{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "7ba92524",
   "metadata": {},
   "source": [
    "# r5r: Accounting for monetary costs\n",
    "\n",
    "This tutorial shows how to configure and use custom fare rules in order to account for monetary travel costs when generating travel time matrices and accessibility estimates with the `r5r` package.\n",
    "\n",
    "```{admonition} Credits:\n",
    "\n",
    "This tutorial is a direct copy from [r5r -documentation](https://ipeagit.github.io/r5r/articles/fare_structure.html) made by r5r contributors.\n",
    "```\n",
    "\n",
    "## Getting started\n",
    "\n",
    "### Run these codes in Binder\n",
    "\n",
    "Before you can run this Notebook, and/or do any programming, you need to launch the Binder instance. You can find buttons for activating the python environment at the top-right of this page which look like this:\n",
    "\n",
    "![Launch Binder](../img/launch_binder.png)\n",
    "\n",
    "### Working with Jupyter Notebooks\n",
    "\n",
    "Jupyter Notebooks are documents that can be used and run inside the JupyterLab programming environment containing the computer code and rich text elements (such as text, figures, tables and links). \n",
    "\n",
    "**A couple of hints**:\n",
    "\n",
    "- You can **execute a cell** by clicking a given cell that you want to run and pressing <kbd>Shift</kbd> + <kbd>Enter</kbd> (or by clicking the \"Play\" button on top)\n",
    "- You can **change the cell-type** between `Markdown` (for writing text) and `Code` (for writing/executing code) from the dropdown menu above. \n",
    "\n",
    "See **further details and help for** [**using Notebooks and JupyterLab from here**](https://pythongis.org/part1/chapter-01/nb/04-using-jupyterlab.html). \n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bcc790db",
   "metadata": {},
   "source": [
    "## 1. Introduction\n",
    "\n",
    "Considering the monetary costs of public transport trips in the calculation of \n",
    "travel time matrices and accessibility estimates is a major challenge faced by \n",
    "researchers and planning practitioners. Each public transport system can have \n",
    "its own set of rules for calculating fares, with varying levels of complexity. \n",
    "Moreover, there are important trade offs between travel time and monetary costs \n",
    "across multiple trip alternatives and are currently not captured by any \n",
    "multimodal routing engine, except for R5.\n",
    "\n",
    "R5 has native capabilities and an open architecture for creating and including \n",
    "fare structures in routing models, making it possible to estimate travel time \n",
    "matrices and accessibility estimates simultaneously considering different \n",
    "combinations of time and monetary cost cutoffs. The main challenge, however, is \n",
    "that a specific fare structure for each city needs to be programmed in Java and \n",
    "tightly integrated into R5, making this functionality out of reach for those who \n",
    "do not know how to code in Java (i.e. most of us!).\n",
    "\n",
    "To help tackle this challenge, `r5r` has a simple generic rule-based fare \n",
    "structure that can be configured via a predefined set of properties and rules \n",
    "that can be set directly from R or using external tools such as text editors and\n",
    "spreadsheets. This approach currently available in `r5r` is able to account for \n",
    "the monetary costs of public transport systems that follow a simple set of fare \n",
    "rules according to which the cost of a journey depends on combinations of modes \n",
    "(see details below).\n",
    "\n",
    "**This tutorial shows the features of `r5r`s fare structure. It also uses a \n",
    "reproducible example to demonstrate how to configure the fare structure to \n",
    "account for monetary costs when generating travel time matrices and accessibility \n",
    "estimates with `r5r`**. \n",
    "\n",
    "### 1.1 Details\n",
    "\n",
    "A common feature among many public transport services is the possibility of \n",
    "discounted transfers, when passengers can use a single ticket for a trip composed \n",
    "of multiple rides sometimes combining different transport modes. Such trips usually \n",
    "come with a discount in the second or subsequent fares, as well as a limit on the \n",
    "number of discounted transfers the user can make and/or a time limit for using that \n",
    "discount. This is the type of fare structure currently covered by `r5r`.\n",
    "\n",
    "We acknowledge that there are several types fare rules that vary from one public \n",
    "transport system to another. According to these rules, the cost of a journey can \n",
    "differ, for example, depending on: different costs for each trip leg, transport \n",
    "mode or route; distance- or zone-based fares; different fares for types of riders \n",
    "(e.g elderly people or students) or time of the day (e.g. peak and off-peak hours); \n",
    "among many others rules. As such, taking all of these possible rules into \n",
    "consideration when calculating the monetary cost of multimodal can be quite \n",
    "difficult. `r5r` currently does not cover these more complex fare rules.\n",
    "\n",
    "The fare calculator currently available in `r5r` is not intended to be a robust \n",
    "solution that can take into consideration all public transport systems and their \n",
    "specific fare rules. That would be a Herculean task. The features included in \n",
    "`r5r`'s fare calculator are inspired by our empirical observations of Brazilian \n",
    "public transport systems, and is meant to be used mainly in the [Access to Opportunities project](https://www.ipea.gov.br/acessooportunidades/en/). Everyone else is welcome to use it, if the current features suit their needs.\n",
    "obs. The GTFS format has some features for specifying public transport fares, but\n",
    "those features are quite limited and are not enough for adequately representing \n",
    "many use cases. A new version of that specification is currently being developed \n",
    "[Fares V2](https://github.com/google/transit/issues/252), but it may take some \n",
    "time for it to be approved and for transport agencies actually start providing \n",
    "GTFS feeds with full fare information.\n",
    "\n",
    "\n",
    "## 2. Reprex: the public transport system of Porto Alegre\n",
    "In this tutorial, we will be using the sample data set for the city of Porto \n",
    "Alegre (Brazil) included in `r5r`.  Before we start, we need to increase the memory available to Java and load the packages used in this tutorial\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "2c219708",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "also installing the dependency ‘tidyr’\n",
      "\n",
      "\n",
      "Updating HTML index of packages in '.Library'\n",
      "\n",
      "Making 'packages.html' ...\n",
      " done\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Install h3jsr package\n",
    "install.packages('h3jsr')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "fa49126e",
   "metadata": {},
   "outputs": [],
   "source": [
    "options(java.parameters = \"-Xmx5G\")\n",
    "library(r5r)\n",
    "library(sf)\n",
    "library(data.table)\n",
    "library(ggplot2)\n",
    "library(patchwork)\n",
    "library(dplyr)\n",
    "library(h3jsr)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "312128fd",
   "metadata": {},
   "source": [
