1910 lines
692 KiB
Plaintext
1910 lines
692 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"from cadCAD.engine import ExecutionMode, ExecutionContext, Executor\n",
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"from cadCAD.configuration import Configuration\n",
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"import networkx as nx\n",
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"import matplotlib.pyplot as plt\n",
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"import numpy as np\n",
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"import scipy.stats as sts\n",
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"import pandas as pd\n",
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"import seaborn as sns\n",
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"import matplotlib.colors as colors\n",
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"import matplotlib.cm as cmx\n",
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"%matplotlib inline\n",
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"\n",
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"from scipy.stats import expon, gamma\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"This notebook uses the differential games framework developed by BlockScience. It is currently in private beta, and building towards a full open source release.\n",
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"\n",
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"**Description:**\n",
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"\n",
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"cadCAD is a Python library that assists in the processes of designing, testing and validating complex systems through simulation. At its core, cadCAD is a differential games engine that supports parameter sweeping and Monte Carlo analyses and can be easily integrated with other scientific computing Python modules and data science workflows.\n",
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"\n",
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"To learn more about cadCAD, follow our [tutorial series](https://github.com/BlockScience/cadCAD-Tutorials/tree/master/01%20Tutorials)\n",
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"\n",
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"**Installing cadCAD:**\n",
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"\n",
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"cadCAD is in private beta. Tokens are issued to participants. Replace `<TOKEN>` in the installation URL below\n",
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"```bash\n",
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"pip3 install cadCAD --extra-index-url https://<TOKEN>@repo.fury.io/blockscience/\n",
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"```\n",
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"\n",
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"If you'd like to participate in the beta program, contact cadcad [at] block [dot] science.\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"#helper functions\n",
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"def get_nodes_by_type(g, node_type_selection):\n",
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" return [node for node in g.nodes if g.nodes[node]['type']== node_type_selection ]\n",
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"\n",
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"def get_edges_by_type(g, edge_type_selection):\n",
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" return [edge for edge in g.edges if g.edges[edge]['type']== edge_type_selection ]\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"#THIS policy is one of the main paramters of this system!\n",
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"\n",
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"#maximum share of funds a proposal can take\n",
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"beta = .2 #later we should set this to be param so we can sweep it\n",
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"# tuning param for the trigger function\n",
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"rho = .001\n",
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"\n",
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"def trigger_threshold(requested, funds, supply):\n",
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" \n",
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" share = requested/funds\n",
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" if share < beta:\n",
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" return rho*supply/(beta-share)**2\n",
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" else: \n",
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" return np.inf\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"116844.75437064185\n"
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]
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}
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],
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"source": [
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"#generate an initial set of 'n' participants\n",
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"network = nx.DiGraph()\n",
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"n = 100\n",
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"for i in range(n):\n",
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" network.add_node(i)\n",
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" network.nodes[i]['type']=\"participant\"\n",
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" \n",
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" h_rv = expon.rvs(loc=0.0, scale=1000)\n",
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" network.nodes[i]['holdings'] = h_rv\n",
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" \n",
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" s_rv = np.random.rand() \n",
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" network.nodes[i]['sentiment'] = s_rv\n",
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"\n",
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"participants = get_nodes_by_type(network, 'participant')\n",
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"initial_supply = np.sum([ network.nodes[i]['holdings'] for i in participants])\n",
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"print(initial_supply)\n",
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"\n",
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"initial_funds = initial_supply\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"1.4735966604467947\n"
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]
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}
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],
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"source": [
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"#generate initial proposals\n",
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"m = 7\n",
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"for ind in range(m):\n",
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" j = n+ind\n",
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" network.add_node(j)\n",
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" network.nodes[j]['type']=\"proposal\"\n",
