mirror of
https://github.com/gsi-upm/soil
synced 2024-11-25 04:12:29 +00:00
feab0ba79e
The examples weren't being properly tested in the last commit. When we fixed that a lot of bugs in the new implementation of environment and agent were found, which accounts for most of these changes. The main difference is the mechanism to load simulations from a configuration file. For that to work, we had to rework our module loading code in `serialization` and add a `source_file` attribute to configurations (and simulations, for that matter).
5237 lines
1.2 MiB
5237 lines
1.2 MiB
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2017-10-19T12:41:48.007238Z",
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"start_time": "2017-10-19T14:41:47.980725+02:00"
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}
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},
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"source": [
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"# Soil Tutorial"
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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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"ExecuteTime": {
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"end_time": "2017-07-02T16:44:14.120953Z",
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"start_time": "2017-07-02T18:44:14.117152+02:00"
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}
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},
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"source": [
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"## Introduction"
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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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"cell_style": "center",
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"collapsed": true
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},
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"source": [
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"This notebook is an introduction to the soil agent-based social network simulation framework.\n",
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"In particular, we will focus on a specific use case: studying the propagation of news in a social network.\n",
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"\n",
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"The steps we will follow are:\n",
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"\n",
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"* Modelling the behavior of agents\n",
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"* Running the simulation using different configurations\n",
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"* Analysing the results of each simulation"
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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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"ExecuteTime": {
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"end_time": "2017-07-03T13:38:48.052876Z",
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||
"start_time": "2017-07-03T15:38:48.044762+02:00"
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}
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},
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"source": [
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"But before that, let's import the soil module and networkx."
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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": 1,
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"metadata": {
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||
"ExecuteTime": {
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"end_time": "2017-11-03T10:58:13.451481Z",
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"start_time": "2017-11-03T11:58:12.643469+01:00"
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||
}
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},
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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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"The autoreload extension is already loaded. To reload it, use:\n",
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" %reload_ext autoreload\n",
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"Populating the interactive namespace from numpy and matplotlib\n"
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]
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}
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],
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"source": [
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"import soil\n",
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"import networkx as nx\n",
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" \n",
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"%load_ext autoreload\n",
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"%autoreload 2\n",
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"\n",
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"%pylab inline\n",
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"# To display plots in the notebooed_"
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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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||
"ExecuteTime": {
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||
"end_time": "2017-07-03T13:41:19.788717Z",
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||
"start_time": "2017-07-03T15:41:19.785448+02:00"
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}
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},
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"source": [
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"## Basic concepts"
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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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"There are three main elements in a soil simulation:\n",
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" \n",
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"* The network topology. A simulation may use an existing NetworkX topology, or generate one on the fly\n",
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"* Agents. There are two types: 1) network agents, which are linked to a node in the topology, and 2) environment agents, which are freely assigned to the environment.\n",
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"* The environment. It assigns agents to nodes in the network, and stores the environment parameters (shared state for all agents).\n",
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"\n",
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"Soil is based on ``simpy``, which is an event-based network simulation library.\n",
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"Soil provides several abstractions over events to make developing agents easier.\n",
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"This means you can use events (timeouts, delays) in soil, but for the most part we will assume your models will be step-based.\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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||
"ExecuteTime": {
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||
"end_time": "2017-07-02T15:55:12.933978Z",
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||
"start_time": "2017-07-02T17:55:12.930860+02:00"
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}
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},
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"source": [
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"## Modeling behaviour"
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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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"ExecuteTime": {
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"end_time": "2017-07-03T13:49:31.269687Z",
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"start_time": "2017-07-03T15:49:31.257850+02:00"
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}
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},
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"source": [
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"Our first step will be to model how every person in the social network reacts when it comes to news.\n",
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"We will follow a very simple model (a finite state machine).\n",
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"\n",
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"There are two types of people, those who have heard about a newsworthy event (infected) or those who have not (neutral).\n",
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"A neutral person may heard about the news either on the TV (with probability **prob_tv_spread**) or through their friends.\n",
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"Once a person has heard the news, they will spread it to their friends (with a probability **prob_neighbor_spread**).\n",
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"Some users do not have a TV, so they only rely on their friends.\n",
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"\n",
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"The spreading probabilities will change over time due to different factors.\n",
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"We will represent this variance using an environment agent."
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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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"### Network Agents"
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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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"ExecuteTime": {
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||
"end_time": "2017-07-03T14:03:07.171127Z",
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"start_time": "2017-07-03T16:03:07.165779+02:00"
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}
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},
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"source": [
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"A basic network agent in Soil would typically inherit from ``soil.agents.NetworkAgent``, and define its behaviour in every step of the simulation by implementing a ``run(self)`` method.\n",
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"The most important attributes of the agent are:\n",
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"\n",
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"* ``agent.state``, a dictionary with the state of the agent. This tate will be saved in every step of the simulation. It can be accessed from the agent as well:\n",
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"```py\n",
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"a = soil.agents.NetworkAgent(env=env)\n",
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"agent.state['hours_of_sleep'] = 10\n",
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"# is the same as\n",
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"a['hours_of_sleep'] = 10\n",
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"```\n",
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" The state of the agent is stored in every step of the simulation:\n",
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" ```py\n",
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" print(a['hours_of_sleep', 10]) # hours of sleep before step #10\n",
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" print(a[None, 0]) # whole state of the agent before step #0\n",
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" ```\n",
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"\n",
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"* ``agent.env``, a reference to the environment. Most commonly used to get access to the environment parameters and the topology:\n",
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" ```py\n",
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" a.env.G.nodes() # Get all nodes ids in the topology\n",
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" a.env['minimum_hours_of_sleep']\n",
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"\n",
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" ```\n",
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"\n",
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"Since our model is a finite state machine, we will be basing it on ``soil.agents.FSM``.\n",
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"\n",
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"Agents that inherit from ``soil.agents.FSM`` do not need to specify a ``step`` method.\n",
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"Instead, we describe each finite state with a function.\n",
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"To change to another state, a function may return the new state, or the ``id`` of a state.\n",
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"If no state is returned, the state remains unchanged.\n",
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"\n",
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"The current state of the agent can be checked with ``agent.state['id']``. That state id can be used to look for other networks in that specific state\n",
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"\n",
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"\n",
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"Our agent will have of two states, ``neutral`` (default) and ``infected``.\n",
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"\n",
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"Here's the code:"
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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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"ExecuteTime": {
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||
"end_time": "2017-11-03T10:58:16.051690Z",
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"start_time": "2017-11-03T11:58:16.006044+01:00"
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}
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},
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"outputs": [],
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"source": [
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"import random\n",
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"\n",
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"class NewsSpread(soil.agents.FSM):\n",
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" @soil.agents.default_state\n",
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" @soil.agents.state\n",
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" def neutral(self):\n",
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" r = random.random()\n",
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" if self['has_tv'] and r < self.model['prob_tv_spread']:\n",
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" return self.infected\n",
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" return\n",
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" \n",
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" @soil.agents.state\n",
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" def infected(self):\n",
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" prob_infect = self.model['prob_neighbor_spread']\n",
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" for neighbor in self.get_neighboring_agents(state_id=self.neutral.id):\n",
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" r = random.random()\n",
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" if r < prob_infect:\n",
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" neighbor.next_state(self.infected.id)\n",
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" return\n",
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" "
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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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||
"ExecuteTime": {
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||
"end_time": "2017-07-02T12:22:53.931963Z",
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||
"start_time": "2017-07-02T14:22:53.928340+02:00"
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}
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},
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"source": [
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"### Environment agents"
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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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"Environment agents allow us to control the state of the environment.\n",
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"In this case, we will use an environment agent to simulate a very viral event.\n",
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"\n",
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"When the event happens, the agent will modify the probability of spreading the rumor."
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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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"ExecuteTime": {
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||
"end_time": "2017-11-03T10:58:17.653736Z",
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"start_time": "2017-11-03T11:58:17.612944+01:00"
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}
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},
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"outputs": [],
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"source": [
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"NEIGHBOR_FACTOR = 0.9\n",
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"TV_FACTOR = 0.5\n",
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"\n",
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"\n",
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"class NewsEnvironmentAgent(soil.agents.NetworkAgent):\n",
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" def step(self):\n",
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" if self.now == self['event_time']:\n",
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" self.model['prob_tv_spread'] = 1\n",
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" self.model['prob_neighbor_spread'] = 1\n",
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" elif self.now > self['event_time']:\n",
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" self.model['prob_tv_spread'] = self.model['prob_tv_spread'] * TV_FACTOR\n",
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" self.model['prob_neighbor_spread'] = self.model['prob_neighbor_spread'] * NEIGHBOR_FACTOR"
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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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||
"ExecuteTime": {
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||
"end_time": "2017-07-02T11:23:18.052235Z",
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"start_time": "2017-07-02T13:23:18.047452+02:00"
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}
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},
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"source": [
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"### Testing the agents"
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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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"ExecuteTime": {
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||
"end_time": "2017-07-02T16:14:54.572431Z",
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||
"start_time": "2017-07-02T18:14:54.564095+02:00"
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}
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||
},
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"source": [
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||
"Feel free to skip this section if this is your first time with soil."
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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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"Testing agents is not easy, and this is not a thorough testing process for agents.\n",
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"Rather, this section is aimed to show you how to access internal pats of soil so you can test your agents."
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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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"cell_style": "split"
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},
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"source": [
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"First of all, let's check if our network agent has the states we would expect:"
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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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||
"ExecuteTime": {
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||
"end_time": "2017-11-03T10:58:19.781155Z",
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"start_time": "2017-11-03T11:58:19.754362+01:00"
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},
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"cell_style": "split"
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{'neutral': <function __main__.NewsSpread.neutral(self)>,\n",
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" 'infected': <function __main__.NewsSpread.infected(self)>}"
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]
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},
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"execution_count": 4,
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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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"NewsSpread.states"
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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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"cell_style": "split"
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||
},
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"source": [
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"Now, let's run a simulation on a simple network. It is comprised of three nodes:\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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||
"ExecuteTime": {
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||
"end_time": "2017-11-03T10:58:20.791777Z",
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"start_time": "2017-11-03T11:58:20.565173+01:00"
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||
},
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||
"cell_style": "split",
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||
"scrolled": false
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},
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"outputs": [
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||
{
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"data": {
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||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"G = nx.Graph()\n",