    "Porto Alegre has a relatively straightforward public transport system, where the vast majority of the population that rely on transit ride buses. The city also has a metropolitan rail service that connects the city center to the neighboring northbound municipalities. That system can be seen in the map below.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "7899cbb7",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using cached R5 version from /home/hentenka/.conda/envs/mamba/envs/r5/lib/R/library/r5r/jar/r5-v6.7-all.jar\n",
      "\n",
      "\n",
      "Using cached network.dat from /home/hentenka/.conda/envs/mamba/envs/r5/lib/R/library/r5r/extdata/poa/network.dat\n",
      "\n"
     ]
    },
    {
     "data": {
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2ykRQFA/iDYAThMFlVq6pJMqou7sdSU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HAUFkZCK7qWjW3BhwxY89To1G838H7WOn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\nIiKKEwx2RERERHHi/wG9s2Hyn7ljPwAAAABJRU5ErkJggg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# setup and load Porto Alegre multimodal network into memory\n",
    "# system.file returns the directory with example data inside the r5r package\n",
    "# set data path to directory containing your own data if not using the examples\n",
    "data_path <- system.file(\"extdata/poa\", package = \"r5r\")\n",
    "r5r_core <- setup_r5(data_path)\n",
    "\n",
    "# load transit network as an SF\n",
    "transit_network <- transit_network_to_sf(r5r_core)\n",
    "\n",
    "# map\n",
    "ggplot() +\n",
    "  geom_sf(data=transit_network$routes, aes(color=mode)) +\n",
    "  theme_void()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "47ed4e64",
   "metadata": {},
   "source": [
    "According to the fare rules in Porto Alegre, as in most Brazilian cities, the \n",
    "cost a a journey depends on a combination of number of subsequent trips and/or \n",
    "transport modes. In the case of Porto Alegre, the fare rules are as follows:\n",
    "\n",
    "- Each bus ticket costs R\\$ 4.80\n",
    "- Riding a second bus adds R\\$ 2.40  to the total cost. \n",
    "- Subsequent bus rides cost the full ticket price of R\\$ 4.80.\n",
    "- Each train ticket costs R\\$ 4.50. Once a passenger enters a train station, she can take an unlimited amount of train trips as long as she doesn't leave a station.\n",
    "- The integrated fare between bus and train has a 10% discount, which totals R\\$ 8.37.\n",
    "\n",
    "In the following sections, we will demonstrate how to implement those rules within r5r's fare calculator.\n",
    "\n",
    "\n",
    "## 3. Setting up the fare structure\n",
    "There are three support functions in `r5r` to help users configure the fare structure:\n",
    "-   `setup_fare_structure()` analyses the study area's GTFS and builds a 'skeleton' fare structure structure with the parameters that need to be set;\n",
    "-   `write_fare_structure()` and `read_fare_structure()` allow saving the current fare structure settings to disk, and reading them back into memory. The settings are saved as standard `.csv` files inside a zipped folder. These files can be edited outside the R session using external text editors and spreadsheet software, for user's convenience.\n",
    "First, we need to call `setup_fare_structure()`, providing three parameters: the\n",
    "current `r5r_core` object, a `base_fare` used to populate the fare structure, and\n",
    "the `by` parameters that identifies what is the main property of the route that \n",
    "defines the different fares.\n",
    "In the example below, the `base_fare` is the standard bus ticket price of R\\$ 4.80. \n",
    "We are also stating that `by = \"MODE\"`, so that each transport mode has its own \n",
    "fares and integration rules. Users can also create a fare structure where fare \n",
    "rules of routes differ by `\"AGENCY_ID\"` or `\"AGENCY_NAME\"`, or simply set `by = \"GENERIC\"` when the entire system follows the same rules.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b77780ee",
   "metadata": {},
   "outputs": [],
   "source": [
    "fare_structure <- setup_fare_structure(r5r_core, \n",
    "                                       base_fare = 4.8,\n",
    "                                       by = \"MODE\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "19c584fb",
   "metadata": {},
   "source": [
    "Now let's check the contents of the `fare_structure` object. We can see below that it is simply a `list` with a few properties and data.frames.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "81e28ef3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<dl>\n",
       "\t<dt>$max_discounted_transfers</dt>\n",
       "\t\t<dd>1</dd>\n",
       "\t<dt>$transfer_time_allowance</dt>\n",
       "\t\t<dd>120</dd>\n",
       "\t<dt>$fare_cap</dt>\n",
       "\t\t<dd>Inf</dd>\n",
       "\t<dt>$fares_per_type</dt>\n",
       "\t\t<dd><table class=\"dataframe\">\n",
       "<caption>A data.table: 2 × 5</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>type</th><th scope=col>unlimited_transfers</th><th scope=col>allow_same_route_transfer</th><th scope=col>use_route_fare</th><th scope=col>fare</th></tr>\n",
       "\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;lgl&gt;</th><th scope=col>&lt;lgl&gt;</th><th scope=col>&lt;lgl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>BUS </td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>4.8</td></tr>\n",
       "\t<tr><td>RAIL</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>4.8</td></tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</dd>\n",
       "\t<dt>$fares_per_transfer</dt>\n",
       "\t\t<dd><table class=\"dataframe\">\n",
       "<caption>A data.table: 4 × 3</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>first_leg</th><th scope=col>second_leg</th><th scope=col>fare</th></tr>\n",
       "\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>BUS </td><td>BUS </td><td>4.8</td></tr>\n",
       "\t<tr><td>RAIL</td><td>BUS </td><td>4.8</td></tr>\n",
       "\t<tr><td>BUS </td><td>RAIL</td><td>4.8</td></tr>\n",
       "\t<tr><td>RAIL</td><td>RAIL</td><td>4.8</td></tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</dd>\n",
       "\t<dt>$fares_per_route</dt>\n",
       "\t\t<dd><table class=\"dataframe\">\n",
       "<caption>A data.table: 117 × 8</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>agency_id</th><th scope=col>agency_name</th><th scope=col>route_id</th><th scope=col>route_short_name</th><th scope=col>route_long_name</th><th scope=col>mode</th><th scope=col>route_fare</th><th scope=col>fare_type</th></tr>\n",
       "\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;chr&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>EPTC</td><td>Empresa Publica de Transportes e Circulação</td><td>1112</td><td>1112</td><td>HIPICA / TRISTEZA                          </td><td>BUS</td><td>4.8</td><td>BUS</td></tr>\n",
       "\t<tr><td>EPTC</td><td>Empresa Publica de Transportes e Circulação</td><td>149 </td><td>149 </td><td>ICARAI                                     </td><td>BUS</td><td>4.8</td><td>BUS</td></tr>\n",
       "\t<tr><td>EPTC</td><td>Empresa Publica de Transportes e Circulação</td><td>165 </td><td>165 </td><td>COHAB                                      </td><td>BUS</td><td>4.8</td><td>BUS</td></tr>\n",
       "\t<tr><td>EPTC</td><td>Empresa Publica de Transportes e Circulação</td><td>168 </td><td>168 </td><td>BELEM NOVO(VIA TRISTEZA)                   </td><td>BUS</td><td>4.8</td><td>BUS</td></tr>\n",
       "\t<tr><td>EPTC</td><td>Empresa Publica de Transportes e Circulação</td><td>173 </td><td>173 </td><td>CAMAQUA                                    </td><td>BUS</td><td>4.8</td><td>BUS</td></tr>\n",