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" network.nodes[j]['conviction']=0\n",
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" network.nodes[j]['status']='candidate'\n",
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" network.nodes[j]['age']=0\n",
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" \n",
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" r_rv = gamma.rvs(3,loc=0.001, scale=10000)\n",
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" network.node[j]['funds_requested'] = r_rv\n",
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" \n",
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" network.nodes[j]['trigger']= trigger_threshold(r_rv, initial_funds, initial_supply)\n",
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" \n",
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" for i in range(n):\n",
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" network.add_edge(i, j)\n",
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" \n",
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" rv = np.random.rand()\n",
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" a_rv = 1-4*(1-rv)*rv #polarized distribution\n",
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" network.edges[(i, j)]['affinity'] = a_rv\n",
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" network.edges[(i,j)]['tokens'] = 0\n",
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" network.edges[(i, j)]['conviction'] = 0\n",
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"\n",
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"proposals = get_nodes_by_type(network, 'proposal')\n",
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"total_requested = np.sum([ network.nodes[i]['funds_requested'] for i in proposals])\n",
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"print(total_requested/initial_funds)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{'type': 'proposal',\n",
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" 'conviction': 0,\n",
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" 'status': 'candidate',\n",
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" 'age': 0,\n",
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" 'funds_requested': 23526.286910659088,\n",
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" 'trigger': inf}"
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]
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},
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"execution_count": 6,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"network.nodes[get_nodes_by_type(network, 'proposal')[0]]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
|
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"{'type': 'participant',\n",
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" 'holdings': 1803.1160251171434,\n",
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" 'sentiment': 0.260654441754802}"
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]
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},
|
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"execution_count": 7,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
|
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"network.nodes[get_nodes_by_type(network, 'participant')[0]]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"Text(0.5, 1.0, 'Histogram of Participants Token Holdings')"
|
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]
|
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},
|
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"execution_count": 8,
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"metadata": {},
|
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"output_type": "execute_result"
|
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},
|
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{
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"data": {
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"image/png": 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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.hist([ network.nodes[i]['holdings'] for i in participants])\n",
|
|
"plt.title('Histogram of Participants Token Holdings')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 9,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"Text(0.5, 1.0, 'Histogram of Proposals Funds Requested')"
|
|
]
|
|
},
|
|
"execution_count": 9,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.hist([ network.nodes[i]['funds_requested'] for i in proposals])\n",
|
|
"plt.title('Histogram of Proposals Funds Requested')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 10,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"Text(0.5, 1.0, 'Histogram of Affinities between Participants and Proposals')"
|
|
]
|
|
},
|
|
"execution_count": 10,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": "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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.hist([ network.edges[e]['affinity'] for e in network.edges])\n",
|
|
"plt.title('Histogram of Affinities between Participants and Proposals')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 11,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"Text(0.5, 1.0, 'Histogram of Affinities between Participants and Proposals weighted by holdings')"
|
|
]
|
|
},
|
|
"execution_count": 11,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
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"data": {
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"image/png": 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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.hist([ network.edges[e]['affinity'] for e in network.edges], weights = [network.nodes[e[0]]['holdings']for e in network.edges],alpha = 1)\n",
|
|
"plt.title('Histogram of Affinities between Participants and Proposals weighted by holdings')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 12,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"T = 200 #iterations of graph update in our simulation\n",
|
|
"#param for conviction accumilation\n",
|
|
"alpha = .5 #later we should set this to be param so we can sweep it\n",
|
|
"\n",
|
|
"#sentiment of the outside world which drives grants\n",
|
|
"initial_sentiment = .8\n",
|
|
"\n",
|
|
"#sentiment decay rate\n",
|
|
"mu =.001 #later we should set this to be param so we can sweep it\n",
|
|
"\n",
|
|
"#minimum periods passed before a proposal can pass\n",
|
|
"tmin = 7\n",
|
|
"\n",
|
|
"#how close to a participant's highest affinity proposal that\n",
|
|
"#another proposal has to be for them to be happy about its advancement\n",
|
|
"sensitivity = .75\n",
|
|
"\n",
|
|
"min_completion_rate = 10"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 13,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # \n",
|
|
"# Settings of general simulation parameters, unrelated to the system itself\n",
|
|
"# `T` is a range with the number of discrete units of time the simulation will run for;\n",
|
|
"# `N` is the number of times the simulation will be run (Monte Carlo runs)\n",
|
|
"# We'll cover the `M` key in a future article. For now, let's leave it empty\n",
|
|
"simulation_parameters = {\n",
|
|
" 'T': range(T),\n",
|
|
" 'N': 1,\n",
|
|
" 'M': {}\n",
|
|
"}"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 14,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"initial_conditions = {'network':network,\n",
