "Edge added: 77 0\n",
      "!מזל טוב\n",
      "Edge added: 77 2\n",
      "!מזל טוב\n",
      "Edge added: 77 54\n",
      "----------> Step 65 <----------\n",
      "Node added: 78\n",
      "!מזל טוב\n",
      "Edge added: 78 58\n",
      "!מזל טוב\n",
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      "!מזל טוב\n",
      "Edge added: 78 73\n",
      "!מזל טוב\n",
      "Edge added: 78 2\n",
      "----------> Step 66 <----------\n",
      "Node added: 79\n",
      "!מזל טוב\n",
      "Edge added: 79 12\n",
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      "Edge added: 79 30\n",
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      "Edge added: 79 40\n",
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      "Edge added: 79 28\n",
      "!ככה לא בונים חומה\n",
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      "Edge added: 79 19\n",
      "!מזל טוב\n",
      "Edge added: 79 77\n",
      "!מזל טוב\n",
      "Edge added: 79 6\n",
      "----------> Step 67 <----------\n",
      "Node added: 80\n",
      "!מזל טוב\n",
      "Edge added: 80 0\n",
      "!מזל טוב\n",
      "Edge added: 80 25\n",
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      "Edge added: 80 20\n",
      "!מזל טוב\n",
      "Edge added: 80 3\n",
      "!מזל טוב\n",
      "Edge added: 80 12\n",
      "----------> Step 68 <----------\n",
      "Node added: 81\n",
      "!מזל טוב\n",
      "Edge added: 81 6\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 81 41\n",
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      "Edge added: 81 12\n",
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      "Edge added: 81 15\n",
      "!מזל טוב\n",
      "Edge added: 81 37\n",
      "!ככה לא בונים חומה\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 81 38\n",
      "!מזל טוב\n",
      "Edge added: 81 79\n",
      "----------> Step 69 <----------\n",
      "Node added: 82\n",
      "!מזל טוב\n",
      "Edge added: 82 11\n",
      "!מזל טוב\n",
      "Edge added: 82 12\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "!מזל טוב\n",
      "Edge added: 82 4\n",
      "!מזל טוב\n",
      "Edge added: 82 7\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 82 8\n",
      "!מזל טוב\n",
      "Edge added: 82 3\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 82 37\n",
      "----------> Step 70 <----------\n",
      "Node added: 83\n",
      "!מזל טוב\n",
      "Edge added: 83 6\n",
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      "!מזל טוב\n",
      "Edge added: 83 31\n",
      "!מזל טוב\n",
      "Edge added: 83 20\n",
      "----------> Step 71 <----------\n",
      "Node added: 84\n",
      "!מזל טוב\n",
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      "!מזל טוב\n",
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      "Edge added: 84 18\n",
      "!מזל טוב\n",
      "Edge added: 84 12\n",
      "----------> Step 72 <----------\n",
      "Node added: 85\n",
      "!מזל טוב\n",
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      "Edge added: 85 47\n",
      "----------> Step 73 <----------\n",
      "Node added: 86\n",
      "!מזל טוב\n",
      "Edge added: 86 10\n",
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      "Edge added: 86 21\n",
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      "Edge added: 86 8\n",
      "!ככה לא בונים חומה\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 86 20\n",
      "----------> Step 74 <----------\n",
      "Node added: 87\n",
      "!מזל טוב\n",
      "Edge added: 87 10\n",
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      "Edge added: 87 3\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 87 41\n",
      "----------> Step 75 <----------\n",
      "Node added: 88\n",
      "!מזל טוב\n",
      "Edge added: 88 40\n",
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      "Edge added: 88 8\n",
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      "Edge added: 88 3\n",
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      "!מזל טוב\n",
      "Edge added: 88 71\n",
      "!מזל טוב\n",
      "Edge added: 88 21\n",
      "----------> Step 76 <----------\n",
      "Node added: 89\n",
      "!מזל טוב\n",
      "Edge added: 89 8\n",
      "!מזל טוב\n",
      "Edge added: 89 0\n",
      "!מזל טוב\n",
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      "!מזל טוב\n",
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      "!מזל טוב\n",
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      "!מזל טוב\n",
      "Edge added: 89 47\n",
      "----------> Step 77 <----------\n",
      "Node added: 90\n",
      "!מזל טוב\n",
      "Edge added: 90 20\n",
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      "Edge added: 90 46\n",
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      "Edge added: 90 26\n",
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      "Edge added: 90 85\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 90 33\n",
      "!מזל טוב\n",
      "Edge added: 90 39\n",
      "----------> Step 78 <----------\n",
      "Node added: 91\n",
      "!מזל טוב\n",
      "Edge added: 91 41\n",
      "!מזל טוב\n",
      "Edge added: 91 5\n",
      "!מזל טוב\n",
      "Edge added: 91 67\n",
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      "!מזל טוב\n",
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      "!מזל טוב\n",
      "Edge added: 91 57\n",
      "!מזל טוב\n",
      "Edge added: 91 2\n",