       "\t<tr><td>EPTC</td><td>Empresa Publica de Transportes e Circulação</td><td>1761</td><td>1761</td><td>SERRARIA / RODOVIARIA / VIA MENDES OURIQUES</td><td>BUS</td><td>4.8</td><td>BUS</td></tr>\n",
       "\t<tr><td>EPTC</td><td>Empresa Publica de Transportes e Circulação</td><td>179 </td><td>179 </td><td>SERRARIA                                   </td><td>BUS</td><td>4.8</td><td>BUS</td></tr>\n",
       "\t<tr><td>EPTC</td><td>Empresa Publica de Transportes e Circulação</td><td>1795</td><td>1795</td><td>SERRARIA / GUAIBA / DIARIO                 </td><td>BUS</td><td>4.8</td><td>BUS</td></tr>\n",
       "\t<tr><td>EPTC</td><td>Empresa Publica de Transportes e Circulação</td><td>186 </td><td>186 </td><td>LIBERAL                                    </td><td>BUS</td><td>4.8</td><td>BUS</td></tr>\n",
       "\t<tr><td>EPTC</td><td>Empresa Publica de Transportes e Circulação</td><td>187 </td><td>187 </td><td>PADRE REUS                                 </td><td>BUS</td><td>4.8</td><td>BUS</td></tr>\n",
       "\t<tr><td>EPTC</td><td>Empresa Publica de Transportes e Circulação</td><td>188 </td><td>188 </td><td>ASSUNCAO                                   </td><td>BUS</td><td>4.8</td><td>BUS</td></tr>\n",
       "\t<tr><td>EPTC</td><td>Empresa Publica de Transportes e Circulação</td><td>195 </td><td>195 </td><td>T V                                        </td><td>BUS</td><td>4.8</td><td>BUS</td></tr>\n",
       "\t<tr><td>EPTC</td><td>Empresa Publica de Transportes e Circulação</td><td>210 </td><td>210 </td><td>RESTINGA NOVA                              </td><td>BUS</td><td>4.8</td><td>BUS</td></tr>\n",
       "\t<tr><td>EPTC</td><td>Empresa Publica de Transportes e Circulação</td><td>211 </td><td>211 </td><td>RESTINGA VELHA                             </td><td>BUS</td><td>4.8</td><td>BUS</td></tr>\n",
       "\t<tr><td>EPTC</td><td>Empresa Publica de Transportes e Circulação</td><td>244 </td><td>244 </td><td>SANTA TERESA                               </td><td>BUS</td><td>4.8</td><td>BUS</td></tr>\n",
       "\t<tr><td>EPTC</td><td>Empresa Publica de Transportes e Circulação</td><td>2441</td><td>2441</td><td>SANTA TERESA / VIA MARIANO DE MATOS        </td><td>BUS</td><td>4.8</td><td>BUS</td></tr>\n",
       "\t<tr><td>EPTC</td><td>Empresa Publica de Transportes e Circulação</td><td>253 </td><td>253 </td><td>RENASCENCA                                 </td><td>BUS</td><td>4.8</td><td>BUS</td></tr>\n",
       "\t<tr><td>EPTC</td><td>Empresa Publica de Transportes e Circulação</td><td>2541</td><td>2541</td><td>EMBRATEL - CANUDOS - CASCATINHA            </td><td>BUS</td><td>4.8</td><td>BUS</td></tr>\n",
       "\t<tr><td>EPTC</td><td>Empresa Publica de Transportes e Circulação</td><td>255 </td><td>255 </td><td>CALDRE FIAO                                </td><td>BUS</td><td>4.8</td><td>BUS</td></tr>\n",
       "\t<tr><td>EPTC</td><td>Empresa Publica de Transportes e Circulação</td><td>256 </td><td>256 </td><td>INTENDENTE AZEVEDO                         </td><td>BUS</td><td>4.8</td><td>BUS</td></tr>\n",
       "\t<tr><td>EPTC</td><td>Empresa Publica de Transportes e Circulação</td><td>2561</td><td>2561</td><td>NAZARETH                                   </td><td>BUS</td><td>4.8</td><td>BUS</td></tr>\n",
       "\t<tr><td>EPTC</td><td>Empresa Publica de Transportes e Circulação</td><td>260 </td><td>260 </td><td>BELEM VELHO / OSCAR PEREIRA                </td><td>BUS</td><td>4.8</td><td>BUS</td></tr>\n",
       "\t<tr><td>EPTC</td><td>Empresa Publica de Transportes e Circulação</td><td>262 </td><td>262 </td><td>JARDIM V. NOVA                             </td><td>BUS</td><td>4.8</td><td>BUS</td></tr>\n",
       "\t<tr><td>EPTC</td><td>Empresa Publica de Transportes e Circulação</td><td>263 </td><td>263 </td><td>ORFANOTROFIO                               </td><td>BUS</td><td>4.8</td><td>BUS</td></tr>\n",
       "\t<tr><td>EPTC</td><td>Empresa Publica de Transportes e Circulação</td><td>264 </td><td>264 </td><td>PRADO                                      </td><td>BUS</td><td>4.8</td><td>BUS</td></tr>\n",
       "\t<tr><td>EPTC</td><td>Empresa Publica de Transportes e Circulação</td><td>2671</td><td>2671</td><td>LAMI / VAREJAO(VIA EDGAR PIRES DE CASTRO)  </td><td>BUS</td><td>4.8</td><td>BUS</td></tr>\n",
       "\t<tr><td>EPTC</td><td>Empresa Publica de Transportes e Circulação</td><td>268 </td><td>268 </td><td>BELEM NOVO(VIA CAVALHADA)                  </td><td>BUS</td><td>4.8</td><td>BUS</td></tr>\n",
       "\t<tr><td>EPTC</td><td>Empresa Publica de Transportes e Circulação</td><td>271 </td><td>271 </td><td>AMAPA                                      </td><td>BUS</td><td>4.8</td><td>BUS</td></tr>\n",
       "\t<tr><td>EPTC</td><td>Empresa Publica de Transportes e Circulação</td><td>272 </td><td>272 </td><td>MORADAS DA HIPICA                          </td><td>BUS</td><td>4.8</td><td>BUS</td></tr>\n",
       "\t<tr><td>EPTC</td><td>Empresa Publica de Transportes e Circulação</td><td>273 </td><td>273 </td><td>BELEM NOVO / HIPICA                        </td><td>BUS</td><td>4.8</td><td>BUS</td></tr>\n",
       "\t<tr><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td></tr>\n",
       "\t<tr><td>EPTC </td><td>Empresa Publica de Transportes e Circulação</td><td>862      </td><td>862   </td><td>RUBEM BERTA (CAIRU)                      </td><td>BUS </td><td>4.8</td><td>BUS </td></tr>\n",
       "\t<tr><td>EPTC </td><td>Empresa Publica de Transportes e Circulação</td><td>B02      </td><td>B02   </td><td>LEOPOLDINA  /  AEROPORTO  /  INDUSTRIAS  </td><td>BUS </td><td>4.8</td><td>BUS </td></tr>\n",
       "\t<tr><td>EPTC </td><td>Empresa Publica de Transportes e Circulação</td><td>B51      </td><td>B51   </td><td>PARQUE  /  POSTAO IAPI / H CONCEICAO     </td><td>BUS </td><td>4.8</td><td>BUS </td></tr>\n",
       "\t<tr><td>EPTC </td><td>Empresa Publica de Transportes e Circulação</td><td>B511     </td><td>B511  </td><td>PARQUE / H CONCEICAO / POSTAO IAPI       </td><td>BUS </td><td>4.8</td><td>BUS </td></tr>\n",
       "\t<tr><td>EPTC </td><td>Empresa Publica de Transportes e Circulação</td><td>B56      </td><td>B56   </td><td>PASSO DAS PEDRAS  /  AEROPORTO           </td><td>BUS </td><td>4.8</td><td>BUS </td></tr>\n",
       "\t<tr><td>EPTC </td><td>Empresa Publica de Transportes e Circulação</td><td>C1       </td><td>C1    </td><td>CIRCULAR CENTRO                          </td><td>BUS </td><td>4.8</td><td>BUS </td></tr>\n",
       "\t<tr><td>EPTC </td><td>Empresa Publica de Transportes e Circulação</td><td>C2       </td><td>C2    </td><td>CIRCULAR PRACA XV                        </td><td>BUS </td><td>4.8</td><td>BUS </td></tr>\n",
       "\t<tr><td>EPTC </td><td>Empresa Publica de Transportes e Circulação</td><td>C3       </td><td>C3    </td><td>CIRCULAR URCA                            </td><td>BUS </td><td>4.8</td><td>BUS </td></tr>\n",
       "\t<tr><td>EPTC </td><td>Empresa Publica de Transportes e Circulação</td><td>D67      </td><td>D67   </td><td>LAMI VIA BELEM NOVO / DIRETA             </td><td>BUS </td><td>4.8</td><td>BUS </td></tr>\n",
       "\t<tr><td>EPTC </td><td>Empresa Publica de Transportes e Circulação</td><td>D72      </td><td>D72   </td><td>DIRETAO / VIA STA. ROSA                  </td><td>BUS </td><td>4.8</td><td>BUS </td></tr>\n",
       "\t<tr><td>EPTC </td><td>Empresa Publica de Transportes e Circulação</td><td>D73      </td><td>D73   </td><td>DIRETAO / VIA FERNANDO FERRARI           </td><td>BUS </td><td>4.8</td><td>BUS </td></tr>\n",