|
||
"G.add_edge(0, 1)\n",
|
||
"G.add_edge(0, 2)\n",
|
||
"G.add_edge(2, 3)\n",
|
||
"G.add_node(4)\n",
|
||
"pos = nx.spring_layout(G)\n",
|
||
"nx.draw_networkx(G, pos, node_color='red')\n",
|
||
"nx.draw_networkx(G, pos, nodelist=[0], node_color='blue')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2017-07-03T11:53:30.997756Z",
|
||
"start_time": "2017-07-03T13:53:30.989609+02:00"
|
||
},
|
||
"cell_style": "split"
|
||
},
|
||
"source": [
|
||
"Let's run a simple simulation that assigns a NewsSpread agent to all the nodes in that network.\n",
|
||
"Notice how node 0 is the only one with a TV."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 6,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<module 'soil.agents' from '/home/j/git/lab.gsi/soil/soil/soil/agents/__init__.py'>"
|
||
]
|
||
},
|
||
"execution_count": 6,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"import importlib\n",
|
||
"importlib.reload(soil.agents)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 7,
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2017-11-03T10:58:55.517768Z",
|
||
"start_time": "2017-11-03T11:58:55.424083+01:00"
|
||
},
|
||
"cell_style": "split"
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"INFO:soil:Using exporters: [<class 'soil.exporters.default'>]\n",
|
||
"INFO:soil:Output directory: None\n",
|
||
"INFO:soil:Starting simulation Unnamed at 21:51:19.\n",
|
||
"INFO:soil:NOT dumping results\n",
|
||
"INFO:soil:Starting Simulation Unnamed trial Unnamed_trial_1605822679-0170248 at 21:51:19.\n",
|
||
"INFO:soil:Finished Simulation Unnamed trial Unnamed_trial_1605822679-0170248 at 21:51:19 in 0.006684064865112305 seconds\n",
|
||
"INFO:soil:Finished simulation Unnamed at 21:51:19 in 0.011702775955200195 seconds\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"env_params = {'prob_tv_spread': 0,\n",
|
||
" 'prob_neighbor_spread': 0}\n",
|
||
"\n",
|
||
"MAX_TIME = 100\n",
|
||
"EVENT_TIME = 10\n",
|
||
"\n",
|
||
"sim = soil.Simulation(topology=G,\n",
|
||
" num_trials=1,\n",
|
||
" max_time=MAX_TIME,\n",
|
||
" environment_agents=[{'agent_class': NewsEnvironmentAgent,\n",
|
||
" 'state': {\n",
|
||
" 'event_time': EVENT_TIME\n",
|
||
" }}],\n",
|
||
" network_agents=[{'agent_class': NewsSpread,\n",
|
||
" 'weight': 1}],\n",
|
||
" states={0: {'has_tv': True}},\n",
|
||
" default_state={'has_tv': False},\n",
|
||
" environment_params=env_params)\n",
|
||
"env = sim.run_simulation(dump=False)[0]"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"cell_style": "split"
|
||
},
|
||
"source": [
|
||
"Now we can access the results of the simulation and compare them to our expected results"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 8,
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2017-11-03T10:59:01.577474Z",
|
||
"start_time": "2017-11-03T11:59:01.414215+01:00"
|
||
},
|
||
"cell_style": "split",
|
||
"scrolled": false
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"agents = list(env.network_agents)\n",
|
||
"\n",
|
||
"# Until the event, all agents are neutral\n",
|
||
"for t in range(10):\n",
|
||
" for a in agents:\n",
|
||
" assert a['id', t] == a.neutral.id\n",
|
||
"\n",
|
||
"# After the event, the node with a TV is infected, the rest are not\n",
|
||
"assert agents[0]['id', 11] == NewsSpread.infected.id\n",
|
||
"assert agents[2]['id', 11] == NewsSpread.neutral.id\n",
|
||
"\n",
|
||
"\n",
|
||
"# At the end, the agents connected to the infected one will probably be infected, too.\n",
|
||
"assert agents[1]['id', MAX_TIME] == NewsSpread.infected.id\n",
|
||
"assert agents[2]['id', MAX_TIME] == NewsSpread.infected.id\n",
|
||
"\n",
|
||
"# But the node with no friends should not be affected\n",
|
||
"assert agents[4]['id', MAX_TIME] == NewsSpread.neutral.id\n",
|
||
" "
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2017-07-02T16:41:09.110652Z",
|
||
"start_time": "2017-07-02T18:41:09.106966+02:00"
|
||
},
|
||
"cell_style": "split"
|
||
},
|
||
"source": [
|
||
"Lastly, let's see if the probabilities have decreased as expected:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 9,
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2017-11-01T14:07:55.288616Z",
|
||
"start_time": "2017-11-01T15:07:55.241116+01:00"
|
||
},
|
||
"cell_style": "split"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"assert abs(env.environment_params['prob_neighbor_spread'] - (NEIGHBOR_FACTOR**(MAX_TIME-1-10))) < 10e-4\n",
|
||
"assert abs(env.environment_params['prob_tv_spread'] - (TV_FACTOR**(MAX_TIME-1-10))) < 10e-6"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Running the simulation"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2017-07-03T11:20:28.566944Z",
|
||
"start_time": "2017-07-03T13:20:28.561052+02:00"
|
||
},
|
||
"cell_style": "split"
|
||
},
|
||
"source": [
|
||
"To run a simulation, we need a configuration.\n",
|
||
"Soil can load configurations from python dictionaries as well as JSON and YAML files.\n",
|
||
"For this demo, we will use a python dictionary:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 10,
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2017-11-01T14:07:57.008940Z",
|
||
"start_time": "2017-11-01T15:07:56.966433+01:00"
|
||
},
|
||
"cell_style": "split"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"config = {\n",
|
||
" 'name': 'ExampleSimulation',\n",
|
||
" 'max_time': 20,\n",
|
||
" 'interval': 1,\n",
|
||
" 'num_trials': 1,\n",
|
||
" 'network_params': {\n",
|
||
" 'generator': 'complete_graph',\n",
|
||
" 'n': 500,\n",
|
||
" },\n",
|
||
" 'network_agents': [\n",
|
||
" {\n",
|
||
" 'agent_class': NewsSpread,\n",
|
||
" 'weight': 1,\n",
|
||
" 'state': {\n",
|
||
" 'has_tv': False\n",
|
||
" }\n",
|
||
" },\n",
|
||
" {\n",
|
||
" 'agent_class': NewsSpread,\n",
|
||
" 'weight': 2,\n",
|
||
" 'state': {\n",
|
||
" 'has_tv': True\n",
|
||
" }\n",
|
||
" }\n",
|
||
" ],\n",
|
||
" 'environment_agents':[\n",
|
||
" {'agent_class': NewsEnvironmentAgent,\n",
|
||
" 'state': {\n",
|
||
" 'event_time': 10\n",
|
||
" }\n",
|
||
" }\n",
|
||
" ],\n",
|
||
" 'states': [ {'has_tv': True} ],\n",
|
||
" 'environment_params':{\n",
|
||
" 'prob_tv_spread': 0.01,\n",
|
||
" 'prob_neighbor_spread': 0.5\n",
|
||
" }\n",
|
||
"}"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2017-07-03T11:57:34.219618Z",
|
||
"start_time": "2017-07-03T13:57:34.213817+02:00"
|
||
},
|
||
"cell_style": "split"
|
||
},
|
||
"source": [
|
||
"Let's run our simulation:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 11,
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2017-11-01T14:08:34.312637Z",
|
||
"start_time": "2017-11-01T15:07:57.774458+01:00"
|
||
},
|
||
"cell_style": "split"
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"INFO:soil:Using config(s): ExampleSimulation\n",
|
||
"INFO:soil:Using exporters: [<class 'soil.exporters.default'>]\n",
|
||
"INFO:soil:Output directory: None\n",
|
||
"INFO:soil:Starting simulation ExampleSimulation at 21:51:20.\n",
|
||
"INFO:soil:NOT dumping results\n",
|
||
"INFO:soil:Starting Simulation ExampleSimulation trial ExampleSimulation_trial_1605822680-0185008 at 21:51:20.\n",
|
||
"INFO:soil:Finished Simulation ExampleSimulation trial ExampleSimulation_trial_1605822680-0185008 at 21:51:22 in 1.9917693138122559 seconds\n",
|
||
"INFO:soil:Finished simulation ExampleSimulation at 21:51:22 in 2.4902079105377197 seconds\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"soil.simulation.run_from_config(config, dump=False)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2017-07-03T12:03:32.183588Z",
|
||
"start_time": "2017-07-03T14:03:32.167797+02:00"
|
||
},
|
||
"cell_style": "split",
|
||
"collapsed": true
|
||
},
|
||
"source": [
|
||
"In real life, you probably want to run several simulations, varying some of the parameters so that you can compare and answer your research questions.\n",
|
||
"\n",
|
||
"For instance:\n",
|
||
" \n",
|
||
"* Does the outcome depend on the structure of our network? We will use different generation algorithms to compare them (Barabasi-Albert and Erdos-Renyi)\n",
|
||
"* How does neighbor spreading probability affect my simulation? We will try probability values in the range of [0, 0.4], in intervals of 0.1."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 12,
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2017-11-01T14:10:38.099667Z",
|
||
"start_time": "2017-11-01T15:10:06.008314+01:00"
|
||
},
|
||
"cell_style": "split",
|
||
"scrolled": true
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"INFO:soil:Using config(s): Spread_erdos_renyi_graph_prob_0.0\n",
|
||
"INFO:soil:Using exporters: ['default', 'csv']\n",
|
||
"INFO:soil:Output directory: None\n",
|
||
"INFO:soil:Starting simulation Spread_erdos_renyi_graph_prob_0.0 at 21:51:22.\n",
|
||
"INFO:soil:Dumping results to /home/j/git/lab.gsi/soil/soil/examples/tutorial/soil_output/Spread_erdos_renyi_graph_prob_0.0\n",
|
||
"INFO:soil:Starting Simulation Spread_erdos_renyi_graph_prob_0.0 trial Spread_erdos_renyi_graph_prob_0-0_trial_1605822684-0959892 at 21:51:24.\n",
|
||
"INFO:soil:Finished Simulation Spread_erdos_renyi_graph_prob_0.0 trial Spread_erdos_renyi_graph_prob_0-0_trial_1605822684-0959892 at 21:51:24 in 0.2903263568878174 seconds\n",
|
||
"INFO:soil:Starting Dumping simulation Spread_erdos_renyi_graph_prob_0.0 trial Spread_erdos_renyi_graph_prob_0-0_trial_1605822684-0959892 at 21:51:24.\n",
|
||
"INFO:soil:Finished Dumping simulation Spread_erdos_renyi_graph_prob_0.0 trial Spread_erdos_renyi_graph_prob_0-0_trial_1605822684-0959892 at 21:51:24 in 0.0013904571533203125 seconds\n",
|
||
"INFO:soil:Starting [CSV] Dumping simulation Spread_erdos_renyi_graph_prob_0.0 trial Spread_erdos_renyi_graph_prob_0-0_trial_1605822684-0959892 @ dir /home/j/git/lab.gsi/soil/soil/examples/tutorial/soil_output/Spread_erdos_renyi_graph_prob_0.0 at 21:51:24.\n",
|
||
"INFO:soil:Finished [CSV] Dumping simulation Spread_erdos_renyi_graph_prob_0.0 trial Spread_erdos_renyi_graph_prob_0-0_trial_1605822684-0959892 @ dir /home/j/git/lab.gsi/soil/soil/examples/tutorial/soil_output/Spread_erdos_renyi_graph_prob_0.0 at 21:51:24 in 0.00780940055847168 seconds\n",
|
||
"INFO:soil:Finished simulation Spread_erdos_renyi_graph_prob_0.0 at 21:51:24 in 1.8845770359039307 seconds\n",
|
||
"INFO:soil:Using config(s): Spread_erdos_renyi_graph_prob_0.1\n",
|
||
"INFO:soil:Using exporters: ['default', 'csv']\n",
|
||
"INFO:soil:Output directory: None\n",
|
||
"INFO:soil:Starting simulation Spread_erdos_renyi_graph_prob_0.1 at 21:51:24.\n",
|
||
"INFO:soil:Dumping results to /home/j/git/lab.gsi/soil/soil/examples/tutorial/soil_output/Spread_erdos_renyi_graph_prob_0.1\n",
|
||
"INFO:soil:Starting Simulation Spread_erdos_renyi_graph_prob_0.1 trial Spread_erdos_renyi_graph_prob_0-1_trial_1605822686-1504185 at 21:51:26.\n",
|
||
"INFO:soil:Finished Simulation Spread_erdos_renyi_graph_prob_0.1 trial Spread_erdos_renyi_graph_prob_0-1_trial_1605822686-1504185 at 21:51:26 in 0.4628722667694092 seconds\n",
|
||
"INFO:soil:Starting Dumping simulation Spread_erdos_renyi_graph_prob_0.1 trial Spread_erdos_renyi_graph_prob_0-1_trial_1605822686-1504185 at 21:51:26.\n",
|
||
"INFO:soil:Finished Dumping simulation Spread_erdos_renyi_graph_prob_0.1 trial Spread_erdos_renyi_graph_prob_0-1_trial_1605822686-1504185 at 21:51:26 in 0.0014166831970214844 seconds\n",
|
||
"INFO:soil:Starting [CSV] Dumping simulation Spread_erdos_renyi_graph_prob_0.1 trial Spread_erdos_renyi_graph_prob_0-1_trial_1605822686-1504185 @ dir /home/j/git/lab.gsi/soil/soil/examples/tutorial/soil_output/Spread_erdos_renyi_graph_prob_0.1 at 21:51:26.\n",
|
||
"INFO:soil:Finished [CSV] Dumping simulation Spread_erdos_renyi_graph_prob_0.1 trial Spread_erdos_renyi_graph_prob_0-1_trial_1605822686-1504185 @ dir /home/j/git/lab.gsi/soil/soil/examples/tutorial/soil_output/Spread_erdos_renyi_graph_prob_0.1 at 21:51:26 in 0.007503986358642578 seconds\n",
|
||
"INFO:soil:Finished simulation Spread_erdos_renyi_graph_prob_0.1 at 21:51:26 in 2.144615888595581 seconds\n",
|
||
"INFO:soil:Using config(s): Spread_erdos_renyi_graph_prob_0.2\n",
|
||
"INFO:soil:Using exporters: ['default', 'csv']\n",
|
||
"INFO:soil:Output directory: None\n",
|
||
"INFO:soil:Starting simulation Spread_erdos_renyi_graph_prob_0.2 at 21:51:26.\n",
|
||
"INFO:soil:Dumping results to /home/j/git/lab.gsi/soil/soil/examples/tutorial/soil_output/Spread_erdos_renyi_graph_prob_0.2\n",
|
||
"INFO:soil:Starting Simulation Spread_erdos_renyi_graph_prob_0.2 trial Spread_erdos_renyi_graph_prob_0-2_trial_1605822688-204787 at 21:51:28.\n",
|
||
"INFO:soil:Finished Simulation Spread_erdos_renyi_graph_prob_0.2 trial Spread_erdos_renyi_graph_prob_0-2_trial_1605822688-204787 at 21:51:28 in 0.37325096130371094 seconds\n",
|
||
"INFO:soil:Starting Dumping simulation Spread_erdos_renyi_graph_prob_0.2 trial Spread_erdos_renyi_graph_prob_0-2_trial_1605822688-204787 at 21:51:28.\n",
|
||
"INFO:soil:Finished Dumping simulation Spread_erdos_renyi_graph_prob_0.2 trial Spread_erdos_renyi_graph_prob_0-2_trial_1605822688-204787 at 21:51:28 in 0.0016696453094482422 seconds\n",
|
||
"INFO:soil:Starting [CSV] Dumping simulation Spread_erdos_renyi_graph_prob_0.2 trial Spread_erdos_renyi_graph_prob_0-2_trial_1605822688-204787 @ dir /home/j/git/lab.gsi/soil/soil/examples/tutorial/soil_output/Spread_erdos_renyi_graph_prob_0.2 at 21:51:28.\n",
|
||
"INFO:soil:Finished [CSV] Dumping simulation Spread_erdos_renyi_graph_prob_0.2 trial Spread_erdos_renyi_graph_prob_0-2_trial_1605822688-204787 @ dir /home/j/git/lab.gsi/soil/soil/examples/tutorial/soil_output/Spread_erdos_renyi_graph_prob_0.2 at 21:51:28 in 0.007451057434082031 seconds\n",
|
||
"INFO:soil:Finished simulation Spread_erdos_renyi_graph_prob_0.2 at 21:51:28 in 1.9053213596343994 seconds\n",
|
||
"INFO:soil:Using config(s): Spread_erdos_renyi_graph_prob_0.3\n",
|
||
"INFO:soil:Using exporters: ['default', 'csv']\n",
|
||
"INFO:soil:Output directory: None\n",
|
||
"INFO:soil:Starting simulation Spread_erdos_renyi_graph_prob_0.3 at 21:51:28.\n",
|
||
"INFO:soil:Dumping results to /home/j/git/lab.gsi/soil/soil/examples/tutorial/soil_output/Spread_erdos_renyi_graph_prob_0.3\n",
|
||
"INFO:soil:Starting Simulation Spread_erdos_renyi_graph_prob_0.3 trial Spread_erdos_renyi_graph_prob_0-3_trial_1605822690-3038263 at 21:51:30.\n",
|
||
"INFO:soil:Finished Simulation Spread_erdos_renyi_graph_prob_0.3 trial Spread_erdos_renyi_graph_prob_0-3_trial_1605822690-3038263 at 21:51:30 in 0.397489070892334 seconds\n",
|
||
"INFO:soil:Starting Dumping simulation Spread_erdos_renyi_graph_prob_0.3 trial Spread_erdos_renyi_graph_prob_0-3_trial_1605822690-3038263 at 21:51:30.\n",
|
||
"INFO:soil:Finished Dumping simulation Spread_erdos_renyi_graph_prob_0.3 trial Spread_erdos_renyi_graph_prob_0-3_trial_1605822690-3038263 at 21:51:30 in 0.0012001991271972656 seconds\n",
|
||
"INFO:soil:Starting [CSV] Dumping simulation Spread_erdos_renyi_graph_prob_0.3 trial Spread_erdos_renyi_graph_prob_0-3_trial_1605822690-3038263 @ dir /home/j/git/lab.gsi/soil/soil/examples/tutorial/soil_output/Spread_erdos_renyi_graph_prob_0.3 at 21:51:30.\n",
|
||
"INFO:soil:Finished [CSV] Dumping simulation Spread_erdos_renyi_graph_prob_0.3 trial Spread_erdos_renyi_graph_prob_0-3_trial_1605822690-3038263 @ dir /home/j/git/lab.gsi/soil/soil/examples/tutorial/soil_output/Spread_erdos_renyi_graph_prob_0.3 at 21:51:30 in 0.007926225662231445 seconds\n",
|
||
"INFO:soil:Finished simulation Spread_erdos_renyi_graph_prob_0.3 at 21:51:30 in 2.0851120948791504 seconds\n",
|
||
"INFO:soil:Using config(s): Spread_erdos_renyi_graph_prob_0.4\n",
|
||
"INFO:soil:Using exporters: ['default', 'csv']\n",
|
||
"INFO:soil:Output directory: None\n",
|
||
"INFO:soil:Starting simulation Spread_erdos_renyi_graph_prob_0.4 at 21:51:30.\n",
|
||
"INFO:soil:Dumping results to /home/j/git/lab.gsi/soil/soil/examples/tutorial/soil_output/Spread_erdos_renyi_graph_prob_0.4\n",
|
||
"INFO:soil:Starting Simulation Spread_erdos_renyi_graph_prob_0.4 trial Spread_erdos_renyi_graph_prob_0-4_trial_1605822692-3893287 at 21:51:32.\n",
|
||
"INFO:soil:Finished Simulation Spread_erdos_renyi_graph_prob_0.4 trial Spread_erdos_renyi_graph_prob_0-4_trial_1605822692-3893287 at 21:51:32 in 0.3599538803100586 seconds\n",
|
||
"INFO:soil:Starting Dumping simulation Spread_erdos_renyi_graph_prob_0.4 trial Spread_erdos_renyi_graph_prob_0-4_trial_1605822692-3893287 at 21:51:32.\n",
|
||
"INFO:soil:Finished Dumping simulation Spread_erdos_renyi_graph_prob_0.4 trial Spread_erdos_renyi_graph_prob_0-4_trial_1605822692-3893287 at 21:51:32 in 0.0013287067413330078 seconds\n",
|
||
"INFO:soil:Starting [CSV] Dumping simulation Spread_erdos_renyi_graph_prob_0.4 trial Spread_erdos_renyi_graph_prob_0-4_trial_1605822692-3893287 @ dir /home/j/git/lab.gsi/soil/soil/examples/tutorial/soil_output/Spread_erdos_renyi_graph_prob_0.4 at 21:51:32.\n",
|
||
"INFO:soil:Finished [CSV] Dumping simulation Spread_erdos_renyi_graph_prob_0.4 trial Spread_erdos_renyi_graph_prob_0-4_trial_1605822692-3893287 @ dir /home/j/git/lab.gsi/soil/soil/examples/tutorial/soil_output/Spread_erdos_renyi_graph_prob_0.4 at 21:51:32 in 0.007839202880859375 seconds\n",
|
||
"INFO:soil:Finished simulation Spread_erdos_renyi_graph_prob_0.4 at 21:51:32 in 2.00582218170166 seconds\n",
|
||
"INFO:soil:Using config(s): Spread_barabasi_albert_graph_prob_0.0\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"INFO:soil:Using exporters: ['default', 'csv']\n",
|
||
"INFO:soil:Output directory: None\n",
|
||
"INFO:soil:Starting simulation Spread_barabasi_albert_graph_prob_0.0 at 21:51:32.\n",
|
||
"INFO:soil:Dumping results to /home/j/git/lab.gsi/soil/soil/examples/tutorial/soil_output/Spread_barabasi_albert_graph_prob_0.0\n",
|
||
"INFO:soil:Starting Simulation Spread_barabasi_albert_graph_prob_0.0 trial Spread_barabasi_albert_graph_prob_0-0_trial_1605822693-02196 at 21:51:33.\n",
|
||
"INFO:soil:Finished Simulation Spread_barabasi_albert_graph_prob_0.0 trial Spread_barabasi_albert_graph_prob_0-0_trial_1605822693-02196 at 21:51:33 in 0.08920121192932129 seconds\n",
|
||
"INFO:soil:Starting Dumping simulation Spread_barabasi_albert_graph_prob_0.0 trial Spread_barabasi_albert_graph_prob_0-0_trial_1605822693-02196 at 21:51:33.\n",
|
||
"INFO:soil:Finished Dumping simulation Spread_barabasi_albert_graph_prob_0.0 trial Spread_barabasi_albert_graph_prob_0-0_trial_1605822693-02196 at 21:51:33 in 0.002248525619506836 seconds\n",
|
||
"INFO:soil:Starting [CSV] Dumping simulation Spread_barabasi_albert_graph_prob_0.0 trial Spread_barabasi_albert_graph_prob_0-0_trial_1605822693-02196 @ dir /home/j/git/lab.gsi/soil/soil/examples/tutorial/soil_output/Spread_barabasi_albert_graph_prob_0.0 at 21:51:33.\n",
|
||
"INFO:soil:Finished [CSV] Dumping simulation Spread_barabasi_albert_graph_prob_0.0 trial Spread_barabasi_albert_graph_prob_0-0_trial_1605822693-02196 @ dir /home/j/git/lab.gsi/soil/soil/examples/tutorial/soil_output/Spread_barabasi_albert_graph_prob_0.0 at 21:51:33 in 0.008725643157958984 seconds\n",
|
||
"INFO:soil:Finished simulation Spread_barabasi_albert_graph_prob_0.0 at 21:51:33 in 0.27675533294677734 seconds\n",
|
||
"INFO:soil:Using config(s): Spread_barabasi_albert_graph_prob_0.1\n",
|
||
"INFO:soil:Using exporters: ['default', 'csv']\n",
|
||
"INFO:soil:Output directory: None\n",
|
||
"INFO:soil:Starting simulation Spread_barabasi_albert_graph_prob_0.1 at 21:51:33.\n",
|
||
"INFO:soil:Dumping results to /home/j/git/lab.gsi/soil/soil/examples/tutorial/soil_output/Spread_barabasi_albert_graph_prob_0.1\n",
|
||
"INFO:soil:Starting Simulation Spread_barabasi_albert_graph_prob_0.1 trial Spread_barabasi_albert_graph_prob_0-1_trial_1605822693-3600936 at 21:51:33.\n",
|
||
"INFO:soil:Finished Simulation Spread_barabasi_albert_graph_prob_0.1 trial Spread_barabasi_albert_graph_prob_0-1_trial_1605822693-3600936 at 21:51:33 in 0.10021758079528809 seconds\n",
|
||
"INFO:soil:Starting Dumping simulation Spread_barabasi_albert_graph_prob_0.1 trial Spread_barabasi_albert_graph_prob_0-1_trial_1605822693-3600936 at 21:51:33.\n",
|
||
"INFO:soil:Finished Dumping simulation Spread_barabasi_albert_graph_prob_0.1 trial Spread_barabasi_albert_graph_prob_0-1_trial_1605822693-3600936 at 21:51:33 in 0.0017764568328857422 seconds\n",
|
||
"INFO:soil:Starting [CSV] Dumping simulation Spread_barabasi_albert_graph_prob_0.1 trial Spread_barabasi_albert_graph_prob_0-1_trial_1605822693-3600936 @ dir /home/j/git/lab.gsi/soil/soil/examples/tutorial/soil_output/Spread_barabasi_albert_graph_prob_0.1 at 21:51:33.\n",
|
||
"INFO:soil:Finished [CSV] Dumping simulation Spread_barabasi_albert_graph_prob_0.1 trial Spread_barabasi_albert_graph_prob_0-1_trial_1605822693-3600936 @ dir /home/j/git/lab.gsi/soil/soil/examples/tutorial/soil_output/Spread_barabasi_albert_graph_prob_0.1 at 21:51:33 in 0.009679555892944336 seconds\n",
|
||
"INFO:soil:Finished simulation Spread_barabasi_albert_graph_prob_0.1 at 21:51:33 in 0.34103941917419434 seconds\n",
|
||
"INFO:soil:Using config(s): Spread_barabasi_albert_graph_prob_0.2\n",
|
||
"INFO:soil:Using exporters: ['default', 'csv']\n",
|
||
"INFO:soil:Output directory: None\n",
|
||
"INFO:soil:Starting simulation Spread_barabasi_albert_graph_prob_0.2 at 21:51:33.\n",
|
||
"INFO:soil:Dumping results to /home/j/git/lab.gsi/soil/soil/examples/tutorial/soil_output/Spread_barabasi_albert_graph_prob_0.2\n",
|
||
"INFO:soil:Starting Simulation Spread_barabasi_albert_graph_prob_0.2 trial Spread_barabasi_albert_graph_prob_0-2_trial_1605822693-6736543 at 21:51:33.\n",
|
||
"INFO:soil:Finished Simulation Spread_barabasi_albert_graph_prob_0.2 trial Spread_barabasi_albert_graph_prob_0-2_trial_1605822693-6736543 at 21:51:33 in 0.10449576377868652 seconds\n",
|
||
"INFO:soil:Starting Dumping simulation Spread_barabasi_albert_graph_prob_0.2 trial Spread_barabasi_albert_graph_prob_0-2_trial_1605822693-6736543 at 21:51:33.\n",
|
||
"INFO:soil:Finished Dumping simulation Spread_barabasi_albert_graph_prob_0.2 trial Spread_barabasi_albert_graph_prob_0-2_trial_1605822693-6736543 at 21:51:33 in 0.0013310909271240234 seconds\n",
|
||
"INFO:soil:Starting [CSV] Dumping simulation Spread_barabasi_albert_graph_prob_0.2 trial Spread_barabasi_albert_graph_prob_0-2_trial_1605822693-6736543 @ dir /home/j/git/lab.gsi/soil/soil/examples/tutorial/soil_output/Spread_barabasi_albert_graph_prob_0.2 at 21:51:33.\n",
|
||
"INFO:soil:Finished [CSV] Dumping simulation Spread_barabasi_albert_graph_prob_0.2 trial Spread_barabasi_albert_graph_prob_0-2_trial_1605822693-6736543 @ dir /home/j/git/lab.gsi/soil/soil/examples/tutorial/soil_output/Spread_barabasi_albert_graph_prob_0.2 at 21:51:33 in 0.008279085159301758 seconds\n",
|
||
"INFO:soil:Finished simulation Spread_barabasi_albert_graph_prob_0.2 at 21:51:33 in 0.3049919605255127 seconds\n",
|
||
"INFO:soil:Using config(s): Spread_barabasi_albert_graph_prob_0.3\n",
|
||
"INFO:soil:Using exporters: ['default', 'csv']\n",
|
||
"INFO:soil:Output directory: None\n",
|
||
"INFO:soil:Starting simulation Spread_barabasi_albert_graph_prob_0.3 at 21:51:33.\n",
|
||
"INFO:soil:Dumping results to /home/j/git/lab.gsi/soil/soil/examples/tutorial/soil_output/Spread_barabasi_albert_graph_prob_0.3\n",
|
||
"INFO:soil:Starting Simulation Spread_barabasi_albert_graph_prob_0.3 trial Spread_barabasi_albert_graph_prob_0-3_trial_1605822693-98245 at 21:51:34.\n",
|
||
"INFO:soil:Finished Simulation Spread_barabasi_albert_graph_prob_0.3 trial Spread_barabasi_albert_graph_prob_0-3_trial_1605822693-98245 at 21:51:34 in 0.10204219818115234 seconds\n",
|
||
"INFO:soil:Starting Dumping simulation Spread_barabasi_albert_graph_prob_0.3 trial Spread_barabasi_albert_graph_prob_0-3_trial_1605822693-98245 at 21:51:34.\n",
|
||
"INFO:soil:Finished Dumping simulation Spread_barabasi_albert_graph_prob_0.3 trial Spread_barabasi_albert_graph_prob_0-3_trial_1605822693-98245 at 21:51:34 in 0.0013041496276855469 seconds\n",