      "----------> Step 79 <----------\n",
      "Node added: 92\n",
      "!מזל טוב\n",
      "Edge added: 92 17\n",
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      "Edge added: 92 3\n",
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      "Edge added: 92 43\n",
      "!מזל טוב\n",
      "Edge added: 92 16\n",
      "----------> Step 80 <----------\n",
      "Node added: 93\n",
      "!מזל טוב\n",
      "Edge added: 93 3\n",
      "!מזל טוב\n",
      "Edge added: 93 27\n",
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      "Edge added: 93 18\n",
      "!מזל טוב\n",
      "Edge added: 93 14\n",
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      "Edge added: 93 15\n",
      "!מזל טוב\n",
      "Edge added: 93 88\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 93 32\n",
      "----------> Step 81 <----------\n",
      "Node added: 94\n",
      "!מזל טוב\n",
      "Edge added: 94 24\n",
      "!מזל טוב\n",
      "Edge added: 94 62\n",
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      "!מזל טוב\n",
      "Edge added: 94 8\n",
      "!מזל טוב\n",
      "Edge added: 94 14\n",
      "----------> Step 82 <----------\n",
      "Node added: 95\n",
      "!מזל טוב\n",
      "Edge added: 95 0\n",
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      "Edge added: 95 21\n",
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      "!מזל טוב\n",
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      "!מזל טוב\n",
      "Edge added: 95 37\n",
      "!מזל טוב\n",
      "Edge added: 95 12\n",
      "----------> Step 83 <----------\n",
      "Node added: 96\n",
      "!מזל טוב\n",
      "Edge added: 96 42\n",
      "!מזל טוב\n",
      "Edge added: 96 23\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 96 84\n",
      "!מזל טוב\n",
      "Edge added: 96 19\n",
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      "Edge added: 96 12\n",
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      "Edge added: 96 27\n",
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      "Edge added: 96 9\n",
      "----------> Step 84 <----------\n",
      "Node added: 97\n",
      "!מזל טוב\n",
      "Edge added: 97 7\n",
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      "Edge added: 97 28\n",
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      "Edge added: 97 10\n",
      "----------> Step 85 <----------\n",
      "Node added: 98\n",
      "!מזל טוב\n",
      "Edge added: 98 2\n",
      "!מזל טוב\n",
      "Edge added: 98 36\n",
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      "Edge added: 98 10\n",
      "!מזל טוב\n",
      "Edge added: 98 79\n",
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      "!מזל טוב\n",
      "Edge added: 98 20\n",
      "!מזל טוב\n",
      "Edge added: 98 17\n",
      "----------> Step 86 <----------\n",
      "Node added: 99\n",
      "!מזל טוב\n",
      "Edge added: 99 86\n",
      "!מזל טוב\n",
      "Edge added: 99 21\n",
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      "Edge added: 99 36\n",
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      "Edge added: 99 8\n",
      "!מזל טוב\n",
      "Edge added: 99 45\n",
      "!מזל טוב\n",
      "Edge added: 99 54\n",
      "!מזל טוב\n",
      "Edge added: 99 90\n",
      "----------> Step 87 <----------\n",
      "Node added: 100\n",
      "!מזל טוב\n",
      "Edge added: 100 17\n",
      "!מזל טוב\n",
      "Edge added: 100 61\n",
      "!מזל טוב\n",
      "Edge added: 100 28\n",
      "!מזל טוב\n",
      "Edge added: 100 33\n",
      "!מזל טוב\n",
      "Edge added: 100 2\n",
      "!מזל טוב\n",
      "Edge added: 100 98\n",
      "!מזל טוב\n",
      "Edge added: 100 70\n",
      "----------> Step 88 <----------\n",
      "Node added: 101\n",
      "!מזל טוב\n",
      "Edge added: 101 54\n",
      "!מזל טוב\n",
      "Edge added: 101 7\n",
      "!מזל טוב\n",
      "Edge added: 101 20\n",
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      "Edge added: 101 77\n",
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      "Edge added: 101 93\n",
      "!מזל טוב\n",
      "Edge added: 101 59\n",
      "!מזל טוב\n",
      "Edge added: 101 51\n",
      "----------> Step 89 <----------\n",
      "Node added: 102\n",
      "!מזל טוב\n",
      "Edge added: 102 20\n",
      "!מזל טוב\n",
      "Edge added: 102 48\n",
      "!מזל טוב\n",
      "Edge added: 102 64\n",
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      "Edge added: 102 19\n",
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      "Edge added: 102 57\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 102 37\n",
      "!מזל טוב\n",
      "Edge added: 102 16\n",
      "----------> Step 90 <----------\n",
      "Node added: 103\n",
      "!מזל טוב\n",
      "Edge added: 103 2\n",
      "!מזל טוב\n",
      "Edge added: 103 27\n",
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      "Edge added: 103 52\n",
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      "Edge added: 103 61\n",
      "!מזל טוב\n",
      "Edge added: 103 83\n",
      "!מזל טוב\n",
      "Edge added: 103 40\n",
      "----------> Step 91 <----------\n",
      "Node added: 104\n",
      "!מזל טוב\n",
      "Edge added: 104 2\n",
      "!מזל טוב\n",
      "Edge added: 104 82\n",
      "!מזל טוב\n",
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      "Edge added: 104 35\n",
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      "!מזל טוב\n",