       "\t<tr><td>EPTC </td><td>Empresa Publica de Transportes e Circulação</td><td>R4       </td><td>R4    </td><td>RAPIDA  -  RESTINGA VELHA                </td><td>BUS </td><td>4.8</td><td>BUS </td></tr>\n",
       "\t<tr><td>EPTC </td><td>Empresa Publica de Transportes e Circulação</td><td>R41      </td><td>R41   </td><td>RAPIDA  -  PROTASIO                      </td><td>BUS </td><td>4.8</td><td>BUS </td></tr>\n",
       "\t<tr><td>EPTC </td><td>Empresa Publica de Transportes e Circulação</td><td>R62      </td><td>R62   </td><td>RAPIDA RUBEM BERTA                       </td><td>BUS </td><td>4.8</td><td>BUS </td></tr>\n",
       "\t<tr><td>EPTC </td><td>Empresa Publica de Transportes e Circulação</td><td>R67      </td><td>R67   </td><td>RAPIDA LAMI VIA BELEM NOVO               </td><td>BUS </td><td>4.8</td><td>BUS </td></tr>\n",
       "\t<tr><td>EPTC </td><td>Empresa Publica de Transportes e Circulação</td><td>T1       </td><td>T1    </td><td>TRANSVERSAL 1                            </td><td>BUS </td><td>4.8</td><td>BUS </td></tr>\n",
       "\t<tr><td>EPTC </td><td>Empresa Publica de Transportes e Circulação</td><td>T11      </td><td>T11   </td><td>3ª PERIMETRAL                            </td><td>BUS </td><td>4.8</td><td>BUS </td></tr>\n",
       "\t<tr><td>EPTC </td><td>Empresa Publica de Transportes e Circulação</td><td>T12      </td><td>T12   </td><td>RESTINGA / CAIRU                         </td><td>BUS </td><td>4.8</td><td>BUS </td></tr>\n",
       "\t<tr><td>EPTC </td><td>Empresa Publica de Transportes e Circulação</td><td>T1D      </td><td>T1D   </td><td>T1 DIRETA                                </td><td>BUS </td><td>4.8</td><td>BUS </td></tr>\n",
       "\t<tr><td>EPTC </td><td>Empresa Publica de Transportes e Circulação</td><td>T2       </td><td>T2    </td><td>TRANSVERSAL 2                            </td><td>BUS </td><td>4.8</td><td>BUS </td></tr>\n",
       "\t<tr><td>EPTC </td><td>Empresa Publica de Transportes e Circulação</td><td>T2A1     </td><td>T2A1  </td><td>TRANSVERSAL 2 / A. J. RENNER             </td><td>BUS </td><td>4.8</td><td>BUS </td></tr>\n",
       "\t<tr><td>EPTC </td><td>Empresa Publica de Transportes e Circulação</td><td>T4       </td><td>T4    </td><td>TRANSVERSAL 4                            </td><td>BUS </td><td>4.8</td><td>BUS </td></tr>\n",
       "\t<tr><td>EPTC </td><td>Empresa Publica de Transportes e Circulação</td><td>T6       </td><td>T6    </td><td>TRANSVERSAL 6                            </td><td>BUS </td><td>4.8</td><td>BUS </td></tr>\n",
       "\t<tr><td>EPTC </td><td>Empresa Publica de Transportes e Circulação</td><td>T7       </td><td>T7    </td><td>NILO / PRAIA DE BELAS                    </td><td>BUS </td><td>4.8</td><td>BUS </td></tr>\n",
       "\t<tr><td>EPTC </td><td>Empresa Publica de Transportes e Circulação</td><td>T8       </td><td>T8    </td><td>CAMPUS  /  FARRAPOS                      </td><td>BUS </td><td>4.8</td><td>BUS </td></tr>\n",
       "\t<tr><td>EPTC </td><td>Empresa Publica de Transportes e Circulação</td><td>T9       </td><td>T9    </td><td>PUC                                      </td><td>BUS </td><td>4.8</td><td>BUS </td></tr>\n",
       "\t<tr><td>EPTC </td><td>Empresa Publica de Transportes e Circulação</td><td>TR60     </td><td>TR60  </td><td>TRONCAL TRI‘NGULO                        </td><td>BUS </td><td>4.8</td><td>BUS </td></tr>\n",
       "\t<tr><td>EPTC </td><td>Empresa Publica de Transportes e Circulação</td><td>TR62     </td><td>TR62  </td><td>TRONCAL BALTAZAR                         </td><td>BUS </td><td>4.8</td><td>BUS </td></tr>\n",
       "\t<tr><td>TRENS</td><td>TRENSURB                                   </td><td>LINHA1   </td><td>LINHA1</td><td>ESTACAO MERCADO ATE ESTACAO NOVO HAMBURGO</td><td>RAIL</td><td>4.8</td><td>RAIL</td></tr>\n",
       "\t<tr><td>TRENS</td><td>TRENSURB                                   </td><td>LINHAAERO</td><td>AREO  </td><td>AEROMOVEL TRENSURB                       </td><td>RAIL</td><td>4.8</td><td>RAIL</td></tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</dd>\n",
       "\t<dt>$debug_settings</dt>\n",
       "\t\t<dd><dl>\n",
       "\t<dt>$output_file</dt>\n",
       "\t\t<dd>''</dd>\n",
       "\t<dt>$trip_info</dt>\n",
       "\t\t<dd>'MODE'</dd>\n",
       "</dl>\n",
       "</dd>\n",
       "</dl>\n"
      ],
      "text/latex": [
       "\\begin{description}\n",
       "\\item[\\$max\\_discounted\\_transfers] 1\n",
       "\\item[\\$transfer\\_time\\_allowance] 120\n",
       "\\item[\\$fare\\_cap] Inf\n",
       "\\item[\\$fares\\_per\\_type] A data.table: 2 × 5\n",
       "\\begin{tabular}{lllll}\n",
       " type & unlimited\\_transfers & allow\\_same\\_route\\_transfer & use\\_route\\_fare & fare\\\\\n",
       " <chr> & <lgl> & <lgl> & <lgl> & <dbl>\\\\\n",
       "\\hline\n",
       "\t BUS  & FALSE & FALSE & FALSE & 4.8\\\\\n",
       "\t RAIL & FALSE & FALSE & FALSE & 4.8\\\\\n",
       "\\end{tabular}\n",
       "\n",
       "\\item[\\$fares\\_per\\_transfer] A data.table: 4 × 3\n",
       "\\begin{tabular}{lll}\n",
       " first\\_leg & second\\_leg & fare\\\\\n",
       " <chr> & <chr> & <dbl>\\\\\n",
       "\\hline\n",
       "\t BUS  & BUS  & 4.8\\\\\n",
       "\t RAIL & BUS  & 4.8\\\\\n",
       "\t BUS  & RAIL & 4.8\\\\\n",
       "\t RAIL & RAIL & 4.8\\\\\n",
       "\\end{tabular}\n",
       "\n",
       "\\item[\\$fares\\_per\\_route] A data.table: 117 × 8\n",
       "\\begin{tabular}{llllllll}\n",
       " agency\\_id & agency\\_name & route\\_id & route\\_short\\_name & route\\_long\\_name & mode & route\\_fare & fare\\_type\\\\\n",
       " <chr> & <chr> & <chr> & <chr> & <chr> & <chr> & <dbl> & <chr>\\\\\n",
       "\\hline\n",
       "\t EPTC & Empresa Publica de Transportes e Circulação & 1112 & 1112 & HIPICA / TRISTEZA                           & BUS & 4.8 & BUS\\\\\n",
       "\t EPTC & Empresa Publica de Transportes e Circulação & 149  & 149  & ICARAI                                      & BUS & 4.8 & BUS\\\\\n",
       "\t EPTC & Empresa Publica de Transportes e Circulação & 165  & 165  & COHAB                                       & BUS & 4.8 & BUS\\\\\n",
       "\t EPTC & Empresa Publica de Transportes e Circulação & 168  & 168  & BELEM NOVO(VIA TRISTEZA)                    & BUS & 4.8 & BUS\\\\\n",
       "\t EPTC & Empresa Publica de Transportes e Circulação & 173  & 173  & CAMAQUA                                     & BUS & 4.8 & BUS\\\\\n",
       "\t EPTC & Empresa Publica de Transportes e Circulação & 1761 & 1761 & SERRARIA / RODOVIARIA / VIA MENDES OURIQUES & BUS & 4.8 & BUS\\\\\n",
       "\t EPTC & Empresa Publica de Transportes e Circulação & 179  & 179  & SERRARIA                                    & BUS & 4.8 & BUS\\\\\n",
       "\t EPTC & Empresa Publica de Transportes e Circulação & 1795 & 1795 & SERRARIA / GUAIBA / DIARIO                  & BUS & 4.8 & BUS\\\\\n",
       "\t EPTC & Empresa Publica de Transportes e Circulação & 186  & 186  & LIBERAL                                     & BUS & 4.8 & BUS\\\\\n",
       "\t EPTC & Empresa Publica de Transportes e Circulação & 187  & 187  & PADRE REUS                                  & BUS & 4.8 & BUS\\\\\n",
       "\t EPTC & Empresa Publica de Transportes e Circulação & 188  & 188  & ASSUNCAO                                    & BUS & 4.8 & BUS\\\\\n",
       "\t EPTC & Empresa Publica de Transportes e Circulação & 195  & 195  & T V                                         & BUS & 4.8 & BUS\\\\\n",
       "\t EPTC & Empresa Publica de Transportes e Circulação & 210  & 210  & RESTINGA NOVA                               & BUS & 4.8 & BUS\\\\\n",
       "\t EPTC & Empresa Publica de Transportes e Circulação & 211  & 211  & RESTINGA VELHA                              & BUS & 4.8 & BUS\\\\\n",