|
|
" 'supply': initial_supply,\n",
|
|
" 'funds':initial_funds,\n",
|
|
" 'sentiment': initial_sentiment}"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 15,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"#functions for partial state update block 1\n",
|
|
"\n",
|
|
"def gen_new_participant(network, new_participant_holdings):\n",
|
|
" \n",
|
|
" i = len([node for node in network.nodes])\n",
|
|
" \n",
|
|
" network.add_node(i)\n",
|
|
" network.nodes[i]['type']=\"participant\"\n",
|
|
" \n",
|
|
" s_rv = np.random.rand() \n",
|
|
" network.nodes[i]['sentiment'] = s_rv\n",
|
|
" network.nodes[i]['holdings']=new_participant_holdings\n",
|
|
" \n",
|
|
" for j in get_nodes_by_type(network, 'proposal'):\n",
|
|
" network.add_edge(i, j)\n",
|
|
" \n",
|
|
" rv = np.random.rand()\n",
|
|
" a_rv = 1-4*(1-rv)*rv #polarized distribution\n",
|
|
" network.edges[(i, j)]['affinity'] = a_rv\n",
|
|
" network.edges[(i,j)]['tokens'] = a_rv*network.nodes[i]['holdings']\n",
|
|
" network.edges[(i, j)]['conviction'] = 0\n",
|
|
" \n",
|
|
" return network\n",
|
|
" \n",
|
|
"\n",
|
|
"def gen_new_proposal(network, funds, supply):\n",
|
|
" j = len([node for node in network.nodes])\n",
|
|
" network.add_node(j)\n",
|
|
" network.nodes[j]['type']=\"proposal\"\n",
|
|
" \n",
|
|
" network.nodes[j]['conviction']=0\n",
|
|
" network.nodes[j]['status']='candidate'\n",
|
|
" network.nodes[j]['age']=0\n",
|
|
" \n",
|
|
" rescale = 10000*funds/initial_funds\n",
|
|
" r_rv = gamma.rvs(3,loc=0.001, scale=rescale)\n",
|
|
" network.node[j]['funds_requested'] = r_rv\n",
|
|
" \n",
|
|
" network.nodes[j]['trigger']= trigger_threshold(r_rv, funds, supply)\n",
|
|
" \n",
|
|
" participants = get_nodes_by_type(network, 'participant')\n",
|
|
" proposing_participant = np.random.choice(participants)\n",
|
|
" \n",
|
|
" for i in participants:\n",
|
|
" network.add_edge(i, j)\n",
|
|
" if i==proposing_participant:\n",
|
|
" network.edges[(i, j)]['affinity']=1\n",
|
|
" else:\n",
|
|
" rv = np.random.rand()\n",
|
|
" a_rv = 1-4*(1-rv)*rv #polarized distribution\n",
|
|
" network.edges[(i, j)]['affinity'] = a_rv\n",
|
|
" \n",
|
|
" network.edges[(i, j)]['conviction'] = 0\n",
|
|
" network.edges[(i,j)]['tokens'] = 0\n",
|
|
" return network\n",
|
|
" \n",
|
|
" \n",
|
|
"\n",
|
|
"def driving_process(params, step, sL, s):\n",
|
|
" \n",
|
|
" #placeholder plumbing for random processes\n",
|
|
" arrival_rate = 10/s['sentiment']\n",
|
|
" rv1 = np.random.rand()\n",
|
|
" new_participant = bool(rv1<1/arrival_rate)\n",
|
|
" if new_participant:\n",
|
|
" h_rv = expon.rvs(loc=0.0, scale=1000)\n",
|
|
" new_participant_holdings = h_rv\n",
|
|
" else:\n",
|
|
" new_participant_holdings = 0\n",
|
|
" \n",
|
|
" network = s['network']\n",
|
|
" affinities = [network.edges[e]['affinity'] for e in network.edges ]\n",
|
|
" median_affinity = np.median(affinities)\n",
|
|
" \n",
|
|
" proposals = get_nodes_by_type(network, 'proposal')\n",
|
|
" fund_requests = [network.nodes[j]['funds_requested'] for j in proposals if network.nodes[j]['status']=='candidate' ]\n",
|
|
" \n",
|
|
" funds = s['funds']\n",
|
|
" total_funds_requested = np.sum(fund_requests)\n",
|
|
" \n",
|
|
" proposal_rate = 10/median_affinity * total_funds_requested/funds\n",
|
|
" rv2 = np.random.rand()\n",
|
|
" new_proposal = bool(rv2<1/proposal_rate)\n",
|
|
" \n",
|
|
" sentiment = s['sentiment']\n",
|
|
" funds = s['funds']\n",
|
|
" scale_factor = 1+4000*sentiment**2\n",
|
|
" \n",
|
|
" #this shouldn't happen but expon is throwing domain errors\n",
|
|
" if scale_factor > 1: \n",
|
|
" funds_arrival = expon.rvs(loc = 0, scale = scale_factor )\n",
|
|
" else:\n",
|
|
" funds_arrival = 0\n",
|
|
" \n",
|
|
" return({'new_participant':new_participant,\n",
|
|
" 'new_participant_holdings':new_participant_holdings,\n",
|
|
" 'new_proposal':new_proposal, \n",
|
|
" 'funds_arrival':funds_arrival})\n",
|
|
"\n",
|
|
"def update_network(params, step, sL, s, _input):\n",
|
|
" \n",
|
|
" network = s['network']\n",
|
|
" funds = s['funds']\n",
|
|
" supply = s['supply']\n",
|
|
" #placeholder plumbing for new proposals and new participants\n",
|
|
" new_participant = _input['new_participant'] #T/F\n",
|
|
" new_proposal = _input['new_proposal'] #T/F\n",
|
|
" # IF THEN logic to create new nodes // left out for now since always FALSE\n",
|
|
" if new_participant:\n",
|
|
" new_participant_holdings = _input['new_participant_holdings']\n",
|
|
" network = gen_new_participant(network, new_participant_holdings)\n",
|
|
" \n",
|
|
" if new_proposal:\n",
|
|
" network= gen_new_proposal(network,funds,supply )\n",
|
|
" \n",
|
|
" #update age of the existing proposals\n",
|
|
" proposals = get_nodes_by_type(network, 'proposal')\n",
|
|
" \n",
|
|
" for j in proposals:\n",
|
|
" network.nodes[j]['age'] = network.nodes[j]['age']+1\n",
|
|
" if network.nodes[j]['status'] == 'candidate':\n",
|
|
" requested = network.nodes[j]['funds_requested']\n",
|
|
" network.nodes[j]['trigger'] = trigger_threshold(requested, funds, supply)\n",
|
|
" else:\n",
|
|
" network.nodes[j]['trigger'] = np.nan\n",
|
|
" \n",
|
|
" key = 'network'\n",
|
|
" value = network\n",
|
|
" \n",
|
|
" return (key, value)\n",
|
|
"\n",
|
|
"def increment_funds(params, step, sL, s, _input):\n",
|
|
" \n",
|
|
" funds = s['funds']\n",
|
|
" funds_arrival = _input['funds_arrival']\n",
|
|
"\n",
|
|
" #increment funds\n",
|
|
" funds = funds + funds_arrival\n",
|
|
" \n",
|
|
" key = 'funds'\n",
|
|
" value = funds\n",
|
|
" \n",
|
|
" return (key, value)\n",
|
|
"\n",
|
|
"def increment_supply(params, step, sL, s, _input):\n",
|
|
" \n",
|
|
" supply = s['supply']\n",
|
|
" supply_arrival = _input['new_participant_holdings']\n",
|
|
"\n",
|
|
" #increment funds\n",
|
|
" supply = supply + supply_arrival\n",
|
|
" \n",
|
|
" key = 'supply'\n",
|
|
" value = supply\n",
|
|
" \n",
|
|
" return (key, value)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 16,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"#partial state update block 2\n",
|
|
"def check_progress(params, step, sL, s):\n",
|
|
" \n",
|
|
" network = s['network']\n",
|
|
" proposals = get_nodes_by_type(network, 'proposal')\n",
|
|
" \n",
|
|
" completed = []\n",
|
|
" for j in proposals:\n",
|
|
" if network.nodes[j]['status'] == 'active':\n",
|
|
" grant_size = network.nodes[j]['funds_requested']\n",
|
|
" likelihood = 1.0/(min_completion_rate+np.log(grant_size))\n",
|
|
" if np.random.rand() < likelihood:\n",
|
|
" completed.append(j)\n",
|
|
" \n",
|
|
" return({'completed':completed})\n",
|
|
"\n",
|
|
"def complete_proposal(params, step, sL, s, _input):\n",
|
|
" \n",
|
|
" network = s['network']\n",
|
|
" participants = get_nodes_by_type(network, 'participant')\n",
|
|
" \n",
|
|
" completed = _input['completed']\n",
|
|
" for j in completed:\n",
|
|
" network.nodes[j]['status']='completed'\n",
|
|
" for i in participants:\n",
|
|
" force = network.edges[(i,j)]['affinity']\n",
|
|
" sentiment = network.node[i]['sentiment']\n",
|
|
" network.node[i]['sentiment'] = get_sentimental(sentiment, force, decay=False)\n",
|
|
" \n",
|
|
" key = 'network'\n",
|
|
" value = network\n",
|
|
" \n",
|
|
" return (key, value)\n",
|
|
"\n",
|
|
"def update_sentiment_on_completion(params, step, sL, s, _input):\n",
|
|
" \n",
|
|
" network = s['network']\n",
|
|
" proposals = get_nodes_by_type(network, 'proposal')\n",
|
|
" completed = _input['completed']\n",
|
|
" \n",