      "Edge added: 104 47\n",
      "!מזל טוב\n",
      "Edge added: 104 103\n",
      "----------> Step 92 <----------\n",
      "Node added: 105\n",
      "!מזל טוב\n",
      "Edge added: 105 26\n",
      "!מזל טוב\n",
      "Edge added: 105 31\n",
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      "Edge added: 105 63\n",
      "!מזל טוב\n",
      "Edge added: 105 1\n",
      "----------> Step 93 <----------\n",
      "Node added: 106\n",
      "!מזל טוב\n",
      "Edge added: 106 28\n",
      "!מזל טוב\n",
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      "!ככה לא בונים חומה\n",
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      "----------> Step 94 <----------\n",
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      "!מזל טוב\n",
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      "Edge added: 107 23\n",
      "!ככה לא בונים חומה\n",
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      "Edge added: 107 98\n",
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      "Edge added: 107 3\n",
      "----------> Step 95 <----------\n",
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      "----------> Step 96 <----------\n",
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      "Edge added: 109 2\n",
      "----------> Step 97 <----------\n",
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      "!ככה לא בונים חומה\n",
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      "Edge added: 110 68\n",
      "----------> Step 98 <----------\n",
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      "----------> Step 99 <----------\n",
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      "!מזל טוב\n",
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      "Edge added: 112 25\n",
      "----------> Step 100 <----------\n",
      "Node added: 113\n",
      "!מזל טוב\n",
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      "!מזל טוב\n",
      "Edge added: 113 39\n",
      "----------> Step 101 <----------\n",
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      "!מזל טוב\n",
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      "Edge added: 114 21\n",
      "----------> Step 102 <----------\n",
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      "Edge added: 115 34\n",
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      "Edge added: 115 41\n",
      "!ככה לא בונים חומה\n",
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      "Edge added: 115 95\n",
      "!מזל טוב\n",
      "Edge added: 115 25\n",
      "----------> Step 103 <----------\n",
      "Node added: 116\n",
      "!מזל טוב\n",
      "Edge added: 116 86\n",
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      "Edge added: 116 12\n",
      "----------> Step 104 <----------\n",
      "Node added: 117\n",
      "!מזל טוב\n",
      "Edge added: 117 1\n",
      "!מזל טוב\n",
      "Edge added: 117 37\n",
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      "Edge added: 117 8\n",
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      "Edge added: 117 54\n",
      "!מזל טוב\n",
      "Edge added: 117 6\n",
      "!מזל טוב\n",
      "Edge added: 117 25\n",
      "----------> Step 105 <----------\n",
      "Node added: 118\n",
      "!מזל טוב\n",
      "Edge added: 118 3\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "!מזל טוב\n",
      "Edge added: 118 1\n",
      "!מזל טוב\n",
      "Edge added: 118 31\n",
      "!מזל טוב\n",
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      "Edge added: 118 104\n",
      "----------> Step 106 <----------\n",
      "Node added: 119\n",
      "!מזל טוב\n",
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      "Edge added: 119 26\n",
      "----------> Step 107 <----------\n",
      "Node added: 120\n",
      "!מזל טוב\n",
      "Edge added: 120 24\n",
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      "Edge added: 120 1\n",
      "----------> Step 108 <----------\n",
      "Node added: 121\n",
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      "Edge added: 121 9\n",
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      "Edge added: 121 78\n",
      "!ככה לא בונים חומה\n",
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      "----------> Step 109 <----------\n",
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      "!מזל טוב\n",
      "Edge added: 122 103\n",
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      "----------> Step 110 <----------\n",
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      "----------> Step 111 <----------\n",
      "Node added: 124\n",
      "!מזל טוב\n",
      "Edge added: 124 109\n",
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      "!מזל טוב\n",
      "Edge added: 124 104\n",
      "----------> Step 112 <----------\n",
      "Node added: 125\n",
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      "Edge added: 125 61\n",
      "!מזל טוב\n",
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      "!מזל טוב\n",
      "Edge added: 125 12\n",
      "----------> Step 113 <----------\n",
      "Node added: 126\n",
      "!מזל טוב\n",
      "Edge added: 126 1\n",
      "!מזל טוב\n",
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      "----------> Step 114 <----------\n",
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      "Edge added: 127 14\n",
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      "!מזל טוב\n",