       "\t EPTC & Empresa Publica de Transportes e Circulação & 244  & 244  & SANTA TERESA                                & BUS & 4.8 & BUS\\\\\n",
       "\t EPTC & Empresa Publica de Transportes e Circulação & 2441 & 2441 & SANTA TERESA / VIA MARIANO DE MATOS         & BUS & 4.8 & BUS\\\\\n",
       "\t EPTC & Empresa Publica de Transportes e Circulação & 253  & 253  & RENASCENCA                                  & BUS & 4.8 & BUS\\\\\n",
       "\t EPTC & Empresa Publica de Transportes e Circulação & 2541 & 2541 & EMBRATEL - CANUDOS - CASCATINHA             & BUS & 4.8 & BUS\\\\\n",
       "\t EPTC & Empresa Publica de Transportes e Circulação & 255  & 255  & CALDRE FIAO                                 & BUS & 4.8 & BUS\\\\\n",
       "\t EPTC & Empresa Publica de Transportes e Circulação & 256  & 256  & INTENDENTE AZEVEDO                          & BUS & 4.8 & BUS\\\\\n",
       "\t EPTC & Empresa Publica de Transportes e Circulação & 2561 & 2561 & NAZARETH                                    & BUS & 4.8 & BUS\\\\\n",
       "\t EPTC & Empresa Publica de Transportes e Circulação & 260  & 260  & BELEM VELHO / OSCAR PEREIRA                 & BUS & 4.8 & BUS\\\\\n",
       "\t EPTC & Empresa Publica de Transportes e Circulação & 262  & 262  & JARDIM V. NOVA                              & BUS & 4.8 & BUS\\\\\n",
       "\t EPTC & Empresa Publica de Transportes e Circulação & 263  & 263  & ORFANOTROFIO                                & BUS & 4.8 & BUS\\\\\n",
       "\t EPTC & Empresa Publica de Transportes e Circulação & 264  & 264  & PRADO                                       & BUS & 4.8 & BUS\\\\\n",
       "\t EPTC & Empresa Publica de Transportes e Circulação & 2671 & 2671 & LAMI / VAREJAO(VIA EDGAR PIRES DE CASTRO)   & BUS & 4.8 & BUS\\\\\n",
       "\t EPTC & Empresa Publica de Transportes e Circulação & 268  & 268  & BELEM NOVO(VIA CAVALHADA)                   & BUS & 4.8 & BUS\\\\\n",
       "\t EPTC & Empresa Publica de Transportes e Circulação & 271  & 271  & AMAPA                                       & BUS & 4.8 & BUS\\\\\n",
       "\t EPTC & Empresa Publica de Transportes e Circulação & 272  & 272  & MORADAS DA HIPICA                           & BUS & 4.8 & BUS\\\\\n",
       "\t EPTC & Empresa Publica de Transportes e Circulação & 273  & 273  & BELEM NOVO / HIPICA                         & BUS & 4.8 & BUS\\\\\n",
       "\t ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮\\\\\n",
       "\t EPTC  & Empresa Publica de Transportes e Circulação & 862       & 862    & RUBEM BERTA (CAIRU)                       & BUS  & 4.8 & BUS \\\\\n",
       "\t EPTC  & Empresa Publica de Transportes e Circulação & B02       & B02    & LEOPOLDINA  /  AEROPORTO  /  INDUSTRIAS   & BUS  & 4.8 & BUS \\\\\n",
       "\t EPTC  & Empresa Publica de Transportes e Circulação & B51       & B51    & PARQUE  /  POSTAO IAPI / H CONCEICAO      & BUS  & 4.8 & BUS \\\\\n",
       "\t EPTC  & Empresa Publica de Transportes e Circulação & B511      & B511   & PARQUE / H CONCEICAO / POSTAO IAPI        & BUS  & 4.8 & BUS \\\\\n",
       "\t EPTC  & Empresa Publica de Transportes e Circulação & B56       & B56    & PASSO DAS PEDRAS  /  AEROPORTO            & BUS  & 4.8 & BUS \\\\\n",
       "\t EPTC  & Empresa Publica de Transportes e Circulação & C1        & C1     & CIRCULAR CENTRO                           & BUS  & 4.8 & BUS \\\\\n",
       "\t EPTC  & Empresa Publica de Transportes e Circulação & C2        & C2     & CIRCULAR PRACA XV                         & BUS  & 4.8 & BUS \\\\\n",
       "\t EPTC  & Empresa Publica de Transportes e Circulação & C3        & C3     & CIRCULAR URCA                             & BUS  & 4.8 & BUS \\\\\n",
       "\t EPTC  & Empresa Publica de Transportes e Circulação & D67       & D67    & LAMI VIA BELEM NOVO / DIRETA              & BUS  & 4.8 & BUS \\\\\n",
       "\t EPTC  & Empresa Publica de Transportes e Circulação & D72       & D72    & DIRETAO / VIA STA. ROSA                   & BUS  & 4.8 & BUS \\\\\n",
       "\t EPTC  & Empresa Publica de Transportes e Circulação & D73       & D73    & DIRETAO / VIA FERNANDO FERRARI            & BUS  & 4.8 & BUS \\\\\n",
       "\t EPTC  & Empresa Publica de Transportes e Circulação & R4        & R4     & RAPIDA  -  RESTINGA VELHA                 & BUS  & 4.8 & BUS \\\\\n",
       "\t EPTC  & Empresa Publica de Transportes e Circulação & R41       & R41    & RAPIDA  -  PROTASIO                       & BUS  & 4.8 & BUS \\\\\n",
       "\t EPTC  & Empresa Publica de Transportes e Circulação & R62       & R62    & RAPIDA RUBEM BERTA                        & BUS  & 4.8 & BUS \\\\\n",
       "\t EPTC  & Empresa Publica de Transportes e Circulação & R67       & R67    & RAPIDA LAMI VIA BELEM NOVO                & BUS  & 4.8 & BUS \\\\\n",
       "\t EPTC  & Empresa Publica de Transportes e Circulação & T1        & T1     & TRANSVERSAL 1                             & BUS  & 4.8 & BUS \\\\\n",
       "\t EPTC  & Empresa Publica de Transportes e Circulação & T11       & T11    & 3ª PERIMETRAL                             & BUS  & 4.8 & BUS \\\\\n",
       "\t EPTC  & Empresa Publica de Transportes e Circulação & T12       & T12    & RESTINGA / CAIRU                          & BUS  & 4.8 & BUS \\\\\n",
       "\t EPTC  & Empresa Publica de Transportes e Circulação & T1D       & T1D    & T1 DIRETA                                 & BUS  & 4.8 & BUS \\\\\n",
       "\t EPTC  & Empresa Publica de Transportes e Circulação & T2        & T2     & TRANSVERSAL 2                             & BUS  & 4.8 & BUS \\\\\n",
       "\t EPTC  & Empresa Publica de Transportes e Circulação & T2A1      & T2A1   & TRANSVERSAL 2 / A. J. RENNER              & BUS  & 4.8 & BUS \\\\\n",
       "\t EPTC  & Empresa Publica de Transportes e Circulação & T4        & T4     & TRANSVERSAL 4                             & BUS  & 4.8 & BUS \\\\\n",
       "\t EPTC  & Empresa Publica de Transportes e Circulação & T6        & T6     & TRANSVERSAL 6                             & BUS  & 4.8 & BUS \\\\\n",
       "\t EPTC  & Empresa Publica de Transportes e Circulação & T7        & T7     & NILO / PRAIA DE BELAS                     & BUS  & 4.8 & BUS \\\\\n",
       "\t EPTC  & Empresa Publica de Transportes e Circulação & T8        & T8     & CAMPUS  /  FARRAPOS                       & BUS  & 4.8 & BUS \\\\\n",
       "\t EPTC  & Empresa Publica de Transportes e Circulação & T9        & T9     & PUC                                       & BUS  & 4.8 & BUS \\\\\n",
       "\t EPTC  & Empresa Publica de Transportes e Circulação & TR60      & TR60   & TRONCAL TRI‘NGULO                         & BUS  & 4.8 & BUS \\\\\n",
       "\t EPTC  & Empresa Publica de Transportes e Circulação & TR62      & TR62   & TRONCAL BALTAZAR                          & BUS  & 4.8 & BUS \\\\\n",
       "\t TRENS & TRENSURB                                    & LINHA1    & LINHA1 & ESTACAO MERCADO ATE ESTACAO NOVO HAMBURGO & RAIL & 4.8 & RAIL\\\\\n",
       "\t TRENS & TRENSURB                                    & LINHAAERO & AREO   & AEROMOVEL TRENSURB                        & RAIL & 4.8 & RAIL\\\\\n",
       "\\end{tabular}\n",
       "\n",
       "\\item[\\$debug\\_settings] \\begin{description}\n",
       "\\item[\\$output\\_file] ''\n",
       "\\item[\\$trip\\_info] 'MODE'\n",
       "\\end{description}\n",
       "\n",
       "\\end{description}\n"
      ],
      "text/markdown": [
       "$max_discounted_transfers\n",
       ":   1\n",
       "$transfer_time_allowance\n",
       ":   120\n",
       "$fare_cap\n",
       ":   Inf\n",
       "$fares_per_type\n",