|
||
"INFO:soil:Starting [CSV] Dumping simulation Spread_barabasi_albert_graph_prob_0.3 trial Spread_barabasi_albert_graph_prob_0-3_trial_1605822693-98245 @ dir /home/j/git/lab.gsi/soil/soil/examples/tutorial/soil_output/Spread_barabasi_albert_graph_prob_0.3 at 21:51:34.\n",
|
||
"INFO:soil:Finished [CSV] Dumping simulation Spread_barabasi_albert_graph_prob_0.3 trial Spread_barabasi_albert_graph_prob_0-3_trial_1605822693-98245 @ dir /home/j/git/lab.gsi/soil/soil/examples/tutorial/soil_output/Spread_barabasi_albert_graph_prob_0.3 at 21:51:34 in 0.007649898529052734 seconds\n",
|
||
"INFO:soil:Finished simulation Spread_barabasi_albert_graph_prob_0.3 at 21:51:34 in 0.33296704292297363 seconds\n",
|
||
"INFO:soil:Using config(s): Spread_barabasi_albert_graph_prob_0.4\n",
|
||
"INFO:soil:Using exporters: ['default', 'csv']\n",
|
||
"INFO:soil:Output directory: None\n",
|
||
"INFO:soil:Starting simulation Spread_barabasi_albert_graph_prob_0.4 at 21:51:34.\n",
|
||
"INFO:soil:Dumping results to /home/j/git/lab.gsi/soil/soil/examples/tutorial/soil_output/Spread_barabasi_albert_graph_prob_0.4\n",
|
||
"INFO:soil:Starting Simulation Spread_barabasi_albert_graph_prob_0.4 trial Spread_barabasi_albert_graph_prob_0-4_trial_1605822694-3096724 at 21:51:34.\n",
|
||
"INFO:soil:Finished Simulation Spread_barabasi_albert_graph_prob_0.4 trial Spread_barabasi_albert_graph_prob_0-4_trial_1605822694-3096724 at 21:51:34 in 0.10178518295288086 seconds\n",
|
||
"INFO:soil:Starting Dumping simulation Spread_barabasi_albert_graph_prob_0.4 trial Spread_barabasi_albert_graph_prob_0-4_trial_1605822694-3096724 at 21:51:34.\n",
|
||
"INFO:soil:Finished Dumping simulation Spread_barabasi_albert_graph_prob_0.4 trial Spread_barabasi_albert_graph_prob_0-4_trial_1605822694-3096724 at 21:51:34 in 0.0014145374298095703 seconds\n",
|
||
"INFO:soil:Starting [CSV] Dumping simulation Spread_barabasi_albert_graph_prob_0.4 trial Spread_barabasi_albert_graph_prob_0-4_trial_1605822694-3096724 @ dir /home/j/git/lab.gsi/soil/soil/examples/tutorial/soil_output/Spread_barabasi_albert_graph_prob_0.4 at 21:51:34.\n",
|
||
"INFO:soil:Finished [CSV] Dumping simulation Spread_barabasi_albert_graph_prob_0.4 trial Spread_barabasi_albert_graph_prob_0-4_trial_1605822694-3096724 @ dir /home/j/git/lab.gsi/soil/soil/examples/tutorial/soil_output/Spread_barabasi_albert_graph_prob_0.4 at 21:51:34 in 0.007404804229736328 seconds\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"INFO:soil:Finished simulation Spread_barabasi_albert_graph_prob_0.4 at 21:51:34 in 0.2759675979614258 seconds\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"network_1 = {\n",
|
||
" 'generator': 'erdos_renyi_graph',\n",
|
||
" 'n': 500,\n",
|
||
" 'p': 0.1\n",
|
||
"}\n",
|
||
"network_2 = {\n",
|
||
" 'generator': 'barabasi_albert_graph',\n",
|
||
" 'n': 500,\n",
|
||
" 'm': 2\n",
|
||
"}\n",
|
||
"\n",
|
||
"\n",
|
||
"for net in [network_1, network_2]:\n",
|
||
" for i in range(5):\n",
|
||
" prob = i / 10\n",
|
||
" config['environment_params']['prob_neighbor_spread'] = prob\n",
|
||
" config['network_params'] = net\n",
|
||
" config['name'] = 'Spread_{}_prob_{}'.format(net['generator'], prob)\n",
|
||
" s = soil.simulation.run_from_config(config, exporters=['default', 'csv'])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2017-07-03T11:05:18.043194Z",
|
||
"start_time": "2017-07-03T13:05:18.034699+02:00"
|
||
},
|
||
"cell_style": "center"
|
||
},
|
||
"source": [
|
||
"The results are conveniently stored in sqlite (history of agent and environment state) and the configuration is saved in a YAML file.\n",
|
||
"\n",
|
||
"You can also export the results to GEXF format (dynamic network) and CSV using .`run_from_config(config, dump=['gexf', 'csv'])` or the command line flags `--graph --csv`."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 13,
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2017-11-01T14:05:56.404540Z",
|
||
"start_time": "2017-11-01T15:05:56.122876+01:00"
|
||
},
|
||
"cell_style": "split",
|
||
"scrolled": true
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"\u001b[01;34msoil_output\u001b[00m\r\n",
|
||
"├── \u001b[01;34mSpread_barabasi_albert_graph_prob_0.0\u001b[00m\r\n",
|
||
"│ ├── \u001b[01;34mbackup\u001b[00m\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.0.dumped.yml@2020-10-20_02.13.09\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.0.dumped.yml@2020-11-19_17.07.59\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.0.dumped.yml@2020-11-19_22.21.31\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.0.dumped.yml@2020-11-19_22.27.50\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.0.dumped.yml@2020-11-19_22.30.03\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.0.dumped.yml@2020-11-19_22.37.58\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.0_trial_0.csv@2020-10-20_02.13.09\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.0_trial_0.sqlite@2020-10-20_02.13.09\r\n",
|
||
"│ │ └── Spread_barabasi_albert_graph_prob_0.0_trial_0.stats.csv@2020-10-20_02.13.09\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0.0.dumped.yml\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0.0_trial_0.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0.0_trial_0.db.sqlite\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0.0_trial_0.sqlite\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0.0_trial_0.stats.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-0_trial_1605820891-4782693.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-0_trial_1605820891-4782693.sqlite\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-0_trial_1605820891-4782693.stats.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-0_trial_1605821270-8135355.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-0_trial_1605821270-8135355.sqlite\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-0_trial_1605821270-8135355.stats.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-0_trial_1605821403-9184299.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-0_trial_1605821403-9184299.sqlite\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-0_trial_1605821403-9184299.stats.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-0_trial_1605821878-07332.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-0_trial_1605821878-07332.sqlite\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-0_trial_1605821878-07332.stats.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-0_trial_1605822693-02196.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-0_trial_1605822693-02196.sqlite\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-0_trial_1605822693-02196.stats.csv\r\n",
|
||
"│ └── Spread_barabasi_albert_graph_prob_0-0_trial_1*.sqlite\r\n",
|
||
"├── \u001b[01;34mSpread_barabasi_albert_graph_prob_0.1\u001b[00m\r\n",
|
||
"│ ├── \u001b[01;34mbackup\u001b[00m\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.1.dumped.yml@2020-10-20_02.13.09\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.1.dumped.yml@2020-11-19_17.07.59\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.1.dumped.yml@2020-11-19_22.21.31\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.1.dumped.yml@2020-11-19_22.27.51\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.1.dumped.yml@2020-11-19_22.30.04\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.1.dumped.yml@2020-11-19_22.37.58\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.1_trial_0.csv@2020-10-20_02.13.10\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.1_trial_0.sqlite@2020-10-20_02.13.10\r\n",
|
||
"│ │ └── Spread_barabasi_albert_graph_prob_0.1_trial_0.stats.csv@2020-10-20_02.13.10\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0.1.dumped.yml\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0.1_trial_0.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0.1_trial_0.sqlite\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0.1_trial_0.stats.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-1_trial_1605820891-7942905.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-1_trial_1605820891-7942905.sqlite\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-1_trial_1605820891-7942905.stats.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-1_trial_1605821271-1282487.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-1_trial_1605821271-1282487.sqlite\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-1_trial_1605821271-1282487.stats.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-1_trial_1605821404-2597992.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-1_trial_1605821404-2597992.sqlite\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-1_trial_1605821404-2597992.stats.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-1_trial_1605821878-3834527.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-1_trial_1605821878-3834527.sqlite\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-1_trial_1605821878-3834527.stats.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-1_trial_1605822693-3600936.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-1_trial_1605822693-3600936.sqlite\r\n",
|
||
"│ └── Spread_barabasi_albert_graph_prob_0-1_trial_1605822693-3600936.stats.csv\r\n",
|
||
"├── \u001b[01;34mSpread_barabasi_albert_graph_prob_0.2\u001b[00m\r\n",
|
||
"│ ├── \u001b[01;34mbackup\u001b[00m\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.2.dumped.yml@2020-10-20_02.13.10\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.2.dumped.yml@2020-11-19_17.07.59\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.2.dumped.yml@2020-11-19_22.21.32\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.2.dumped.yml@2020-11-19_22.27.51\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.2.dumped.yml@2020-11-19_22.30.04\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.2.dumped.yml@2020-11-19_22.37.58\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.2_trial_0.csv@2020-10-20_02.13.10\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.2_trial_0.sqlite@2020-10-20_02.13.10\r\n",
|
||
"│ │ └── Spread_barabasi_albert_graph_prob_0.2_trial_0.stats.csv@2020-10-20_02.13.10\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0.2.dumped.yml\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0.2_trial_0.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0.2_trial_0.sqlite\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0.2_trial_0.stats.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-2_trial_1605820892-0839.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-2_trial_1605820892-0839.sqlite\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-2_trial_1605820892-0839.stats.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-2_trial_1605821271-4662864.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-2_trial_1605821271-4662864.sqlite\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-2_trial_1605821271-4662864.stats.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-2_trial_1605821404-5465293.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-2_trial_1605821404-5465293.sqlite\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-2_trial_1605821404-5465293.stats.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-2_trial_1605821878-6511369.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-2_trial_1605821878-6511369.sqlite\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-2_trial_1605821878-6511369.stats.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-2_trial_1605822693-6736543.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-2_trial_1605822693-6736543.sqlite\r\n",
|
||
"│ └── Spread_barabasi_albert_graph_prob_0-2_trial_1605822693-6736543.stats.csv\r\n",
|
||
"├── \u001b[01;34mSpread_barabasi_albert_graph_prob_0.3\u001b[00m\r\n",
|
||
"│ ├── \u001b[01;34mbackup\u001b[00m\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.3.dumped.yml@2020-10-20_02.13.10\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.3.dumped.yml@2020-11-19_17.08.00\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.3.dumped.yml@2020-11-19_22.21.32\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.3.dumped.yml@2020-11-19_22.27.51\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.3.dumped.yml@2020-11-19_22.30.04\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.3.dumped.yml@2020-11-19_22.37.58\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.3_trial_0.csv@2020-10-20_02.13.10\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.3_trial_0.sqlite@2020-10-20_02.13.10\r\n",
|
||
"│ │ └── Spread_barabasi_albert_graph_prob_0.3_trial_0.stats.csv@2020-10-20_02.13.10\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0.3.dumped.yml\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0.3_trial_0.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0.3_trial_0.sqlite\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0.3_trial_0.stats.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-3_trial_1605820892-4140177.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-3_trial_1605820892-4140177.sqlite\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-3_trial_1605820892-4140177.stats.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-3_trial_1605821271-7566118.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-3_trial_1605821271-7566118.sqlite\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-3_trial_1605821271-7566118.stats.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-3_trial_1605821404-8982599.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-3_trial_1605821404-8982599.sqlite\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-3_trial_1605821404-8982599.stats.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-3_trial_1605821878-9966376.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-3_trial_1605821878-9966376.sqlite\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-3_trial_1605821878-9966376.stats.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-3_trial_1605822693-98245.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-3_trial_1605822693-98245.sqlite\r\n",
|
||
"│ └── Spread_barabasi_albert_graph_prob_0-3_trial_1605822693-98245.stats.csv\r\n",
|
||
"├── \u001b[01;34mSpread_barabasi_albert_graph_prob_0.4\u001b[00m\r\n",
|
||
"│ ├── \u001b[01;34mbackup\u001b[00m\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.4.dumped.yml@2020-10-20_02.13.11\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.4.dumped.yml@2020-11-19_17.08.00\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.4.dumped.yml@2020-11-19_22.21.32\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.4.dumped.yml@2020-11-19_22.27.52\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.4.dumped.yml@2020-11-19_22.30.05\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.4.dumped.yml@2020-11-19_22.37.59\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.4_trial_0.csv@2020-10-20_02.13.11\r\n",
|
||
"│ │ ├── Spread_barabasi_albert_graph_prob_0.4_trial_0.sqlite@2020-10-20_02.13.11\r\n",
|
||
"│ │ └── Spread_barabasi_albert_graph_prob_0.4_trial_0.stats.csv@2020-10-20_02.13.11\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0.4.dumped.yml\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0.4_trial_0.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0.4_trial_0.sqlite\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0.4_trial_0.stats.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-4_trial_1605820892-7289681.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-4_trial_1605820892-7289681.sqlite\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-4_trial_1605820892-7289681.stats.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-4_trial_1605821272-094621.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-4_trial_1605821272-094621.sqlite\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-4_trial_1605821272-094621.stats.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-4_trial_1605821405-182661.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-4_trial_1605821405-182661.sqlite\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-4_trial_1605821405-182661.stats.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-4_trial_1605821879-2909274.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-4_trial_1605821879-2909274.sqlite\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-4_trial_1605821879-2909274.stats.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-4_trial_1605822694-3096724.csv\r\n",
|
||
"│ ├── Spread_barabasi_albert_graph_prob_0-4_trial_1605822694-3096724.sqlite\r\n",
|
||
"│ └── Spread_barabasi_albert_graph_prob_0-4_trial_1605822694-3096724.stats.csv\r\n",
|
||
"├── \u001b[01;34mSpread_erdos_renyi_graph_prob_0.0\u001b[00m\r\n",
|
||
"│ ├── \u001b[01;34mbackup\u001b[00m\r\n",
|
||
"│ │ ├── Spread_erdos_renyi_graph_prob_0.0.dumped.yml@2020-10-20_02.13.01\r\n",
|
||
"│ │ ├── Spread_erdos_renyi_graph_prob_0.0.dumped.yml@2020-11-19_17.07.50\r\n",
|
||
"│ │ ├── Spread_erdos_renyi_graph_prob_0.0.dumped.yml@2020-11-19_22.21.23\r\n",
|
||
"│ │ ├── Spread_erdos_renyi_graph_prob_0.0.dumped.yml@2020-11-19_22.27.42\r\n",
|
||
"│ │ ├── Spread_erdos_renyi_graph_prob_0.0.dumped.yml@2020-11-19_22.29.55\r\n",
|
||
"│ │ ├── Spread_erdos_renyi_graph_prob_0.0.dumped.yml@2020-11-19_22.37.49\r\n",
|
||
"│ │ ├── Spread_erdos_renyi_graph_prob_0.0_trial_0.csv@2020-10-20_02.13.01\r\n",
|
||
"│ │ ├── Spread_erdos_renyi_graph_prob_0.0_trial_0.sqlite@2020-10-20_02.13.01\r\n",
|
||
"│ │ └── Spread_erdos_renyi_graph_prob_0.0_trial_0.stats.csv@2020-10-20_02.13.01\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0.0.dumped.yml\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0.0_trial_0.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0.0_trial_0.sqlite\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0.0_trial_0.stats.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-0_trial_1605820883-06455.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-0_trial_1605820883-06455.sqlite\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-0_trial_1605820883-06455.stats.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-0_trial_1605821262-320959.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-0_trial_1605821262-320959.sqlite\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-0_trial_1605821262-320959.stats.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-0_trial_1605821395-1533184.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-0_trial_1605821395-1533184.sqlite\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-0_trial_1605821395-1533184.stats.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-0_trial_1605821869-3048918.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-0_trial_1605821869-3048918.sqlite\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-0_trial_1605821869-3048918.stats.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-0_trial_1605822684-0959892.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-0_trial_1605822684-0959892.sqlite\r\n",
|
||
"│ └── Spread_erdos_renyi_graph_prob_0-0_trial_1605822684-0959892.stats.csv\r\n",
|
||
"├── \u001b[01;34mSpread_erdos_renyi_graph_prob_0.1\u001b[00m\r\n",
|
||
"│ ├── \u001b[01;34mbackup\u001b[00m\r\n",
|
||
"│ │ ├── Spread_erdos_renyi_graph_prob_0.1.dumped.yml@2020-10-20_02.13.03\r\n",
|
||
"│ │ ├── Spread_erdos_renyi_graph_prob_0.1.dumped.yml@2020-11-19_17.07.52\r\n",
|
||
"│ │ ├── Spread_erdos_renyi_graph_prob_0.1.dumped.yml@2020-11-19_22.21.24\r\n",
|
||
"│ │ ├── Spread_erdos_renyi_graph_prob_0.1.dumped.yml@2020-11-19_22.27.44\r\n",
|
||
"│ │ ├── Spread_erdos_renyi_graph_prob_0.1.dumped.yml@2020-11-19_22.29.57\r\n",
|
||
"│ │ ├── Spread_erdos_renyi_graph_prob_0.1.dumped.yml@2020-11-19_22.37.51\r\n",
|
||
"│ │ ├── Spread_erdos_renyi_graph_prob_0.1_trial_0.csv@2020-10-20_02.13.03\r\n",
|
||
"│ │ ├── Spread_erdos_renyi_graph_prob_0.1_trial_0.sqlite@2020-10-20_02.13.03\r\n",
|
||
"│ │ └── Spread_erdos_renyi_graph_prob_0.1_trial_0.stats.csv@2020-10-20_02.13.03\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0.1.dumped.yml\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0.1_trial_0.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0.1_trial_0.sqlite\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0.1_trial_0.stats.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-1_trial_1605820884-9897068.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-1_trial_1605820884-9897068.sqlite\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-1_trial_1605820884-9897068.stats.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-1_trial_1605821264-2528372.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-1_trial_1605821264-2528372.sqlite\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-1_trial_1605821264-2528372.stats.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-1_trial_1605821397-0991232.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-1_trial_1605821397-0991232.sqlite\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-1_trial_1605821397-0991232.stats.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-1_trial_1605821871-3203213.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-1_trial_1605821871-3203213.sqlite\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-1_trial_1605821871-3203213.stats.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-1_trial_1605822686-1504185.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-1_trial_1605822686-1504185.sqlite\r\n",
|
||
"│ └── Spread_erdos_renyi_graph_prob_0-1_trial_1605822686-1504185.stats.csv\r\n",
|
||
"├── \u001b[01;34mSpread_erdos_renyi_graph_prob_0.2\u001b[00m\r\n",
|
||
"│ ├── \u001b[01;34mbackup\u001b[00m\r\n",
|
||
"│ │ ├── Spread_erdos_renyi_graph_prob_0.2.dumped.yml@2020-10-20_02.13.05\r\n",
|
||
"│ │ ├── Spread_erdos_renyi_graph_prob_0.2.dumped.yml@2020-11-19_17.07.54\r\n",
|
||
"│ │ ├── Spread_erdos_renyi_graph_prob_0.2.dumped.yml@2020-11-19_22.21.26\r\n",
|
||
"│ │ ├── Spread_erdos_renyi_graph_prob_0.2.dumped.yml@2020-11-19_22.27.46\r\n",
|
||
"│ │ ├── Spread_erdos_renyi_graph_prob_0.2.dumped.yml@2020-11-19_22.29.59\r\n",
|
||
"│ │ ├── Spread_erdos_renyi_graph_prob_0.2.dumped.yml@2020-11-19_22.37.53\r\n",
|
||
"│ │ ├── Spread_erdos_renyi_graph_prob_0.2_trial_0.csv@2020-10-20_02.13.05\r\n",
|
||
"│ │ ├── Spread_erdos_renyi_graph_prob_0.2_trial_0.sqlite@2020-10-20_02.13.05\r\n",
|
||
"│ │ └── Spread_erdos_renyi_graph_prob_0.2_trial_0.stats.csv@2020-10-20_02.13.05\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0.2.dumped.yml\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0.2_trial_0.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0.2_trial_0.sqlite\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0.2_trial_0.stats.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-2_trial_1605820886-9976044.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-2_trial_1605820886-9976044.sqlite\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-2_trial_1605820886-9976044.stats.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-2_trial_1605821266-2571487.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-2_trial_1605821266-2571487.sqlite\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-2_trial_1605821266-2571487.stats.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-2_trial_1605821399-2090585.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-2_trial_1605821399-2090585.sqlite\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-2_trial_1605821399-2090585.stats.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-2_trial_1605821873-299152.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-2_trial_1605821873-299152.sqlite\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-2_trial_1605821873-299152.stats.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-2_trial_1605822688-204787.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-2_trial_1605822688-204787.sqlite\r\n",