|
|
" grants_outstanding = np.sum([network.nodes[j]['funds_requested'] for j in proposals if network.nodes[j]['status']=='active'])\n",
|
|
" \n",
|
|
" grants_completed = np.sum([network.nodes[j]['funds_requested'] for j in completed])\n",
|
|
" \n",
|
|
" sentiment = s['sentiment']\n",
|
|
" \n",
|
|
" force = grants_completed/grants_outstanding\n",
|
|
" if (force >=0) and (force <=1):\n",
|
|
" sentiment = get_sentimental(sentiment, force, True)\n",
|
|
" else:\n",
|
|
" sentiment = get_sentimental(sentiment, 0, True)\n",
|
|
" \n",
|
|
" \n",
|
|
" key = 'sentiment'\n",
|
|
" value = sentiment\n",
|
|
" \n",
|
|
" return (key, value)\n",
|
|
"\n",
|
|
"def get_sentimental(sentiment, force, decay=True):\n",
|
|
" sentiment = sentiment*(1-int(decay)*mu) + force\n",
|
|
" \n",
|
|
" if sentiment > 1:\n",
|
|
" sentiment = 1\n",
|
|
" \n",
|
|
" return sentiment"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 17,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"#partial state update block 3\n",
|
|
"def trigger_function(params, step, sL, s):\n",
|
|
" \n",
|
|
" network = s['network']\n",
|
|
" funds = s['funds']\n",
|
|
" supply = s['supply']\n",
|
|
" proposals = get_nodes_by_type(network, 'proposal')\n",
|
|
" \n",
|
|
" accepted = []\n",
|
|
" triggers = {}\n",
|
|
" for j in proposals:\n",
|
|
" if network.nodes[j]['status'] == 'candidate':\n",
|
|
" requested = network.nodes[j]['funds_requested']\n",
|
|
" age = network.nodes[j]['age']\n",
|
|
" threshold = trigger_threshold(requested, funds, supply)\n",
|
|
" if age > tmin:\n",
|
|
" conviction = network.nodes[j]['conviction']\n",
|
|
" if conviction >threshold:\n",
|
|
" accepted.append(j)\n",
|
|
" else:\n",
|
|
" threshold = np.nan\n",
|
|
" \n",
|
|
" triggers[j] = threshold\n",
|
|
" \n",
|
|
" \n",
|
|
" \n",
|
|
" return({'accepted':accepted, 'triggers':triggers})\n",
|
|
"\n",
|
|
"def decrement_funds(params, step, sL, s, _input):\n",
|
|
" \n",
|
|
" funds = s['funds']\n",
|
|
" network = s['network']\n",
|
|
" accepted = _input['accepted']\n",
|
|
"\n",
|
|
" #decrement funds\n",
|
|
" for j in accepted:\n",
|
|
" funds = funds - network.nodes[j]['funds_requested']\n",
|
|
" \n",
|
|
" key = 'funds'\n",
|
|
" value = funds\n",
|
|
" \n",
|
|
" return (key, value)\n",
|
|
"\n",
|
|
"def update_proposals(params, step, sL, s, _input):\n",
|
|
" \n",
|
|
" network = s['network']\n",
|
|
" accepted = _input['accepted']\n",
|
|
" triggers = _input['triggers']\n",
|
|
" participants = get_nodes_by_type(network, 'participant')\n",
|
|
" proposals = get_nodes_by_type(network, 'proposals')\n",
|
|
" \n",
|
|
" for j in proposals:\n",
|
|
" network.nodes[j]['trigger'] = triggers[j]\n",
|
|
" \n",
|
|
" #bookkeeping conviction and participant sentiment\n",
|
|
" for j in accepted:\n",
|
|
" network.nodes[j]['status']='active'\n",
|
|
" network.nodes[j]['conviction']=np.nan\n",
|
|
" #change status to active\n",
|
|
" for i in participants:\n",
|
|
" \n",
|
|
" edge = (i,j)\n",
|
|
" #reset tokens assigned to other candidates\n",
|
|
" network.edges[(i,j)]['tokens']=0\n",
|
|
" network.edges[(i,j)]['conviction'] = np.nan\n",
|
|
" \n",
|
|
" #update participants sentiments (positive or negative) \n",
|
|
" affinities = [network.edges[(i,p)]['affinity'] for p in proposals if not(p in accepted)]\n",
|
|
" if len(affinities)>1:\n",
|
|
" max_affinity = np.max(affinities)\n",
|
|
" force = network.edges[(i,j)]['affinity']-sensitivity*max_affinity\n",
|
|
" else:\n",
|
|
" force = 0\n",
|
|
" \n",
|
|
" #based on what their affinities to the accepted proposals\n",
|
|
" network.nodes[i]['sentiment'] = get_sentimental(network.nodes[i]['sentiment'], force, False)\n",
|
|
" \n",
|
|
" \n",
|
|
" key = 'network'\n",
|
|
" value = network\n",
|
|
" \n",
|
|
" return (key, value)\n",
|
|
"\n",
|
|
"def update_sentiment_on_release(params, step, sL, s, _input):\n",
|
|
" \n",
|
|
" network = s['network']\n",
|
|
" proposals = get_nodes_by_type(network, 'proposal')\n",
|
|
" accepted = _input['accepted']\n",
|
|
" \n",
|
|
" proposals_outstanding = np.sum([network.nodes[j]['funds_requested'] for j in proposals if network.nodes[j]['status']=='candidate'])\n",
|
|
" \n",
|
|
" proposals_accepted = np.sum([network.nodes[j]['funds_requested'] for j in accepted])\n",
|
|
" \n",
|
|
" sentiment = s['sentiment']\n",
|
|
" force = proposals_accepted/proposals_outstanding\n",
|
|
" if (force >=0) and (force <=1):\n",
|
|
" sentiment = get_sentimental(sentiment, force, False)\n",
|
|
" else:\n",
|
|
" sentiment = get_sentimental(sentiment, 0, False)\n",
|
|
" \n",
|
|
" key = 'sentiment'\n",
|
|
" value = sentiment\n",
|
|
" \n",
|
|
" return (key, value)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 18,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"def participants_decisions(params, step, sL, s):\n",
|
|
" \n",
|
|
" network = s['network']\n",
|
|
" participants = get_nodes_by_type(network, 'participant')\n",
|
|
" proposals = get_nodes_by_type(network, 'proposal')\n",
|
|
" candidates = [j for j in proposals if network.nodes[j]['status']=='candidate']\n",
|
|
" \n",
|
|
" gain = .01\n",
|
|
" delta_holdings={}\n",
|
|
" proposals_supported ={}\n",
|
|
" for i in participants:\n",
|
|
" force = network.nodes[i]['sentiment']-sensitivity\n",
|
|
" delta_holdings[i] = network.nodes[i]['holdings']*gain*force\n",
|
|
" \n",
|
|
" support = []\n",
|
|
" for j in candidates:\n",
|
|
" affinity = network.edges[(i, j)]['affinity']\n",
|
|
" cutoff = sensitivity*np.max([network.edges[(i,p)]['affinity'] for p in candidates])\n",
|
|
" if affinity > cutoff:\n",
|
|
" support.append(j)\n",
|
|
" \n",
|
|
" proposals_supported[i] = support\n",
|
|
" \n",
|
|
" return({'delta_holdings':delta_holdings, 'proposals_supported':proposals_supported})\n",
|
|
"\n",
|
|
"def update_tokens(params, step, sL, s, _input):\n",
|
|
" \n",
|
|
" network = s['network']\n",
|
|
" delta_holdings = _input['delta_holdings']\n",
|
|
" proposals = get_nodes_by_type(network, 'proposal')\n",
|
|
" proposals_supported = _input['proposals_supported']\n",
|
|
" participants = get_nodes_by_type(network, 'participant')\n",
|
|
" \n",
|
|
" for i in participants:\n",
|
|
" network.nodes[i]['holdings'] = network.nodes[i]['holdings']+delta_holdings[i]\n",
|
|
" supported = proposals_supported[i]\n",
|
|
" total_affinity = np.sum([ network.edges[(i, j)]['affinity'] for j in supported])\n",
|
|
" for j in proposals:\n",
|
|
" if j in supported:\n",
|
|
" normalized_affinity = network.edges[(i, j)]['affinity']/total_affinity\n",
|
|
" network.edges[(i, j)]['tokens'] = normalized_affinity*network.nodes[i]['holdings']\n",
|
|
" else:\n",
|
|
" network.edges[(i, j)]['tokens'] = 0\n",
|
|
" \n",
|
|
" prior_conviction = network.edges[(i, j)]['conviction']\n",
|
|
" current_tokens = network.edges[(i, j)]['tokens']\n",
|
|
" network.edges[(i, j)]['conviction'] =current_tokens+alpha*prior_conviction\n",
|
|
" \n",
|
|
" for j in proposals:\n",
|
|
" network.nodes[j]['conviction'] = np.sum([ network.edges[(i, j)]['conviction'] for i in participants])\n",
|
|
" \n",
|
|
" key = 'network'\n",
|
|
" value = network\n",
|
|
" \n",
|
|
" return (key, value)\n",
|
|
"\n",
|
|
"def update_supply(params, step, sL, s, _input):\n",
|
|
" \n",
|
|
" supply = s['supply']\n",
|
|
" delta_holdings = _input['delta_holdings']\n",
|
|
" delta_supply = np.sum([v for v in delta_holdings.values()])\n",
|
|
" \n",
|
|
" supply = supply + delta_supply\n",
|
|
" \n",
|
|