       ":   \n",
       "A data.table: 2 × 5\n",
       "\n",
       "| type &lt;chr&gt; | unlimited_transfers &lt;lgl&gt; | allow_same_route_transfer &lt;lgl&gt; | use_route_fare &lt;lgl&gt; | fare &lt;dbl&gt; |\n",
       "|---|---|---|---|---|\n",
       "| BUS  | FALSE | FALSE | FALSE | 4.8 |\n",
       "| RAIL | FALSE | FALSE | FALSE | 4.8 |\n",
       "\n",
       "\n",
       "$fares_per_transfer\n",
       ":   \n",
       "A data.table: 4 × 3\n",
       "\n",
       "| first_leg &lt;chr&gt; | second_leg &lt;chr&gt; | fare &lt;dbl&gt; |\n",
       "|---|---|---|\n",
       "| BUS  | BUS  | 4.8 |\n",
       "| RAIL | BUS  | 4.8 |\n",
       "| BUS  | RAIL | 4.8 |\n",
       "| RAIL | RAIL | 4.8 |\n",
       "\n",
       "\n",
       "$fares_per_route\n",
       ":   \n",
       "A data.table: 117 × 8\n",
       "\n",
       "| agency_id &lt;chr&gt; | agency_name &lt;chr&gt; | route_id &lt;chr&gt; | route_short_name &lt;chr&gt; | route_long_name &lt;chr&gt; | mode &lt;chr&gt; | route_fare &lt;dbl&gt; | fare_type &lt;chr&gt; |\n",
       "|---|---|---|---|---|---|---|---|\n",
       "| EPTC | Empresa Publica de Transportes e Circulação | 1112 | 1112 | HIPICA / TRISTEZA                           | BUS | 4.8 | BUS |\n",
       "| EPTC | Empresa Publica de Transportes e Circulação | 149  | 149  | ICARAI                                      | BUS | 4.8 | BUS |\n",
       "| EPTC | Empresa Publica de Transportes e Circulação | 165  | 165  | COHAB                                       | BUS | 4.8 | BUS |\n",
       "| EPTC | Empresa Publica de Transportes e Circulação | 168  | 168  | BELEM NOVO(VIA TRISTEZA)                    | BUS | 4.8 | BUS |\n",
       "| EPTC | Empresa Publica de Transportes e Circulação | 173  | 173  | CAMAQUA                                     | BUS | 4.8 | BUS |\n",
       "| EPTC | Empresa Publica de Transportes e Circulação | 1761 | 1761 | SERRARIA / RODOVIARIA / VIA MENDES OURIQUES | BUS | 4.8 | BUS |\n",
       "| EPTC | Empresa Publica de Transportes e Circulação | 179  | 179  | SERRARIA                                    | BUS | 4.8 | BUS |\n",
       "| EPTC | Empresa Publica de Transportes e Circulação | 1795 | 1795 | SERRARIA / GUAIBA / DIARIO                  | BUS | 4.8 | BUS |\n",
       "| EPTC | Empresa Publica de Transportes e Circulação | 186  | 186  | LIBERAL                                     | BUS | 4.8 | BUS |\n",
       "| EPTC | Empresa Publica de Transportes e Circulação | 187  | 187  | PADRE REUS                                  | BUS | 4.8 | BUS |\n",
       "| EPTC | Empresa Publica de Transportes e Circulação | 188  | 188  | ASSUNCAO                                    | BUS | 4.8 | BUS |\n",
       "| EPTC | Empresa Publica de Transportes e Circulação | 195  | 195  | T V                                         | BUS | 4.8 | BUS |\n",
       "| EPTC | Empresa Publica de Transportes e Circulação | 210  | 210  | RESTINGA NOVA                               | BUS | 4.8 | BUS |\n",
       "| EPTC | Empresa Publica de Transportes e Circulação | 211  | 211  | RESTINGA VELHA                              | BUS | 4.8 | BUS |\n",
       "| EPTC | Empresa Publica de Transportes e Circulação | 244  | 244  | SANTA TERESA                                | BUS | 4.8 | BUS |\n",
       "| EPTC | Empresa Publica de Transportes e Circulação | 2441 | 2441 | SANTA TERESA / VIA MARIANO DE MATOS         | BUS | 4.8 | BUS |\n",
       "| EPTC | Empresa Publica de Transportes e Circulação | 253  | 253  | RENASCENCA                                  | BUS | 4.8 | BUS |\n",
       "| EPTC | Empresa Publica de Transportes e Circulação | 2541 | 2541 | EMBRATEL - CANUDOS - CASCATINHA             | BUS | 4.8 | BUS |\n",
       "| EPTC | Empresa Publica de Transportes e Circulação | 255  | 255  | CALDRE FIAO                                 | BUS | 4.8 | BUS |\n",
       "| EPTC | Empresa Publica de Transportes e Circulação | 256  | 256  | INTENDENTE AZEVEDO                          | BUS | 4.8 | BUS |\n",
       "| EPTC | Empresa Publica de Transportes e Circulação | 2561 | 2561 | NAZARETH                                    | BUS | 4.8 | BUS |\n",
       "| EPTC | Empresa Publica de Transportes e Circulação | 260  | 260  | BELEM VELHO / OSCAR PEREIRA                 | BUS | 4.8 | BUS |\n",
       "| EPTC | Empresa Publica de Transportes e Circulação | 262  | 262  | JARDIM V. NOVA                              | BUS | 4.8 | BUS |\n",
       "| EPTC | Empresa Publica de Transportes e Circulação | 263  | 263  | ORFANOTROFIO                                | BUS | 4.8 | BUS |\n",
       "| EPTC | Empresa Publica de Transportes e Circulação | 264  | 264  | PRADO                                       | BUS | 4.8 | BUS |\n",
       "| EPTC | Empresa Publica de Transportes e Circulação | 2671 | 2671 | LAMI / VAREJAO(VIA EDGAR PIRES DE CASTRO)   | BUS | 4.8 | BUS |\n",
       "| EPTC | Empresa Publica de Transportes e Circulação | 268  | 268  | BELEM NOVO(VIA CAVALHADA)                   | BUS | 4.8 | BUS |\n",
       "| EPTC | Empresa Publica de Transportes e Circulação | 271  | 271  | AMAPA                                       | BUS | 4.8 | BUS |\n",
       "| EPTC | Empresa Publica de Transportes e Circulação | 272  | 272  | MORADAS DA HIPICA                           | BUS | 4.8 | BUS |\n",
       "| EPTC | Empresa Publica de Transportes e Circulação | 273  | 273  | BELEM NOVO / HIPICA                         | BUS | 4.8 | BUS |\n",
       "| ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ |\n",
       "| EPTC  | Empresa Publica de Transportes e Circulação | 862       | 862    | RUBEM BERTA (CAIRU)                       | BUS  | 4.8 | BUS  |\n",
       "| EPTC  | Empresa Publica de Transportes e Circulação | B02       | B02    | LEOPOLDINA  /  AEROPORTO  /  INDUSTRIAS   | BUS  | 4.8 | BUS  |\n",
       "| EPTC  | Empresa Publica de Transportes e Circulação | B51       | B51    | PARQUE  /  POSTAO IAPI / H CONCEICAO      | BUS  | 4.8 | BUS  |\n",
       "| EPTC  | Empresa Publica de Transportes e Circulação | B511      | B511   | PARQUE / H CONCEICAO / POSTAO IAPI        | BUS  | 4.8 | BUS  |\n",
       "| EPTC  | Empresa Publica de Transportes e Circulação | B56       | B56    | PASSO DAS PEDRAS  /  AEROPORTO            | BUS  | 4.8 | BUS  |\n",
       "| EPTC  | Empresa Publica de Transportes e Circulação | C1        | C1     | CIRCULAR CENTRO                           | BUS  | 4.8 | BUS  |\n",
       "| EPTC  | Empresa Publica de Transportes e Circulação | C2        | C2     | CIRCULAR PRACA XV                         | BUS  | 4.8 | BUS  |\n",
       "| EPTC  | Empresa Publica de Transportes e Circulação | C3        | C3     | CIRCULAR URCA                             | BUS  | 4.8 | BUS  |\n",
       "| EPTC  | Empresa Publica de Transportes e Circulação | D67       | D67    | LAMI VIA BELEM NOVO / DIRETA              | BUS  | 4.8 | BUS  |\n",
       "| EPTC  | Empresa Publica de Transportes e Circulação | D72       | D72    | DIRETAO / VIA STA. ROSA                   | BUS  | 4.8 | BUS  |\n",
       "| EPTC  | Empresa Publica de Transportes e Circulação | D73       | D73    | DIRETAO / VIA FERNANDO FERRARI            | BUS  | 4.8 | BUS  |\n",
       "| EPTC  | Empresa Publica de Transportes e Circulação | R4        | R4     | RAPIDA  -  RESTINGA VELHA                 | BUS  | 4.8 | BUS  |\n",
       "| EPTC  | Empresa Publica de Transportes e Circulação | R41       | R41    | RAPIDA  -  PROTASIO                       | BUS  | 4.8 | BUS  |\n",
       "| EPTC  | Empresa Publica de Transportes e Circulação | R62       | R62    | RAPIDA RUBEM BERTA                        | BUS  | 4.8 | BUS  |\n",
