{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "import networkx as nx\n", "import pandas as pd\n", "import numpy as np\n", "from scipy import stats\n", "import scipy as sp\n", "import datetime as dt\n", "\n", "from ei_net import *\n", "from ce_net import *\n", "\n", "from collections import Counter\n", "\n", "%matplotlib inline" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# The emergence of informative higher scales in complex networks" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Chapter 09 - Spectral Causal Emergence\n", "_______________" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 9.1 Example of spectral coarse graining" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "N = 500\n", "m = 1\n", "G = check_network(nx.barabasi_albert_graph(N,m))\n", "micro_ei = effective_information(G)" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "CE = causal_emergence_spectral(G)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(7.3501707201207225, 6.915527921375582)" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "CE['EI_macro'], CE['EI_micro']" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "def preferential_attachment_network(N, alpha=1.0, m=1):\n", " \"\"\"\n", " Generates a network based off of a preferential attachment \n", " growth rule. Under this growth rule, new nodes place their \n", " $m$ edges to nodes already present in the graph, G, with \n", " a probability proportional to $k^\\alpha$.\n", " \n", " Params\n", " ------\n", " N (int): the desired number of nodes in the final network\n", " alpha (float): the exponent of preferential attachment. \n", " When alpha is less than 1.0, we describe it\n", " as sublinear preferential attachment. At\n", " alpha > 1.0, it is superlinear preferential\n", " attachment. And at alpha=1.0, the network \n", " was grown under linear preferential attachment,\n", " as in the case of Barabasi-Albert networks.\n", " m (int): the number of new links that each new node joins\n", " the network with.\n", " \n", " Returns\n", " -------\n", " G (nx.Graph): a graph grown under preferential attachment.\n", " \n", " \"\"\"\n", " G = nx.Graph()\n", " G = nx.complete_graph(m+1)\n", "\n", " for node_i in range(m+1,N):\n", " degrees = np.array(list(dict(G.degree()).values()))\n", " probs = (degrees**alpha) / sum(degrees**alpha)\n", " eijs = np.random.choice(\n", " G.number_of_nodes(), size=(m,), \n", " replace=False, p=probs)\n", " for node_j in eijs:\n", " G.add_edge(node_i, node_j)\n", "\n", " return G" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Done with 000 iterations at: 2020-04-06 09:02:15.483216\n", "Done with 050 iterations at: 2020-04-06 09:02:35.884519\n", "Done with 100 iterations at: 2020-04-06 09:02:56.906697\n", "Done with 150 iterations at: 2020-04-06 09:03:18.625842\n", "Done with 200 iterations at: 2020-04-06 09:03:39.493574\n", "Done with 250 iterations at: 2020-04-06 09:03:59.876086\n", "Done with 300 iterations at: 2020-04-06 09:04:23.914008\n", "Done with 350 iterations at: 2020-04-06 09:04:45.960118\n", "Done with 400 iterations at: 2020-04-06 09:05:05.929902\n", "Done with 450 iterations at: 2020-04-06 09:05:25.437096\n", "Done with 500 iterations at: 2020-04-06 09:05:45.083683\n", "Done with 550 iterations at: 2020-04-06 09:06:04.703855\n", "Done with 600 iterations at: 2020-04-06 09:06:24.021142\n", "Done with 650 iterations at: 2020-04-06 09:06:43.287885\n", "Done with 700 iterations at: 2020-04-06 09:07:03.243323\n", "Done with 750 iterations at: 2020-04-06 09:07:22.952634\n", "Done with 800 iterations at: 2020-04-06 09:07:42.952682\n", "Done with 850 iterations at: 2020-04-06 09:08:03.642744\n", "Done with 900 iterations at: 2020-04-06 09:08:22.967929\n", "Done with 950 iterations at: 2020-04-06 09:08:44.359410\n" ] } ], "source": [ "N = 100\n", "m = 1\n", "n_iter = 1000\n", "alphas = np.random.uniform(-1, 3, n_iter)\n", "out_alphas = {}\n", "for ai, alpha in enumerate(alphas):\n", " if ai % 50 == 0:\n", " print(\"Done with %03i iterations at:\"%ai,dt.datetime.now())\n", " G = preferential_attachment_network(N, alpha, m)\n", " CE = causal_emergence_spectral(G)\n", " ei_gain = CE['EI_macro'] - CE['EI_micro']\n", " eff_gain = ei_gain / np.log2(N)\n", " out_alphas[alpha] = {'ei_gain':ei_gain, 'eff_gain':eff_gain}" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 800x450 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.rc('axes', axisbelow=True)\n", "\n", "ei_gains = [i['ei_gain'] for i in out_alphas.values()]\n", "eff_gains = [i['eff_gain'] for i in out_alphas.values()]\n", "\n", "fig, ax = plt.subplots(1, 1, figsize=(4,2.25), dpi=200)\n", "\n", "ax.scatter(alphas, eff_gains, marker='o', s=10, c='.2', lw=0.25, edgecolors='.9')\n", "\n", "ax.set_ylabel('Effectiveness gain')\n", "ax.set_xlabel(r'$\\alpha$')\n", "ax.grid(linestyle='-', linewidth=1.3, color='.5', alpha=0.3)\n", "\n", "plt.show()" ] }, { "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": "3.7.4" } }, "nbformat": 4, "nbformat_minor": 2 }