|
||
"│ └── Spread_erdos_renyi_graph_prob_0-2_trial_1605822688-204787.stats.csv\r\n",
|
||
"├── \u001b[01;34mSpread_erdos_renyi_graph_prob_0.3\u001b[00m\r\n",
|
||
"│ ├── \u001b[01;34mbackup\u001b[00m\r\n",
|
||
"│ │ ├── Spread_erdos_renyi_graph_prob_0.3.dumped.yml@2020-10-20_02.13.07\r\n",
|
||
"│ │ ├── Spread_erdos_renyi_graph_prob_0.3.dumped.yml@2020-11-19_17.07.56\r\n",
|
||
"│ │ ├── Spread_erdos_renyi_graph_prob_0.3.dumped.yml@2020-11-19_22.21.28\r\n",
|
||
"│ │ ├── Spread_erdos_renyi_graph_prob_0.3.dumped.yml@2020-11-19_22.27.48\r\n",
|
||
"│ │ ├── Spread_erdos_renyi_graph_prob_0.3.dumped.yml@2020-11-19_22.30.01\r\n",
|
||
"│ │ ├── Spread_erdos_renyi_graph_prob_0.3.dumped.yml@2020-11-19_22.37.55\r\n",
|
||
"│ │ ├── Spread_erdos_renyi_graph_prob_0.3_trial_0.csv@2020-10-20_02.13.07\r\n",
|
||
"│ │ ├── Spread_erdos_renyi_graph_prob_0.3_trial_0.sqlite@2020-10-20_02.13.07\r\n",
|
||
"│ │ └── Spread_erdos_renyi_graph_prob_0.3_trial_0.stats.csv@2020-10-20_02.13.07\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0.3.dumped.yml\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0.3_trial_0.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0.3_trial_0.sqlite\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0.3_trial_0.stats.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-3_trial_1605820888-9462104.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-3_trial_1605820888-9462104.sqlite\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-3_trial_1605820888-9462104.stats.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-3_trial_1605821268-2217143.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-3_trial_1605821268-2217143.sqlite\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-3_trial_1605821268-2217143.stats.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-3_trial_1605821401-1938107.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-3_trial_1605821401-1938107.sqlite\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-3_trial_1605821401-1938107.stats.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-3_trial_1605821875-4654636.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-3_trial_1605821875-4654636.sqlite\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-3_trial_1605821875-4654636.stats.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-3_trial_1605822690-3038263.csv\r\n",
|
||
"│ ├── Spread_erdos_renyi_graph_prob_0-3_trial_1605822690-3038263.sqlite\r\n",
|
||
"│ └── Spread_erdos_renyi_graph_prob_0-3_trial_1605822690-3038263.stats.csv\r\n",
|
||
"└── \u001b[01;34mSpread_erdos_renyi_graph_prob_0.4\u001b[00m\r\n",
|
||
" ├── \u001b[01;34mbackup\u001b[00m\r\n",
|
||
" │ ├── Spread_erdos_renyi_graph_prob_0.4.dumped.yml@2020-10-20_02.13.09\r\n",
|
||
" │ ├── Spread_erdos_renyi_graph_prob_0.4.dumped.yml@2020-11-19_17.07.58\r\n",
|
||
" │ ├── Spread_erdos_renyi_graph_prob_0.4.dumped.yml@2020-11-19_22.21.30\r\n",
|
||
" │ ├── Spread_erdos_renyi_graph_prob_0.4.dumped.yml@2020-11-19_22.27.50\r\n",
|
||
" │ ├── Spread_erdos_renyi_graph_prob_0.4.dumped.yml@2020-11-19_22.30.03\r\n",
|
||
" │ ├── Spread_erdos_renyi_graph_prob_0.4.dumped.yml@2020-11-19_22.37.57\r\n",
|
||
" │ ├── Spread_erdos_renyi_graph_prob_0.4_trial_0.csv@2020-10-20_02.13.09\r\n",
|
||
" │ ├── Spread_erdos_renyi_graph_prob_0.4_trial_0.sqlite@2020-10-20_02.13.09\r\n",
|
||
" │ └── Spread_erdos_renyi_graph_prob_0.4_trial_0.stats.csv@2020-10-20_02.13.09\r\n",
|
||
" ├── Spread_erdos_renyi_graph_prob_0.4.dumped.yml\r\n",
|
||
" ├── Spread_erdos_renyi_graph_prob_0.4_trial_0.csv\r\n",
|
||
" ├── Spread_erdos_renyi_graph_prob_0.4_trial_0.sqlite\r\n",
|
||
" ├── Spread_erdos_renyi_graph_prob_0.4_trial_0.stats.csv\r\n",
|
||
" ├── Spread_erdos_renyi_graph_prob_0-4_trial_1605820890-8584282.csv\r\n",
|
||
" ├── Spread_erdos_renyi_graph_prob_0-4_trial_1605820890-8584282.sqlite\r\n",
|
||
" ├── Spread_erdos_renyi_graph_prob_0-4_trial_1605820890-8584282.stats.csv\r\n",
|
||
" ├── Spread_erdos_renyi_graph_prob_0-4_trial_1605821270-1897953.csv\r\n",
|
||
" ├── Spread_erdos_renyi_graph_prob_0-4_trial_1605821270-1897953.sqlite\r\n",
|
||
" ├── Spread_erdos_renyi_graph_prob_0-4_trial_1605821270-1897953.stats.csv\r\n",
|
||
" ├── Spread_erdos_renyi_graph_prob_0-4_trial_1605821403-3238373.csv\r\n",
|
||
" ├── Spread_erdos_renyi_graph_prob_0-4_trial_1605821403-3238373.sqlite\r\n",
|
||
" ├── Spread_erdos_renyi_graph_prob_0-4_trial_1605821403-3238373.stats.csv\r\n",
|
||
" ├── Spread_erdos_renyi_graph_prob_0-4_trial_1605821877-5024807.csv\r\n",
|
||
" ├── Spread_erdos_renyi_graph_prob_0-4_trial_1605821877-5024807.sqlite\r\n",
|
||
" ├── Spread_erdos_renyi_graph_prob_0-4_trial_1605821877-5024807.stats.csv\r\n",
|
||
" ├── Spread_erdos_renyi_graph_prob_0-4_trial_1605822692-3893287.csv\r\n",
|
||
" ├── Spread_erdos_renyi_graph_prob_0-4_trial_1605822692-3893287.sqlite\r\n",
|
||
" └── Spread_erdos_renyi_graph_prob_0-4_trial_1605822692-3893287.stats.csv\r\n",
|
||
"\r\n",
|
||
"20 directories, 282 files\r\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"364K\tsoil_output/Spread_barabasi_albert_graph_prob_0.0/backup\r\n",
|
||
"1.2M\tsoil_output/Spread_barabasi_albert_graph_prob_0.0\r\n",
|
||
"368K\tsoil_output/Spread_barabasi_albert_graph_prob_0.1/backup\r\n",
|
||
"1.2M\tsoil_output/Spread_barabasi_albert_graph_prob_0.1\r\n",
|
||
"364K\tsoil_output/Spread_barabasi_albert_graph_prob_0.2/backup\r\n",
|
||
"1.2M\tsoil_output/Spread_barabasi_albert_graph_prob_0.2\r\n",
|
||
"368K\tsoil_output/Spread_barabasi_albert_graph_prob_0.3/backup\r\n",
|
||
"1.2M\tsoil_output/Spread_barabasi_albert_graph_prob_0.3\r\n",
|
||
"364K\tsoil_output/Spread_barabasi_albert_graph_prob_0.4/backup\r\n",
|
||
"1.2M\tsoil_output/Spread_barabasi_albert_graph_prob_0.4\r\n",
|
||
"2.5M\tsoil_output/Spread_erdos_renyi_graph_prob_0.0/backup\r\n",
|
||
"3.6M\tsoil_output/Spread_erdos_renyi_graph_prob_0.0\r\n",
|
||
"2.5M\tsoil_output/Spread_erdos_renyi_graph_prob_0.1/backup\r\n",
|
||
"3.6M\tsoil_output/Spread_erdos_renyi_graph_prob_0.1\r\n",
|
||
"2.5M\tsoil_output/Spread_erdos_renyi_graph_prob_0.2/backup\r\n",
|
||
"3.6M\tsoil_output/Spread_erdos_renyi_graph_prob_0.2\r\n",
|
||
"2.5M\tsoil_output/Spread_erdos_renyi_graph_prob_0.3/backup\r\n",
|
||
"3.6M\tsoil_output/Spread_erdos_renyi_graph_prob_0.3\r\n",
|
||
"2.5M\tsoil_output/Spread_erdos_renyi_graph_prob_0.4/backup\r\n",
|
||
"3.6M\tsoil_output/Spread_erdos_renyi_graph_prob_0.4\r\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"!tree soil_output\n",
|
||
"!du -xh soil_output/*"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2017-07-02T10:40:14.384177Z",
|
||
"start_time": "2017-07-02T12:40:14.381885+02:00"
|
||
}
|
||
},
|
||
"source": [
|
||
"## Analysing the results"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"### Loading data"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"Once the simulations are over, we can use soil to analyse the results.\n",
|
||
"\n",
|
||
"Soil allows you to load results for specific trials, or for a set of trials if you specify a pattern. The specific methods are:\n",
|
||
"\n",
|
||
"* `analysis.read_data(<directory pattern>)` to load all the results from a directory. e.g. `read_data('my_simulation/')`. For each trial it finds in each folder matching the pattern, it will return the dumped configuration for the simulation, the results of the trial, and the configuration itself. By default, it will try to load data from the sqlite database. \n",
|
||
"* `analysis.read_csv(<csv_file>)` to load all the results from a CSV file. e.g. `read_csv('my_simulation/my_simulation_trial0.environment.csv')`\n",
|
||
"* `analysis.read_sql(<sqlite_file>)` to load all the results from a sqlite database . e.g. `read_sql('my_simulation/my_simulation_trial0.db.sqlite')`"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2017-07-03T14:44:30.978223Z",
|
||
"start_time": "2017-07-03T16:44:30.971952+02:00"
|
||
}
|
||
},
|
||
"source": [
|
||
"Let's see it in action by loading the stored results into a pandas dataframe:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 54,
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2017-10-19T15:57:43.662893Z",
|
||
"start_time": "2017-10-19T17:57:43.632252+02:00"
|
||
},
|
||
"cell_style": "center"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"from soil import analysis\n",
|
||
"import pandas as pd"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 3,
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2017-10-19T15:57:44.101253Z",
|
||
"start_time": "2017-10-19T17:57:44.039710+02:00"
|
||
},
|
||
"scrolled": true
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"<div>\n",
|
||
"<style scoped>\n",
|
||
" .dataframe tbody tr th:only-of-type {\n",
|
||
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|
||
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|
||
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|
||
" .dataframe tbody tr th {\n",
|
||
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|
||
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|
||
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|
||
" .dataframe thead tr th {\n",
|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
" <thead>\n",
|
||
" <tr>\n",
|
||
" <th>key</th>\n",
|
||
" <th>SEED</th>\n",
|
||
" <th>agents.model_count.NewsSpread</th>\n",
|
||
" <th>agents.state_count.infected</th>\n",
|
||
" <th>agents.state_count.neutral</th>\n",
|
||
" <th>event_time</th>\n",
|
||
" <th colspan=\"5\" halign=\"left\">has_tv</th>\n",
|
||
" <th>...</th>\n",
|
||
" <th colspan=\"6\" halign=\"left\">id</th>\n",
|
||
" <th>network .n_edges</th>\n",
|
||
" <th>network .n_nodes</th>\n",
|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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||
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|
||
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|
||
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|
||
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||
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||
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||
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||
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||
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||
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||
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||
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|
||
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||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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||
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|
||
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|
||
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|
||
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||
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|
||
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||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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||
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|
||
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|
||
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|
||
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|
||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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|
||
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|
||
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|
||
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|
||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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|
||
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|
||
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|
||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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|
||
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|
||
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|
||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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|
||
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||
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||
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||
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||
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||
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||
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||
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||
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|
||
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||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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|
||
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|
||
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|
||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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|
||
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|
||
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|
||
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|
||
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|
||
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||
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||
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||
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||
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||
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||
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|
||
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||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
" <td>0.01</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>7</th>\n",
|
||
" <td>Spread_barabasi_albert_graph_prob_0.0_trial_0</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>0.0</td>\n",
|
||
" <td>0.01</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>8</th>\n",
|
||
" <td>Spread_barabasi_albert_graph_prob_0.0_trial_0</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>0.0</td>\n",
|
||
" <td>0.01</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>9</th>\n",
|
||
" <td>Spread_barabasi_albert_graph_prob_0.0_trial_0</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>0.0</td>\n",
|
||
" <td>0.01</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>10</th>\n",
|
||
" <td>Spread_barabasi_albert_graph_prob_0.0_trial_0</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>1</td>\n",
|
||
" <td>1</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>11</th>\n",
|
||
" <td>Spread_barabasi_albert_graph_prob_0.0_trial_0</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>0.9</td>\n",
|
||
" <td>0.5</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>12</th>\n",
|
||
" <td>Spread_barabasi_albert_graph_prob_0.0_trial_0</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>0.81</td>\n",
|
||
" <td>0.25</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>13</th>\n",
|
||
" <td>Spread_barabasi_albert_graph_prob_0.0_trial_0</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>0.7290000000000001</td>\n",
|
||
" <td>0.125</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>14</th>\n",
|
||
" <td>Spread_barabasi_albert_graph_prob_0.0_trial_0</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>0.6561000000000001</td>\n",
|
||
" <td>0.0625</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>15</th>\n",
|
||
" <td>Spread_barabasi_albert_graph_prob_0.0_trial_0</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>0.5904900000000002</td>\n",
|
||
" <td>0.03125</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>16</th>\n",
|
||
" <td>Spread_barabasi_albert_graph_prob_0.0_trial_0</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>0.5314410000000002</td>\n",
|
||
" <td>0.015625</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>17</th>\n",
|
||
" <td>Spread_barabasi_albert_graph_prob_0.0_trial_0</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>0.47829690000000014</td>\n",
|
||
" <td>0.0078125</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>18</th>\n",
|
||
" <td>Spread_barabasi_albert_graph_prob_0.0_trial_0</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>0.43046721000000016</td>\n",
|
||
" <td>0.00390625</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>19</th>\n",
|
||
" <td>Spread_barabasi_albert_graph_prob_0.0_trial_0</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>0.38742048900000015</td>\n",
|
||
" <td>0.001953125</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>20</th>\n",
|
||
" <td>Spread_barabasi_albert_graph_prob_0.0_trial_0</td>\n",
|
||
" <td>500</td>\n",
|
||
" <td>480</td>\n",
|
||
" <td>20</td>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>500</td>\n",
|
||
" <td>500</td>\n",
|
||
" <td>0.38742048900000015</td>\n",
|
||
" <td>0.001953125</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"<p>21 rows × 1009 columns</p>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
"key SEED \\\n",
|
||
"agent_id env \n",
|
||
"t_step \n",
|
||
"0 Spread_barabasi_albert_graph_prob_0.0_trial_0 \n",
|
||
"1 Spread_barabasi_albert_graph_prob_0.0_trial_0 \n",
|
||
"2 Spread_barabasi_albert_graph_prob_0.0_trial_0 \n",
|
||
"3 Spread_barabasi_albert_graph_prob_0.0_trial_0 \n",
|
||
"4 Spread_barabasi_albert_graph_prob_0.0_trial_0 \n",
|
||
"5 Spread_barabasi_albert_graph_prob_0.0_trial_0 \n",
|
||
"6 Spread_barabasi_albert_graph_prob_0.0_trial_0 \n",
|
||
"7 Spread_barabasi_albert_graph_prob_0.0_trial_0 \n",
|
||
"8 Spread_barabasi_albert_graph_prob_0.0_trial_0 \n",
|
||
"9 Spread_barabasi_albert_graph_prob_0.0_trial_0 \n",
|
||
"10 Spread_barabasi_albert_graph_prob_0.0_trial_0 \n",
|
||
"11 Spread_barabasi_albert_graph_prob_0.0_trial_0 \n",
|
||
"12 Spread_barabasi_albert_graph_prob_0.0_trial_0 \n",
|
||
"13 Spread_barabasi_albert_graph_prob_0.0_trial_0 \n",
|
||
"14 Spread_barabasi_albert_graph_prob_0.0_trial_0 \n",
|
||
"15 Spread_barabasi_albert_graph_prob_0.0_trial_0 \n",
|
||
"16 Spread_barabasi_albert_graph_prob_0.0_trial_0 \n",
|
||
"17 Spread_barabasi_albert_graph_prob_0.0_trial_0 \n",
|
||
"18 Spread_barabasi_albert_graph_prob_0.0_trial_0 \n",
|
||
"19 Spread_barabasi_albert_graph_prob_0.0_trial_0 \n",
|
||
"20 Spread_barabasi_albert_graph_prob_0.0_trial_0 \n",
|
||
"\n",
|
||
"key agents.model_count.NewsSpread agents.state_count.infected \\\n",
|
||
"agent_id stats stats \n",
|
||
"t_step \n",
|
||
"0 NaN NaN \n",
|
||
"1 NaN NaN \n",
|
||
"2 NaN NaN \n",
|
||
"3 NaN NaN \n",
|
||
"4 NaN NaN \n",
|
||
"5 NaN NaN \n",
|
||
"6 NaN NaN \n",
|
||
"7 NaN NaN \n",
|
||
"8 NaN NaN \n",
|
||
"9 NaN NaN \n",
|
||
"10 NaN NaN \n",
|
||
"11 NaN NaN \n",
|
||
"12 NaN NaN \n",
|
||
"13 NaN NaN \n",
|
||
"14 NaN NaN \n",
|
||
"15 NaN NaN \n",
|
||
"16 NaN NaN \n",
|
||
"17 NaN NaN \n",
|
||
"18 NaN NaN \n",
|
||
"19 NaN NaN \n",
|
||
"20 500 480 \n",
|
||
"\n",
|
||
"key agents.state_count.neutral event_time has_tv \\\n",
|
||
"agent_id stats NewsEnvironmentAgent 0 1 10 \n",
|
||
"t_step \n",
|
||
"0 NaN 10 True True True \n",
|
||
"1 NaN 10 True True True \n",
|
||
"2 NaN 10 True True True \n",
|
||
"3 NaN 10 True True True \n",
|
||
"4 NaN 10 True True True \n",
|
||
"5 NaN 10 True True True \n",
|
||
"6 NaN 10 True True True \n",
|
||
"7 NaN 10 True True True \n",
|
||
"8 NaN 10 True True True \n",
|
||
"9 NaN 10 True True True \n",
|
||
"10 NaN 10 True True True \n",
|
||
"11 NaN 10 True True True \n",
|
||
"12 NaN 10 True True True \n",
|
||
"13 NaN 10 True True True \n",
|
||
"14 NaN 10 True True True \n",
|
||
"15 NaN 10 True True True \n",
|
||
"16 NaN 10 True True True \n",
|
||
"17 NaN 10 True True True \n",
|
||
"18 NaN 10 True True True \n",
|
||
"19 NaN 10 True True True \n",
|
||
"20 20 10 True True True \n",
|
||
"\n",
|
||
"key ... id \\\n",
|
||
"agent_id 100 101 ... 94 95 96 97 98 \n",
|
||
"t_step ... \n",
|
||
"0 True True ... neutral neutral neutral neutral neutral \n",
|
||
"1 True True ... neutral neutral neutral neutral neutral \n",
|
||
"2 True True ... neutral neutral neutral neutral neutral \n",
|
||
"3 True True ... neutral neutral neutral neutral neutral \n",
|
||
"4 True True ... neutral neutral neutral neutral neutral \n",
|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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||
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|
||
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|
||
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|
||
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|
||
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|
||
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||
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|
||
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|
||
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|
||
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|
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|
||
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|
||
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|
||
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|
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|
||
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|
||
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|
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|
||
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|
||
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|
||
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|
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||
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||
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||
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||
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||
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||
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||
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|
||
" <th>12</th>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>13</th>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>14</th>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>15</th>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>16</th>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>17</th>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>18</th>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>19</th>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>20</th>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"<p>21 rows × 1001 columns</p>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
"key event_time has_tv \\\n",
|
||
"agent_id NewsEnvironmentAgent 0 1 10 100 101 102 103 \n",
|
||
"t_step \n",
|
||
"0 10 True True True True True True True \n",
|
||
"1 10 True True True True True True True \n",
|
||
"2 10 True True True True True True True \n",
|
||
"3 10 True True True True True True True \n",
|
||
"4 10 True True True True True True True \n",
|
||
"5 10 True True True True True True True \n",
|
||
"6 10 True True True True True True True \n",
|
||
"7 10 True True True True True True True \n",
|
||
"8 10 True True True True True True True \n",
|
||
"9 10 True True True True True True True \n",
|
||
"10 10 True True True True True True True \n",
|
||
"11 10 True True True True True True True \n",
|
||
"12 10 True True True True True True True \n",
|
||
"13 10 True True True True True True True \n",
|
||
"14 10 True True True True True True True \n",
|
||
"15 10 True True True True True True True \n",
|
||
"16 10 True True True True True True True \n",
|
||
"17 10 True True True True True True True \n",
|
||