      "Edge added: 127 12\n",
      "----------> Step 115 <----------\n",
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      "Edge added: 128 57\n",
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      "Edge added: 128 28\n",
      "----------> Step 116 <----------\n",
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      "Edge added: 129 41\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 129 20\n",
      "----------> Step 117 <----------\n",
      "Node added: 130\n",
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      "Edge added: 130 31\n",
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      "----------> Step 118 <----------\n",
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      "!מזל טוב\n",
      "Edge added: 131 68\n",
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      "Edge added: 131 8\n",
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      "Edge added: 131 129\n",
      "----------> Step 119 <----------\n",
      "Node added: 132\n",
      "!מזל טוב\n",
      "Edge added: 132 6\n",
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      "----------> Step 120 <----------\n",
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      "Edge added: 133 4\n",
      "----------> Step 121 <----------\n",
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      "Edge added: 134 26\n",
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      "Edge added: 134 67\n",
      "----------> Step 122 <----------\n",
      "Node added: 135\n",
      "!מזל טוב\n",
      "Edge added: 135 3\n",
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      "Edge added: 135 16\n",
      "!מזל טוב\n",
      "Edge added: 135 61\n",
      "!מזל טוב\n",
      "Edge added: 135 131\n",
      "!מזל טוב\n",
      "Edge added: 135 24\n",
      "----------> Step 123 <----------\n",
      "Node added: 136\n",
      "!מזל טוב\n",
      "Edge added: 136 9\n",
      "!מזל טוב\n",
      "Edge added: 136 20\n",
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      "Edge added: 136 2\n",
      "!מזל טוב\n",
      "Edge added: 136 94\n",
      "!מזל טוב\n",
      "Edge added: 136 50\n",
      "----------> Step 124 <----------\n",
      "Node added: 137\n",
      "!מזל טוב\n",
      "Edge added: 137 12\n",
      "!מזל טוב\n",
      "Edge added: 137 0\n",
      "!מזל טוב\n",
      "Edge added: 137 73\n",
      "!מזל טוב\n",
      "Edge added: 137 59\n",
      "!ככה לא בונים חומה\n",
      "!מזל טוב\n",
      "Edge added: 137 10\n",
      "!מזל טוב\n",
      "Edge added: 137 2\n",
      "!מזל טוב\n",
      "Edge added: 137 7\n",
      "----------> Step 125 <----------\n",
      "Node added: 138\n",
      "!מזל טוב\n",
      "Edge added: 138 20\n",
      "!מזל טוב\n",
      "Edge added: 138 35\n",
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      "Edge added: 138 106\n",
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      "!מזל טוב\n",
      "Edge added: 138 2\n",
      "!מזל טוב\n",
      "Edge added: 138 72\n",
      "----------> Step 126 <----------\n",
      "Node added: 139\n",
      "!מזל טוב\n",
      "Edge added: 139 21\n",
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      "Edge added: 139 7\n",
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      "!מזל טוב\n",
      "Edge added: 139 6\n",
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      "Edge added: 139 69\n",
      "!מזל טוב\n",
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      "!מזל טוב\n",
      "Edge added: 139 70\n",
      "----------> Step 127 <----------\n",
      "Node added: 140\n",
      "!מזל טוב\n",
      "Edge added: 140 20\n",
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      "Edge added: 140 26\n",
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      "Edge added: 140 12\n",
      "----------> Step 128 <----------\n",
      "Node added: 141\n",
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      "Edge added: 141 27\n",
      "!מזל טוב\n",
      "Edge added: 141 41\n",
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      "Edge added: 141 0\n",
      "!ככה לא בונים חומה\n",
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      "Edge added: 141 26\n",
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      "Edge added: 141 120\n",
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      "Edge added: 141 134\n",
      "----------> Step 129 <----------\n",
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      "----------> Step 132 <----------\n",
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      "----------> Step 134 <----------\n",
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      "----------> Step 135 <----------\n",
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      "----------> Step 136 <----------\n",
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      "----------> Step 137 <----------\n",
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      "----------> Step 138 <----------\n",
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      "----------> Step 139 <----------\n",
      "Node added: 152\n",
      "!מזל טוב\n",
      "Edge added: 152 51\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "!מזל טוב\n",
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      "!מזל טוב\n",
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      "----------> Step 140 <----------\n",