" key = 'supply'\n",
|
|
" value = supply\n",
|
|
" \n",
|
|
" return (key, value)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 19,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # \n",
|
|
"# The Partial State Update Blocks\n",
|
|
"partial_state_update_blocks = [\n",
|
|
" { \n",
|
|
" 'policies': { \n",
|
|
" #new proposals or new participants\n",
|
|
" 'random': driving_process\n",
|
|
" },\n",
|
|
" 'variables': {\n",
|
|
" 'network': update_network,\n",
|
|
" 'funds':increment_funds,\n",
|
|
" 'supply':increment_supply\n",
|
|
" }\n",
|
|
" },\n",
|
|
" {\n",
|
|
" 'policies': {\n",
|
|
" 'completion': check_progress #see if any of the funded proposals completes\n",
|
|
" },\n",
|
|
" 'variables': { # The following state variables will be updated simultaneously\n",
|
|
" 'sentiment': update_sentiment_on_completion, #note completing decays sentiment, completing bumps it\n",
|
|
" 'network': complete_proposal #book-keeping\n",
|
|
" }\n",
|
|
" },\n",
|
|
" {\n",
|
|
" 'policies': {\n",
|
|
" 'release': trigger_function #check each proposal to see if it passes\n",
|
|
" },\n",
|
|
" 'variables': { # The following state variables will be updated simultaneously\n",
|
|
" 'funds': decrement_funds, #funds expended\n",
|
|
" 'sentiment': update_sentiment_on_release, #releasing funds can bump sentiment\n",
|
|
" 'network': update_proposals #reset convictions, and participants sentiments\n",
|
|
" #update based on affinities\n",
|
|
" }\n",
|
|
" },\n",
|
|
" { \n",
|
|
" 'policies': { \n",
|
|
" 'participants_act': participants_decisions, #high sentiment, high affinity =>buy\n",
|
|
" #low sentiment, low affinities => burn\n",
|
|
" #assign tokens to top affinities\n",
|
|
" },\n",
|
|
" 'variables': {\n",
|
|
" 'supply': update_supply,\n",
|
|
" 'network': update_tokens #update everyones holdings \n",
|
|
" #and their conviction for each proposal\n",
|
|
" }\n",
|
|
" }\n",
|
|
"]"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 20,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # \n",
|
|
"# The configurations above are then packaged into a `Configuration` object\n",
|
|
"config = Configuration(initial_state=initial_conditions, #dict containing variable names and initial values\n",
|
|
" partial_state_update_blocks=partial_state_update_blocks, #dict containing state update functions\n",
|
|
" sim_config=simulation_parameters #dict containing simulation parameters\n",
|
|
" )"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 21,
|
|
"metadata": {
|
|
"scrolled": true
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"single_proc: [<cadCAD.configuration.Configuration object at 0x1a18defe48>]\n"
|
|
]
|
|
},
|
|
{
|
|
"name": "stderr",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:47: RuntimeWarning: invalid value encountered in double_scalars\n",
|
|
"/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:47: RuntimeWarning: divide by zero encountered in double_scalars\n",
|
|
"/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:95: RuntimeWarning: divide by zero encountered in double_scalars\n",
|
|
"/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:83: RuntimeWarning: divide by zero encountered in double_scalars\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"exec_mode = ExecutionMode()\n",
|
|
"exec_context = ExecutionContext(exec_mode.single_proc)\n",
|
|
"executor = Executor(exec_context, [config]) # Pass the configuration object inside an array\n",
|
|
"raw_result, tensor = executor.main() # The `main()` method returns a tuple; its first elements contains the raw results"
|
|
]
|
|
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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"df.supply.plot()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 25,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<matplotlib.axes._subplots.AxesSubplot at 0x1a2f7869b0>"
|
|
]
|
|
},
|
|
"execution_count": 25,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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\n",
|
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"text/plain": [
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|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"df.sentiment.plot()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 26,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<matplotlib.axes._subplots.AxesSubplot at 0x1a2f7c5780>"
|
|
]
|
|
},
|
|
"execution_count": 26,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"df.plot(x='timestep', y='funds')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 27,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"def pad(vec, length,fill=True):\n",
|
|
" \n",
|
|
" if fill:\n",
|
|
" padded = np.zeros(length,)\n",
|
|
" else:\n",
|
|
" padded = np.empty(length,)\n",
|
|
" padded[:] = np.nan\n",
|
|
" \n",
|
|
" for i in range(len(vec)):\n",
|
|
" padded[i]= vec[i]\n",
|
|
" \n",
|
|
" return padded\n",
|
|
"\n",
|
|
"def make2D(key, data, fill=False):\n",
|
|
" maxL = data[key].apply(len).max()\n",
|
|
" newkey = 'padded_'+key\n",
|
|
" data[newkey] = data[key].apply(lambda x: pad(x,maxL,fill))\n",
|
|
" reshaped = np.array([a for a in data[newkey].values])\n",
|
|
" \n",
|
|
" return reshaped"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 28,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"df['conviction'] = df.network.apply(lambda g: np.array([g.nodes[j]['conviction'] for j in get_nodes_by_type(g, 'proposal') if g.nodes[j]['status']=='candidate']))\n",
|
|
"df['candidate_count'] = df.network.apply(lambda g: len([j for j in get_nodes_by_type(g, 'proposal') if g.nodes[j]['status']=='candidate']))\n",
|
|
"df['candidate_funds'] = df.network.apply(lambda g: np.sum([g.nodes[j]['funds_requested'] for j in get_nodes_by_type(g, 'proposal') if g.nodes[j]['status']=='candidate']))\n",
|
|
"df['candidate_funds_requested'] = df.network.apply(lambda g: np.array([g.nodes[j]['funds_requested'] for j in get_nodes_by_type(g, 'proposal') if g.nodes[j]['status']=='candidate']))\n",
|
|
"df['active_count'] = df.network.apply(lambda g: len([j for j in get_nodes_by_type(g, 'proposal') if g.nodes[j]['status']=='active']))\n",
|
|
"df['active_funds'] = df.network.apply(lambda g: np.sum([g.nodes[j]['funds_requested'] for j in get_nodes_by_type(g, 'proposal') if g.nodes[j]['status']=='active']))\n",
|
|
"df['completed_count'] = df.network.apply(lambda g: len([j for j in get_nodes_by_type(g, 'proposal') if g.nodes[j]['status']=='completed']))\n",
|
|
"df['completed_funds'] = df.network.apply(lambda g: np.sum([g.nodes[j]['funds_requested'] for j in get_nodes_by_type(g, 'proposal') if g.nodes[j]['status']=='completed']))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 29,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"df['funds_requested'] = df.network.apply(lambda g: np.array([g.nodes[j]['funds_requested'] for j in get_nodes_by_type(g, 'proposal')]))\n",
|
|
"df['share_of_funds_requested'] = df.candidate_funds_requested/df.funds\n",
|
|
"\n",
|
|
"df['share_of_funds_requested_all'] = df.funds_requested/df.funds"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 30,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"df['triggers'] = df.network.apply(lambda g: np.array([g.nodes[j]['trigger'] for j in get_nodes_by_type(g, 'proposal') if g.nodes[j]['status']=='candidate' ]))\n",
|
|
"df['conviction_share_of_trigger'] = df.conviction/df.triggers\n",
|
|