"18 10 True True True True True True True \n",
|
||
"19 10 True True True True True True True \n",
|
||
"20 10 True True True True True True True \n",
|
||
"\n",
|
||
"key ... id \\\n",
|
||
"agent_id 104 105 ... 90 91 92 93 94 \n",
|
||
"t_step ... \n",
|
||
"0 True True ... neutral neutral neutral neutral neutral \n",
|
||
"1 True True ... neutral neutral neutral neutral neutral \n",
|
||
"2 True True ... neutral infected neutral neutral neutral \n",
|
||
"3 True True ... neutral infected neutral neutral neutral \n",
|
||
"4 True True ... neutral infected neutral neutral neutral \n",
|
||
"5 True True ... neutral infected neutral neutral neutral \n",
|
||
"6 True True ... neutral infected neutral neutral neutral \n",
|
||
"7 True True ... neutral infected neutral neutral neutral \n",
|
||
"8 True True ... neutral infected neutral neutral neutral \n",
|
||
"9 True True ... neutral infected neutral neutral neutral \n",
|
||
"10 True True ... infected infected neutral infected neutral \n",
|
||
"11 True True ... infected infected neutral infected neutral \n",
|
||
"12 True True ... infected infected neutral infected neutral \n",
|
||
"13 True True ... infected infected neutral infected neutral \n",
|
||
"14 True True ... infected infected neutral infected neutral \n",
|
||
"15 True True ... infected infected neutral infected neutral \n",
|
||
"16 True True ... infected infected neutral infected neutral \n",
|
||
"17 True True ... infected infected neutral infected neutral \n",
|
||
"18 True True ... infected infected neutral infected infected \n",
|
||
"19 True True ... infected infected neutral infected infected \n",
|
||
"20 True True ... infected infected neutral infected infected \n",
|
||
"\n",
|
||
"key \n",
|
||
"agent_id 95 96 97 98 99 \n",
|
||
"t_step \n",
|
||
"0 neutral neutral neutral neutral neutral \n",
|
||
"1 neutral neutral neutral neutral neutral \n",
|
||
"2 neutral neutral neutral neutral neutral \n",
|
||
"3 neutral neutral neutral neutral neutral \n",
|
||
"4 neutral neutral neutral neutral neutral \n",
|
||
"5 neutral neutral neutral neutral neutral \n",
|
||
"6 neutral neutral neutral neutral neutral \n",
|
||
"7 neutral neutral neutral neutral neutral \n",
|
||
"8 neutral neutral neutral neutral neutral \n",
|
||
"9 neutral neutral neutral neutral neutral \n",
|
||
"10 neutral infected infected infected infected \n",
|
||
"11 neutral infected infected infected infected \n",
|
||
"12 neutral infected infected infected infected \n",
|
||
"13 neutral infected infected infected infected \n",
|
||
"14 infected infected infected infected infected \n",
|
||
"15 infected infected infected infected infected \n",
|
||
"16 infected infected infected infected infected \n",
|
||
"17 infected infected infected infected infected \n",
|
||
"18 infected infected infected infected infected \n",
|
||
"19 infected infected infected infected infected \n",
|
||
"20 infected infected infected infected infected \n",
|
||
"\n",
|
||
"[21 rows x 1001 columns]"
|
||
]
|
||
},
|
||
"execution_count": 5,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"agents"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2017-10-18T14:01:00.669671Z",
|
||
"start_time": "2017-10-18T16:01:00.635624+02:00"
|
||
}
|
||
},
|
||
"source": [
|
||
"The index of the results are the simulation step. Hence, we can access the state of the simulation at a given step (e.g., 13): "
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 6,
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2017-10-19T15:57:47.132212Z",
|
||
"start_time": "2017-10-19T17:57:47.084737+02:00"
|
||
},
|
||
"scrolled": true
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"agent_id\n",
|
||
"0 infected\n",
|
||
"1 infected\n",
|
||
"10 infected\n",
|
||
"100 infected\n",
|
||
"101 infected\n",
|
||
" ... \n",
|
||
"95 neutral\n",
|
||
"96 infected\n",
|
||
"97 infected\n",
|
||
"98 infected\n",
|
||
"99 infected\n",
|
||
"Name: 13, Length: 500, dtype: object"
|
||
]
|
||
},
|
||
"execution_count": 6,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"agents.loc[13, 'id']"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"Or, we can perform more complex tasks such as showing the agents that have changed their state between two simulation steps (2 and 1):"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 7,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"5"
|
||
]
|
||
},
|
||
"execution_count": 7,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"(agents.loc[2]['id'] != agents.loc[1]['id']).sum()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"To focus on specific agents, we can swap the levels of the index:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 8,
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2017-10-19T15:57:49.046261Z",
|
||
"start_time": "2017-10-19T17:57:49.019721+02:00"
|
||
},
|
||
"scrolled": true
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"<div>\n",
|
||
"<style scoped>\n",
|
||
" .dataframe tbody tr th:only-of-type {\n",
|
||
" vertical-align: middle;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe tbody tr th {\n",
|
||
" vertical-align: top;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe thead tr th {\n",
|
||
" text-align: left;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe thead tr:last-of-type th {\n",
|
||
" text-align: right;\n",
|
||
" }\n",
|
||
"</style>\n",
|
||
"<table border=\"1\" class=\"dataframe\">\n",
|
||
" <thead>\n",
|
||
" <tr>\n",
|
||
" <th>agent_id</th>\n",
|
||
" <th>NewsEnvironmentAgent</th>\n",
|
||
" <th>0</th>\n",
|
||
" <th>1</th>\n",
|
||
" <th>10</th>\n",
|
||
" <th>100</th>\n",
|
||
" <th>101</th>\n",
|
||
" <th>102</th>\n",
|
||
" <th>103</th>\n",
|
||
" <th>104</th>\n",
|
||
" <th>105</th>\n",
|
||
" <th>...</th>\n",
|
||
" <th>90</th>\n",
|
||
" <th>91</th>\n",
|
||
" <th>92</th>\n",
|
||
" <th>93</th>\n",
|
||
" <th>94</th>\n",
|
||
" <th>95</th>\n",
|
||
" <th>96</th>\n",
|
||
" <th>97</th>\n",
|
||
" <th>98</th>\n",
|
||
" <th>99</th>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>key</th>\n",
|
||
" <th>event_time</th>\n",
|
||
" <th>has_tv</th>\n",
|
||
" <th>has_tv</th>\n",
|
||
" <th>has_tv</th>\n",
|
||
" <th>has_tv</th>\n",
|
||
" <th>has_tv</th>\n",
|
||
" <th>has_tv</th>\n",
|
||
" <th>has_tv</th>\n",
|
||
" <th>has_tv</th>\n",
|
||
" <th>has_tv</th>\n",
|
||
" <th>...</th>\n",
|
||
" <th>id</th>\n",
|
||
" <th>id</th>\n",
|
||
" <th>id</th>\n",
|
||
" <th>id</th>\n",
|
||
" <th>id</th>\n",
|
||
" <th>id</th>\n",
|
||
" <th>id</th>\n",
|
||
" <th>id</th>\n",
|
||
" <th>id</th>\n",
|
||
" <th>id</th>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>t_step</th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>0</th>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>1</th>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2</th>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>3</th>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>4</th>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>5</th>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>6</th>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>7</th>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>8</th>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>9</th>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>10</th>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>11</th>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>12</th>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>13</th>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>14</th>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>15</th>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>16</th>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>17</th>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>18</th>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>19</th>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>20</th>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"<p>21 rows × 1001 columns</p>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
"agent_id NewsEnvironmentAgent 0 1 10 100 101 102 \\\n",
|
||
"key event_time has_tv has_tv has_tv has_tv has_tv has_tv \n",
|
||
"t_step \n",
|
||
"0 10 True True True True True True \n",
|
||
"1 10 True True True True True True \n",
|
||
"2 10 True True True True True True \n",
|
||
"3 10 True True True True True True \n",
|
||
"4 10 True True True True True True \n",
|
||
"5 10 True True True True True True \n",
|
||
"6 10 True True True True True True \n",
|
||
"7 10 True True True True True True \n",
|
||
"8 10 True True True True True True \n",
|
||
"9 10 True True True True True True \n",
|
||
"10 10 True True True True True True \n",
|
||
"11 10 True True True True True True \n",
|
||
"12 10 True True True True True True \n",
|
||
"13 10 True True True True True True \n",
|
||
"14 10 True True True True True True \n",
|
||
"15 10 True True True True True True \n",
|
||
"16 10 True True True True True True \n",
|
||
"17 10 True True True True True True \n",
|
||
"18 10 True True True True True True \n",
|
||
"19 10 True True True True True True \n",
|
||
"20 10 True True True True True True \n",
|
||
"\n",
|
||
"agent_id 103 104 105 ... 90 91 92 93 \\\n",
|
||
"key has_tv has_tv has_tv ... id id id id \n",
|
||
"t_step ... \n",
|
||
"0 True True True ... neutral neutral neutral neutral \n",
|
||
"1 True True True ... neutral neutral neutral neutral \n",
|
||
"2 True True True ... neutral infected neutral neutral \n",
|
||
"3 True True True ... neutral infected neutral neutral \n",
|
||
"4 True True True ... neutral infected neutral neutral \n",
|
||
"5 True True True ... neutral infected neutral neutral \n",
|
||
"6 True True True ... neutral infected neutral neutral \n",
|
||
"7 True True True ... neutral infected neutral neutral \n",
|
||
"8 True True True ... neutral infected neutral neutral \n",
|
||
"9 True True True ... neutral infected neutral neutral \n",
|
||
"10 True True True ... infected infected neutral infected \n",
|
||
"11 True True True ... infected infected neutral infected \n",
|
||
"12 True True True ... infected infected neutral infected \n",
|
||
"13 True True True ... infected infected neutral infected \n",
|
||
"14 True True True ... infected infected neutral infected \n",
|
||
"15 True True True ... infected infected neutral infected \n",
|
||
"16 True True True ... infected infected neutral infected \n",
|
||
"17 True True True ... infected infected neutral infected \n",
|
||
"18 True True True ... infected infected neutral infected \n",
|
||
"19 True True True ... infected infected neutral infected \n",
|
||
"20 True True True ... infected infected neutral infected \n",
|
||
"\n",
|
||
"agent_id 94 95 96 97 98 99 \n",
|
||
"key id id id id id id \n",
|
||
"t_step \n",
|
||
"0 neutral neutral neutral neutral neutral neutral \n",
|
||
"1 neutral neutral neutral neutral neutral neutral \n",
|
||
"2 neutral neutral neutral neutral neutral neutral \n",
|
||
"3 neutral neutral neutral neutral neutral neutral \n",
|
||
"4 neutral neutral neutral neutral neutral neutral \n",
|
||
"5 neutral neutral neutral neutral neutral neutral \n",
|
||
"6 neutral neutral neutral neutral neutral neutral \n",
|
||
"7 neutral neutral neutral neutral neutral neutral \n",
|
||
"8 neutral neutral neutral neutral neutral neutral \n",
|
||
"9 neutral neutral neutral neutral neutral neutral \n",
|
||
"10 neutral neutral infected infected infected infected \n",
|
||
"11 neutral neutral infected infected infected infected \n",
|
||
"12 neutral neutral infected infected infected infected \n",
|
||
"13 neutral neutral infected infected infected infected \n",
|
||
"14 neutral infected infected infected infected infected \n",
|
||
"15 neutral infected infected infected infected infected \n",
|
||
"16 neutral infected infected infected infected infected \n",
|
||
"17 neutral infected infected infected infected infected \n",
|
||
"18 infected infected infected infected infected infected \n",
|
||
"19 infected infected infected infected infected infected \n",
|
||
"20 infected infected infected infected infected infected \n",
|
||
"\n",
|
||
"[21 rows x 1001 columns]"
|
||
]
|
||
},
|
||
"execution_count": 8,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"agents.swaplevel(axis=1)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2017-10-19T10:35:40.140920Z",
|
||
"start_time": "2017-10-19T12:35:40.106265+02:00"
|
||
}
|
||
},
|
||
"source": [
|
||
"### Plotting data"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"If you don't want to work with pandas, you can also use some pre-defined functions from soil to conveniently plot the results:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 72,
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2017-10-19T15:57:52.271094Z",
|
||
"start_time": "2017-10-19T17:57:51.102434+02:00"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
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"text/plain": [
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||
"<Figure size 432x288 with 1 Axes>"
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]
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},
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"metadata": {
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"needs_background": "light"
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||
},
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||
"output_type": "display_data"
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||
},
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{
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"data": {
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"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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eEIX08HkzTe6hJioBBh5nH96Msf38PcneO/nXltvEX1sBxu3fflxRNuFHJdgTvjGpENvPtv/HpNpn72nP8sjYrn/PSnWjnYWVTjI/wPJthVTUNuAKE44bnMxt045m1MBEhqXHMSQ1lghX8Pwa1uTeV4hA4gD7GHqq7zLGQEONTfJ15VBX6UxXHPwH0DSv3D7XltueP1VFULTNPrc8J+AtPLp58o9OtvNaXgXc7CphX/OcK4cjYiBpECRm2vWV6qTymnqWbytk6Zb9LN18gF1FVQBkpsTw3XEDmTw8nZOO7EdSTHD/etXkrg4SsckyIgbwec9d/7jrobrYXgVcVXQw+VcVOtPFznMh7P8G3LVeF43V29cNtdjBSP2NPQwSBrbeqygpU5uSlE/uRsO6/FKWbt7Px1sOsHpXMQ2NhthIFycN68fsU4Yy+eh0svvF9njTSmdoclddzxUB8Rn20RmN7kOvEvb+B+Cut78mSvMP7VH09ctgDp7QajX5px8DmRP1OoI+6KvcEv72ybf8d/N+iqvqARg9KJE5k4dx6vB0JmSlEBkePM0sHaXJXQWvMJfTRn8Y7fTueihrkfSbkv8nzZP/nP/CwHFdGbkKUsYYPttexJ8/2srHWw6QGB3O9FH9Oe3odL5zVBpp8aEzJpQmdxWaXBG2J1BKtu/l7nrYtRyevcCeWNbkHtKMMXy4aR9/WrKV1btKSIuP4pfnHMOVJ2Z1W1fEQAvNd6VUe1wRMMi5artkR0BDUd3H3Wj419d7+POSrWzaW05mSgz/d9Fovjchk+iI0L7HgyZ31XdFxkJchr0KWIWU2gY3r63O5y//3caOwiqOyojn4UvHcsHYgUHVXbE7aXJXfVtKlh3TR4WEqroG/r4il6eWbmdvWQ1jBiXxl6smcOao/oSF9a2T5prcVd+WnAV5XwQ6CtVJpVX1PLd8Bws++ZbiqnpOHJbKg9/L4ZSj0npV98WupMld9W0pWXbMfXcDuPTr0NvsL6/l6WXf8sJnO6mobWDaMRn86PQjmZClI6Xqp1n1bclZdsiFsnyb6FWvsG1/BfM//pZXVufR4G7kvJyB3HTakYwamBjo0IKGJnfVt3kSeslOTe5BzhjD598WMf/j7by/cR9R4WFcMj6TOZOHMTQtLtDhBR1N7qpvS3YSevFOGBrYUJRvDe5G/r1uL099vJ21eaWkxkVy2/ThXH1iFv1C6KKjrqbJXfVtSZl2aALtMRN0KmobeGnFLv72yQ7yS6oZlhbHfTNGc8n40O+j3hU0uau+zRVhR5TUvu5BY09pNc98soMXV+yivKaBE4amcvd3j2XaMRl9rjtjZ2hyVyolC4p3BDqKPm/D7jLmf7ydN7/aTaMxnDNmAD84dRjjBicHOrReSZO7UslZsPW9QEfRJxlj+O/m/cz/+FuWbT1AbKSLq0/K4vrvDGVwqt7YpTM0uSuVkgUVBVBf7Yxlr3rCp9sOcO8/N7Bpbzn9E6O44+xj+P4JQ0iK1XH3u4Imd6U8PWZKdkH6iMDG0gcUVdZx37828srqPIakxvKH79kxX3rz2OnBSJO7Uile3SE1uXcbYwyvrM7nvn9toLymgZtPP5IfTx2uPV+6iSZ3pTxjvmt3yG6zfX8Fv3ptHcu3FzIhK4XfzhjDiCMSAh1WSNPkrlR8f3uTbu0x0+VqG9z89b/b+eOSrUSFh3HfjNFccfwQ7dLYAzS5KyVi76eqNfcuteLbIv73ta/Zuq+C83MGcOf5o8hIjA50WH2GJnelwJ5U1QuZukRJVR33v72JRStzGZQcw9+uO57TR3TyZumqwzS5KwX2pGreikBH0asZY3hjzW7+760NlFTXc+PkYfxk+nBiIzXNBILfR11EXMBKIN8Yc76IDAVeAvoBq4CrjTF1IhIFPAdMAAqBy4wxO7o8cqW6UnIW1JRCdQnEJAc6ml5nZ2Elv359HR9vOcDYwck8P2OMDr8bYB3pWPoTYKPX698B84wxRwHFwGxn/myg2Jk/zymnVHDzHvpX+a2uoZE/LdnKmfOW8uWuEu698FhevelkTexBwK/kLiKZwHnAfOe1AFOBxU6RZ4GLnOkLndc4y6dJX73Pleo9vIf+Ve2qbXDz6uo8zn/8Yx585xumHpPB+z87jWtOysalPWGCgr/NMo8AvwA8HVP7ASXGmAbndR4wyJkeBOQCGGMaRKTUKX/Ae4MiMgeYAzBkyJDDDF+pLqI1d78UlNWw8LOdvLhiFwcq6hiWHsf8ayYyfVT/QIemWmg3uYvI+cA+Y8wqEZnSVTs2xjwJPAkwceJE01XbVeqwxKRAVJLW3H0wxrBqZzHPfLqD/6zbi9sYpo7IYNbJ2ZxyVJr2WQ9S/tTcvwN8V0TOBaKBROBRIFlEwp3aeyaQ75TPBwYDeSISDiRhT6wqFdxStK+7t5p6N//8ajfPfLqD9bvLSIgO59qTs7n6pCyy+ult7YJdu8ndGPNL4JcATs39f4wxV4rIP4CZ2B4zs4A3nFXedF4vd5Z/aIzRmrkKfslZcGBLoKMIuN0l1bzw2U5e+iKXoso6ju4fz30zRjPjuEHarbEX6cxf6g7gJRH5DfAl8LQz/2ngeRHZChQBl3cuRKV6SEo2bP0AjLFXrfYhnptPP/vpDt7dUIAxhukj+3PtydmcdGQ/tE9E79Oh5G6M+Qj4yJneDpzgo0wN8L0uiE2pnpWcBQ3VULEPEvrGCcLqOjdvrMnnmU93sGlvOUkxEdxw6lCumpSlN8vo5fQ3llIe3j1mQjy5F1fW8cynO3h2+Q5Kquo55ogEHrh4DBeOG0RMpA7BGwo0uSvl4d3XffAhP0pDQkFZDfM/3s7Cz3dRVefmjFH9ueGUoZwwNFWbXkKMJnelPJKd6y1KdgQ0jO6wq7CKvyzdxuKVebiN4btjB3LTlCM5ur+OqR6qNLkr5REZC3EZIdXX/Zu95fz5o63886vdhIeF8b2Jmdw4+UiG9NP29FCnyV0pbylZIdHX/ctdxfz5o228t6GA2EgXN5w6jNmnDKW/jqfeZ2hyV8pbchbkfRHoKA6LMYZPtxXypyVb+XRbIUkxEdw2fTizTsomJS4y0OGpHqbJXSlvKVmw/jVwN4Crd3w9GhsN728s4E8fbeOr3BIyEqL41bkjuWLSEOKjesd7UF1P//JKeUvOAuOGsvyDXSODVG2Dm7e/3sMTH21jc0EFg1NjuG/GaC4Zn0l0hHZn7Os0uSvlzbuvexAmd2MM6/LLWLwqlze+2k1JVT1H94/nkcvGcX7OAMJdHblFgwplmtyV8ubd131oYEPxtr+8ljfW5LN4VR6b9pYTGR7GWccewcwJmZyqIzMqHzS5K+UtKRMkLCh6zNQ1NPLhpn0sXpXHR9/so6HRMG5wMr+5aDQX5AwkKTYi0CGqIKbJXSlvrghIzAxoX/f1u0tZvCqPN9bspqiyjvSEKGafOpSZ4zMZrhcdKT9pcleqpQD0dS+sqOWNNbv5x6o8Nu4pI9IVxhmj+ttml+Fp2pauOkyTu1ItJWfB1ve7bfM19W6Kq+oorqxnZ2Elr32Zz4ebbLNLTmYS9154LN8dO5DkWO2brg6fJnelWkrJgoq9UF8NETFtFq2qa6Cwoo6iyjqKq+ooqap3Encdxc50SVU9RZV1lFTZedX17mbbSIuP5LrvZDNzwmBGHKHNLqpraHJXqiVPj5mSXEg/utViG/eUccHjy2hoPPRGYyKQFBNBSmwkKbERDEiKZuSARFJiI0iJi2yan5YQxbjByURos4vqYprclWrJu697G8n96/xSGhoNvz5vJNn94kiJ8yTzSBJjInBp90QVQJrclWopJds+F+9os1heURVhArNOztaatwo6+olUqqX4/hAe3W6PmdziagYkxWhiV0FJP5VKtSRib9zRTl/33KIqMlPaPuGqVKBoclfKl+T2+7rnFlfpTaRV0NLkrpQvKVlttrnX1LspKKtlcIomdxWcNLkr5UtyFtSUQnWJz8X5JdUADE7VZhkVnDS5K+WLd3dIH3KLqgC0WUYFLU3uSvniPfSvD7nFTs1dm2VUkNLkrpQv7dTc84qqiAwPIyMhqgeDUsp/mtyV8iUmBaKS2qi5V5GZHKM3yVBBS5O7Uq1JGdJGm3u1treroKbJXanWJGe1WXPXnjIqmGlyV6o1KdlQsgtM81Efy2vqKamq15OpKqhpcleqNclZ0FANFfuazc4t8vRx1+Sugle7o0KKSDSwFIhyyi82xtwlIkOBl4B+wCrgamNMnYhEAc8BE4BC4DJjzI5uil+p7uPdYyahf9Ps3GKnj3uI19zr6+vJy8ujpqYm0KH0edHR0WRmZhIR4f9N0f0Z8rcWmGqMqRCRCGCZiPwb+Bkwzxjzkoj8BZgNPOE8FxtjjhKRy4HfAZd19M0oFXDefd0Hn9A0++AFTKHd5p6Xl0dCQgLZ2dmIaK+gQDHGUFhYSF5eHkOHDvV7vXabZYxV4byMcB4GmAosduY/C1zkTF/ovMZZPk30k6F6o+Qh9rlkR7PZecXVJESFkxTjfy2qN6qpqaFfv36a2ANMROjXr1+Hf0H51eYuIi4RWQPsA94DtgElxpgGp0geMMiZHgTkAjjLS7FNN0r1LpGxEJdxSI+Z3KIqMlNj+0TS6wvvsTc4nL+DX8ndGOM2xowDMoETgGM6vKcWRGSOiKwUkZX79+/v7OaU6h4phw79m1tcxWAdx71TRITbb7+96fVDDz3E3Xff3a37zM7O5pJLLml6vXjxYq699tpu3Wcgdai3jDGmBFgCnAQki4inzT4TyHem84HBAM7yJOyJ1ZbbetIYM9EYMzE9Pf3wolequ7Xo626M0QuYukBUVBSvvvoqBw4c6NH9rlq1ig0bNvToPgOl3eQuIukikuxMxwBnABuxSX6mU2wW8IYz/abzGmf5h8aYQ28Pr1RvkJIFpXngti2QhZV1VNe7tebeSeHh4cyZM4d58+YdsmzHjh1MnTqVnJwcpk2bxq5duwC49tprufXWWzn55JMZNmwYixcvblrnwQcf5PjjjycnJ4e77rqr1f3efvvt3HfffYfMLyoq4qKLLiInJ4cTTzyRtWvXAnD33Xdz/fXXM2XKFIYNG8Zjjz3WtM4LL7zACSecwLhx47jxxhtxu92HfTy6gz819wHAEhFZC3wBvGeMeQu4A/iZiGzFtqk/7ZR/GujnzP8ZMLfrw1aqhyRngXFDmf1hqkP9dp2bb76ZhQsXUlpa2mz+j3/8Y2bNmsXatWu58sorufXWW5uW7dmzh2XLlvHWW28xd65NLe+++y5btmxhxYoVrFmzhlWrVrF06VKf+7z00ktZvXo1W7dubTb/rrvu4rjjjmPt2rX89re/5ZprrmlatmnTJt555x1WrFjBPffcQ319PRs3bmTRokV88sknrFmzBpfLxcKFC7vq0HSJdrtCGmPWAsf5mL8d2/7ecn4N8L0uiU6pQPPu656SdXCoX03unZaYmMg111zDY489RkzMwV9Cy5cv59VXXwXg6quv5he/+EXTsosuuoiwsDBGjRpFQUEBYJP7u+++y3HH2TRVUVHBli1bmDx58iH7dLlc/PznP+f+++/nnHPOaZq/bNkyXnnlFQCmTp1KYWEhZWVlAJx33nlERUURFRVFRkYGBQUFfPDBB6xatYrjjz8egOrqajIyMrry8HSaP/3cleq7vPu6Dz1Yc9cbY3eN2267jfHjx3Pdddf5VT4q6uAQy57WXmMMv/zlL7nxxhv92sbVV1/N/fffz+jRozu8T5fLRUNDA8YYZs2axf333+/XNgJBhx9Qqi1JmSBhTT1m8oqrSIuPJDZS60VdITU1lUsvvZSnn366ad7JJ5/MSy+9BMDChQs59dRT29zGWWedxYIFC6iosJfj5Ofns2+fHTJi2rRp5OfnNysfERHBT3/602bt/aeeempTs8pHH31EWloaiYmJre5z2rRpLF68uGk/RUVF7NzZ9g3Ve5omd6Xa4oqAxMymHjO5RdVkhviwAz3t9ttvb9Zr5vHHH+dvf/sbOTk5PP/88zz66KNtrn/mmWfy/e9/n5NOOokxY8Ywc+ZMysvLaWxsZOvWraSmph6yzuzZs2loaGh6fffdd7Nq1SpycnKYO3cuzz777CHreBs1ahS/+c1vOPPMM8nJyeGMM85gz549HXzn3UuCoSPLxIkTzcqVKwMdhlK+PXM+uOtg9ruc9uAScjKTefyKQ05DhZyNGzcycuTIQIdx2NatW8eCBQt4+OGHAx1Kl/D19xCRVcaYib7Ka81dqfY4fd3djYbdJdXaDbKXGD16dMgk9sOhyV2p9qRkQcVe9hYVU+822lNG9Qqa3JVqj9NjZt8u2zc61If6VaFBk7tS7UnJBqB8r5PcQ3yoXxUaNLkr1R7nQqb6/d8SJjAwWZO7Cn6a3JVqT3x/CI9GSncxICmGCJd+bVTw00+pUu0RgeQhxFTm6pWpPay6uprTTjsNt9vN7t27mTlzps9yU6ZMob3u1HfeeSfvv/9+m2Vqa2uZPn0648aNY9GiRR2KdceOHbz44osdWgfsgGieQdAuv/xytmzZ0uFt+KLJXSl/JGeRUrdHe8r0sAULFnDxxRfjcrkYOHBgs5EgO+ree+9l+vTpbZb58ssvAVizZg2XXdaxu4MebnL3dtNNN/H73/++U9vw0OSulB8akoZwRGOB9pTpYQsXLuTCCy8EbPL0jAdTXV3N5ZdfzsiRI5kxYwbV1dXtbsu7hpydnc1dd93F+PHjGTNmDJs2bWLfvn1cddVVfPHFF4wbN45t27axatUqTjvtNCZMmMBZZ53VdBXq1q1bmT59OmPHjmX8+PFs27aNuXPn8vHHHzNu3DjmzZuH2+3m5z//edNQxH/9618BOxbOLbfcwogRI5g+fXrTEAZgh0F4//33m109e7h0gAyl/FASNZA0qWRoQue/dL3RPf9cz4bdZV26zVEDE7nrgmNbXV5XV8f27dvJzs4+ZNkTTzxBbGwsGzduZO3atYwfP77D+09LS2P16tX8+c9/5qGHHmL+/PnMnz+fhx56iLfeeov6+nquvvpq3njjDdLT01m0aBG/+tWvWLBgAVdeeSVz585lxowZ1NTU0NjYyAMPPNC0LsCTTz5JUlISX3zxBbW1tXznO9/hzDPP5Msvv+Sbb75hw4YNFBQUMGrUKK6//noAwsLCOOqoo/jqq6+YMGFCh9+TN03uSvlhb1gGacCw8ENuKqa6yYEDB0hOTva5bOnSpU3jvOfk5JCTk9Ph7V988cUATJgwoWmIYW/ffPMN69at44wzzgDA7XYzYMAAysvLyc/PZ8aMGQBER0f73P67777L2rVrm34tlJaWsmXLFpYuXcoVV1zR1NQ0derUZutlZGSwe/duTe5K9YSd7nRGA4PY127ZUNRWDbu7xMTEUFNT023b9wzl6xnGtyVjDMceeyzLly9vNr+8vNyv7RtjePzxxznrrLOazX/77bfbXK+mpqbZ+PaHS9vclfLD5lo7smBSTX47JVVXSUlJwe12+0zwkydPbjp5uW7duqbb4gFcc801rFixotP7HzFiBPv3729K7vX19axfv56EhAQyMzN5/fXXAdvDpqqqioSEhGaJ/6yzzuKJJ56gvr4egM2bN1NZWcnkyZNZtGgRbrebPXv2sGTJkmb73bx5s99jzbdFk7tSfthSHk4FcYSV7gp0KH3KmWeeybJlyw6Zf9NNN1FRUcHIkSO58847mzVhrF27loEDB3Z635GRkSxevJg77riDsWPHMm7cOD799FMAnn/+eR577DFycnI4+eST2bt3Lzk5ObhcLsaOHcu8efO44YYbGDVqFOPHj2f06NHceOONNDQ0MGPGDIYPH86oUaO45pprOOmkk5r2WVBQQExMDEcccUSn49chf5XywwWPL+OPZbeSlX0UXPlyoMPpEcEw5O/q1auZN28ezz//vF/ly8rKmD17Nv/4xz+6ObLuMW/ePBITE5k9e/Yhy3TIX6W6QW5xFRWxg5ruyKR6xvjx4zn99NNxu91+lU9MTOy1iR0gOTmZWbNmdcm2NLkr1Y7ymnpKquppSBxi78gUBL92+5Lrr78el8sV6DB6xHXXXUd4eNf0c9HkrlQ7covsBTKu1GxoqIaKvtljRvUumtyVakducRUAcf2H2RnaNKN6AU3uSrUjt8gm99RBR9sZxZrcVfDT5K5UO/KKq4mPCidxgKfmviOg8SjlD03uSrUjt6iKzJQYJDIO4jK05t6DunLI3670yCOPUFVV1eH1umt4X180uSvVjtziqoND/aZkaZt7D+rKIX+7UlvJ3d9um105vK8vmtyVaoMxhtyiaoZ4kntyltbce1BXDvk7ZcoU7rjjDk444QSOPvpoPv74Y4BWh+b96KOPOP/885vWv+WWW3jmmWd47LHH2L17N6effjqnn346APHx8dx+++2MHTuW5cuXc++993L88cczevRo5syZg6+LRbtyeF9fdOAwpdpQWFlHdb2bwZ47MKVkwfrXwN0Arj709fn3XNj7dddu84gxcM4DrS7ujiF/GxoaWLFiBW+//Tb33HMP77//Pk8//bTPoXlbc+utt/Lwww+zZMkS0tLSAKisrGTSpEn84Q9/AGDUqFHceeedAFx99dW89dZbXHDBBc2205XD+/qiNXel2uDpKTPYu+Zu3FCmA4h1t/aG/L3qqquAjg356z3M744dOwA7NO9zzz3HuHHjmDRpEoWFhR1uC3e5XFxyySVNr5csWcKkSZMYM2YMH374IevXr/e5nmd43+7Qh6oeSnVcbrH9ud+szR1su7tnui9oo4bdXbpjyF9fw/y2NjTvsmXLaGxsbHrdVizR0dFNV9HW1NTwox/9iJUrVzJ48GDuvvvuVtftquF9fWm35i4ig0VkiYhsEJH1IvITZ36qiLwnIluc5xRnvojIYyKyVUTWikjHb5GiVJDw1Nybboyd7CR0bXfvdj015G9rQ/NmZWWxYcMGamtrKSkp4YMPPmhap+Xwvt488aalpVFRUdHmSeCuGt7XF39q7g3A7caY1SKSAKwSkfeAa4EPjDEPiMhcYC5wB3AOMNx5TAKecJ6V6nXyiqtIi48kNtL5qiRlgoRpj5ke4hnyt+WNrW+66Sauu+46Ro4cyciRIzs15O8NN9zAjh07GD9+PMYY0tPTef311xk8eDCXXnopo0ePZujQoRx33HFN68yZM4ezzz6bgQMHHjIee3JyMj/4wQ8YPXo0RxxxBMcff7zP/Xbl8L4+GWM69ADeAM4AvgEGOPMGAN84038FrvAq31SutceECROMUsHoyqc+Mxf+cVnzmQ+PNmbxDYEJqAdt2LAh0CGYVatWmauuusrv8qWlpWbmzJndGFHXefjhh838+fP9Lu/r7wGsNK3k1Q6dUBWRbOA44HOgvzFmj7NoL9DfmR4E5HqtlufMU6rXadbH3UP7uveYUB7ytyuH9/XF7+QuIvHAK8Btxphmt0F3/oN0aBxUEZkjIitFZOX+/fs7sqpSPcLdaNhdUn2wG6SH9nXvUaE65G9XDu/ri1/JXUQisIl9oTHGc5vwAhEZ4CwfAE13Ds4HBnutnunMa8YY86QxZqIxZmJ6evrhxq9Ut9lbVkO92/iuuVfshfr2L5xRKlD86S0jwNPARmPMw16L3gQ8vylmYdviPfOvcXrNnAiUejXfKNVr7Cp0+rintEjunh4zJbmEOqM3JgkKh/N38Kfm/h3gamCqiKxxHucCDwBniMgWYLrzGuBtYDuwFXgK+FGHo1IqCHjGcR+c2qJZJiXbPod4u3t0dDSFhYWa4APMGENhYSHR0dEdWq/dBh9jzDJAWlk8zUd5A9zcoSiUCkJ5RVWECQxMbpncPX3dd/R4TD0pMzOTvLw89JxY4EVHR5OZmdmhdfQKVaVakVtczYCkGCJcLX7gxveH8OiQr7lHREQwdOjQQIehDpOOLaNUKzzjuB9CBJKHaI8ZFdQ0uSvVCp993D2Sta+7Cm6a3JXyoabeTUFZ7aE9ZTxStK+7Cm6a3JXyIb/EMxpkKyP2JWdBTQnUlPZcUEp1gCZ3pXw4ZBz3llJ0dEgV3DS5K+VD0zjurTXLJHuN665UENLkrpQPeUVVRIaHkZEQ5buA1txVkNPkrpQPucVVZCbHEBbWyvV7MSkQlaQ1dxW0NLkr5UNuUTWZrbW3e6RoX3cVvDS5K+VDbnHVoUP9tqR93VUQ0+SuVAvlNfWUVNW33lPGIyUbSnaBDqylgpAmd6VayC1qp6eMR3IW1FdB2e4eiEqpjtGBw5RqodWhfltKHWaf542CiFiISYVY5xHj/dzPazrl4LyoBDtOjVLdQJO7Ui00XcDUXs192BS46C9Qvhuqiuyj2nkuybXT1SW0egfKsHA7wuSIc2Hc92HgcZrsVZfR5K5UC3nF1cRHhZMcG9F2QVc4jLui7TKNbjtEQVVh8+RfVWini7bD6ufgi6cgY5RN8mMuhYT+bW9XqXZocleqBc9Qv9IVtegw18GmmtZUl8D6V2HNi/Dur+G9u2D4mTbRH302hEd2Pg7V52hyV6qF3OIqsvrF9dwOY5Jh4vX2sf8bm+S/egk2/9u2z+dcahP9gLE9F5Pq9bS3jFJejDHkFlW3397eXdJHwBn3wE/Xw5WLYdhpsHIB/HUyPHEKLP8zVOht71T7tOaulJfCyjqq693t95Tpbq5wGH6GfVQVwbpXbI3+nV/Ce/8Php8Fx11pm29c7ZwbUH2SJnelvPjdU6YnxabCCT+wj30bYc1C+GoRfPMviE2DSTfaZTEpgY5UBRFtllHKS9NQv+1dnRooGSPhzN/AzzbC91+GQRNgyX0wbzS8dyeUFwQ6QhUkNLkr5cVTc/d5Y+xg4gqHo8+CK1+GHy6z058+Do+MgX/drgOaKU3uSnnLK66iX1wkcVG9qMXyiDEwcwHcshLGXg6rnoXHjoPXfmh736g+SZO7Ul78Guo3WPU7Er77GPzkK9sOv+EN+NMkWHQV5K8OdHSqh2lyV8qLX0P9BrukQXD2/XDbOpj8c/h2KTx1Ojw/A3Ys01Es+whN7ko53I2G/OLq4D2Z2lFx/WDqr2ySn34P7F0Hz5wHC86Cze9okg9xmtyVcuwpraah0TAkVJK7R3QinHIb3LYWzn0IyvbAi5fCX06BrxeDuyHQEapuoMldKYff47j3VhExtj/8ravtaJbuOnhlNjw6Fj7+A1QWBjpC1YU0uSvl8Hsc997OFWFHs/zR53D5i/ZE7Af3wsMj4fWbYc9XgY5QdYFe1N9Lqe6VV1RFmMDA5BBP7h5hYXDMefaxbyOseNIOWLbmBRh8IkyaAyO/q8Mb9FLt1txFZIGI7BORdV7zUkXkPRHZ4jynOPNFRB4Tka0islZExndn8Ep1pdziagYkxRDh6oM/aDNGwvnz7JWvZ/0WKvbC4uvtRVH//T1U7At0hKqD/PkUPwOc3WLeXOADY8xw4APnNcA5wHDnMQd4omvCVKr7ecZx79NikuGkm+HHX9rhDTJGOcMbHAuv3gj5qwIdofJTu8ndGLMUKGox+0LgWWf6WeAir/nPGeszIFlEBnRRrEp1q9ziqtDpBtlZYWF2SIOrX7VXvk64Fja9BU9NhaemwdqXoaEu0FGqNhzu78/+xpg9zvRewHNPsEFArle5PGeeUkGtpt5NQVlt6PaU6Yy04XDug7bJ5pzfQ00JvPoDW5tfcr+9jaAKOp1uXDTGGFq9A3DrRGSOiKwUkZX79+vNB1Rg5Zd4RoPs480ybYlOtMMa3PwFXPkKDBwH//0d/PEEWP+6XhQVZA43uRd4mlucZ8/ZlnxgsFe5TGfeIYwxTxpjJhpjJqanpx9mGEp1jaZx3LVZpn1hYTB8Olz5D/jBhxCfAf+YBS9eBiW7Ah2dchxucn8TmOVMzwLe8Jp/jdNr5kSg1Kv5Rqmg1TSOuzbLdMyg8fCDJbaHzY5ldqCyTx/Xq16DgD9dIf8OLAdGiEieiMwGHgDOEJEtwHTnNcDbwHZgK/AU8KNuiVqpLpZXVEVkeBgZCVGBDqX3cYXbHjY3fwZDJ8O7v4anpmjPmgBr9yImY8wVrSya5qOsAW7ubFBK9bTc4ioyk2MIC5NAh9J7JQ+BK16CjW/C27+A+dPhhDkw9dcQlRDo6PqcPni1hlKH6tXjuAcTERh1IdyyAibOhs//ak+4bnwr0JH1OZrclSJExnEPJtFJcN5DcMP79gbfi66Ev38fSvMCHVmfocld9XnlNfWUVNVrT5nukDkR5nwEZ9wL2z60J1w/ewIa3YGOLORpcld9XsgP9Rtorgj4zk/sCdchJ8J/5sL8aTr6ZDfT5K76vD4z1G+gpWTDlYth5t+gNB+enALv/AqqWo5uorqCJnfV5zVdwKQ19+4nAqMvhlu+sOPVLP+jHcbg7Z9D0beBji6kaHJXfV5ecTXxUeEkx+q45T0mJtkOMXzTpzDqIlj5N3h8PLx8DeR+EejoQoImd9XneYb6FdE+7j2u/7Ew4wm47WvbLr/9I3h6Ojx9Fmz8p5547QRN7qrP06F+g0DiAJh+N/x0A5z9OyjfDYuugj9OhC/mQ11VoCPsdTS5qz7NGENuUbW2tweLqHg48Yf2ZiHfewZiUuBft9t2+Q/v0ztCdYAmd9WnFVbWUV3v1p4ywcYVDsfOgBs+gOv+A0NOgqUPwrzR8OaPYf83gY4w6OkNslWfpj1lgpwIZJ1kHwe2wmd/gjUvwurnYPhZcPItkH2qLaea0Zq76tOahvrVNvfgl3aU7WHz0/Uw5X/tqJPPXmAviNr0L2hsDHSEQUWTu+rTPDX3Pn9j7N4kLg2m3AE/XWeTfVUhvPR9eOJke29XHUse0OSu+ri84ir6xUUSF6UtlL1ORAxMvB5uWQUXz7fzXv2B7S+/cgHU1wQ2vgDT5K76NB3qNwS4wiHne/aCqMv/bmv2b/0UHh1r7wpVWxHoCANCk7vq03So3xASFgbHnGt72FzzJqSPsHeFemQ0fPRAnxvDRpO76rPcjYb84mo9mRpqRGDYaTDrTZvoh5wMH90Pj4yxyb58b6Aj7BGa3FWftae0moZGo90gQ1nmRLjiRbhpOYw4F5b/CR7Jsc02IT5QmZ5FUiGvus5NfkkVucXV5BVXk1dcRV5xNdv22bZYvYCpD+g/Ci55Ck7/JXzyKHz5Aqx6FkZfAjmXQtZ3IDK0/slrcle9Xk29u1nS9kznFleTX1zFgYq6ZuUjXWEMSokhMyWGE4f14/js1ABFrnpc6jC44FE4ba4dbnjl3+Drl8EVaa+CPWoaHDkV+o/u9RdGiTEm0DEwceJEs3LlykCHobqJMYaqOjdFlXWUVNVTXFVnH5V1lNU0UNvgpt5tqGtopM7dSF1DI/Vu+7DzDHVeZQ7Ob6S6zk1hZevJ2z5im02nx0cRFta7v7iqi9RXw67lsPUDexvAfRvs/Pj+NskfORWGnQ7x6YGNsxUissoYM9HXMq25K78YY6iud1NZ66aytoGK2oam5+KqekqchF1UeXC6uNIm8pKqeurcrV89GB4mRLjCiAwPs88uOTjdNC+MmAgXidHhTfMjXWFERbgYlBxNZkosg1M1easOiog5mMQByvbYJL/tA9j8Dnz1dzt/wFin3DQYPAnCIwMXs5+05t4HldXU8+3+SrYfqCCvqJpyJ1HbZG2Td2WdZ97B143tfFRcYUJKbAQpsZGkxEaS7JmOizw435lOjo0kNS6SxOhwwl16Xl8FocZG2LPGJvptSyD3c2hsgIg4GHqqTfRHToV+RwasCaetmrsm9xBV19DIrqIqvj1Qyfb9Fc5zJdsPVHKgorZZ2ajwMOKjwolzHvFRLmIjw515LmeeszzS5VXOPqfERpASF0lCVLje8EKFrpoy2PGxrdlv/QCKnd42EbE2wfcbDv2OgrThzuujIDqpW0PSZpkQZYxhX3mtk7QrnNq4Tea5xdW4varaafGRDE2LY9oxGQxNj2NYWhzD0uMYnBpLVLgrgO9CqV4iOhGOOc8+AIq2w/b/woHNcGAL7P4SNrwOxqsJMi7DK9l7Jf+UbHB1720dNbkHMWMM+ytqm/UA8Z7OL66mtuHgByk6IozsfnEcOzCJ83MGMiw9jqFpcQxLiydJ7w+qVNdKHWYf3hpqoXiHTfaFW6FwCxRug01vQ9WBg+XEZRN8v6Ng0hw4anqXh6fJPYCMMRyoqDskaXs/eydvgNS4SDJTYjjmiASmj+xPZkoMw9LiGZoex4DEaD2RqFQghUfZYQ/SRxy6rLrYJvrCrV7Jf2u3jX2jyb2HlNfUs7mgnE17y/lm78Hn0ur6ZuVSYiPITInl6P4JTD0mg8GpsU1d+AYlx+johUr1VjEp9orZTJ9N5F1OM0UXq3c3sn1/JZv2lvGNVyLPL6luKhMfFc7R/eM5d8wAju4fz5DUWJu8U2KI1+StlOoCmkla0dhoqPO6kKbebah3N1Lb4gKb0up6vikob0rk2/ZXUO+2JzLDw4Rh6XGMz0rh+5OGMKJ/AiOOSCAzJUZ7lSilulW3JHcRORt4FHAB840xD3THftpjjKG0up6Cslr2lddQUFZLQVkN+8pq2Fdup4sq65qugqz3ujqyob1O3S0MSo5hxBEJnH5MBsccYZP4sLR4IsO1D7dSqud1eXIXERfwJ+AMIA/4QkTeNMZs6Op97SurYXNBBQVlNRSU17DPK4l7nusaDr0yMiE6nP6J0WQkRDF6UBLRES4iXGFEhYcR4Wp+tWRUiyslI1zSbF5cVDhHZcSTGK29UZRSwaM7au4nAFuNMdsBROQl4EKgy5P7K6vz+d1/NjW9TogKJyMxioyEaCYMSaF/YjTpCVH0T4x2HnZZTKT261ZKhbbuSO6DgFyv13nApG7YD+fnDGD8kGRbC0+MIjZSTyEopRQE8ISqiMwB5gAMGTLksLYxODVW76KjlFI+dMfZvnxgsNfrTGdeM8aYJ40xE40xE9PTg3M4TaWU6q26I7l/AQwXkaEiEglcDrzZDftRSinVii5vljHGNIjILcA72K6QC4wx67t6P0oppVrXLW3uxpi3gbe7Y9tKKaXap1fYKKVUCNLkrpRSIUiTu1JKhaCguM2eiOwHdh7m6mnAgXZLBY7G1zkaX+cFe4wa3+HLMsb47EseFMm9M0RkZWv3EAwGGl/naHydF+wxanzdQ5tllFIqBGlyV0qpEBQKyf3JQAfQDo2vczS+zgv2GDW+btDr29yVUkodKhRq7koppVrQ5K6UUiGo1yR3ETlbRL4Rka0iMtfH8igRWeQs/1xEsnswtsEiskRENojIehH5iY8yU0SkVETWOI87eyo+Z/87RORrZ98rfSwXEXnMOX5rRWR8D8Y2wuu4rBGRMhG5rUWZHj9+IrJARPaJyDqveaki8p6IbHGeU1pZd5ZTZouIzOqh2B4UkU3O3+81EUluZd02PwvdHOPdIpLv9Xc8t5V12/y+d2N8i7xi2yEia1pZt0eOYacYY4L+gR1dchswDIgEvgJGtSjzI+AvzvTlwKIejG8AMN6ZTgA2+4hvCvBWAI/hDiCtjeXnAv8GBDgR+DyAf+u92IszAnr8gMnAeGCd17zfA3Od6bnA73yslwpsd55TnOmUHojtTCDcmf6dr9j8+Sx0c4x3A//jx2egze97d8XXYvkfgDsDeQw78+gtNfem+7IaY+oAz31ZvV0IPOtMLwamiYj0RHDGmD3GmNXOdDmwEXu7wd7kQuA5Y30GJIvIgADEMQ3YZow53CuWu4wxZilQ1GK29+fsWeAiH6ueBbxnjCkyxhQD7wFnd3dsxph3jTENzsvPsDfKCZhWjp8//Pm+d1pb8Tm541Lg7129357SW5K7r/uytkyeTWWcD3gp0K9HovPiNAcdB3zuY/FJIvKViPxbRI7t2cgwwLsissq5xWFL/hzjnnA5rX+hAnn8PPobY/Y403uB/j7KBMOxvB77S8yX9j4L3e0Wp+loQSvNWsFw/E4FCowxW1pZHuhj2K7ektx7BRGJB14BbjPGlLVYvBrb1DAWeBx4vYfDO8UYMx44B7hZRCb38P7b5dy567vAP3wsDvTxO4Sxv8+Dri+xiPwKaAAWtlIkkJ+FJ4AjgXHAHmzTRzC6grZr7UH/feotyd2f+7I2lRGRcCAJKOyR6Ow+I7CJfaEx5tWWy40xZcaYCmf6bSBCRNJ6Kj5jTL7zvA94DfvT15tf977tZucAq40xBS0XBPr4eSnwNFc5z/t8lAnYsRSRa4HzgSudfz6H8OOz0G2MMQXGGLcxphF4qpV9B/Sz6OSPi4FFrZUJ5DH0V29J7v7cl/VNwNMrYSbwYWsf7q7mtM89DWw0xjzcSpkjPOcAROQE7LHvkX8+IhInIgmeaeyJt3Utir0JXOP0mjkRKPVqfugprdaWAnn8WvD+nM0C3vBR5h3gTBFJcZodznTmdSsRORv4BfBdY0xVK2X8+Sx0Z4ze53FmtLLvQN+HeTqwyRiT52thoI+h3wJ9RtffB7Y3x2bsWfRfOfPuxX6QAaKxP+e3AiuAYT0Y2ynYn+drgTXO41zgh8APnTK3AOuxZ/4/A07uwfiGOfv9yonBc/y84xPgT87x/RqY2MN/3zhssk7ymhfQ44f9R7MHqMe2+87Gnsf5ANgCvA+kOmUnAvO91r3e+SxuBa7rodi2YtuqPZ9BT++xgcDbbX0WevD4Pe98vtZiE/aAljE6rw/5vvdEfM78ZzyfO6+yATmGnXno8ANKKRWCekuzjFJKqQ7Q5K6UUiFIk7tSSoUgTe5KKRWCNLmrPkFEkkXkR4ex3v92RzxKdTftLaP6BGdYiLeMMaM7uF6FMSa+e6JSqvtozV31FQ8ARzpDtD7YcqGIDBCRpc7ydSJyqog8AMQ48xY65a4SkRXOvL+KiMuZXyEi88QO+fyBiKT37NtTqjmtuas+ob2au4jcDkQbY+5zEnasMabcu+YuIiOxQ/5ebIypF5E/A58ZY54TEQNcZYxZKHas+QxjzC098uaU8iE80AEoFSS+ABY4YwS9boxZ46PMNGAC8IUzEkIMB8eWaeTgWCQvAIeML6RUT9JmGaVoGtt7MnaAqmdE5BofxQR41hgzznmMMMbc3domuylUpfyiyV31FeXYu2T5JCJZ2PG7nwLmY+/QA1Dv1ObBjikzU0QynHVSnfXAfpdmOtPfB5Z1cfxKdYgmd9UnGGMKgU+ck6WHnFDF3sbvKxH5ErgMeNSZ/ySwVkQWGmM2AL/G3qRhLfYOS55RDiuBE8Tej3MqdlA7pQJGT6gq1QW0y6QKNlpzV0qpEKQ1d9WniMgY7Jji3mqNMZMCEY9S3UWTu1JKhSBtllFKqRCkyV0ppUKQJnellApBmtyVUioEaXJXSqkQpMldKaVC0P8HaNHkwboimVIAAAAASUVORK5CYII=",
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||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"analysis.plot_all('soil_output/Spread_barabasi_albert_graph_prob_0.0/', analysis.get_count, 'id');"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 71,
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2017-10-19T15:57:57.982007Z",
|
||
"start_time": "2017-10-19T17:57:52.273160+02:00"
|
||
},
|
||
"scrolled": false
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"analysis.plot_all('soil_output/Spread_barabasi_albert_graph_prob_0.3/', analysis.get_count, 'id');"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 12,
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2017-10-19T15:58:26.903783Z",
|
||
"start_time": "2017-10-19T17:57:57.983957+02:00"
|
||
},
|
||
"scrolled": true
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"/home/j/.local/lib/python3.8/site-packages/pandas/plotting/_matplotlib/core.py:328: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).\n",
|
||
" fig = self.plt.figure(figsize=self.figsize)\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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8eDCpqamnvB5N6Kpe2rgnn4nT0+neIoanXbr110ZSQhQbdx/CGs5InYqysjKPrMeJhF5aWurT7Z2IXoeu6p28wyXc9G4qEaFBTLo2hQZhwTUvVIWkhCjyi0rZk19Es5gID0fpeY98vpo1Ow56dJ3dWsTw0KXdT1gmMzPz6PjlS5cupXv37kyZMoVu3boxatQovvnmG+69916MMfz73//GGMMll1zCU089dXQd99xzD19//TWJiYlMnz6dqu6nMGvWLFJTUxk7diwNGjTgiSee4K233jo67suCBQt49tlnmTNnznHLlpWVceONN5KamoqIcMMNN3DPPfcwePBgevXqxffff09paSlvvfUW/fv35+GHH2bTpk1s3ryZNm3a8MILL3Drrbeybds2AP773/8ycOBAfv31VyZOnEhhYSENGjTg7bffpnPnzhw5coQ//OEPLF++nC5dunDkiGeultIauqpXKrr1Zx84wmvj+tEirkHNC1Wjk54Yddu6deu4/fbbycjIICYmhldeeQWAJk2asHTpUgYNGsTf/vY35s+fT3p6OkuWLOHTTz8FoKCggJSUFFavXs0555zDI488UuU2Ro4cSUpKCu+//z7p6elceOGFLF68mIICaxC1GTNmMHr06CqXTU9PJzs7m1WrVrFy5cpjBvc6fPgw6enpvPLKK9xwww1Hp69Zs4Zvv/2WadOmMXHiRO655x6WLFnCRx99xE033QRAly5d+PHHH1m2bBmPPvoo999/PwCvvvoqDRs2JCMjg0ceeYS0tLRT28E2raGreuXJeWv5cUMuT17Rg5R2jU9pXRVXumzYnc/ApKaeCM+raqpJe1Pr1q0ZOHAgAOPGjeOFF14AYNSoUQAsWbKEwYMHH615jx07lh9++IHLLruMoKCgo+XGjRvHFVdc4dY2Q0JCGDJkCJ9//jkjR47kiy++4Omnn66ybIcOHdi8eTN33XUXl1xyCRdddNHReRUDfQ0aNIiDBw9y4MABAIYPH06DBlaF4Ntvv2XNmjVHlzl48CCHDh0iLy+P6667jg0bNiAiR++g9MMPP3D33XcD0LNnT3r27OnWe6rxPXtkLUrVAbPSsnhj4RauP7Mdo/u3OeX1xUeHExMRoidG3VD5HEXF68jIyFNe14mMHj2al156icaNG5OSkkJ0dNWXpTZq1Ijly5fz1Vdf8dprrzFz5kzeeustt2MvLy9n0aJFREQc2/R25513cu655/LJJ5+QmZnJ4MGD3Y79ZGiTi6oXlm7bz/0fr+TMjk144JKuHlmniOiYLm7atm0bv/zyCwAffPABZ5111jHz+/fvz/fff09ubi5lZWVMmzaNc845B7CS5axZs6pd1lV0dDT5+b919jrnnHNYunQpkydPrra5BSA3N5fy8nKuvPJKHnvsMZYuXXp03owZMwBrJMfY2FhiY2OPW/6iiy46ZiyZihtw5OXl0bJlS8A6YVth0KBBfPDBBwCsWrWKFStWVBtbbWhCVwFvV14ht0xNIzE2gpev6evRuwwl2WO6qBPr3LkzL7/8Ml27dmX//v3cdtttx8xv3rw5Tz75JOeeey69evWiX79+jBgxArBqwr/++ivJycnMnz+fBx98sNrtXH/99dx666307t2bI0eOEBwczLBhw5g3bx7Dhg2rdrns7GwGDx5M7969GTduHE888cTReREREfTp04dbb72VN998s8rlX3jhBVJTU+nZsyfdunXjtddeA+Dee+/l73//O3369DnmapjbbruNQ4cO0bVrVx588EH69etX8050gzh1yVVKSorxxHWXSp1IYUkZo17/hY17DvHx7QPpnOheT1B3Tf5hM4/PzWDZPy+kUWTNQwb4WkZGBl27euYXycnKzMxk2LBhR8c1r0sGDx7Ms88+S0pKiiPbr+rzE5E0Y0yVAWkNXQUsYwx//3gly7Py+M+o3h5P5uA6povW0pXz9KSoCliTf9zMJ8uy+dOFp3FR90SvbMN1TJfTT/GqmUDletchT7njjjv46aefjpk2ceJEt+4lOmDAAIqKio6ZNnXqVHr06HFc2QULFpxSnL6mCV0FpO/W7eHJeWu5uEcid52X5LXttIxrQIPQYD0x6mMvv/zySS+7ePFiD0biX7TJRQWcTTmHuHvaMjonxvDsVb1Oqlu/u4KChA7xkX7d5KJDE9RNJ/O5aUJXASXvSAk3v5tKWHAQk8f3o2GY93+EdkqIYpOf9haNiIhg7969mtTrGGMMe/fuPe669ppok4sKGGXlhrunLWPbvsN8cPMZtGrU0CfbTUqI4tP0HRQUlRIZ7l9fqVatWpGVlUVOTo7ToahaioiIoFWrVrVaxr+OPqVOwdNfruX79Tk8fnky/dv77gRlUoJ19cymnEP0bBXns+26IzQ0lPbt2zsdhvIRbXJRAeGTZVm8/sNmxp3RhrED2vp027+N6eKfzS6q/tCEruq85dsP8LePVjKgfWNHBqBq26QhIUHi1ydGVf2gCV3VaXsOFjJhairxUeG8Mtaz3frdFRocRPumkVpDV47ThK7qrMKSMiZMTSO/sJQ3rkuhSVS4Y7HomC7KH2hCV3WSMYYHPllF+vYDPHd1L7o2j3E0nk4JUWzdW0BRqWdupabUyXAroYvIEBFZJyIbReS+Kua3EZHvRGSZiKwQkYs9H6pSv3lz4RY+WprFxPM7MSS5udPh0DEhinIDW3ILnA5F1WM1JnQRCQZeBoYC3YAxItKtUrF/ADONMX2A0cArng5UqQo/rM/h33Mz+H33Zkw8v5PT4QDHjumilFPcqaH3BzYaYzYbY4qB6cCISmUMUPGbNxbw7W23Vb2xJbeAOz9YymnNonnu6t4EBXmvW39tdIyPQkQvXVTOciehtwS2u7zOsqe5ehgYJyJZwFzgrqpWJCITRCRVRFK155qqrfzCEm6ekkpwkDB5fIpf9cqMCA2mdaOGeumicpSnToqOAd4xxrQCLgamishx6zbGTDLGpBhjUipuBquUO8rKDROnp5OZW8ArY/vRurFvuvXXhj+P6aLqB3cSejbQ2uV1K3uaqxuBmQDGmF+ACMD/b4Ou6oxnv17H/LV7eOjSbvyuYxOnw6lSUkIUm3MKKC0rdzoUVU+5k9CXAJ1EpL2IhGGd9Jxdqcw24HwAEemKldC1TUV5xGfp2by6YBNj+rdh3Bm+7dZfGx0ToiguK2f7/iNOh6LqqRoTujGmFLgT+ArIwLqaZbWIPCoiw+1ifwZuFpHlwDTgeqPjdSoPWJmVx72zVtC/XWMeGd7dq2Obn6pOR8d0ya+hpFLe4dZZJWPMXKyTna7THnR5vgYY6NnQVH23J9/q1t80KpxXxvUlLMS/+8F1dLm/6EUOx6LqJ/+5TEApF0WlZdz23lL2Hy7mo9vOpKmD3frdFRMRSmJMhF6LrhyjCV35HWMMD366mrSt+3npmj50bxHrdEhuS0qI0oSuHOPfv2FVvfTuz5nMSN3OXeclMaxnC6fDqZWKhK6nkJQTNKErv/LTxlz+9UUGF3Zrxj0XnOZ0OLWWlBDF4eIyduQVOh2Kqoc0oSu/sXVvAbe/v5SO8ZH8Z5T/dOuvDR3TRTlJE7ryC4eKSrl5SioiMHl8ClF+1K2/NjppQlcOqpvfGhVQyssN98xIZ1NOAVNu6E/bJpFOh3TSmkSF06hhKBv36LXoyve0hq4c959v1/PNmt3845KuDEyq+yNG6JUuyima0JWjvlixkxfnb+TqlFZcf2Y7p8PxiKSEaDbolS7KAZrQlWNWZefx5w/T6de2Ef+6LNmvu/XXRlJCFAcOl7C3oNjpUFQ9owldOSL3UBETpqTSqGEYr43rR3hIsNMheYyeGFVO0YSufK64tJzb3ktjb0Exk65NIT7a/7v110bFpYsbNKErH9OrXJRPGWN4aPZqlmTu5/nRvenRqu5063dX89gIIsOC9WYXyue0hq586r1FW5n26zZuG9yREb0r38kwMIgISQlRbNBLF5WPaUJXPvPLpr088vkazuuSwF8u6ux0OF7VUS9dVA7QhK58Yvu+w9z+fhptmzTkv6N7E1wHu/XXRqeEaHYfLOJgYYnToah6RBO68roCu1t/WbnhjetOJyYi1OmQvE7HdFFO0ISuvKq83PCnmems353PS9f0pX3Tututvzb00kXlBE3oyque/98Gvlq9m/sv7sqg0+KdDsdnWjduSFhIkCZ05VOa0JXXzFu5k+f/t4Er+7bixrPaOx2OTwUHCR2aRmpCVz6lCV15RcbOg/xp5nJ6t47j8csDp1t/beggXcrXNKErj9tXUMzNU1KJaRDCpGv7EREaON36ayMpIYrt+w9TWFLmdCiqntCErjyqpKyc299PY09+EZOuTSEhJsLpkBzTKSEaY2BTjtbSlW9oQlce9ejna1i0eR9PXdmDXq3jnA7HUXrpovI1TejKY95fvJWpi7Zyy6AOXN6nldPhOK5d04YEiSZ05Tua0JVHLN68l4c+W83gzvHcO6SL0+H4hfCQYNo1iWTDbk3oyjc0oatTlrX/MLe9v5Q2TRry/Og+Ad+tvzY6JkSxUdvQlY9oQlen5HBxKTdPSaOkrJzJ41OIbRD43fpro1NCFJm5BZSUlTsdiqoHNKGrk2aM4a8frmDtroO8MKYPHeOjnA7J7yQlRFFabti6t8DpUFQ9oAldnbSX5m/ki5U7uW9IF87tnOB0OH5Jr3RRvuRWQheRISKyTkQ2ish91ZS5WkTWiMhqEfnAs2Eqf/P16l383zfrubxPSyYM6uB0OH6r4leLnhhVvlDjLehEJBh4GbgQyAKWiMhsY8walzKdgL8DA40x+0VEq2sBbN2ufO6ZkU6vVrE8cUWPetmt312R4SG0jGugJ0aVT7hTQ+8PbDTGbDbGFAPTgRGVytwMvGyM2Q9gjNnj2TCVv9hfUMxNU5YQGR7C69em1Ntu/bWhY7ooX3EnobcEtru8zrKnuToNOE1EfhKRRSIyxFMBKv9RUlbOHR8sZXdeEa9d24/E2Prbrb82khKi2JRziPJy43QoKsB56qRoCNAJGAyMASaLSFzlQiIyQURSRSQ1JyfHQ5tWvvL4Fxn8vGkv/76iB33bNHI6nDojKSGKwpJysg8ccToUFeDcSejZQGuX163saa6ygNnGmBJjzBZgPVaCP4YxZpIxJsUYkxIfX39udhAIZizZxjs/Z3LjWe0Z2U+79ddGxd2LNuzJdzgSFejcSehLgE4i0l5EwoDRwOxKZT7Fqp0jIk2xmmA2ey5M5aTUzH3849NVnN2pKX8fqt36a0svXVS+UmNCN8aUAncCXwEZwExjzGoReVREhtvFvgL2isga4Dvgr8aYvd4KWvnOjgNHuPW9NFrGNeClMX0JCdauC7UV1zCMplHhmtCV19V42SKAMWYuMLfStAddnhvgT/ZDBYgjxWVMmJpKYUk50yekENtQu/WfrKSESDZoQldeptUtVSVjDH+dtZzVOw7ywpjeJCVEOx1SnVZx6aJV91HKOzShqyq9smATc1bs5K+/78x5XZo5HU6d1ykhmvzCUvbkFzkdigpgmtDVcb5ds5tnv17H8F4tuO2cjk6HExD0xKjyBU3o6hgbdufzxxnpdG8Rw1NX9tRu/R7SSRO68gFN6OqovMMl3DwllYjQYCZdm0KDMO3W7ynx0eFER4TotejKqzShKwBKy8q5c9pSsg8c4fVr+9IiroHTIQUUEdExXZTXaUJXADwxby0/bsjl8ct60K9tY6fDCUidNKErL9OErvgwdTtvLtzC9We24+rTW9e8gDopSQlR5B4q5sDhYqdDUQFKE3o9l7Z1Pw98soqBSU34xyVdnQ4noHWyr+XXWrryFk3o9diuvEJufS+NxNgI7dbvA0lHB+nShK68w62u/yrwFJZY3foPF5Xy/k0DaBQZ5nRIAa9lXAMiQoO0hq68RhN6PWSM4b6PVrAyO49J16ZwWjPt1u8LQUFCx/goraErr9Hf2PXQpB8282n6Dv584Wlc2E279ftSUkIUmzShKy/RhF7PfLd2D09+uZZLejbnjnOTnA6n3umUEEX2gSMUFJU6HYoKQJrQ65GNew5x97RldE2M4ZmR2q3fCXpiVHmTJvR6Iu9ICROmpBIWEsTk61JoGKanT5zQt20jRGDBuj1Oh6ICkCb0eqCs3HD3tGVs33+YV8f1o6V263dMQnQEKW0b8eWqXU6HogKQJvR64Kkv1/L9+hweGZ5M//bard9pQ5Kbs3ZXPltyC5wORQUYTegB7uOlWUz6YTPjf9eWawa0cTocBQxJTgTQWrryOE3oASx9+wHu+3glv+vQhH8O6+Z0OMrWMq4BvVrF8uWqnU6HogKMJvQAtftgIbdMTSUhOpyXx/YlVLv1+5Uhyc1ZnpVH9oEjToeiAoh+ywOQ1a0/jfzCUt64LoXG2q3f72izi/IGTegBxhjD/Z+sZPn2Azx3dW+6JMY4HZKqQvumkXRJjNZmF+VRmtADzJsLt/Dx0mz+eEGno7VA5Z+GJCeSunU/e/ILnQ5FBQhN6AHk+/U5/HtuBkOTE7n7vE5Oh6NqMDS5OcbA16t3Ox2KChCa0APEltwC7vpgKac1i+bZq3oRFKTd+v3dac2i6NA0UtvRlcdoQg8ABwtLuOndJYQEBzF5fAqR4dqtvy4QEX6fnMgvm/eyv0BvS6dOnSb0Oq6s3PDH6els3XuYV8b2pXXjhk6HpGphaHIiZeWGbzK02UWdOk3oddwzX61j/to9PDS8O2d0aOJ0OKqWerSMpWVcA212UR6hCb0O+yw9m9e+38Q1A9pw7RltnQ5HnQQRYUhyIgs35JJfWOJ0OKqO04ReR63IOsC9s1bQv11jHr60u9PhqFMwNDmR4rJy5q/VIXXVqXEroYvIEBFZJyIbReS+E5S7UkSMiKR4LkRV2Z78QiZMSaNpVDivjOtLWIj+X67L+rZpRHx0uDa7qFNWYyYQkWDgZWAo0A0YIyLHjfQkItHARGCxp4NUvykqLePWqWnkHSlh0vh+NI0KdzokdYqCgoTfd2/GgnU5HCkuczocVYe5U7XrD2w0xmw2xhQD04ERVZT7F/AUoN3evMQYwz8/XcXSbQf4v6t70b1FrNMhKQ8ZmtycIyVlfL9em13UyXMnobcEtru8zrKnHSUifYHWxpgvPBibquSdnzOZmZrF3eclcXGP5k6HozxoQPvGNGoYyjxtdlGn4JQbX0UkCHgO+LMbZSeISKqIpObk5JzqpuuVhRtyeeyLDC7q1ow/XnCa0+EoDwsJDuLCbs2Yn7GHolJtdlEnx52Eng20dnndyp5WIRpIBhaISCZwBjC7qhOjxphJxpgUY0xKfHz8yUddz2TmFnDHB0vpGB/Jc6N6a7f+ADU0uTn5RaX8vHGv06GoOsqdhL4E6CQi7UUkDBgNzK6YaYzJM8Y0Nca0M8a0AxYBw40xqV6JuJ7JLyzh5impiMAb408nSrv1B6wzk5oQHR7CPB1SV52kGhO6MaYUuBP4CsgAZhpjVovIoyIy3NsB1mfl5YZ7ZqSzObeAV67pS5sm2q0/kIWHBHNe1wS+WbOb0rJyp8NRdZBb1T1jzFxgbqVpD1ZTdvCph6UAnvtmPd9m7OGR4d05M6mp0+EoHxianMhn6TtYvGUfA/UzV7WkPVL81JwVO3jpu42MPr0143+n3frri3NOS6BBaLA2u6iTogndD63KzuMvHy4npW0jHh2RjIieBK0vGoQFM7hzPF+t3k15uXE6HFXHaEL3Mzn5RUyYkkrjhmG8Oq6fduuvh4YkJ5KTX8TSbfudDkXVMZot/EhxaTm3vZfGvsPFTBqfQny0duuvj87rkkBYcJB2MlK1pgndTxhjeGj2KlK37ueZkb1Ibqnd+uur6IhQzurUlC9X7cIYbXZR7tOE7iemLtrKtF+3c/vgjlzaq4XT4SiHDUlOJPvAEVZm5zkdiqpDNKH7gZ835fLI52u4oGsCf7mos9PhKD9wYddmBAeJNruoWtGE7rDt+w5zx/tL6dA0kv9ot35laxQZxu86NNFmF1UrmtAddKiolJveTaXcwOTxKURHhDodkvIjQ5IT2ZJbwPrdh5wORdURmtAdUl5u+NOMdDbsyeela/rQrmmk0yEpP3NR92aIoJ2MlNs0oTvkv//bwNdrdvPAJd04u5OOPKmOlxAdQUrbRnprOuU2TegOmLdyJy/8bwMj+7XihoHtnA5H+bEhyc1ZuyufLbkFToei6gBN6D62ZsdB/jRzOX3axPH45dqtX53YkOREQJtdlHs0ofvQ3kNF3DwlldgGobw+rh/hIcFOh6T8XMu4BvRqFctX2uyi3KAJ3UdKysq5/f2l5B4qYtL4fiTERDgdkqojfp+cyPKsPLIPHHE6FOXnNKH7yCOfr2bxln08PbInPVvFOR2OqkOGJls3BNeTo6ommtB94L1FW3lv0TZuOacDI3q3dDocVce0bxpJl8RovtR2dFUDTehetmjzXh6evZpzO8dz7++7OB2OqqOGJCeSunU/e/ILnQ5F+TFN6F60fd9hbn9/KW2aNOT5MX0I1m796iQNTW6OMfDV6t1Oh6L8mCZ0LzlcXMrNU1IpKSvnjfEpxGi3fnUKTmsWRYemkXq1izohTeheYIzhLx8uZ/3ufF66pi8d4qOcDknVcSLC75MT+WXzXvYXFDsdjvJTmtC94MX5G5m7chd/H9qVc07Tbv3KM4YmJ1JWbvgmQ5tdVNU0oXvYl6t28dw367miT0tuOru90+GoANKjZSwt4xro5YuqWprQPWjtroP8aWY6vVrH8e8remi3fuVRIsKQ5EQWbsglv7DE6XCUH9KE7iH7Coq5eUoqUeEhTLq2HxGh2q1fed6wns0pLivnrYWZToei/JAmdA8oKSvnjveXsvtgEa9f249m2q1feUmfNo0Y3qsFL323gQ27850OR/kZTege8NicNfyyeS9PXN6DPm0aOR2OCnAPXdqNqPAQ7v1oBWXlens69RtN6Kdo+q/bePeXrdx8dnuu7NfK6XBUPdAkKpyHLu3Osm0HePfnTKfDUX5EE/opWJK5j39+topBp8Vz39CuToej6pERvVtwbud4nvlqHdv3HXY6HOUnNKGfpOwDR7jtvTRaNWrIi6O1W7/yLRHh8ct7ECRw/ycrMUabXpQm9JNypLiMCVNSKSopZ/L4FGIbard+5Xst4hpw39Au/Lghl1lpWU6Ho/yAWwldRIaIyDoR2Sgi91Ux/08iskZEVojI/0SkredD9Q/GGP46azlrdh7khTF9SErQbv3KOWMHtOX0do147IsMHYlR1ZzQRSQYeBkYCnQDxohIt0rFlgEpxpiewCzgaU8H6i9eWbCJOSt2cu/vu3BulwSnw1H1XFCQ8OSVPTlSUsbDs1c7HY5ymDs19P7ARmPMZmNMMTAdGOFawBjznTGm4szMIiAgL/f4ds1unv16HSN6t+DWczo4HY5SAHSMj2Li+Z2Yu3KXDgtQz7mT0FsC211eZ9nTqnMjMK+qGSIyQURSRSQ1JyfH/Sj9wIbd+fxxRjo9Wsby1JU9tVu/8isTBnWgW/MY/vnZKvIO67AA9ZVHT4qKyDggBXimqvnGmEnGmBRjTEp8fN0ZhfDA4WJumpJKRGgwr2u3fuWHQoODeHpkT/YVFPPvuRlOh6Mc4k5CzwZau7xuZU87hohcADwADDfGFHkmPOeVlpVz5wfL2HmgkNev7Ufz2AZOh6RUlZJbxnLz2R2YkbqdnzbmOh2OcoA7CX0J0ElE2otIGDAamO1aQET6AK9jJfM9ng/TOY/PzWDhxlweuzyZfm21W7/yb3+8oBPtm0by949Xcri41OlwlI/VmNCNMaXAncBXQAYw0xizWkQeFZHhdrFngCjgQxFJF5HZ1ayuTpmZup23f8rkDwPbcXVK65oXUMphEaHBPHlFD7btO8xzX693OhzlYyHuFDLGzAXmVpr2oMvzCzwcl+PStu7nH5+s4qykpjxwsXbrV3XHgA5NGDugDW/9tIVhvVrQu3Wc0yEpH9GeolXYmXeEW6am0Twugpeu6UNIsO4mVbfcN7QLzWIi+NusFRSXljsdjvIRzVSVFJaUMWFKGoUlZbwxPoW4hmFOh6RUrUVHhPLYZcms253Pqws2OR2O8hFN6C6MMfztoxWs2pHHf0f1plOzaKdDUuqknd+1md4Mo57RhO7i9R8281n6Dv5yUWcu6NbM6XCUOmV6M4z6RRO6bf7a3Tz15VqG9WzO7YM7Oh2OUh7hejOMKb9kOh2O8jJN6MDGPflMnJZOt+YxPDOyl3brVwGl4mYYT3+pN8MIdPU+oecdLuHmKWmEhwYxaXwKDcK0W78KLHozjPqjXif0snLDXdOXkbX/MK+O60fLOO3WrwKT680wPlp63MgdKkDU64T+5LwMflifw79GJHN6u8ZOh6OUV1XcDONfc9aQmVvgdDjKC+ptQv8oLYvJP27hut+1ZXT/Nk6Ho5TXBQUJT13ZE4BLX1rIt2t2OxyR8rR6mdCXbdvP3z9Zye86NOEfwyrffEmpwNUhPoo5d51F2yYNuWlKKk9/uZbSMu1JGijqXULffbCQW6am0SwmnFfG9iVUu/WreqZ144bMuvVMxvRvzSsLNjH+rV/JPRQwI17Xa/UqmxWWlDFhahqHikqZPD6FRpHarV/VTxGhwTxxRU+eHtmTtK37ueSFH0nbus/psNQpqjcJ3RjD/R+vZPn2Azx3dW+6JMY4HZJSjrs6pTUf334m4SHBjHp9EW//tEUva6zD6k1Cf+PHLXy8LJs/XXgaQ5ITnQ5HKb/RvUUsn991FoM7J/DI52u4a9oyCor05hh1Ub1I6N+vz+GJeRlc3CORu85LcjocpfxObINQJl3bj78N6cLclTsZ/tJCHdCrDgr4hL455xB3frCUzokxPHuVdutXqjpBQcJtgzvy3k0DyDtSwoiXf2L28h1Oh6VqIaAT+sHCEm6akkpocBCTx/ejYZhbN2hSql47s2NT5tx1Nl2bx3D3tGU8PHu13iSjjgjYhF5Wbrh72jK27T3Mq2P70qpRQ6dDUqrOSIyNYPqEM7hhYHve+TmT0ZN+YWfeEafDUjUI2IT+9FdrWbAuh4eHd2dAhyZOh6NUnRMaHMSDl3bjpWv6sG5XPpe8sJCfNuY6HZY6gYBM6J8uy+b17zczdkAbxp3R1ulwlKrThvVswWd3nkWTyDCufXMxL83fQIn2LvVLAZfQV2Qd4G8frWBA+8Y8dGl3p8NRKiAkJUTx6R0DGdazBc9+vZ7fPTGfJ+ZmsCnnkNOhKRfiVCeClJQUk5qa6tF17jlYyPCXfiI4SJh950CaRIV7dP1K1XfGGL5bt4dpv25n/to9lJUbUto24urTW3NJj+ZEhuuFB94mImnGmJQq5wVKQi8qLWPMpEVk7Mzno9vOpFsL7QmqlDftyS/k46XZzFyync25BUSGBXNprxZcldKavm3i9BJhLwn4hG6M4a+zVjArLYtXx/ZlaI/mHlmvUqpmxhjStu5nxpLtzFmxkyMlZXRKiOLqlNZc3rclTfWXskcFfEJ/c+EW/jVnDXef34k/XXiaR9aplKq9Q0WlzFm+gxmp21m27QAhQcIFXZsx6vTWDDotnuAgrbWfqoBO6D9uyOG6t37lwm7NeHVsP4L0gFHKL2zYnc+MJdv5eFk2+wqKSYyJYGS/VlyV0oq2TSKdDq/OCtiEnplbwIiXfyIxJoKPbz9TT8go5YeKS8v5X8ZuZqZu5/v1OZQbaBEbQfeWsXRvEUNyi1i6t4whMSZC293dcKKEXmczYL7drT9I4I3rUjSZK+WnwkKCGNqjOUN7NGdn3hG+WLGTFVl5rNqRx7cZu6moUzaJDKNbixiS7UTfvUUsbRs31F/dtVAns2B5ueGeGelsyS1g6o39ad1Yu/UrVRc0j23ATWd3OPq6oKiUjJ0HWb3jIKuy81i94yCTf9hMabmV5aPCQ+jWPIbuLa0En9wyho7xUXqnsWq4ldBFZAjwPBAMvGGMebLS/HBgCtAP2AuMMsZkejbU3/zfN+v4NmMPj47ozpkdm3prM0opL4sMDyGlXWNS2jU+Oq2otIwNuw+xekceq7IPsnpHHtN+3UZhidU7NSw4iGax4cRHhZMQHUFCTDgJ0eHER1uv46PDSYgJp0lkeL07CVtjQheRYOBl4EIgC1giIrONMWtcit0I7DfGJInIaOApYJQ3Av58+Q5e/m4TY/q35lrt1q9UwAkPCSa5ZSzJLWMZdbo1razcsCX3EKuyD5Kx6yC78wrZk1/ExpxD/LJ5L3lHSo5bT5BAkygr2VdO+DENQmgYFkJkWAiR4cFEhofQMCyYqHBrelhI3fwF4E4NvT+w0RizGUBEpgMjANeEPgJ42H4+C3hJRMR44Yxrk8gwLuzWjEeGJ+sJFKXqieAgISkhmqSEaC6j5XHzC0vKyMkvYk9+ETn5ReTkWwl/z8Eicg4VsSe/kNU7DpJ7qIhyN7JSWHAQDcODjyb8hmEhdrK3kn94SBChwfYjRAgL/u11WEgQYcHiMv+312H2ch2aRpIQE+Hx/eROQm8JbHd5nQUMqK6MMaZURPKAJoDHh2Y7M6kpZyZpM4tS6jcRocG0btywxvNpZeWGfQXFFBSVcqiolMPFZRQUl1JQVMrhot+eFxSXcbiolENFZRwutl4XFJWSe6iIw8VlFJeWU1JWTnFpOcVl1qM21dfHLkv2ysCBPj0pKiITgAkAbdq08eWmlVKK4CAh3m5+8bSyckNJWTlFdrIvKSunpNRYCd9lWnFZOe2beuc6fHcSejbQ2uV1K3taVWWyRCQEiMU6OXoMY8wkYBJY16GfTMBKKeWPgoOE4KBgIkKDHYvBnZb/JUAnEWkvImHAaGB2pTKzgevs5yOB+d5oP1dKKVW9Gmvodpv4ncBXWJctvmWMWS0ijwKpxpjZwJvAVBHZCOzDSvpKKaV8yK02dGPMXGBupWkPujwvBK7ybGhKKaVqo25ebKmUUuo4mtCVUipAaEJXSqkAoQldKaUChGPjoYtIDrD1JBdvihd6oXqQxndqNL5T5+8xanwnr60xJr6qGY4l9FMhIqnVDfDuDzS+U6PxnTp/j1Hj8w5tclFKqQChCV0ppQJEXU3ok5wOoAYa36nR+E6dv8eo8XlBnWxDV0opdby6WkNXSilViSZ0pZQKEH6d0EVkiIisE5GNInJfFfPDRWSGPX+xiLTzYWytReQ7EVkjIqtFZGIVZQaLSJ6IpNuPB6talxdjzBSRlfa2U6uYLyLygr3/VohIXx/G1tllv6SLyEER+WOlMj7ffyLylojsEZFVLtMai8g3IrLB/tuommWvs8tsEJHrqirjhdieEZG19uf3iYjEVbPsCY8FL8f4sIhku3yOF1ez7Am/716Mb4ZLbJkikl7Nsj7Zh6fEGOOXD6yhejcBHYAwYDnQrVKZ24HX7OejgRk+jK850Nd+Hg2sryK+wcAcB/dhJtD0BPMvBuYBApwBLHbws96F1WHC0f0HDAL6Aqtcpj0N3Gc/vw94qorlGgOb7b+N7OeNfBDbRUCI/fypqmJz51jwcowPA39x4xg44ffdW/FVmv9/wINO7sNTefhzDf3ozamNMcVAxc2pXY0A3rWfzwLOFx/dOdoYs9MYs9R+ng9kQBV3r/VvI4ApxrIIiBOR5g7EcT6wyRhzsj2HPcYY8wPWmP6uXI+zd4HLqlj098A3xph9xpj9wDfAEG/HZoz52hhTar9chHVHMcdUs//c4c73/ZSdKD47d1wNTPP0dn3FnxN6VTenrpwwj7k5NVBxc2qfspt6+gCLq5j9OxFZLiLzRKS7byPDAF+LSJp9P9fK3NnHvjCa6r9ETu6/Cs2MMTvt57uAZlWU8Yd9eQPWL66q1HQseNuddrPQW9U0WfnD/jsb2G2M2VDNfKf3YY38OaHXCSISBXwE/NEYc7DS7KVYzQi9gBeBT30c3lnGmL7AUOAOERnk4+3XSKzbGg4HPqxittP77zjG+u3td9f6isgDQCnwfjVFnDwWXgU6Ar2BnVjNGv5oDCeunfv998mfE3ptbk6NnODm1N4iIqFYyfx9Y8zHlecbYw4aYw7Zz+cCoSLS1FfxGWOy7b97gE+wfta6cmcfe9tQYKkxZnflGU7vPxe7K5qi7L97qijj2L4UkeuBYcBY+x/Ocdw4FrzGGLPbGFNmjCkHJlezbUePRTt/XAHMqK6Mk/vQXf6c0P365tR2e9ubQIYx5rlqyiRWtOmLSH+s/e2TfzgiEiki0RXPsU6erapUbDYw3r7a5Qwgz6VpwVeqrRU5uf8qcT3OrgM+q6LMV8BFItLIblK4yJ7mVSIyBLgXGG6MOVxNGXeOBW/G6Hpe5vJqtu3O992bLgDWGmOyqprp9D50m9NnZU/0wLoKYz3W2e8H7GmPYh28ABFYP9U3Ar8CHXwY21lYP71XAOn242LgVuBWu8ydwGqsM/aLgDN9GF8He7vL7Rgq9p9rfAK8bO/flUCKjz/fSKwEHesyzdH9h/XPZSdQgtWOeyPWeZn/ARuAb4HGdtkU4A2XZW+wj8WNwB98FNtGrLbnimOw4qqvFsDcEx0LPtx/U+3jawVWkm5eOUb79XHfd1/EZ09/p+K4cynryD48lYd2/VdKqQDhz00uSimlakETulJKBQhN6EopFSA0oSulVIDQhK4ClojEicjtJ7Hc/d6IRylv06tcVMCyh2SYY4xJruVyh4wxUd6JSinv0Rq6CmRPAh3t4U6fqTxTRJqLyA/2/FUicraIPAk0sKe9b5cbJyK/2tNeF5Fge/ohEfmPWMMn/09E4n379pQ6ltbQVcCqqYYuIn8GIowxj9tJuqExJt+1hi4iXbGGz73CGFMiIq8Ai4wxU0TEAOOMMe+LNVZ7gjHmTp+8OaWqEOJ0AEo5aAnwlj0mz6fGmPQqypwP9AOW2KMQNOC3sVzK+W3sj/eA48bzUcqXtMlF1VvGGht7ENYgUO+IyPgqignwrjGmt/3obIx5uLpVeilUpdyiCV0Fsnysu0lVSUTaYo1/PRl4A+tONgAldq0drDFcRopIgr1MY3s5sL4/I+3n1wALPRy/UrWiCV0FLGPMXuAn+4TncSdFsW5xt1xElgGjgOft6ZOAFSLyvjFmDfAPrBsbrMC6E1HF6IEFQH+x7k95HtbAcUo5Rk+KKnWS9PJG5W+0hq6UUgFCa+gq4IlID6wxuV0VGWMGOBGPUt6iCV0ppQKENrkopVSA0ISulFIBQhO6UkoFCE3oSikVIDShK6VUgNCErpRSAeL/AeUqh5Bu2kKuAAAAAElFTkSuQmCC",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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Z6XRv0ZCnXLr110ZSYjQbdx/CGs5InYqysjKPrMeJhF5aWurT7