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      "Edge added: 153 0\n",
      "!ככה לא בונים חומה\n",
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      "----------> Step 141 <----------\n",
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      "----------> Step 142 <----------\n",
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      "----------> Step 143 <----------\n",
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      "----------> Step 144 <----------\n",
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      "----------> Step 145 <----------\n",
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      "----------> Step 146 <----------\n",
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      "----------> Step 147 <----------\n",
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      "----------> Step 148 <----------\n",
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      "----------> Step 149 <----------\n",
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      "----------> Step 150 <----------\n",
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      "----------> Step 152 <----------\n",
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      "----------> Step 154 <----------\n",
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      "----------> Step 155 <----------\n",
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      "----------> Step 156 <----------\n",
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      "----------> Step 157 <----------\n",
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      "----------> Step 158 <----------\n",
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      "----------> Step 159 <----------\n",
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      "Edge added: 172 29\n",
      "!ככה לא בונים חומה\n",
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      "----------> Step 160 <----------\n",
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      "----------> Step 161 <----------\n",
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      "----------> Step 162 <----------\n",
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      "----------> Step 163 <----------\n",
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      "----------> Step 164 <----------\n",
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      "----------> Step 165 <----------\n",
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      "----------> Step 167 <----------\n",
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      "----------> Step 168 <----------\n",
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      "----------> Step 169 <----------\n",
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      "----------> Step 170 <----------\n",
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      "----------> Step 171 <----------\n",
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      "----------> Step 172 <----------\n",
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      "Edge added: 185 92\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "!מזל טוב\n",
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      "!מזל טוב\n",
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      "----------> Step 173 <----------\n",
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      "----------> Step 174 <----------\n",
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      "----------> Step 175 <----------\n",
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      "----------> Step 177 <----------\n",
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      "----------> Step 178 <----------\n",
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      "----------> Step 179 <----------\n",
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      "----------> Step 180 <----------\n",
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      "!ככה לא בונים חומה\n",
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      "----------> Step 181 <----------\n",
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      "----------> Step 182 <----------\n",
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      "----------> Step 190 <----------\n",
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      "----------> Step 191 <----------\n",
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      "----------> Step 192 <----------\n",
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      "----------> Step 193 <----------\n",
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      "----------> Step 194 <----------\n",
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      "----------> Step 195 <----------\n",
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      "----------> Step 196 <----------\n",
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      "----------> Step 197 <----------\n",
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      "----------> Step 198 <----------\n",
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      "----------> Step 199 <----------\n",
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      "----------> Step 200 <----------\n",
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      "----------> Step 201 <----------\n",
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      "----------> Step 202 <----------\n",