       "| EPTC  | Empresa Publica de Transportes e Circulação | R67       | R67    | RAPIDA LAMI VIA BELEM NOVO                | BUS  | 4.8 | BUS  |\n",
       "| EPTC  | Empresa Publica de Transportes e Circulação | T1        | T1     | TRANSVERSAL 1                             | BUS  | 4.8 | BUS  |\n",
       "| EPTC  | Empresa Publica de Transportes e Circulação | T11       | T11    | 3ª PERIMETRAL                             | BUS  | 4.8 | BUS  |\n",
       "| EPTC  | Empresa Publica de Transportes e Circulação | T12       | T12    | RESTINGA / CAIRU                          | BUS  | 4.8 | BUS  |\n",
       "| EPTC  | Empresa Publica de Transportes e Circulação | T1D       | T1D    | T1 DIRETA                                 | BUS  | 4.8 | BUS  |\n",
       "| EPTC  | Empresa Publica de Transportes e Circulação | T2        | T2     | TRANSVERSAL 2                             | BUS  | 4.8 | BUS  |\n",
       "| EPTC  | Empresa Publica de Transportes e Circulação | T2A1      | T2A1   | TRANSVERSAL 2 / A. J. RENNER              | BUS  | 4.8 | BUS  |\n",
       "| EPTC  | Empresa Publica de Transportes e Circulação | T4        | T4     | TRANSVERSAL 4                             | BUS  | 4.8 | BUS  |\n",
       "| EPTC  | Empresa Publica de Transportes e Circulação | T6        | T6     | TRANSVERSAL 6                             | BUS  | 4.8 | BUS  |\n",
       "| EPTC  | Empresa Publica de Transportes e Circulação | T7        | T7     | NILO / PRAIA DE BELAS                     | BUS  | 4.8 | BUS  |\n",
       "| EPTC  | Empresa Publica de Transportes e Circulação | T8        | T8     | CAMPUS  /  FARRAPOS                       | BUS  | 4.8 | BUS  |\n",
       "| EPTC  | Empresa Publica de Transportes e Circulação | T9        | T9     | PUC                                       | BUS  | 4.8 | BUS  |\n",
       "| EPTC  | Empresa Publica de Transportes e Circulação | TR60      | TR60   | TRONCAL TRI‘NGULO                         | BUS  | 4.8 | BUS  |\n",
       "| EPTC  | Empresa Publica de Transportes e Circulação | TR62      | TR62   | TRONCAL BALTAZAR                          | BUS  | 4.8 | BUS  |\n",
       "| TRENS | TRENSURB                                    | LINHA1    | LINHA1 | ESTACAO MERCADO ATE ESTACAO NOVO HAMBURGO | RAIL | 4.8 | RAIL |\n",
       "| TRENS | TRENSURB                                    | LINHAAERO | AREO   | AEROMOVEL TRENSURB                        | RAIL | 4.8 | RAIL |\n",
       "\n",
       "\n",
       "$debug_settings\n",
       ":   $output_file\n",
       ":   ''\n",
       "$trip_info\n",
       ":   'MODE'\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "$max_discounted_transfers\n",
       "[1] 1\n",
       "\n",
       "$transfer_time_allowance\n",
       "[1] 120\n",
       "\n",
       "$fare_cap\n",
       "[1] Inf\n",
       "\n",
       "$fares_per_type\n",
       "   type unlimited_transfers allow_same_route_transfer use_route_fare fare\n",
       "1:  BUS               FALSE                     FALSE          FALSE  4.8\n",
       "2: RAIL               FALSE                     FALSE          FALSE  4.8\n",
       "\n",
       "$fares_per_transfer\n",
       "   first_leg second_leg fare\n",
       "1:       BUS        BUS  4.8\n",
       "2:      RAIL        BUS  4.8\n",
       "3:       BUS       RAIL  4.8\n",
       "4:      RAIL       RAIL  4.8\n",
       "\n",
       "$fares_per_route\n",
       "     agency_id                                 agency_name  route_id\n",
       "  1:      EPTC Empresa Publica de Transportes e Circulação      1112\n",
       "  2:      EPTC Empresa Publica de Transportes e Circulação       149\n",
       "  3:      EPTC Empresa Publica de Transportes e Circulação       165\n",
       "  4:      EPTC Empresa Publica de Transportes e Circulação       168\n",
       "  5:      EPTC Empresa Publica de Transportes e Circulação       173\n",
       " ---                                                                \n",
       "113:      EPTC Empresa Publica de Transportes e Circulação        T9\n",
       "114:      EPTC Empresa Publica de Transportes e Circulação      TR60\n",
       "115:      EPTC Empresa Publica de Transportes e Circulação      TR62\n",
       "116:     TRENS                                    TRENSURB    LINHA1\n",
       "117:     TRENS                                    TRENSURB LINHAAERO\n",
       "     route_short_name                           route_long_name mode route_fare\n",
       "  1:             1112                         HIPICA / TRISTEZA  BUS        4.8\n",
       "  2:              149                                    ICARAI  BUS        4.8\n",
       "  3:              165                                     COHAB  BUS        4.8\n",
       "  4:              168                  BELEM NOVO(VIA TRISTEZA)  BUS        4.8\n",
       "  5:              173                                   CAMAQUA  BUS        4.8\n",
       " ---                                                                           \n",
       "113:               T9                                       PUC  BUS        4.8\n",
       "114:             TR60                         TRONCAL TRI‘NGULO  BUS        4.8\n",
       "115:             TR62                          TRONCAL BALTAZAR  BUS        4.8\n",
       "116:           LINHA1 ESTACAO MERCADO ATE ESTACAO NOVO HAMBURGO RAIL        4.8\n",
       "117:             AREO                        AEROMOVEL TRENSURB RAIL        4.8\n",
       "     fare_type\n",
       "  1:       BUS\n",
       "  2:       BUS\n",
       "  3:       BUS\n",
       "  4:       BUS\n",
       "  5:       BUS\n",
       " ---          \n",
       "113:       BUS\n",
       "114:       BUS\n",
       "115:       BUS\n",
       "116:      RAIL\n",
       "117:      RAIL\n",
       "\n",
       "$debug_settings\n",
       "$debug_settings$output_file\n",
       "[1] \"\"\n",
       "\n",
       "$debug_settings$trip_info\n",
       "[1] \"MODE\"\n",
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "head(fare_structure, n=7)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5230ff2a",
   "metadata": {},
   "source": [
    "### 3.1 Global Properties\n",
    "\n",
    "Let's configure the global properties first, which are the ones that are applied \n",
    "to the entire system. \n",
    "\n",
    "#### `max_discounted_transfers`\n",
    "\n",
    "Note that `max_discounted_transfers` is set to 1 by default. This means that the \n",
    "passenger gets a fare discount in the first transfer between buses, but she would \n",
    "pay the full fare price in subsequent transfers. \n",
    "\n",
    "#### `transfer_time_allowance`\n",
    "\n",
    "By default, `transfer_time_allowance` is set to 120 minutes. We have to set it to \n",
    "60 minutes to fit our use case (passengers have 60 minutes to take the second bus \n",
    "on a discounted fare, otherwise a full fare is charged).\n",
    "\n",
    "#### `fare_cap`\n",
    "\n",
    "Finally, the `fare_cap` setting indicates if there is a maximum value that can be \n",
    "charged in a trip, beyond which all subsequent rides are free of charge. In this \n",
    "example, we can leave `fare_cap` set to its default `Inf` value because this \n",
    "feature is not applicable to Porto Alegre.\n",
    "Here is how we can check or update the values of these components:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "b13d804c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "1"
      ],
      "text/latex": [
       "1"
      ],
      "text/markdown": [
       "1"
      ],
      "text/plain": [