Z2IXoeu6p28wyXc8E4qEaFBTB6fQoOw4JoXqkJSYjT5RaXsyS+iacMID0fpeQ9/tpo1Ow56dJ3dWjTkwUu7n7BMZmbm0fHLly5dSvfu3Zk6dSrdunVj1KhRfP3119x9990YY/j3v/+NMYZLLrmEJ5988ug67rrrLr766iuaNWvGjBkzqOp+CrNnzyY1NZWxY8fSoEEDHn/8cd58882j474sWLCAZ555hrlz5x63bFlZGddffz2pqamICNdddx133XUXgwcPplevXnz//feUlpby5ptv0r9/fx566CE2bdrE5s2badOmDc8//zw333wz27ZtA+C///0vAwcO5Ndff2XSpEkUFhbSoEED3nrrLTp37syRI0f44x//yPLly+nSpQtHjnjmaimtoat6paJbf/aBI7w6rh8t4hrUvFA1OumJUbetW7eOW2+9lYyMDBo2bMjLL78MQJMmTVi6dCmDBg3i73//O99++y3p6eksWbKETz75BICCggJSUlJYvXo155xzDg8//HCV2xg5ciQpKSm89957pKenc+GFF7J48WIKCqxB1GbOnMno0aOrXDY9PZ3s7GxWrVrFypUrjxnc6/Dhw6Snp/Pyyy9z3XXXHZ2+Zs0avvnmG6ZPn86kSZO46667WLJkCR9++CE33HADAF26dOHHH39k2bJlPPLII9x3330AvPLKK0RGRpKRkcHDDz9MWlraqe1gm9bQVb3yxPy1/Lghlyeu6EFKu8antK6KK1027M5nYFK8J8Lzqppq0t7UunVrBg4cCMC4ceN4/vnnARg1ahQAS5YsYfDgwUdr3mPHjuWHH37gsssuIygo6Gi5cePGccUVV7i1zZCQEIYMGcJnn33GyJEj+fzzz3nqqaeqLNuhQwc2b97MHXfcwSWXXMJFF110dF7FQF+DBg3i4MGDHDhwAIDhw4fToIFVIfjmm29Ys2bN0WUOHjzIoUOHyMvL45prrmHDhg2IyNE7KP3www/ceeedAPTs2ZOePXu69Z5qfM8eWYtSdcDstCxeX7iFa89sx+j+bU55fQkx4TSMCNETo26ofI6i4nVUVNQpr+tERo8ezYsvvkjjxo1JSUkhJqbqy1IbNWrE8uXL+fLLL3n11VeZNWsWb775ptuxl5eXs2jRIiIijm16u/322zn33HP5+OOPyczMZPDgwW7HfjK0yUXVC0u37ee+j1ZyZscm3H9JV4+sU0R0TBc3bdu2jV9++QWA999/n7POOuuY+f379+f7778nNzeXsrIypk+fzjnnnANYyXL27NnVLusqJiaG/PzfOnudc845LF26lClTplTb3AKQm5tLeXk5V155JY8++ihLly49Om/mzJmANZJjbGwssbGxxy1/0UUXHTOWTMUNOPLy8mjZsiVgnbCtMGjQIN5//30AVq1axYoVK6qNrTY0oauAtyuvkJumpdEsNoKXru7r0bsMJdljuqgT69y5My+99BJdu3Zl//793HLLLcfMb968OU888QTnnnsuvXr1ol+/fowYMQKwasK//vorycnJfPvttzzwwAPVbufaa6/l5ptvpnfv3hw5coTg4GCGDRvG/PnzGTZsWLXLZWdnM3jwYHr37s24ceN4/PHHj86LiIigT58+3HzzzbzxxhtVLv/888+TmppKz5496datG6+++ioAd999N/feey99+vQ55mqYW265hUOHDtG1a1ceeOAB+vXrV/NOdIM4dclVSkqK8cR1l0qdSGFJGaNe+4WNew7x0a0D6dzMvZ6g7pryw2Yem5fBsn9eSKOomocM8LWMjAy6dvXML5KTlZmZybBhw46Oa16XDB48mGeeeYaUlBRHtl/V5yciacaYKgPSGroKWMYY7v1oJcuz8vjPqN4eT+bgOqaL1tKV8/SkqApYU37czMfLsvnzhadxUfdmXtmG65gup5/iVTOByvWuQ55y22238dNPPx0zbdKkSW7dS3TAgAEUFRUdM23atGn06NHjuLILFiw4pTh9TRO6CkjfrdvDE/PXcnGPZtxxXpLXttMyrgENQoP1xKiPvfTSSye97OLFiz0YiX/RJhcVcDblHOLO6cvo3Kwhz/yh10l163dXUJDQISHKr5tcdGiCuulkPjdN6Cqg5B0p4cZ3UgkLDmLKhH5Ehnn/R2inxGg2+Wlv0YiICPbu3atJvY4xxrB3797jrmuviTa5qIBRVm64c/oytu07zPs3nkGrRpE+2W5SYjSfpO+goKiUqHD/+kq1atWKrKwscnJynA5F1VJERAStWrWq1TL+dfQpdQqe+mIt36/P4bHLk+nf3ncnKJMSratnNuUcomerOJ9t1x2hoaG0b9/e6TCUj2iTiwoIHy/L4rUfNjPujDaMHdDWp9v+bUwX/2x2UfWHJnRV5y3ffoC/f7iSAe0bOzIAVdsmkYQEiV+fGFX1gyZ0VaftOVjIxGmpJESH8/JYz3brd1docBDt46O0hq4cpwld1VmFJWVMnJZGfmEpr1+TQpPocMdi0TFdlD/QhK7qJGMM93+8ivTtB3j2ql50bd7Q0Xg6JUazdW8BRaWeuZWaUifDrYQuIkNEZJ2IbBSRe6qY30ZEvhORZSKyQkQu9nyoSv3mjYVb+HBpFpPO78SQ5OZOh0PHxGjKDWzJLXA6FFWP1ZjQRSQYeAkYCnQDxohIt0rF/gHMMsb0AUYDL3s6UKUq/LA+h3/Py+D33Zsy6fxOTocDHDumi1JOcaeG3h/YaIzZbIwpBmYAIyqVMUDFb95YwLe33Vb1xpbcAm5/fymnNY3h2at6ExTkvW79tdExIRoRvXRROcudhN4S2O7yOsue5uohYJyIZAHzgDuqWpGITBSRVBFJ1Z5rqrbyC0u4cWoqwUHClAkpftUrMyI0mNaNIvXSReUoT50UHQO8bYxpBVwMTBOR49ZtjJlsjEkxxqRU3AxWKXeUlRsmzUgnM7eAl8f2o3Vj33Trrw1/HtNF1Q/uJPRsoLXL61b2NFfXA7MAjDG/ABGA/98GXdUZz3y1jm/X7uHBS7vxu45NnA6nSkmJ0WzOKaC0rNzpUFQ95U5CXwJ0EpH2IhKGddJzTqUy24DzAUSkK1ZC1zYV5RGfpmfzyoJNjOnfhnFn+LZbf210TIymuKyc7fuPOB2KqqdqTOjGmFLgduBLIAPrapbVIvKIiAy3i/0FuFFElgPTgWuNjtepPGBlVh53z15B/3aNeXh4d6+ObX6qOh0d0yW/hpJKeYdbZ5WMMfOwTna6TnvA5fkaYKBnQ1P13Z58q1t/fHQ4L4/rS1iIf/eD6+hyf9GLHI5F1U/+c5mAUi6KSsu45d2l7D9czIe3nEm8g9363dUwIpRmDSP0WnTlGE3oyu8YY3jgk9Wkbd3Pi1f3oXuLWKdDcltSYrQmdOUY//4Nq+qld37OZGbqdu44L4lhPVs4HU6tVCR0PYWknKAJXfmVnzbm8q/PM7iwW1PuuuA0p8OptaTEaA4Xl7Ejr9DpUFQ9pAld+Y2tewu49b2ldEyI4j+j/Kdbf23omC7KSZrQlV84VFTKjVNTEYEpE1KI9qNu/bXRSRO6clDd/NaogFJebrhrZjqbcgqYel1/2jaJcjqkk9YkOpxGkaFs3KPXoivf0xq6ctx/vlnP12t2849LujIwqe6PGKFXuiinaEJXjvp8xU5e+HYjV6W04toz2zkdjkckJcawQa90UQ7QhK4csyo7j798kE6/to3412XJft2tvzaSEqM5cLiEvQXFToei6hlN6MoRuYeKmDg1lUaRYbw6rh/hIcFOh+QxemJUOUUTuvK54tJybnk3jb0FxUwen0JCjP9366+NiksXN2hCVz6mV7konzLG8OCc1SzJ3M9zo3vTo1Xd6dbvruaxEUSFBevNLpTPaQ1d+dS7i7Yy/ddt3DK4IyN6V76TYWAQEZISo9mgly4qH9OErnzml017efizNZzXJZG/XtTZ6XC8qqNeuqgcoAld+cT2fYe59b002jaJ5L+jexNcB7v110anxBh2HyziYGGJ06GoekQTuvK6Artbf1m54fVrTqdhRKjTIXmdjuminKAJXXlVebnhz7PSWb87nxev7kv7+Lrbrb829NJF5QRN6MqrnvvfBr5cvZv7Lu7KoNMSnA7HZ1o3jiQsJEgTuvIpTejKa+av3Mlz/9vAlX1bcf1Z7Z0Ox6eCg4QO8VGa0JVPaUJXXpGx8yB/nrWc3q3jeOzywOnWXxs6SJfyNU3oyuP2FRRz49RUGjYIYfL4fkSEBk63/tpISoxm+/7DFJaUOR2Kqic0oSuPKikr59b30tiTX8Tk8SkkNoxwOiTHdEqMwRjYlKO1dOUbmtCVRz3y2RoWbd7Hk1f2oFfrOKfDcZReuqh8TRO68pj3Fm9l2qKt3DSoA5f3aeV0OI5rFx9JkGhCV76jCV15xOLNe3nw09UM7pzA3UO6OB2OXwgPCaZdkyg27NaErnxDE7o6ZVn7D3PLe0tp0ySS50b3Cfhu/bXRMTGajdqGrnxEE7o6JYeLS7lxaholZeVMmZBCbIPA79ZfG50So8nMLaCkrNzpUFQ9oAldnTRjDH/7YAVrdx3k+TF96JgQ7XRIficpMZrScsPWvQVOh6LqAU3o6qS9+O1GPl+5k3uGdOHczolOh+OX9EoX5UtuJXQRGSIi60Rko4jcU02Zq0RkjYisFpH3PRum8jdfrd7F/329nsv7tGTioA5Oh+O3Kn616IlR5Qs13oJORIKBl4ALgSxgiYjMMcascSnTCbgXGGiM2S8iWl0LYOt25XPXzHR6tYrl8St61Mtu/e6KCg+hZVwDPTGqfMKdGnp/YKMxZrMxphiYAYyoVOZG4CVjzH4AY8wez4ap/MX+gmJumLqEqPAQXhufUm+79deGjumifMWdhN4S2O7yOsue5uo04DQR+UlEFonIEE8FqPxHSVk5t72/lN15Rbw6vh/NYutvt/7aSEqMZlPOIcrLjdOhqADnqZOiIUAnYDAwBpgiInGVC4nIRBFJFZHUnJwcD21a+cpjn2fw86a9/PuKHvRt08jpcOqMpMRoCkvKyT5wxOlQVIBzJ6FnA61dXreyp7nKAuYYY0qMMVuA9VgJ/hjGmMnGmBRjTEpCQv252UEgmLlkG2//nMn1Z7VnZD/t1l8bFXcv2rAn3+FIVKBzJ6EvATqJSHsRCQNGA3MqlfkEq3aOiMRjNcFs9lyYykmpmfv4xyerOLtTPPcO1W79taWXLipfqTGhG2NKgduBL4EMYJYxZrWIPCIiw+1iXwJ7RWQN8B3wN2PMXm8FrXxnx4Ej3PxuGi3jGvDimL6EBGvXhdqKiwwjPjpcE7ryuhovWwQwxswD5lWa9oDLcwP82X6oAHGkuIyJ01IpLClnxsQUYiO1W//JSkqMYoMmdOVlWt1SVTLG8LfZy1m94yDPj+lNUmKM0yHVaRWXLlp1H6W8QxO6qtLLCzYxd8VO/vb7zpzXpanT4dR5nRJjyC8sZU9+kdOhqACmCV0d55s1u3nmq3UM79WCW87p6HQ4AUFPjCpf0ISujrFhdz5/mplO9xYNefLKntqt30M6aUJXPqAJXR2Vd7iEG6emEhEazOTxKTQI0279npIQE05MRIhei668ShO6AqC0rJzbpy8l+8ARXhvflxZxDZwOKaCIiI7porxOE7oC4PH5a/lxQy6PXdaDfm0bOx1OQOqkCV15mSZ0xQep23lj4RauPbMdV53euuYF1ElJSowm91AxBw4XOx2KClCa0Ou5tK37uf/jVQxMasI/LunqdDgBrZN9Lb/W0pW3aEKvx3blFXLzu2k0i43Qbv0+kHR0kC5N6Mo73Or6rwJPYYnVrf9wUSnv3TCARlFhTocU8FrGNSAiNEhr6MprNKHXQ8YY7vlwBSuz85g8PoXTmmq3fl8IChI6JkRrDV15jf7Grocm/7CZT9J38JcLT+PCbtqt35eSEqPZpAldeYkm9Hrmu7V7eOKLtVzSszm3nZvkdDj1TqfEaLIPHKGgqNTpUFQA0oRej2zcc4g7py+ja7OGPD1Su/U7QU+MKm/ShF5P5B0pYeLUVMJCgphyTQqRYXr6xAl92zZCBBas2+N0KCoAaUKvB8rKDXdOX8b2/Yd5ZVw/Wmq3fsckxkSQ0rYRX6za5XQoKgBpQq8HnvxiLd+vz+Hh4cn0b6/d+p02JLk5a3flsyW3wOlQVIDRhB7gPlqaxeQfNjPhd225ekAbp8NRwJDkZgBaS1cepwk9gKVvP8A9H63kdx2a8M9h3ZwOR9laxjWgV6tYvli10+lQVIDRhB6gdh8s5KZpqSTGhPPS2L6Eard+vzIkuTnLs/LIPnDE6VBUANFveQCyuvWnkV9YyuvXpNBYu/X7HW12Ud6gCT3AGGO47+OVLN9+gGev6k2XZg2dDklVoX18FF2axWizi/IoTegB5o2FW/hoaTZ/uqDT0Vqg8k9DkpuRunU/e/ILnQ5FBQhN6AHk+/U5/HteBkOTm3HneZ2cDkfVYGhyc4yBr1bvdjoUFSA0oQeILbkF3PH+Uk5rGsMzf+hFUJB26/d3pzWNpkN8lLajK4/RhB4ADhaWcMM7SwgJDmLKhBSiwrVbf10gIvw+uRm/bN7L/gK9LZ06dZrQ67iycsOfZqSzde9hXh7bl9aNI50OSdXC0ORmlJUbvs7QZhd16jSh13FPf7mOb9fu4cHh3TmjQxOnw1G11KNlLC3jGmizi/IITeh12Kfp2bz6/SauHtCG8We0dTocdRJEhCHJzVi4IZf8whKnw1F1nCb0OmpF1gHunr2C/u0a89Cl3Z0OR52CocnNKC4r59u1OqSuOjVuJXQRGSIi60Rko4jcc4JyV4qIEZEUz4WoKtuTX8jEqWnER4fz8ri+hIXo/+W6rG+bRiTEhGuzizplNWYCEQkGXgKGAt2AMSJy3EhPIhIDTAIWezpI9Zui0jJunpZG3pESJk/oR3x0uNMhqVMUFCT8vntTFqzL4UhxmdPhqDrMnapdf2CjMWazMaYYmAGMqKLcv4AnAe325iXGGP75ySqWbjvA/13Vi+4tYp0OSXnI0OTmHCkp4/v12uyiTp47Cb0lsN3ldZY97SgR6Qu0NsZ87sHYVCVv/5zJrNQs7jwviYt7NHc6HOVBA9o3plFkKPO12UWdglNufBWRIOBZ4C9ulJ0oIqkikpqTk3Oqm65XFm7I5dHPM7ioW1P+dMFpToejPCwkOIgLuzXl24w9FJVqs4s6Oe4k9GygtcvrVva0CjFAMrBARDKBM4A5VZ0YNcZMNsakGGNSEhISTj7qeiYzt4Db3l9Kx4Qonh3VW7v1B6ihyc3JLyrl5417nQ5F1VHuJPQlQCcRaS8iYcBoYE7FTGNMnjEm3hjTzhjTDlgEDDfGpHol4nomv7CEG6emIgKvTzidaO3WH7DOTGpCTHgI83VIXXWSakzoxphS4HbgSyADmGWMWS0ij4jIcG8HWJ+VlxvumpnO5twCXr66L22aaLf+QBYeEsx5XRP5es1uSsvKnQ5H1UFuVfeMMfOAeZWmPVBN2cGnHpYCePbr9XyTsYeHh3fnzKR4p8NRPjA0uRmfpu9g8ZZ9DNTPXNWS9kjxU3NX7ODF7zYy+vTWTPidduuvL845LZEGocHa7KJOiiZ0P7QqO4+/frCclLaNeGREMiJ6ErS+aBAWzODOCXy5ejfl5cbpcFQdowndz+TkFzFxaiqNI8N4ZVw/7dZfDw1JbkZOfhFLt+13OhRVx2i28CPFpeXc8m4a+w4XM3lCCgkx2q2/PjqvSyJhwUHayUjVmiZ0P2GM4cE5q0jdup+nR/YiuaV266+vYiJCOatTPF+s2oUx2uyi3KcJ3U9MW7SV6b9u59bBHbm0Vwunw1EOG5LcjOwDR1iZned0KKoO0YTuB37elMvDn63hgq6J/PWizk6Ho/zAhV2bEhwk2uyiakUTusO27zvMbe8tpUN8FP/Rbv3K1igqjN91aKLNLqpWNKE76FBRKTe8k0q5gSkTUoiJCHU6JOVHhiQ3Y0tuAet3H3I6FFVHaEJ3SHm54c8z09mwJ58Xr+5Du/gop0NSfuai7k0RQTsZKbdpQnfIf/+3ga/W7Ob+S7pxdicdeVIdLzEmgpS2jfTWdMptmtAdMH/lTp7/3wZG9mvFdQPbOR2O8mNDkpuzdlc+W3ILnA5F1QGa0H1szY6D/HnWcvq0ieOxy7VbvzqxIcnNAG12Ue7RhO5Dew8VcePUVGIbhPLauH6EhwQ7HZLycy3jGtCrVSxfarOLcoMmdB8pKSvn1veWknuoiMkT+pHYMMLpkFQd8fvkZizPyiP7wBGnQ1F+ThO6jzz82WoWb9nHUyN70rNVnNPhqDpkaLJ1Q3A9OapqogndB95dtJV3F23jpnM6MKJ3S6fDUXVM+/goujSL4QttR1c10ITuZYs27+WhOas5t3MCd/++i9PhqDpqSHIzUrfuZ09+odOhKD+mCd2Ltu87zK3vLaVNk0ieG9OHYO3Wr07S0OTmGANfrt7tdCjKj2lC95LDxaXcODWVkrJyXp+QQkPt1q9OwWlNo+kQH6VXu6gT0oTuBcYY/vrBctbvzufFq/vSISHa6ZBUHSci/D65Gb9s3sv+gmKnw1F+ShO6F7zw7UbmrdzFvUO7cs5p2q1fecbQ5GaUlRu+ztBmF1U1Tege9sWqXTz79Xqu6NOSG85u73Q4KoD0aBlLy7gGevmiqpYmdA9au+sgf56VTq/Wcfz7ih7arV95lIgwJLkZCzfkkl9Y4nQ4yg9pQveQfQXF3Dg1lejwECaP70dEqHbrV543rGdzisvKeXNhptOhKD+kCd0DSsrKue29pew+WMRr4/vRVLv1Ky/p06YRw3u14MXvNrBhd77T4Sg/owndAx6du4ZfNu/l8ct70KdNI6fDUQHuwUu7ER0ewt0frqCsXG9Pp36jCf0Uzfh1G+/8spUbz27Plf1aOR2OqgeaRIfz4KXdWbbtAO/8nOl0OMqPaEI/BUsy9/HPT1cx6LQE7hna1elwVD0yoncLzu2cwNNfrmP7vsNOh6P8hCb0k5R94Ai3vJtGq0aRvDBau/Ur3xIRHru8B0EC9328EmO06UVpQj8pR4rLmDg1laKScqZMSCE2Urv1K99rEdeAe4Z24ccNucxOy3I6HOUH3EroIjJERNaJyEYRuaeK+X8WkTUiskJE/icibT0fqn8wxvC32ctZs/Mgz4/pQ1KidutXzhk7oC2nt2vEo59n6EiMquaELiLBwEvAUKAbMEZEulUqtgxIMcb0BGYDT3k6UH/x8oJNzF2xk7t/34VzuyQ6HY6q54KChCeu7MmRkjIemrPa6XCUw9ypofcHNhpjNhtjioEZwAjXAsaY74wxFWdmFgEBebnHN2t288xX6xjRuwU3n9PB6XCUAqBjQjSTzu/EvJW7dFiAes6dhN4S2O7yOsueVp3rgflVzRCRiSKSKiKpOTk57kfpBzbszudPM9Pp0TKWJ6/sqd36lV+ZOKgD3Zo35J+friLvsA4LUF959KSoiIwDUoCnq5pvjJlsjEkxxqQkJNSdUQgPHC7mhqmpRIQG85p261d+KDQ4iKdG9mRfQTH/npfhdDjKIe4k9GygtcvrVva0Y4jIBcD9wHBjTJFnwnNeaVk5t7+/jJ0HCnltfD+axzZwOiSlqpTcMpYbz+7AzNTt/LQx1+lwlAPcSehLgE4i0l5EwoDRwBzXAiLSB3gNK5nv8XyYznlsXgYLN+by6OXJ9Gur3fqVf/vTBZ1oHx/FvR+t5HBxqdPhKB+rMaEbY0qB24EvgQxgljFmtYg8IiLD7WJPA9HAByKSLiJzqlldnTIrdTtv/ZTJHwe246qU1jUvoJTDIkKDeeKKHmzbd5hnv1rvdDjKx0LcKWSMmQfMqzTtAZfnF3g4Lselbd3PPz5exVlJ8dx/sXbrV3XHgA5NGDugDW/+tIVhvVrQu3Wc0yEpH9GeolXYmXeEm6al0Twughev7kNIsO4mVbfcM7QLTRtG8PfZKyguLXc6HOUjmqkqKSwpY+LUNApLynh9QgpxkWFOh6RUrcVEhPLoZcms253PKws2OR2O8hFN6C6MMfz9wxWs2pHHf0f1plPTGKdDUuqknd+1qd4Mo57RhO7itR8282n6Dv56UWcu6NbU6XCUOmV6M4z6RRO67du1u3nyi7UM69mcWwd3dDocpTzC9WYYU3/JdDoc5WWa0IGNe/KZND2dbs0b8vTIXtqtXwWUipthPPWF3gwj0NX7hJ53uIQbp6YRHhrE5AkpNAjTbv0qsOjNMOqPep3Qy8oNd8xYRtb+w7wyrh8t47RbvwpMrjfD+HDpcSN3qABRrxP6E/Mz+GF9Dv8akczp7Ro7HY5SXlVxM4x/zV1DZm6B0+EoL6i3Cf3DtCym/LiFa37XltH92zgdjlJeFxQkPHllTwAufXEh36zZ7XBEytPqZUJftm0/9368kt91aMI/hlW++ZJSgatDQjRz7ziLtk0iuWFqKk99sZbSMu1JGijqXULffbCQm6al0bRhOC+P7UuodutX9UzrxpHMvvlMxvRvzcsLNjHhzV/JPRQwI17Xa/UqmxWWlDFxWhqHikqZMiGFRlHarV/VTxGhwTx+RU+eGtmTtK37ueT5H0nbus/psNQpqjcJ3RjDfR+tZPn2Azx7VW+6NGvodEhKOe6qlNZ8dOuZhIcEM+q1Rbz10xa9rLEOqzcJ/fUft/DRsmz+fOFpDElu5nQ4SvmN7i1i+eyOsxjcOZGHP1vDHdOXUVCkN8eoi+pFQv9+fQ6Pz8/g4h7NuOO8JKfDUcrvxDYIZfL4fvx9SBfmrdzJ8BcX6oBedVDAJ/TNOYe4/f2ldG7WkGf+oN36lapOUJBwy+COvHvDAPKOlDDipZ+Ys3yH02GpWgjohH6wsIQbpqYSGhzElAn9iAxz6wZNStVrZ3aMZ+4dZ9O1eUPunL6Mh+as1ptk1BEBm9DLyg13Tl/Gtr2HeWVsX1o1inQ6JKXqjGaxEcyYeAbXDWzP2z9nMnryL+zMO+J0WKoGAZvQn/pyLQvW5fDQ8O4M6NDE6XCUqnNCg4N44NJuvHh1H9btyueS5xfy08Zcp8NSJxCQCf2TZdm89v1mxg5ow7gz2jodjlJ12rCeLfj09rNoEhXG+DcW8+K3GyjR3qV+KeAS+oqsA/z9wxUMaN+YBy/t7nQ4SgWEpMRoPrltIMN6tuCZr9bzu8e/5fF5GWzKOeR0aMqFONWJICUlxaSmpnp0nXsOFjL8xZ8IDhLm3D6QJtHhHl2/UvWdMYbv1u1h+q/b+XbtHsrKDSltG3HV6a25pEdzosL1wgNvE5E0Y0xKlfMCJaEXlZYxZvIiMnbm8+EtZ9KthfYEVcqb9uQX8tHSbGYt2c7m3AKiwoK5tFcL/pDSmr5t4vQSYS8J+IRujOFvs1cwOy2LV8b2ZWiP5h5Zr1KqZsYY0rbuZ+aS7cxdsZMjJWV0SozmqpTWXN63JfH6S9mjAj6hv7FwC/+au4Y7z+/Eny88zSPrVErV3qGiUuYu38HM1O0s23aAkCDhgq5NGXV6awadlkBwkNbaT1VAJ/QfN+RwzZu/cmG3prwyth9BesAo5Rc27M5n5pLtfLQsm30FxTRrGMHIfq34Q0or2jaJcjq8OitgE3pmbgEjXvqJZg0j+OjWM/WEjFJ+qLi0nP9l7GZW6na+X59DuYEWsRF0bxlL9xYNSW4RS/eWDWnWMELb3d1wooReZzNgvt2tP0jg9WtSNJkr5afCQoIY2qM5Q3s0Z2feET5fsZMVWXms2pHHNxm7qahTNokKo1uLhiTbib57i1jaNo7UX921UCezYHm54a6Z6WzJLWDa9f1p3Vi79StVFzSPbcANZ3c4+rqgqJSMnQdZveMgq7LzWL3jIFN+2ExpuZXlo8ND6Na8Id1bWgk+uWVDOiZE653GquFWQheRIcBzQDDwujHmiUrzw4GpQD9gLzDKGJPp2VB/839fr+ObjD08MqI7Z3aM99ZmlFJeFhUeQkq7xqS0a3x0WlFpGRt2H2L1jjxWZR9k9Y48pv+6jcISq3dqWHAQTWPDSYgOJzEmgsSG4STGhJMQY71OiAknsWE4TaLC691J2BoTuogEAy8BFwJZwBIRmWOMWeNS7HpgvzEmSURGA08Co7wR8GfLd/DSd5sY078147Vbv1IBJzwkmOSWsSS3jGXU6da0snLDltxDrMo+SMaug+zOK2RPfhEbcw7xy+a95B0pOW49QQJNoq1kXznhN2wQQmRYCFFhIUSFBxMVHkJkWDDR4db0sJC6+QvAnRp6f2CjMWYzgIjMAEYArgl9BPCQ/Xw28KKIiPHCGdcmUWFc2K0pDw9P1hMoStUTwUFCUmIMSYkxXEbL4+YXlpSRk1/EnvwicvKLyMm3Ev6eg0XkHCpiT34hq3ccJPdQEeVuZKWw4CAiw4OPJvzIsBA72VvJPzwkiNBg+xEihAX/9josJIiwYHGZ/9vrMHu5DvFRJDaM8Ph+ciehtwS2u7zOAgZUV8YYUyoieUATwONDs52ZFM+ZSdrMopT6TURoMK0bR9Z4Pq2s3LCvoJiColIOFZVyuLiMguJSCopKOVz02/OC4jIOF5VyqKiMw8XW64KiUnIPFXG4uIzi0nJKysopLi2nuMx61Kb6+uhlyV4ZONCnJ0VFZCIwEaBNmza+3LRSShEcJCTYzS+eVlZuKCkrp8hO9iVl5ZSUGivhu0wrLiunfbx3rsN3J6FnA61dXreyp1VVJktEQoBYrJOjxzDGTAYmg3Ud+skErJRS/ig4SAgOCiYiNNixGNxp+V8CdBKR9iISBowG5lQqMwe4xn4+EvjWG+3nSimlqldjDd1uE78d+BLrssU3jTGrReQRINUYMwd4A5gmIhuBfVhJXymllA+51YZujJkHzKs07QGX54XAHzwbmlJKqdqomxdbKqWUOo4mdKWUChCa0JVSKkBoQldKqQDh2HjoIpIDbD3JxePxQi9UD9L4To3Gd+r8PUaN7+S1NcYkVDXDsYR+KkQktboB3v2BxndqNL5T5+8xanzeoU0uSikVIDShK6VUgKirCX2y0wHUQOM7NRrfqfP3GDU+L6iTbehKKaWOV1dr6EoppSrRhK6UUgHCrxO6iAwRkXUislFE7qlifriIzLTnLxaRdj6MrbWIfCcia0RktYhMqqLMYBHJE5F0+/FAVevyYoyZIrLS3nZqFfNFRJ63998KEenrw9g6u+yXdBE5KCJ/qlTG5/tPRN4UkT0issplWmMR+VpENth/G1Wz7DV2mQ0ick1VZbwQ29Mistb+/D4Wkbhqlj3hseDlGB8SkWyXz/HiapY94ffdi/HNdIktU0TSq1nWJ/vwlBhj/PKBNVTvJqADEAYsB7pVKnMr8Kr9fDQw04fxNQf62s9jgPVVxDcYmOvgPswE4k8w/2JgPiDAGcBiBz/rXVgdJhzdf8AgoC+wymXaU8A99vN7gCerWK4xsNn+28h+3sgHsV0EhNjPn6wqNneOBS/H+BDwVzeOgRN+370VX6X5/wc84OQ+PJWHP9fQj96c2hhTDFTcnNrVCOAd+/ls4Hzx0Z2jjTE7jTFL7ef5QAZUcfda/zYCmGosi4A4EWnuQBznA5uMMSfbc9hjjDE/YI3p78r1OHsHuKyKRX8PfG2M2WeM2Q98DQzxdmzGmK+MMaX2y0VYdxRzTDX7zx3ufN9P2Ynis3PHVcB0T2/XV/w5oVd1c+rKCfOYm1MDFTen9im7qacPsLiK2b8TkeUiMl9Euvs2MgzwlYik2fdzrcydfewLo6n+S+Tk/qvQ1Biz036+C2haRRl/2JfXYf3iqkpNx4K33W43C71ZTZOVP+y/s4HdxpgN1cx3eh/WyJ8Tep0gItHAh8CfjDEHK81eitWM0At4AfjEx+GdZYzpCwwFbhORQT7efo3Euq3hcOCDKmY7vf+OY6zf3n53ra+I3A+UAu9VU8TJY+EVoCPQG9iJ1azhj8Zw4tq533+f/Dmh1+bm1MgJbk7tLSISipXM3zPGfFR5vjHmoDHmkP18HhAqIvG+is8Yk23/3QN8jPWz1pU7+9jbhgJLjTG7K89wev+52F3RFGX/3VNFGcf2pYhcCwwDxtr/cI7jxrHgNcaY3caYMmNMOTClmm07eiza+eMKYGZ1ZZzch+7y54Tu1zenttvb3gAyjDHPVlOmWUWbvoj0x9rfPvmHIyJRIhJT8Rzr5NmqSsXmABPsq13OAPJcmhZ8pdpakZP7rxLX4+wa4NMqynwJXCQijewmhYvsaV4lIkOAu4HhxpjD1ZRx51jwZoyu52Uur2bb7nzfvekCYK0xJquqmU7vQ7c5fVb2RA+sqzDWY539vt+e9gjWwQsQgfVTfSPwK9DBh7GdhfXTewWQbj8uBm4GbrbL3A6sxjpjvwg404fxdbC3u9yOoWL/ucYnwEv2/l0JpPj4843CStCxLtMc3X9Y/1x2AiVY7bjXY52X+R+wAfgGaGyXTQFed1n2OvtY3Aj80UexbcRqe644Biuu+moBzDvRseDD/TfNPr5WYCXp5pVjtF8f9333RXz29LcrjjuXso7sw1N5aNd/pZQKEP7c5KKUUqoWNKErpVSA0ISulFIBQhO6UkoFCE3oKmCJSJyI3HoSy93njXiU8ja9ykUFLHtIhrnGmORaLnfIGBPtnaiU8h6toatA9gTQ0R7u9OnKM0WkuYj8YM9fJSJni8gTQAN72nt2uXEi8qs97TURCbanHxKR/4g1fPL/RCTBt29PqWNpDV0FrJpq6CLyFyDCGPOYnaQjjTH5rjV0EemKNXzuFcaYEhF5GVhkjJkqIgYYZ4x5T6yx2hONMbf75M0pVYUQpwNQykFLgDftMXk+McakV1HmfKAfsMQehaABv43lUs5vY3+8Cxw3no9SvqRNLqreMtbY2IOwBoF6W0QmVFFMgHeMMb3tR2djzEPVrdJLoSrlFk3oKpDlY91Nqkoi0hZr/OspwOtYd7IBKLFr7WCN4TJSRBLtZRrby4H1/RlpP78aWOjh+JWqFU3oKmAZY/YCP9knPI87KYp1i7vlIrIMGAU8Z0+fDKwQkfeMMWuAf2Dd2GAF1p2IKkYPLAD6i3V/yvOwBo5TyjF6UlSpk6SXNyp/ozV0pZQKEFpDVwFPRHpgjcntqsgYM8CJeJTyFk3oSikVILTJRSmlAoQmdKWUChCa0JVSKkBoQldKqQChCV0ppQKEJnSllAoQ/w9DZh8NQBMVdwAAAABJRU5ErkJggg==",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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Z6XRv0ZCnXLr110ZSYjQbdx/CGs5InYqysjKPrMeJhF5aWurT7Z2IXoeu6p28wyXc8E4qEaFBTB6fQoOw4JoXqkJSYjT5RaXsyS+iacMID0fpeQ9/tpo1Ow56dJ3dWjTkwUu7n7BMZmbm0fHLly5dSvfu3Zk6dSrdunVj1KhRfP3119x9990YY/j3v/+NMYZLLrmEJ5988ug67rrrLr766iuaNWvGjBkzqOp+CrNnzyY1NZWxY8fSoEEDHn/8cd58882j474sWLCAZ555hrlz5x63bFlZGddffz2pqamICNdddx133XUXgwcPplevXnz//feUlpby5ptv0r9/fx566CE2bdrE5s2badOmDc8//zw333wz27ZtA+C///0vAwcO5Ndff2XSpEkUFhbSoEED3nrrLTp37syRI0f44x//yPLly+nSpQtHjnjmaimtoat6paJbf/aBI7w6rh8t4hrUvFA1OumJUbetW7eOW2+9lYyMDBo2bMjLL78MQJMmTVi6dCmDBg3i73//O99++y3p6eksWbKETz75BICCggJSUlJYvXo155xzDg8//HCV2xg5ciQpKSm89957pKenc+GFF7J48WIKCqxB1GbOnMno0aOrXDY9PZ3s7GxWrVrFypUrjxnc6/Dhw6Snp/Pyyy9z3XXXHZ2+Zs0avvnmG6ZPn86kSZO46667WLJkCR9++CE33HADAF26dOHHH39k2bJlPPLII9x3330AvPLKK0RGRpKRkcHDDz9MWlraqe1gm9bQVb3yxPy1/Lghlyeu6EFKu8antK6KK1027M5nYFK8J8Lzqppq0t7UunVrBg4cCMC4ceN4/vnnARg1ahQAS5YsYfDgwUdr3mPHjuWHH37gsssuIygo6Gi5cePGccUVV7i1zZCQEIYMGcJnn33GyJEj+fzzz3nqqaeqLNuhQwc2b97MHXfcwSWXXMJFF110dF7FQF+DBg3i4MGDHDhwAIDhw4fToIFVIfjmm29Ys2bN0WUOHjzIoUOHyMvL45prrmHDhg2IyNE7KP3www/ceeedAPTs2ZOePXu69Z5qfM8eWYtSdcDstCxeX7iFa89sx+j+bU55fQkx4TSMCNETo26ofI6i4nVUVNQpr+tERo8ezYsvvkjjxo1JSUkhJqbqy1IbNWrE8uXL+fLLL3n11VeZNWsWb775ptuxl5eXs2jRIiIijm16u/322zn33HP5+OOPyczMZPDgwW7HfjK0yUXVC0u37ee+j1ZyZscm3H9JV4+sU0R0TBc3bdu2jV9++QWA999/n7POOuuY+f379+f7778nNzeXsrIypk+fzjnnnANYyXL27NnVLusqJiaG/PzfOnudc845LF26lClTplTb3AKQm5tLeXk5V155JY8++ihLly49Om/mzJmANZJjbGwssbGxxy1/0UUXHTOWTMUNOPLy8mjZsiVgnbCtMGjQIN5//30AVq1axYoVK6qNrTY0oauAtyuvkJumpdEsNoKXru7r0bsMJdljuqgT69y5My+99BJdu3Zl//793HLLLcfMb968OU888QTnnnsuvXr1ol+/fowYMQKwasK//vorycnJfPvttzzwwAPVbufaa6/l5ptvpnfv3hw5coTg4GCGDRvG/PnzGTZsWLXLZWdnM3jwYHr37s24ceN4/PHHj86LiIigT58+3HzzzbzxxhtVLv/888+TmppKz5496datG6+++ioAd999N/feey99+vQ55mqYW265hUOHDtG1a1ceeOAB+vXrV/NOdIM4dclVSkqK8cR1l0qdSGFJGaNe+4WNew7x0a0D6dzMvZ6g7pryw2Yem5fBsn9eSKOomocM8LWMjAy6dvXML5KTlZmZybBhw46Oa16XDB48mGeeeYaUlBRHtl/V5yciacaYKgPSGroKWMYY7v1oJcuz8vjPqN4eT+bgOqaL1tKV8/SkqApYU37czMfLsvnzhadxUfdmXtmG65gup5/iVTOByvWuQ55y22238dNPPx0zbdKkSW7dS3TAgAEUFRUdM23atGn06NHjuLILFiw4pTh9TRO6CkjfrdvDE/PXcnGPZtxxXpLXttMyrgENQoP1xKiPvfTSSye97OLFiz0YiX/RJhcVcDblHOLO6cvo3Kwhz/yh10l163dXUJDQISHKr5tcdGiCuulkPjdN6Cqg5B0p4cZ3UgkLDmLKhH5Ehnn/R2inxGg2+Wlv0YiICPbu3atJvY4xxrB3797jrmuviTa5qIBRVm64c/oytu07zPs3nkGrRpE+2W5SYjSfpO+goKiUqHD/+kq1atWKrKwscnJynA5F1VJERAStWrWq1TL+dfQpdQqe+mIt36/P4bHLk+nf3ncnKJMSratnNuUcomerOJ9t1x2hoaG0b9/e6TCUj2iTiwoIHy/L4rUfNjPujDaMHdDWp9v+bUwX/2x2UfWHJnRV5y3ffoC/f7iSAe0bOzIAVdsmkYQEiV+fGFX1gyZ0VaftOVjIxGmpJESH8/JYz3brd1docBDt46O0hq4cpwld1VmFJWVMnJZGfmEpr1+TQpPocMdi0TFdlD/QhK7qJGMM93+8ivTtB3j2ql50bd7Q0Xg6JUazdW8BRaWeuZWaUifDrYQuIkNEZJ2IbBSRe6qY30ZEvhORZSKyQkQu9nyoSv3mjYVb+HBpFpPO78SQ5OZOh0PHxGjKDWzJLXA6FFWP1ZjQRSQYeAkYCnQDxohIt0rF/gHMMsb0AUYDL3s6UKUq/LA+h3/Py+D33Zsy6fxOTocDHDumi1JOcaeG3h/YaIzZbIwpBmYAIyqVMUDFb95YwLe33Vb1xpbcAm5/fymnNY3h2at6ExTkvW79tdExIRoRvXRROcudhN4S2O7yOsue5uohYJyIZAHzgDuqWpGITBSRVBFJ1Z5rqrbyC0u4cWoqwUHClAkpftUrMyI0mNaNIvXSReUoT50UHQO8bYxpBVwMTBOR49ZtjJlsjEkxxqRU3AxWKXeUlRsmzUgnM7eAl8f2o3Vj33Trrw1/HtNF1Q/uJPRsoLXL61b2NFfXA7MAjDG/ABGA/98GXdUZz3y1jm/X7uHBS7vxu45NnA6nSkmJ0WzOKaC0rNzpUFQ95U5CXwJ0EpH2IhKGddJzTqUy24DzAUSkK1ZC1zYV5RGfpmfzyoJNjOnfhnFn+LZbf210TIymuKyc7fuPOB2KqqdqTOjGmFLgduBLIAPrapbVIvKIiAy3i/0FuFFElgPTgWuNjtepPGBlVh53z15B/3aNeXh4d6+ObX6qOh0d0yW/hpJKeYdbZ5WMMfOwTna6TnvA5fkaYKBnQ1P13Z58q1t/fHQ4L4/rS1iIf/eD6+hyf9GLHI5F1U/+c5mAUi6KSsu45d2l7D9czIe3nEm8g9363dUwIpRmDSP0WnTlGE3oyu8YY3jgk9Wkbd3Pi1f3oXuLWKdDcltSYrQmdOUY//4Nq+qld37OZGbqdu44L4lhPVs4HU6tVCR0PYWknKAJXfmVnzbm8q/PM7iwW1PuuuA0p8OptaTEaA4Xl7Ejr9DpUFQ9pAld+Y2tewu49b2ldEyI4j+j/Kdbf23omC7KSZrQlV84VFTKjVNTEYEpE1KI9qNu/bXRSRO6clDd/NaogFJebrhrZjqbcgqYel1/2jaJcjqkk9YkOpxGkaFs3KPXoivf0xq6ctx/vlnP12t2849LujIwqe6PGKFXuiinaEJXjvp8xU5e+HYjV6W04toz2zkdjkckJcawQa90UQ7QhK4csyo7j798kE6/to3412XJft2tvzaSEqM5cLiEvQXFToei6hlN6MoRuYeKmDg1lUaRYbw6rh/hIcFOh+QxemJUOUUTuvK54tJybnk3jb0FxUwen0JCjP9366+NiksXN2hCVz6mV7konzLG8OCc1SzJ3M9zo3vTo1Xd6dbvruaxEUSFBevNLpTPaQ1d+dS7i7Yy/ddt3DK4IyN6V76TYWAQEZISo9mgly4qH9OErnzml017efizNZzXJZG/XtTZ6XC8qqNeuqgcoAld+cT2fYe59b002jaJ5L+jexNcB7v110anxBh2HyziYGGJ06GoekQTuvK6Artbf1m54fVrTqdhRKjTIXmdjuminKAJXXlVebnhz7PSWb87nxev7kv7+Lrbrb829NJF5QRN6MqrnvvfBr5cvZv7Lu7KoNMSnA7HZ1o3jiQsJEgTuvIpTejKa+av3Mlz/9vAlX1bcf1Z7Z0Ox6eCg4QO8VGa0JVPaUJXXpGx8yB/nrWc3q3jeOzywOnWXxs6SJfyNU3oyuP2FRRz49RUGjYIYfL4fkSEBk63/tpISoxm+/7DFJaUOR2Kqic0oSuPKikr59b30tiTX8Tk8SkkNoxwOiTHdEqMwRjYlKO1dOUbmtCVRz3y2RoWbd7Hk1f2oFfrOKfDcZReuqh8TRO68pj3Fm9l2qKt3DSoA5f3aeV0OI5rFx9JkGhCV76jCV15xOLNe3nw09UM7pzA3UO6OB2OXwgPCaZdkyg27NaErnxDE7o6ZVn7D3PLe0tp0ySS50b3Cfhu/bXRMTGajdqGrnxEE7o6JYeLS7lxaholZeVMmZBCbIPA79ZfG50So8nMLaCkrNzpUFQ9oAldnTRjDH/7YAVrdx3k+TF96JgQ7XRIficpMZrScsPWvQVOh6LqAU3o6qS9+O1GPl+5k3uGdOHczolOh+OX9EoX5UtuJXQRGSIi60Rko4jcU02Zq0RkjYisFpH3PRum8jdfrd7F/329nsv7tGTioA5Oh+O3Kn616IlR5Qs13oJORIKBl4ALgSxgiYjMMcascSnTCbgXGGiM2S8iWl0LYOt25XPXzHR6tYrl8St61Mtu/e6KCg+hZVwDPTGqfMKdGnp/YKMxZrMxphiYAYyoVOZG4CVjzH4AY8wez4ap/MX+gmJumLqEqPAQXhufUm+79deGjumifMWdhN4S2O7yOsue5uo04DQR+UlEFonIEE8FqPxHSVk5t72/lN15Rbw6vh/NYutvt/7aSEqMZlPOIcrLjdOhqADnqZOiIUAnYDAwBpgiInGVC4nIRBFJFZHUnJwcD21a+cpjn2fw86a9/PuKHvRt08jpcOqMpMRoCkvKyT5wxOlQVIBzJ6FnA61dXreyp7nKAuYYY0qMMVuA9VgJ/hjGmMnGmBRjTEpCQv252UEgmLlkG2//nMn1Z7VnZD/t1l8bFXcv2rAn3+FIVKBzJ6EvATqJSHsRCQNGA3MqlfkEq3aOiMRjNcFs9lyYykmpmfv4xyerOLtTPPcO1W79taWXLipfqTGhG2NKgduBL4EMYJYxZrWIPCIiw+1iXwJ7RWQN8B3wN2PMXm8FrXxnx4Ej3PxuGi3jGvDimL6EBGvXhdqKiwwjPjpcE7ryuhovWwQwxswD5lWa9oDLcwP82X6oAHGkuIyJ01IpLClnxsQUYiO1W//JSkqMYoMmdOVlWt1SVTLG8LfZy1m94yDPj+lNUmKM0yHVaRWXLlp1H6W8QxO6qtLLCzYxd8VO/vb7zpzXpanT4dR5nRJjyC8sZU9+kdOhqACmCV0d55s1u3nmq3UM79WCW87p6HQ4AUFPjCpf0ISujrFhdz5/mplO9xYNefLKntqt30M6aUJXPqAJXR2Vd7iEG6emEhEazOTxKTQI0279npIQE05MRIhei668ShO6AqC0rJzbpy8l+8ARXhvflxZxDZwOKaCIiI7porxOE7oC4PH5a/lxQy6PXdaDfm0bOx1OQOqkCV15mSZ0xQep23lj4RauPbMdV53euuYF1ElJSowm91AxBw4XOx2KClCa0Ou5tK37uf/jVQxMasI/LunqdDgBrZN9Lb/W0pW3aEKvx3blFXLzu2k0i43Qbv0+kHR0kC5N6Mo73Or6rwJPYYnVrf9wUSnv3TCARlFhTocU8FrGNSAiNEhr6MprNKHXQ8YY7vlwBSuz85g8PoXTmmq3fl8IChI6JkRrDV15jf7Grocm/7CZT9J38JcLT+PCbtqt35eSEqPZpAldeYkm9Hrmu7V7eOKLtVzSszm3nZvkdDj1TqfEaLIPHKGgqNTpUFQA0oRej2zcc4g7py+ja7OGPD1Su/U7QU+MKm/ShF5P5B0pYeLUVMJCgphyTQqRYXr6xAl92zZCBBas2+N0KCoAaUKvB8rKDXdOX8b2/Yd5ZVw/Wmq3fsckxkSQ0rYRX6za5XQoKgBpQq8HnvxiLd+vz+Hh4cn0b6/d+p02JLk5a3flsyW3wOlQVIDRhB7gPlqaxeQfNjPhd225ekAbp8NRwJDkZgBaS1cepwk9gKVvP8A9H63kdx2a8M9h3ZwOR9laxjWgV6tYvli10+lQVIDRhB6gdh8s5KZpqSTGhPPS2L6Eard+vzIkuTnLs/LIPnDE6VBUANFveQCyuvWnkV9YyuvXpNBYu/X7HW12Ud6gCT3AGGO47+OVLN9+gGev6k2XZg2dDklVoX18FF2axWizi/IoTegB5o2FW/hoaTZ/uqDT0Vqg8k9DkpuRunU/e/ILnQ5FBQhN6AHk+/U5/HteBkOTm3HneZ2cDkfVYGhyc4yBr1bvdjoUFSA0oQeILbkF3PH+Uk5rGsMzf+hFUJB26/d3pzWNpkN8lLajK4/RhB4ADhaWcMM7SwgJDmLKhBSiwrVbf10gIvw+uRm/bN7L/gK9LZ06dZrQ67iycsOfZqSzde9hXh7bl9aNI50OSdXC0ORmlJUbvs7QZhd16jSh13FPf7mOb9fu4cHh3TmjQxOnw1G11KNlLC3jGmizi/IITeh12Kfp2bz6/SauHtCG8We0dTocdRJEhCHJzVi4IZf8whKnw1F1nCb0OmpF1gHunr2C/u0a89Cl3Z0OR52CocnNKC4r59u1OqSuOjVuJXQRGSIi60Rko4jcc4JyV4qIEZEUz4WoKtuTX8jEqWnER4fz8ri+hIXo/+W6rG+bRiTEhGuzizplNWYCEQkGXgKGAt2AMSJy3EhPIhIDTAIWezpI9Zui0jJunpZG3pESJk/oR3x0uNMhqVMUFCT8vntTFqzL4UhxmdPhqDrMnapdf2CjMWazMaYYmAGMqKLcv4AnAe325iXGGP75ySqWbjvA/13Vi+4tYp0OSXnI0OTmHCkp4/v12uyiTp47Cb0lsN3ldZY97SgR6Qu0NsZ87sHYVCVv/5zJrNQs7jwviYt7NHc6HOVBA9o3plFkKPO12UWdglNufBWRIOBZ4C9ulJ0oIqkikpqTk3Oqm65XFm7I5dHPM7ioW1P+dMFpToejPCwkOIgLuzXl24w9FJVqs4s6Oe4k9GygtcvrVva0CjFAMrBARDKBM4A5VZ0YNcZMNsakGGNSEhISTj7qeiYzt4Db3l9Kx4Qonh3VW7v1B6ihyc3JLyrl5417nQ5F1VHuJPQlQCcRaS8iYcBoYE7FTGNMnjEm3hjTzhjTDlgEDDfGpHol4nomv7CEG6emIgKvTzidaO3WH7DOTGpCTHgI83VIXXWSakzoxphS4HbgSyADmGWMWS0ij4jIcG8HWJ+VlxvumpnO5twCXr66L22aaLf+QBYeEsx5XRP5es1uSsvKnQ5H1UFuVfeMMfOAeZWmPVBN2cGnHpYCePbr9XyTsYeHh3fnzKR4p8NRPjA0uRmfpu9g8ZZ9DNTPXNWS9kjxU3NX7ODF7zYy+vTWTPidduuvL845LZEGocHa7KJOiiZ0P7QqO4+/frCclLaNeGREMiJ6ErS+aBAWzODOCXy5ejfl5cbpcFQdowndz+TkFzFxaiqNI8N4ZVw/7dZfDw1JbkZOfhFLt+13OhRVx2i28CPFpeXc8m4a+w4XM3lCCgkx2q2/PjqvSyJhwUHayUjVmiZ0P2GM4cE5q0jdup+nR/YiuaV266+vYiJCOatTPF+s2oUx2uyi3KcJ3U9MW7SV6b9u59bBHbm0Vwunw1EOG5LcjOwDR1iZned0KKoO0YTuB37elMvDn63hgq6J/PWizk6Ho/zAhV2bEhwk2uyiakUTusO27zvMbe8tpUN8FP/Rbv3K1igqjN91aKLNLqpWNKE76FBRKTe8k0q5gSkTUoiJCHU6JOVHhiQ3Y0tuAet3H3I6FFVHaEJ3SHm54c8z09mwJ58Xr+5Du/gop0NSfuai7k0RQTsZKbdpQnfIf/+3ga/W7Ob+S7pxdicdeVIdLzEmgpS2jfTWdMptmtAdMH/lTp7/3wZG9mvFdQPbOR2O8mNDkpuzdlc+W3ILnA5F1QGa0H1szY6D/HnWcvq0ieOxy7VbvzqxIcnNAG12Ue7RhO5Dew8VcePUVGIbhPLauH6EhwQ7HZLycy3jGtCrVSxfarOLcoMmdB8pKSvn1veWknuoiMkT+pHYMMLpkFQd8fvkZizPyiP7wBGnQ1F+ThO6jzz82WoWb9nHUyN70rNVnNPhqDpkaLJ1Q3A9OapqogndB95dtJV3F23jpnM6MKJ3S6fDUXVM+/goujSL4QttR1c10ITuZYs27+WhOas5t3MCd/++i9PhqDpqSHIzUrfuZ09+odOhKD+mCd2Ltu87zK3vLaVNk0ieG9OHYO3Wr07S0OTmGANfrt7tdCjKj2lC95LDxaXcODWVkrJyXp+QQkPt1q9OwWlNo+kQH6VXu6gT0oTuBcYY/vrBctbvzufFq/vSISHa6ZBUHSci/D65