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      "----------> Step 203 <----------\n",
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      "----------> Step 204 <----------\n",
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      "----------> Step 205 <----------\n",
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      "Edge added: 218 9\n",
      "----------> Step 206 <----------\n",
      "Node added: 219\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "!מזל טוב\n",
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      "!מזל טוב\n",
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      "----------> Step 207 <----------\n",
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      "----------> Step 208 <----------\n",
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      "----------> Step 210 <----------\n",
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      "----------> Step 211 <----------\n",
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      "----------> Step 212 <----------\n",
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      "----------> Step 213 <----------\n",
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      "----------> Step 214 <----------\n",
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      "----------> Step 215 <----------\n",
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      "----------> Step 216 <----------\n",
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      "----------> Step 217 <----------\n",
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      "----------> Step 218 <----------\n",
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      "----------> Step 219 <----------\n",
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      "----------> Step 220 <----------\n",
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      "----------> Step 223 <----------\n",
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      "----------> Step 224 <----------\n",
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      "----------> Step 225 <----------\n",
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      "----------> Step 226 <----------\n",
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      "----------> Step 227 <----------\n",
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      "----------> Step 228 <----------\n",
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      "----------> Step 229 <----------\n",
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      "----------> Step 230 <----------\n",
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      "----------> Step 231 <----------\n",
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      "----------> Step 232 <----------\n",
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      "----------> Step 233 <----------\n",
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      "----------> Step 234 <----------\n",
      "Node added: 247\n",
      "!מזל טוב\n",
      "Edge added: 247 149\n",
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      "----------> Step 235 <----------\n",
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      "Edge added: 248 16\n",
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      "!מזל טוב\n",
      "Edge added: 248 31\n",
      "!מזל טוב\n",
      "Edge added: 248 121\n",
      "----------> Step 236 <----------\n",
      "Node added: 249\n",
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      "Edge added: 249 222\n",
      "----------> Step 237 <----------\n",
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      "!מזל טוב\n",
      "Edge added: 250 3\n",
      "\n",
      "Final number of nodes (250) reached\n",
      "\n",
      "\n",
      "Thanks! !תודה רבה :)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(\"***\\nWelcome to Barabási–Albert (BA) model simulation\\nAuthor: Aleksander Molak (2017)\\n!איזה כיף\\n\\n\")\n",
    "\n",
    "# Get parameters\n",
    "init_nodes = int(input(\"Please type in the initial number of nodes (m_0): \"))\n",
    "final_nodes = int(input(\"\\nPlease type in the final number of nodes: \"))\n",
    "m_parameter = int(input(\"\\nPlease type in the value of m parameter (m<=m_0): \"))\n",
    "\n",
    "print(\"\\n\")\n",
    "print(\"Creating initial graph...\")\n",
    "\n",
    "G = nx.complete_graph(init_nodes)\n",
    "\n",
    "print(\"Graph created. Number of nodes: {}\".format(len(G.nodes())))\n",
    "print(\"Adding nodes...\")\n",
    "\n",
    "count = 0\n",
    "new_node = init_nodes\n",
    "\n",
    "for f in range(final_nodes - init_nodes):\n",
    "    print(\"----------> Step {} <----------\".format(count))\n",
    "    G.add_node(init_nodes + count)\n",
    "    print(\"Node added: {}\".format(init_nodes + count + 1))\n",
    "    count += 1\n",
    "    for e in range(0, m_parameter):\n",
    "        add_edge()\n",
    "    new_node += 1\n",
    "\n",
    "\n",
    "print(\"\\nFinal number of nodes ({}) reached\".format(len(G.nodes())))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(None, None)"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "k_distrib(G), k_distrib(G, scale = 'log', fit_line = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the network\n",
    "nx.draw(G, alpha = .3, edge_color = COLOR, node_color = COLOR, node_size=50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}