"df['age'] = df.network.apply(lambda g: np.array([g.nodes[j]['age'] for j in get_nodes_by_type(g, 'proposal') if g.nodes[j]['status']=='candidate' ]))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 31,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"df['age_all'] = df.network.apply(lambda g: np.array([g.nodes[j]['age'] for j in get_nodes_by_type(g, 'proposal') ]))\n",
|
|
"df['conviction_all'] = df.network.apply(lambda g: np.array([g.nodes[j]['conviction'] for j in get_nodes_by_type(g, 'proposal') ]))\n",
|
|
"df['triggers_all'] = df.network.apply(lambda g: np.array([g.nodes[j]['trigger'] for j in get_nodes_by_type(g, 'proposal') ]))\n",
|
|
"\n",
|
|
"df['conviction_share_of_trigger_all'] = df.conviction_all/df.triggers_all"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 32,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"rdf= df[df.substep==4].copy()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 69,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"last_net= df.network.values[-1]\n",
|
|
"last_props=get_nodes_by_type(last_net, 'proposal')\n",
|
|
"M = len(last_props)\n",
|
|
"last_parts=get_nodes_by_type(last_net, 'participant')\n",
|
|
"N = len(last_parts)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 70,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"affinities = np.empty((N,M))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 71,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"for i_ind in range(N):\n",
|
|
" for j_ind in range(M):\n",
|
|
" i = last_parts[i_ind]\n",
|
|
" j = last_props[j_ind]\n",
|
|
" affinities[i_ind][j_ind] = last_net.edges[(i,j)]['affinity']"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 95,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"Text(5167.977272727274, 0.5, 'participant_id')"
|
|
]
|
|
},
|
|
"execution_count": 95,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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\n",
|
|
"text/plain": [
|
|
"<Figure size 7200x1800 with 2 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"dims = (100, 25)\n",
|
|
"fig, ax = plt.subplots(figsize=dims)\n",
|
|
"\n",
|
|
"sns.heatmap(affinities,\n",
|
|
" yticklabels=last_parts,\n",
|
|
" xticklabels=last_props,\n",
|
|
" square=True,\n",
|
|
" cbar=True,\n",
|
|
" ax=ax)\n",
|
|
"\n",
|
|
"plt.title('affinities between participants and proposals')\n",
|
|
"plt.xlabel('proposal_id')\n",
|
|
"plt.ylabel('participant_id')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 33,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"#working on deduplicating colors\n",
|
|
"#\n",
|
|
"#last_props=get_nodes_by_type(last_net, 'proposal')\n",
|
|
"#M = len(last_props)\n",
|
|
"\n",
|
|
"#cm = plt.get_cmap('gist_rainbow')\n",
|
|
"#c= [cm(1.*j/M) for j in range(M)] "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 34,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"Text(0.5, 1.0, 'check age')"
|
|
]
|
|
},
|
|
"execution_count": 34,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.plot(rdf.timestep,make2D('age_all', rdf))\n",
|
|
"plt.title('check age')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 35,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<matplotlib.axes._subplots.AxesSubplot at 0x1a2fb4e8d0>"
|
|
]
|
|
},
|
|
"execution_count": 35,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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\n",
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"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"rdf.plot(x='timestep',y=['candidate_count','active_count','completed_count'])"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 36,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<matplotlib.axes._subplots.AxesSubplot at 0x1a2fe04be0>"
|
|
]
|
|
},
|
|
"execution_count": 36,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"rdf.plot(x='timestep',y=['candidate_funds','active_funds','completed_funds'])"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 50,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"Text(0, 0.5, 'conviction')"
|
|
]
|
|
},
|
|
"execution_count": 50,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.semilogy(rdf.timestep,make2D('conviction_all', rdf))\n",
|
|
"plt.title('conviction by proposal')\n",
|
|
"plt.xlabel('time $t$')\n",
|
|
"plt.ylabel('conviction')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 49,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"Text(0, 0.5, 'conviction')"
|
|
]
|
|
},
|
|
"execution_count": 49,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.semilogy(make2D('age_all', rdf),make2D('conviction_all', rdf))\n",
|
|
"plt.title('conviction by proposal')\n",
|
|
"plt.xlabel('proposal age')\n",
|
|
"plt.ylabel('conviction')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 51,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"Text(0, 0.5, 'share_of_funds_requested')"
|
|
]
|
|
},
|
|
"execution_count": 51,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.plot(rdf.timestep,make2D('share_of_funds_requested_all', rdf))\n",
|
|
"plt.title('share_of_funds_requested by proposal')\n",
|
|
"plt.xlabel('time $t$')\n",
|
|
"plt.ylabel('share_of_funds_requested')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 40,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"Text(0, 0.5, 'share_of_funds_requested')"
|
|
]
|
|
},
|
|
"execution_count": 40,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.semilogy(make2D('age_all', rdf),make2D('share_of_funds_requested_all', rdf))\n",
|
|
"plt.title('share_of_funds_requested by proposal')\n",
|
|
"plt.xlabel('proposal age')\n",
|
|
"plt.ylabel('share_of_funds_requested')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 41,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"Text(0.5, 0, 'share_of_funds_requested')"
|
|
]
|
|
},
|
|
"execution_count": 41,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.loglog(make2D('share_of_funds_requested_all', rdf), make2D('conviction_all', rdf))\n",
|
|
"plt.ylabel('conviction')\n",
|
|
"plt.xlabel('share_of_funds_requested')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 42,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"Text(0.5, 0, 'proposal_age')"
|
|
]
|
|
},
|
|
"execution_count": 42,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.semilogy(make2D('age_all', rdf), make2D('triggers_all', rdf))\n",
|
|
"plt.ylabel('triggers')\n",
|
|
"plt.xlabel('proposal_age')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 48,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"Text(0.5, 1.0, 'phase: Triggers & Conviction')"
|
|
]
|
|
},
|
|
"execution_count": 48,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.loglog(make2D('conviction_all', rdf), make2D('triggers_all', rdf))\n",
|
|
"a = plt.axis()\n",
|
|
"plt.loglog(a[:2],a[2:], 'k',alpha=.5 )\n",
|
|
"plt.ylabel('triggers')\n",
|
|
"plt.xlabel('conviction')\n",
|
|
"plt.title('phase: Triggers & Conviction')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 44,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"Text(0, 0.5, 'conviction_share_of_trigger')"
|
|
]
|
|
},
|
|
"execution_count": 44,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.semilogy(rdf.timestep,make2D('conviction_share_of_trigger_all', rdf))\n",
|
|
"plt.title('conviction_share_of_trigger')\n",
|
|
"plt.xlabel('time $t$')\n",
|
|
"plt.ylabel('conviction_share_of_trigger')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 45,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"Text(0.5, 0, 'proposal_age')"
|
|
]
|
|
},