Gb9s3sv+gmKnw1F+ShO6F7zw7UbmrdzFvUO7cs5p2q1fecbQ5GaUlRu+ztBmF1U1Tege9sWqXTz79Xqu6NOSG85u73Q4KoD0aBlLy7gGevmiqpYmdA9au+sgf56VTq/Wcfz7ih7arV95lIgwJLkZCzfkkl9Y4nQ4yg9pQveQfQXF3Dg1lejwECaP70dEqHbrV543rGdzisvKeXNhptOhKD+kCd0DSsrKue29pew+WMRr4/vRVLv1Ky/p06YRw3u14MXvNrBhd77T4Sg/owndAx6du4ZfNu/l8ct70KdNI6fDUQHuwUu7ER0ewt0frqCsXG9Pp36jCf0Uzfh1G+/8spUbz27Plf1aOR2OqgeaRIfz4KXdWbbtAO/8nOl0OMqPaEI/BUsy9/HPT1cx6LQE7hna1elwVD0yoncLzu2cwNNfrmP7vsNOh6P8hCb0k5R94Ai3vJtGq0aRvDBau/Ur3xIRHru8B0EC9328EmO06UVpQj8pR4rLmDg1laKScqZMSCE2Urv1K99rEdeAe4Z24ccNucxOy3I6HOUH3EroIjJERNaJyEYRuaeK+X8WkTUiskJE/icibT0fqn8wxvC32ctZs/Mgz4/pQ1KidutXzhk7oC2nt2vEo59n6EiMquaELiLBwEvAUKAbMEZEulUqtgxIMcb0BGYDT3k6UH/x8oJNzF2xk7t/34VzuyQ6HY6q54KChCeu7MmRkjIemrPa6XCUw9ypofcHNhpjNhtjioEZwAjXAsaY74wxFWdmFgEBebnHN2t288xX6xjRuwU3n9PB6XCUAqBjQjSTzu/EvJW7dFiAes6dhN4S2O7yOsueVp3rgflVzRCRiSKSKiKpOTk57kfpBzbszudPM9Pp0TKWJ6/sqd36lV+ZOKgD3Zo35J+friLvsA4LUF959KSoiIwDUoCnq5pvjJlsjEkxxqQkJNSdUQgPHC7mhqmpRIQG85p261d+KDQ4iKdG9mRfQTH/npfhdDjKIe4k9GygtcvrVva0Y4jIBcD9wHBjTJFnwnNeaVk5t7+/jJ0HCnltfD+axzZwOiSlqpTcMpYbz+7AzNTt/LQx1+lwlAPcSehLgE4i0l5EwoDRwBzXAiLSB3gNK5nv8XyYznlsXgYLN+by6OXJ9Gur3fqVf/vTBZ1oHx/FvR+t5HBxqdPhKB+rMaEbY0qB24EvgQxgljFmtYg8IiLD7WJPA9HAByKSLiJzqlldnTIrdTtv/ZTJHwe246qU1jUvoJTDIkKDeeKKHmzbd5hnv1rvdDjKx0LcKWSMmQfMqzTtAZfnF3g4Lselbd3PPz5exVlJ8dx/sXbrV3XHgA5NGDugDW/+tIVhvVrQu3Wc0yEpH9GeolXYmXeEm6al0Twughev7kNIsO4mVbfcM7QLTRtG8PfZKyguLXc6HOUjmqkqKSwpY+LUNApLynh9QgpxkWFOh6RUrcVEhPLoZcms253PKws2OR2O8hFN6C6MMfz9wxWs2pHHf0f1plPTGKdDUuqknd+1qd4Mo57RhO7itR8282n6Dv56UWcu6NbU6XCUOmV6M4z6RRO67du1u3nyi7UM69mcWwd3dDocpTzC9WYYU3/JdDoc5WWa0IGNe/KZND2dbs0b8vTIXtqtXwWUipthPPWF3gwj0NX7hJ53uIQbp6YRHhrE5AkpNAjTbv0qsOjNMOqPep3Qy8oNd8xYRtb+w7wyrh8t47RbvwpMrjfD+HDpcSN3qABRrxP6E/Mz+GF9Dv8akczp7Ro7HY5SXlVxM4x/zV1DZm6B0+EoL6i3Cf3DtCym/LiFa37XltH92zgdjlJeFxQkPHllTwAufXEh36zZ7XBEytPqZUJftm0/9368kt91aMI/hlW++ZJSgatDQjRz7ziLtk0iuWFqKk99sZbSMu1JGijqXULffbCQm6al0bRhOC+P7UuodutX9UzrxpHMvvlMxvRvzcsLNjHhzV/JPRQwI17Xa/UqmxWWlDFxWhqHikqZMiGFRlHarV/VTxGhwTx+RU+eGtmTtK37ueT5H0nbus/psNQpqjcJ3RjDfR+tZPn2Azx7VW+6NGvodEhKOe6qlNZ8dOuZhIcEM+q1Rbz10xa9rLEOqzcJ/fUft/DRsmz+fOFpDElu5nQ4SvmN7i1i+eyOsxjcOZGHP1vDHdOXUVCkN8eoi+pFQv9+fQ6Pz8/g4h7NuOO8JKfDUcrvxDYIZfL4fvx9SBfmrdzJ8BcX6oBedVDAJ/TNOYe4/f2ldG7WkGf+oN36lapOUJBwy+COvHvDAPKOlDDipZ+Ys3yH02GpWgjohH6wsIQbpqYSGhzElAn9iAxz6wZNStVrZ3aMZ+4dZ9O1eUPunL6Mh+as1ptk1BEBm9DLyg13Tl/Gtr2HeWVsX1o1inQ6JKXqjGaxEcyYeAbXDWzP2z9nMnryL+zMO+J0WKoGAZvQn/pyLQvW5fDQ8O4M6NDE6XCUqnNCg4N44NJuvHh1H9btyueS5xfy08Zcp8NSJxCQCf2TZdm89v1mxg5ow7gz2jodjlJ12rCeLfj09rNoEhXG+DcW8+K3GyjR3qV+KeAS+oqsA/z9wxUMaN+YBy/t7nQ4SgWEpMRoPrltIMN6tuCZr9bzu8e/5fF5GWzKOeR0aMqFONWJICUlxaSmpnp0nXsOFjL8xZ8IDhLm3D6QJtHhHl2/UvWdMYbv1u1h+q/b+XbtHsrKDSltG3HV6a25pEdzosL1wgNvE5E0Y0xKlfMCJaEXlZYxZvIiMnbm8+EtZ9KthfYEVcqb9uQX8tHSbGYt2c7m3AKiwoK5tFcL/pDSmr5t4vQSYS8J+IRujOFvs1cwOy2LV8b2ZWiP5h5Zr1KqZsYY0rbuZ+aS7cxdsZMjJWV0SozmqpTWXN63JfH6S9mjAj6hv7FwC/+au4Y7z+/Eny88zSPrVErV3qGiUuYu38HM1O0s23aAkCDhgq5NGXV6awadlkBwkNbaT1VAJ/QfN+RwzZu/cmG3prwyth9BesAo5Rc27M5n5pLtfLQsm30FxTRrGMHIfq34Q0or2jaJcjq8OitgE3pmbgEjXvqJZg0j+OjWM/WEjFJ+qLi0nP9l7GZW6na+X59DuYEWsRF0bxlL9xYNSW4RS/eWDWnWMELb3d1wooReZzNgvt2tP0jg9WtSNJkr5afCQoIY2qM5Q3s0Z2feET5fsZMVWXms2pHHNxm7qahTNokKo1uLhiTbib57i1jaNo7UX921UCezYHm54a6Z6WzJLWDa9f1p3Vi79StVFzSPbcANZ3c4+rqgqJSMnQdZveMgq7LzWL3jIFN+2ExpuZXlo8ND6Na8Id1bWgk+uWVDOiZE653GquFWQheRIcBzQDDwujHmiUrzw4GpQD9gLzDKGJPp2VB/839fr+ObjD08MqI7Z3aM99ZmlFJeFhUeQkq7xqS0a3x0WlFpGRt2H2L1jjxWZR9k9Y48pv+6jcISq3dqWHAQTWPDSYgOJzEmgsSG4STGhJMQY71OiAknsWE4TaLC691J2BoTuogEAy8BFwJZwBIRmWOMWeNS7HpgvzEmSURGA08Co7wR8GfLd/DSd5sY078147Vbv1IBJzwkmOSWsSS3jGXU6da0snLDltxDrMo+SMaug+zOK2RPfhEbcw7xy+a95B0pOW49QQJNoq1kXznhN2wQQmRYCFFhIUSFBxMVHkJkWDDR4db0sJC6+QvAnRp6f2CjMWYzgIjMAEYArgl9BPCQ/Xw28KKIiPHCGdcmUWFc2K0pDw9P1hMoStUTwUFCUmIMSYkxXEbL4+YXlpSRk1/EnvwicvKLyMm3Ev6eg0XkHCpiT34hq3ccJPdQEeVuZKWw4CAiw4OPJvzIsBA72VvJPzwkiNBg+xEihAX/9josJIiwYHGZ/9vrMHu5DvFRJDaM8Ph+ciehtwS2u7zOAgZUV8YYUyoieUATwONDs52ZFM+ZSdrMopT6TURoMK0bR9Z4Pq2s3LCvoJiColIOFZVyuLiMguJSCopKOVz02/OC4jIOF5VyqKiMw8XW64KiUnIPFXG4uIzi0nJKysopLi2nuMx61Kb6+uhlyV4ZONCnJ0VFZCIwEaBNmza+3LRSShEcJCTYzS+eVlZuKCkrp8hO9iVl5ZSUGivhu0wrLiunfbx3rsN3J6FnA61dXreyp1VVJktEQoBYrJOjxzDGTAYmg3Ud+skErJRS/ig4SAgOCiYiNNixGNxp+V8CdBKR9iISBowG5lQqMwe4xn4+EvjWG+3nSimlqldjDd1uE78d+BLrssU3jTGrReQRINUYMwd4A5gmIhuBfVhJXymllA+51YZujJkHzKs07QGX54XAHzwbmlJKqdqomxdbKqWUOo4mdKWUChCa0JVSKkBoQldKqQDh2HjoIpIDbD3JxePxQi9UD9L4To3Gd+r8PUaN7+S1NcYkVDXDsYR+KkQktboB3v2BxndqNL5T5+8xanzeoU0uSikVIDShK6VUgKirCX2y0wHUQOM7NRrfqfP3GDU+L6iTbehKKaWOV1dr6EoppSrRhK6UUgHCrxO6iAwRkXUislFE7qlifriIzLTnLxaRdj6MrbWIfCcia0RktYhMqqLMYBHJE5F0+/FAVevyYoyZIrLS3nZqFfNFRJ63998KEenrw9g6u+yXdBE5KCJ/qlTG5/tPRN4UkT0issplWmMR+VpENth/G1Wz7DV2mQ0ick1VZbwQ29Mistb+/D4Wkbhqlj3hseDlGB8SkWyXz/HiapY94ffdi/HNdIktU0TSq1nWJ/vwlBhj/PKBNVTvJqADEAYsB7pVKnMr8Kr9fDQw04fxNQf62s9jgPVVxDcYmOvgPswE4k8w/2JgPiDAGcBiBz/rXVgdJhzdf8AgoC+wymXaU8A99vN7gCerWK4xsNn+28h+3sgHsV0EhNjPn6wqNneOBS/H+BDwVzeOgRN+370VX6X5/wc84OQ+PJWHP9fQj96c2hhTDFTcnNrVCOAd+/ls4Hzx0Z2jjTE7jTFL7ef5QAZUcfda/zYCmGosi4A4EWnuQBznA5uMMSfbc9hjjDE/YI3p78r1OHsHuKyKRX8PfG2M2WeM2Q98DQzxdmzGmK+MMaX2y0VYdxRzTDX7zx3ufN9P2Ynis3PHVcB0T2/XV/w5oVd1c+rKCfOYm1MDFTen9im7qacPsLiK2b8TkeUiMl9Euvs2MgzwlYik2fdzrcydfewLo6n+S+Tk/qvQ1Biz036+C2haRRl/2JfXYf3iqkpNx4K33W43C71ZTZOVP+y/s4HdxpgN1cx3eh/WyJ8Tep0gItHAh8CfjDEHK81eitWM0At4AfjEx+GdZYzpCwwFbhORQT7efo3Euq3hcOCDKmY7vf+OY6zf3n53ra+I3A+UAu9VU8TJY+EVoCPQG9iJ1azhj8Zw4tq533+f/Dmh1+bm1MgJbk7tLSISipXM3zPGfFR5vjHmoDHmkP18HhAqIvG+is8Yk23/3QN8jPWz1pU7+9jbhgJLjTG7K89wev+52F3RFGX/3VNFGcf2pYhcCwwDxtr/cI7jxrHgNcaY3caYMmNMOTClmm07eiza+eMKYGZ1ZZzch+7y54Tu1zenttvb3gAyjDHPVlOmWUWbvoj0x9rfPvmHIyJRIhJT8Rzr5NmqSsXmABPsq13OAPJcmhZ8pdpakZP7rxLX4+wa4NMqynwJXCQijewmhYvsaV4lIkOAu4HhxpjD1ZRx51jwZoyu52Uur2bb7nzfvekCYK0xJquqmU7vQ7c5fVb2RA+sqzDWY539vt+e9gjWwQsQgfVTfSPwK9DBh7GdhfXTewWQbj8uBm4GbrbL3A6sxjpjvwg404fxdbC3u9yOoWL/ucYnwEv2/l0JpPj4843CStCxLtMc3X9Y/1x2AiVY7bjXY52X+R+wAfgGaGyXTQFed1n2OvtY3Aj80UexbcRqe644Biuu+moBzDvRseDD/TfNPr5WYCXp5pVjtF8f9333RXz29LcrjjuXso7sw1N5aNd/pZQKEP7c5KKUUqoWNKErpVSA0ISulFIBQhO6UkoFCE3oKmCJSJyI3HoSy93njXiU8ja9ykUFLHtIhrnGmORaLnfIGBPtnaiU8h6toatA9gTQ0R7u9OnKM0WkuYj8YM9fJSJni8gTQAN72nt2uXEi8qs97TURCbanHxKR/4g1fPL/RCTBt29PqWNpDV0FrJpq6CLyFyDCGPOYnaQjjTH5rjV0EemKNXzuFcaYEhF5GVhkjJkqIgYYZ4x5T6yx2hONMbf75M0pVYUQpwNQykFLgDftMXk+McakV1HmfKAfsMQehaABv43lUs5vY3+8Cxw3no9SvqRNLqreMtbY2IOwBoF6W0QmVFFMgHeMMb3tR2djzEPVrdJLoSrlFk3oKpDlY91Nqkoi0hZr/OspwOtYd7IBKLFr7WCN4TJSRBLtZRrby4H1/RlpP78aWOjh+JWqFU3oKmAZY/YCP9knPI87KYp1i7vlIrIMGAU8Z0+fDKwQkfeMMWuAf2Dd2GAF1p2IKkYPLAD6i3V/yvOwBo5TyjF6UlSpk6SXNyp/ozV0pZQKEFpDVwFPRHpgjcntqsgYM8CJeJTyFk3oSikVILTJRSmlAoQmdKWUChCa0JVSKkBoQldKqQChCV0ppQKEJnSllAoQ/w9DZh8NQBMVdwAAAABJRU5ErkJggg==",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"analysis.plot_all('soil_output/Spread_erdos*', analysis.get_value, 'prob_tv_spread');"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"### Manually plotting with pandas"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2017-10-19T11:00:37.003972Z",
|
||
"start_time": "2017-10-19T13:00:36.983128+02:00"
|
||
}
|
||
},
|
||
"source": [
|
||
"Although the simplest way to visualize the results of a simulation is to use the built-in methods in the analysis module, sometimes the setup is more complicated and we need to explore the data a little further.\n",
|
||
"\n",
|
||
"For that, we can use native pandas over the results.\n",
|
||
"\n",
|
||
"Soil provides some convenience methods to simplify common operations:\n",
|
||
"\n",
|
||
"* `analysis.split_df` to separate a history dataframe into environment and agent parameters.\n",
|
||
"* `analysis.get_count` to get a dataframe with the value counts for different attributes during the simulation.\n",
|
||
"* `analysis.get_value` to get the evolution of the value of an attribute during the simulation.\n",
|
||
"\n",
|
||
"And, as we saw earlier, `analysis.process` can turn a dataframe in canonical form into a dataframe with a column per attribute.\n"
|
||
]
|
||
},
|
||
{
|
||
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|
||
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|
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|
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|
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|
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|
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|
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|
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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|
||
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|
||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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||
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||
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||
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||
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|
||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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||
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|
||
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|
||
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||
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||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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||
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||
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|
||
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||
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||
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|
||
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||
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||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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||
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||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
" <td>0.250000</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>13</th>\n",
|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
" <th>14</th>\n",
|
||
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|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>0.656100</td>\n",
|
||
" <td>0.062500</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>15</th>\n",
|
||
" <td>Spread_barabasi_albert_graph_prob_0.0_trial_Sp...</td>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>0.590490</td>\n",
|
||
" <td>0.031250</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>16</th>\n",
|
||
" <td>Spread_barabasi_albert_graph_prob_0.0_trial_Sp...</td>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>0.531441</td>\n",
|
||
" <td>0.015625</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>17</th>\n",
|
||
" <td>Spread_barabasi_albert_graph_prob_0.0_trial_Sp...</td>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>0.478297</td>\n",
|
||
" <td>0.007812</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>18</th>\n",
|
||
" <td>Spread_barabasi_albert_graph_prob_0.0_trial_Sp...</td>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>0.430467</td>\n",
|
||
" <td>0.003906</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>19</th>\n",
|
||
" <td>Spread_barabasi_albert_graph_prob_0.0_trial_Sp...</td>\n",
|
||
" <td>10</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>True</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>infected</td>\n",
|
||
" <td>0.387420</td>\n",
|
||
" <td>0.001953</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"<p>20 rows × 1004 columns</p>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
"key SEED \\\n",
|
||
"agent_id env \n",
|
||
"t_step \n",
|
||
"0 Spread_barabasi_albert_graph_prob_0.0_trial_Sp... \n",
|
||
"1 Spread_barabasi_albert_graph_prob_0.0_trial_Sp... \n",
|
||
"2 Spread_barabasi_albert_graph_prob_0.0_trial_Sp... \n",
|
||
"3 Spread_barabasi_albert_graph_prob_0.0_trial_Sp... \n",
|
||
"4 Spread_barabasi_albert_graph_prob_0.0_trial_Sp... \n",
|
||
"5 Spread_barabasi_albert_graph_prob_0.0_trial_Sp... \n",
|
||
"6 Spread_barabasi_albert_graph_prob_0.0_trial_Sp... \n",
|
||
"7 Spread_barabasi_albert_graph_prob_0.0_trial_Sp... \n",
|
||
"8 Spread_barabasi_albert_graph_prob_0.0_trial_Sp... \n",
|
||
"9 Spread_barabasi_albert_graph_prob_0.0_trial_Sp... \n",
|
||
"10 Spread_barabasi_albert_graph_prob_0.0_trial_Sp... \n",
|
||
"11 Spread_barabasi_albert_graph_prob_0.0_trial_Sp... \n",
|
||
"12 Spread_barabasi_albert_graph_prob_0.0_trial_Sp... \n",
|
||
"13 Spread_barabasi_albert_graph_prob_0.0_trial_Sp... \n",
|
||
"14 Spread_barabasi_albert_graph_prob_0.0_trial_Sp... \n",
|
||
"15 Spread_barabasi_albert_graph_prob_0.0_trial_Sp... \n",
|
||
"16 Spread_barabasi_albert_graph_prob_0.0_trial_Sp... \n",
|
||
"17 Spread_barabasi_albert_graph_prob_0.0_trial_Sp... \n",
|
||
"18 Spread_barabasi_albert_graph_prob_0.0_trial_Sp... \n",
|
||
"19 Spread_barabasi_albert_graph_prob_0.0_trial_Sp... \n",
|
||
"\n",
|
||
"key event_time has_tv \\\n",
|
||
"agent_id NewsEnvironmentAgent 0 1 10 100 101 102 103 \n",
|
||
"t_step \n",
|
||
"0 10 True True True True True True True \n",
|
||
"1 10 True True True True True True True \n",
|
||
"2 10 True True True True True True True \n",
|
||
"3 10 True True True True True True True \n",
|
||
"4 10 True True True True True True True \n",
|
||
"5 10 True True True True True True True \n",
|
||
"6 10 True True True True True True True \n",
|
||
"7 10 True True True True True True True \n",
|
||
"8 10 True True True True True True True \n",
|
||
"9 10 True True True True True True True \n",
|
||
"10 10 True True True True True True True \n",
|
||
"11 10 True True True True True True True \n",
|
||
"12 10 True True True True True True True \n",
|
||
"13 10 True True True True True True True \n",
|
||
"14 10 True True True True True True True \n",
|
||
"15 10 True True True True True True True \n",
|
||
"16 10 True True True True True True True \n",
|
||
"17 10 True True True True True True True \n",
|
||
"18 10 True True True True True True True \n",
|
||
"19 10 True True True True True True True \n",
|
||
"\n",
|
||
"key ... id \\\n",
|
||
"agent_id 104 ... 92 93 94 95 96 97 \n",
|
||
"t_step ... \n",
|
||
"0 True ... neutral neutral neutral neutral neutral neutral \n",
|
||
"1 True ... neutral neutral neutral neutral neutral neutral \n",
|
||
"2 True ... neutral neutral neutral neutral neutral neutral \n",
|
||
"3 True ... neutral neutral neutral neutral neutral neutral \n",
|
||
"4 True ... neutral neutral neutral neutral neutral neutral \n",
|
||
"5 True ... neutral neutral neutral neutral neutral neutral \n",
|
||
"6 True ... neutral neutral neutral neutral neutral neutral \n",
|
||
"7 True ... neutral neutral neutral neutral neutral neutral \n",
|
||
"8 True ... neutral neutral neutral neutral neutral neutral \n",
|
||
"9 True ... neutral neutral neutral neutral neutral neutral \n",
|
||
"10 True ... infected neutral infected infected neutral neutral \n",
|
||
"11 True ... infected neutral infected infected neutral neutral \n",
|
||
"12 True ... infected neutral infected infected neutral neutral \n",
|
||
"13 True ... infected neutral infected infected neutral neutral \n",
|
||
"14 True ... infected neutral infected infected neutral neutral \n",
|
||
"15 True ... infected neutral infected infected neutral neutral \n",
|
||
"16 True ... infected neutral infected infected neutral neutral \n",
|
||
"17 True ... infected neutral infected infected neutral infected \n",
|
||
"18 True ... infected neutral infected infected neutral infected \n",
|
||
"19 True ... infected neutral infected infected neutral infected \n",
|
||
"\n",
|
||
"key prob_neighbor_spread prob_tv_spread \n",
|
||
"agent_id 98 99 env env \n",
|
||
"t_step \n",
|
||
"0 neutral neutral 0.000000 0.010000 \n",
|
||
"1 neutral neutral 0.000000 0.010000 \n",
|
||
"2 neutral neutral 0.000000 0.010000 \n",
|
||
"3 neutral neutral 0.000000 0.010000 \n",
|
||
"4 neutral neutral 0.000000 0.010000 \n",
|
||
"5 neutral neutral 0.000000 0.010000 \n",
|
||
"6 neutral neutral 0.000000 0.010000 \n",
|
||
"7 neutral neutral 0.000000 0.010000 \n",
|
||
"8 neutral neutral 0.000000 0.010000 \n",
|
||
"9 neutral neutral 0.000000 0.010000 \n",
|
||
"10 neutral infected 1.000000 1.000000 \n",
|
||
"11 neutral infected 0.900000 0.500000 \n",
|
||
"12 neutral infected 0.810000 0.250000 \n",
|
||
"13 neutral infected 0.729000 0.125000 \n",
|
||
"14 neutral infected 0.656100 0.062500 \n",
|
||
"15 neutral infected 0.590490 0.031250 \n",
|
||
"16 infected infected 0.531441 0.015625 \n",
|
||
"17 infected infected 0.478297 0.007812 \n",
|
||
"18 infected infected 0.430467 0.003906 \n",
|
||
"19 infected infected 0.387420 0.001953 \n",
|
||
"\n",
|
||
"[20 rows x 1004 columns]"
|
||
]
|
||
},
|
||
"execution_count": 14,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"df = analysis.read_sql('soil_output/Spread_barabasi_albert_graph_prob_0.0/Spread_barabasi_albert_graph_prob_0-0_trial_1605820891-4782693.sqlite')\n",
|
||
"df"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"Let's look at the evolution of agent parameters in the simulation"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 15,
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2017-10-19T15:59:17.153282Z",
|
||
"start_time": "2017-10-19T17:59:16.830872+02:00"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<AxesSubplot:xlabel='t_step'>"
|
||
]
|
||
},
|
||
"execution_count": 15,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"df.plot()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2017-10-19T11:10:36.086913Z",
|
||
"start_time": "2017-10-19T13:10:36.058547+02:00"
|
||
}
|
||
},
|
||
"source": [
|
||
"As we can see, `event_time` is cluttering our results, "
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 16,
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2017-10-19T15:59:18.418348Z",
|
||
"start_time": "2017-10-19T17:59:18.143443+02:00"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<AxesSubplot:xlabel='t_step'>"
|
||
]
|
||
},
|
||
"execution_count": 16,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"del df['event_time']\n",
|
||
"df.plot()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"The `soil.analysis` module also provides convenient functions to count the number of agents in a given state:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 19,
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2017-10-19T15:59:51.165806Z",
|
||
"start_time": "2017-10-19T17:59:50.886780+02:00"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"analysis.get_count(agents, 'id').plot();"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Dealing with bigger data"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 20,
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2017-10-19T16:00:18.148006Z",
|
||
"start_time": "2017-10-19T18:00:18.117654+02:00"
|
||
}
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"from soil import analysis"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 21,
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2017-10-19T16:00:18.636440Z",
|
||
"start_time": "2017-10-19T18:00:18.504421+02:00"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"215M\t../rabbits/soil_output/rabbits_example/\r\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"!du -xsh ../rabbits/soil_output/rabbits_example/"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2017-10-19T11:22:22.301765Z",
|
||
"start_time": "2017-10-19T13:22:22.281986+02:00"
|
||
}
|
||
},
|
||
"source": [
|
||
"If we tried to load the entire history, we would probably run out of memory. Hence, it is recommended that you also specify the attributes you are interested in."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 31,
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2017-10-19T16:00:25.080582Z",
|
||
"start_time": "2017-10-19T18:00:19.594165+02:00"
|
||
},
|
||
"scrolled": false
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"p = analysis.plot_all('../rabbits/soil_output/rabbits_example/', analysis.get_count, 'id')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 60,
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2017-10-19T16:00:38.434367Z",
|
||
"start_time": "2017-10-19T18:00:33.645762+02:00"
|
||
}
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"df = analysis.read_sql('../rabbits/soil_output/rabbits_example/rabbits_example_trial_1605825338-8931234.sqlite', keys=['id', 'rabbits_alive'])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 61,
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2017-10-19T16:00:39.160418Z",
|
||
"start_time": "2017-10-19T18:00:38.436153+02:00"
|
||
},
|
||
"scrolled": true
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<AxesSubplot:xlabel='t_step'>"
|
||
]
|
||
},
|
||
"execution_count": 61,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"states = analysis.get_count(df, 'id')\n",
|
||
"states.plot()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 62,
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2017-10-19T16:00:39.515032Z",
|
||
"start_time": "2017-10-19T18:00:39.162240+02:00"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<AxesSubplot:xlabel='t_step'>"
|
||
]
|
||
},
|
||
"execution_count": 62,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"alive = analysis.get_value(df, 'rabbits_alive', aggfunc='sum').apply(pd.to_numeric)\n",
|
||
"alive.plot()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 63,
|
||
"metadata": {
|
||
"ExecuteTime": {
|
||
"end_time": "2017-10-19T16:00:58.815038Z",
|
||
"start_time": "2017-10-19T18:00:58.566807+02:00"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"/home/j/.local/lib/python3.8/site-packages/pandas/core/reshape/merge.py:643: UserWarning: merging between different levels can give an unintended result (1 levels on the left,2 on the right)\n",
|
||
" warnings.warn(msg, UserWarning)\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"h = alive.join(states);\n",
|
||
"h.plot();"
|
||
]
|
||
}
|
||
],
|
||
"metadata": {
|
||
"kernelspec": {
|
||
"display_name": ".venv",
|
||
"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": "3.8.10"
|
||
},
|
||
"toc": {
|
||
"colors": {
|
||
"hover_highlight": "#DAA520",
|
||
"navigate_num": "#000000",
|
||
"navigate_text": "#333333",
|
||
"running_highlight": "#FF0000",
|
||
"selected_highlight": "#FFD700",
|
||
"sidebar_border": "#EEEEEE",
|
||
"wrapper_background": "#FFFFFF"
|
||
},
|
||
"moveMenuLeft": true,
|
||
"nav_menu": {
|
||
"height": "31px",
|
||
"width": "252px"
|
||
},
|
||
"navigate_menu": true,
|
||
"number_sections": true,
|
||
"sideBar": true,
|
||
"threshold": 4,
|
||
"toc_cell": false,
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"toc_position": {
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"height": "867px",
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"left": "0px",
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"right": "1670px",
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"top": "106px",
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"width": "250px"
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},
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"toc_section_display": "block",
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"toc_window_display": false,
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"widenNotebook": false
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},
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"vscode": {
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"interpreter": {
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"hash": "3581132406f7320837865a422f37590c78ed7dabfbcb5bc7771b9d116b13a5cf"
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}
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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