|
|
"execution_count": 45,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.semilogy(make2D('age_all', rdf), make2D('conviction_share_of_trigger_all', rdf))\n",
|
|
"plt.ylabel('triggers')\n",
|
|
"plt.xlabel('proposal_age')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 99,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"pos = {}\n",
|
|
"for ind in range(N):\n",
|
|
" i = last_parts[ind] \n",
|
|
" pos[i] = np.array([0, ind-N/2])\n",
|
|
"\n",
|
|
"for ind in range(M):\n",
|
|
" j = last_props[ind] \n",
|
|
" pos[j] = np.array([1, 2*N/M *ind-N])\n",
|
|
"\n",
|
|
"for i in last_parts:\n",
|
|
" for j in last_props:\n",
|
|
" "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 120,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"final_supply = df.supply.values[-1]"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 121,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"edges = last_net.edges\n",
|
|
"\n",
|
|
"E = len(edges)\n",
|
|
"\n",
|
|
"node_color = np.empty((M+N,4))\n",
|
|
"node_size = np.empty(M+N)\n",
|
|
"\n",
|
|
"edge_color = np.empty((E,4))\n",
|
|
"cm = plt.get_cmap('Reds')\n",
|
|
"\n",
|
|
"cNorm = colors.Normalize(vmin=0, vmax=final_supply)\n",
|
|
"scalarMap = cmx.ScalarMappable(norm=cNorm, cmap=cm)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 122,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"size_scale = 1/1000\n",
|
|
"\n",
|
|
"for j in last_props:\n",
|
|
" node_size[j] = last_net.nodes[j]['funds_requested']*size_scale\n",
|
|
" if last_net.nodes[j]['status']==\"candidate\":\n",
|
|
" node_color[j] = colors.to_rgba('blue')\n",
|
|
" elif last_net.nodes[j]['status']==\"active\":\n",
|
|
" node_color[j] = colors.to_rgba('orange')\n",
|
|
" elif last_net.nodes[j]['status']==\"completed\":\n",
|
|
" node_color[j] = colors.to_rgba('green')\n",
|
|
"\n",
|
|
"for i in last_parts: \n",
|
|
" node_size[i] = last_net.nodes[i]['holdings']*size_scale\n",
|
|
" node_color[i] = colors.to_rgba('red')\n",
|
|
" \n",
|
|
"for e in edges:\n",
|
|
" tokens = last_net.edges[e]['tokens']\n",
|
|
" edge_color[i] = scalarMap.to_rgba(tokens)\n",
|
|
" \n",
|
|
" "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 124,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"ename": "ValueError",
|
|
"evalue": "RGBA values should be within 0-1 range",
|
|
"output_type": "error",
|
|
"traceback": [
|
|
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
|
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
|
|
"\u001b[0;32m/anaconda3/lib/python3.6/site-packages/matplotlib/colors.py\u001b[0m in \u001b[0;36mto_rgba\u001b[0;34m(c, alpha)\u001b[0m\n\u001b[1;32m 173\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 174\u001b[0;31m \u001b[0mrgba\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_colors_full_map\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcache\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0malpha\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 175\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mKeyError\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;31m# Not in cache, or unhashable.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
|
"\u001b[0;31mTypeError\u001b[0m: unhashable type: 'numpy.ndarray'",
|
|
"\nDuring handling of the above exception, another exception occurred:\n",
|
|
"\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
|
|
"\u001b[0;32m<ipython-input-124-4b1dd1c61068>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mnx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdraw\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlast_net\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpos\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mpos\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnode_size\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnode_size\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnode_color\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnode_color\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0medge_color\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0medge_color\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
|
"\u001b[0;32m/anaconda3/lib/python3.6/site-packages/networkx/drawing/nx_pylab.py\u001b[0m in \u001b[0;36mdraw\u001b[0;34m(G, pos, ax, **kwds)\u001b[0m\n\u001b[1;32m 124\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 125\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 126\u001b[0;31m \u001b[0mdraw_networkx\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mG\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpos\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mpos\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 127\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_axis_off\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 128\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdraw_if_interactive\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
|
"\u001b[0;32m/anaconda3/lib/python3.6/site-packages/networkx/drawing/nx_pylab.py\u001b[0m in \u001b[0;36mdraw_networkx\u001b[0;34m(G, pos, arrows, with_labels, **kwds)\u001b[0m\n\u001b[1;32m 276\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 277\u001b[0m \u001b[0mnode_collection\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdraw_networkx_nodes\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mG\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpos\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 278\u001b[0;31m \u001b[0medge_collection\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdraw_networkx_edges\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mG\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpos\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0marrows\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0marrows\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 279\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mwith_labels\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 280\u001b[0m \u001b[0mdraw_networkx_labels\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mG\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpos\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
|
"\u001b[0;32m/anaconda3/lib/python3.6/site-packages/networkx/drawing/nx_pylab.py\u001b[0m in \u001b[0;36mdraw_networkx_edges\u001b[0;34m(G, pos, edgelist, width, edge_color, style, alpha, arrowstyle, arrowsize, edge_cmap, edge_vmin, edge_vmax, ax, arrows, label, node_size, nodelist, node_shape, **kwds)\u001b[0m\n\u001b[1;32m 682\u001b[0m \u001b[0mcolor\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0marrow_color\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 683\u001b[0m \u001b[0mlinewidth\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mline_width\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 684\u001b[0;31m zorder=1) # arrows go behind nodes\n\u001b[0m\u001b[1;32m 685\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 686\u001b[0m \u001b[0;31m# There seems to be a bug in matplotlib to make collections of\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
|
"\u001b[0;32m/anaconda3/lib/python3.6/site-packages/matplotlib/patches.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, posA, posB, path, arrowstyle, arrow_transmuter, connectionstyle, connector, patchA, patchB, shrinkA, shrinkB, mutation_scale, mutation_aspect, dpi_cor, **kwargs)\u001b[0m\n\u001b[1;32m 4019\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'connector'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4020\u001b[0m obj_type='keyword argument')\n\u001b[0;32m-> 4021\u001b[0;31m \u001b[0mPatch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__init__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 4022\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4023\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mposA\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mposB\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mpath\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
|
"\u001b[0;32m/anaconda3/lib/python3.6/site-packages/matplotlib/patches.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, edgecolor, facecolor, color, linewidth, linestyle, antialiased, hatch, fill, capstyle, joinstyle, **kwargs)\u001b[0m\n\u001b[1;32m 75\u001b[0m warnings.warn(\"Setting the 'color' property will override\"\n\u001b[1;32m 76\u001b[0m \"the edgecolor or facecolor properties.\")\n\u001b[0;32m---> 77\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_color\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcolor\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 78\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 79\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_edgecolor\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0medgecolor\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
|
"\u001b[0;32m/anaconda3/lib/python3.6/site-packages/matplotlib/patches.py\u001b[0m in \u001b[0;36mset_color\u001b[0;34m(self, c)\u001b[0m\n\u001b[1;32m 314\u001b[0m \u001b[0mc\u001b[0m \u001b[0;34m:\u001b[0m \u001b[0mcolor\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 315\u001b[0m \"\"\"\n\u001b[0;32m--> 316\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_facecolor\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 317\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_edgecolor\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 318\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
|
|
"\u001b[0;32m/anaconda3/lib/python3.6/site-packages/matplotlib/patches.py\u001b[0m in \u001b[0;36mset_facecolor\u001b[0;34m(self, color)\u001b[0m\n\u001b[1;32m 299\u001b[0m \"\"\"\n\u001b[1;32m 300\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_original_facecolor\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcolor\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 301\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_set_facecolor\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcolor\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 302\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 303\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mset_color\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
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"\u001b[0;32m/anaconda3/lib/python3.6/site-packages/matplotlib/patches.py\u001b[0m in \u001b[0;36m_set_facecolor\u001b[0;34m(self, color)\u001b[0m\n\u001b[1;32m 287\u001b[0m \u001b[0mcolor\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmpl\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrcParams\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'patch.facecolor'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 288\u001b[0m \u001b[0malpha\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_alpha\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_fill\u001b[0m \u001b[0;32melse\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 289\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_facecolor\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcolors\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mto_rgba\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcolor\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0malpha\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 290\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstale\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 291\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
|
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"\u001b[0;32m/anaconda3/lib/python3.6/site-packages/matplotlib/colors.py\u001b[0m in \u001b[0;36mto_rgba\u001b[0;34m(c, alpha)\u001b[0m\n\u001b[1;32m 174\u001b[0m \u001b[0mrgba\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_colors_full_map\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcache\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0malpha\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 175\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mKeyError\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;31m# Not in cache, or unhashable.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 176\u001b[0;31m \u001b[0mrgba\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_to_rgba_no_colorcycle\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0malpha\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 177\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 178\u001b[0m \u001b[0m_colors_full_map\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcache\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0malpha\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrgba\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;32m/anaconda3/lib/python3.6/site-packages/matplotlib/colors.py\u001b[0m in \u001b[0;36m_to_rgba_no_colorcycle\u001b[0;34m(c, alpha)\u001b[0m\n\u001b[1;32m 235\u001b[0m \u001b[0mc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;36m3\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0malpha\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 236\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0many\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0melem\u001b[0m \u001b[0;34m<\u001b[0m \u001b[0;36m0\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0melem\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m1\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0melem\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 237\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"RGBA values should be within 0-1 range\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 238\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mc\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 239\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
|
|
"\u001b[0;31mValueError\u001b[0m: RGBA values should be within 0-1 range"
|
|
]
|
|
},
|
|
{
|
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"data": {
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"image/png": 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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"nx.draw(last_net, pos=pos, node_size = node_size, node_color = node_color, edge_color = edge_color)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"df['node_count']=df.network.apply(lambda g:len(g.nodes))\n",
|
|
"df['net_growth']= df.node_count.diff()\n",
|
|
"nets = df[df.net_growth>0].network.values"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "raw",
|
|
"metadata": {
|
|
"scrolled": false
|
|
},
|
|
"source": [
|
|
"for i in range(len(nets)-1):\n",
|
|
" nx.draw(nets[i],pos=pos, alpha=.5, node_color='b')\n",
|
|
" nx.draw(nets[i+1],pos=pos, alpha=.5, node_color='g')\n",
|
|
" plt.title(\"Update: $G_{\"+str(i)+\"}$ to $G_{\"+str(i+1)+\"}$\")\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": "3.6.8"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 2
|
|
}
|