       "[1] 1"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Inf"
      ],
      "text/latex": [
       "Inf"
      ],
      "text/markdown": [
       "Inf"
      ],
      "text/plain": [
       "[1] Inf"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fare_structure$max_discounted_transfers\n",
    "fare_structure$transfer_time_allowance <- 60 # update transfer_time_allowance\n",
    "fare_structure$fare_cap"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "add7b82d",
   "metadata": {},
   "source": [
    "### 3.2 Configure fares by transport mode\n",
    "To configure mode-, transfer-, and route-specific properties, we can use the three `data.frames` inside our `fare_structure` list. Let's configure the modes first. \n",
    "Below, we can see that the `fares_per_type` data.frame contains five columns:\n",
    "\n",
    "-   `mode`: the transport mode to which rules on each row refer to;\n",
    "-   `unlimited_transfers`: a logical value `TRUE` or `FALSE` that indicates if that transport mode allows unlimited transfers between trips of the same mode, such as a metro/subway system where the passenger pays a fare to access a station and then can use as many services as she wants as long as she doesn't exit the system;\n",
    "-   `allow_same_route_transfer`: a logical value indicating if a discounted transfer can be done between vehicles ??? of the same route;\n",
    "-   `use_route_fare`: another logical value that indicates if each route will have its own fare, or if all routes in this mode will use the fare indicated in this table;\n",
    "-   `fare`: the full fare price of this mode."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "102c7a95",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.table: 2 × 5</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>type</th><th scope=col>unlimited_transfers</th><th scope=col>allow_same_route_transfer</th><th scope=col>use_route_fare</th><th scope=col>fare</th></tr>\n",
       "\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;lgl&gt;</th><th scope=col>&lt;lgl&gt;</th><th scope=col>&lt;lgl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>BUS </td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>4.8</td></tr>\n",
       "\t<tr><td>RAIL</td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>4.8</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.table: 2 × 5\n",
       "\\begin{tabular}{lllll}\n",
       " type & unlimited\\_transfers & allow\\_same\\_route\\_transfer & use\\_route\\_fare & fare\\\\\n",
       " <chr> & <lgl> & <lgl> & <lgl> & <dbl>\\\\\n",
       "\\hline\n",
       "\t BUS  & FALSE & FALSE & FALSE & 4.8\\\\\n",
       "\t RAIL & FALSE & FALSE & FALSE & 4.8\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.table: 2 × 5\n",
       "\n",
       "| type &lt;chr&gt; | unlimited_transfers &lt;lgl&gt; | allow_same_route_transfer &lt;lgl&gt; | use_route_fare &lt;lgl&gt; | fare &lt;dbl&gt; |\n",
       "|---|---|---|---|---|\n",
       "| BUS  | FALSE | FALSE | FALSE | 4.8 |\n",
       "| RAIL | FALSE | FALSE | FALSE | 4.8 |\n",
       "\n"
      ],
      "text/plain": [
       "  type unlimited_transfers allow_same_route_transfer use_route_fare fare\n",
       "1 BUS  FALSE               FALSE                     FALSE          4.8 \n",
       "2 RAIL FALSE               FALSE                     FALSE          4.8 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fare_structure$fares_per_type"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c7496785",
   "metadata": {},
   "source": [
    "We need to do a few small changes in the `fares_per_type` table to accomodate the\n",
    "fare rules of Porto Alegre. In the `\"RAIL\"` mode, we need to set `unlimited_transfers`\n",
    "and `allow_same_route_transfer` to `TRUE`, and update `fare` to 4.50. In the `\"BUS\"` \n",
    "mode, we can let the `allow_same_route_transfer` set to its default `FALSE` value, \n",
    "because even though there is a discount for transfers between buses (which is set \n",
    "in the following section), that discount is not valid when transferring between \n",
    "buses within the same route (for example, from bus route T1 to another T1). We'll \n",
    "do those changes below, using `data.table` notation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "26b883d8",
   "metadata": {},
   "outputs": [],
   "source": [
    "fare_structure$fares_per_type[type == \"RAIL\", unlimited_transfers := TRUE]\n",
    "fare_structure$fares_per_type[type == \"RAIL\", fare := 4.50]\n",
    "fare_structure$fares_per_type[type == \"RAIL\", allow_same_route_transfer := TRUE]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8ed1626c",
   "metadata": {},
   "source": [
    "Checking the results below, everything looks OK:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "c8a3ef4a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.table: 2 × 5</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>type</th><th scope=col>unlimited_transfers</th><th scope=col>allow_same_route_transfer</th><th scope=col>use_route_fare</th><th scope=col>fare</th></tr>\n",
       "\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;lgl&gt;</th><th scope=col>&lt;lgl&gt;</th><th scope=col>&lt;lgl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>BUS </td><td>FALSE</td><td>FALSE</td><td>FALSE</td><td>4.8</td></tr>\n",
       "\t<tr><td>RAIL</td><td> TRUE</td><td> TRUE</td><td>FALSE</td><td>4.5</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.table: 2 × 5\n",
       "\\begin{tabular}{lllll}\n",
       " type & unlimited\\_transfers & allow\\_same\\_route\\_transfer & use\\_route\\_fare & fare\\\\\n",
       " <chr> & <lgl> & <lgl> & <lgl> & <dbl>\\\\\n",
       "\\hline\n",
       "\t BUS  & FALSE & FALSE & FALSE & 4.8\\\\\n",
       "\t RAIL &  TRUE &  TRUE & FALSE & 4.5\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.table: 2 × 5\n",
       "\n",
       "| type &lt;chr&gt; | unlimited_transfers &lt;lgl&gt; | allow_same_route_transfer &lt;lgl&gt; | use_route_fare &lt;lgl&gt; | fare &lt;dbl&gt; |\n",
       "|---|---|---|---|---|\n",
       "| BUS  | FALSE | FALSE | FALSE | 4.8 |\n",
       "| RAIL |  TRUE |  TRUE | FALSE | 4.5 |\n",
       "\n"
      ],
      "text/plain": [
       "  type unlimited_transfers allow_same_route_transfer use_route_fare fare\n",
       "1 BUS  FALSE               FALSE                     FALSE          4.8 \n",
       "2 RAIL  TRUE                TRUE                     FALSE          4.5 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fare_structure$fares_per_type"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "90c3f494",
   "metadata": {},
   "source": [
    "### 3.3 Configure fares by transfers\n",
    "\n",
    "The fare rules for transfer are stored in the `fares_per_transfer` data.frame, \n",
    "which is shown below. Each row contains the fare prices for transfers between the\n",
    "modes specified in `first_leg` and `second_leg` columns."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "fe297471",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.table: 4 × 3</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>first_leg</th><th scope=col>second_leg</th><th scope=col>fare</th></tr>\n",
       "\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>BUS </td><td>BUS </td><td>4.8</td></tr>\n",
       "\t<tr><td>RAIL</td><td>BUS </td><td>4.8</td></tr>\n",
       "\t<tr><td>BUS </td><td>RAIL</td><td>4.8</td></tr>\n",
       "\t<tr><td>RAIL</td><td>RAIL</td><td>4.8</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.table: 4 × 3\n",
       "\\begin{tabular}{lll}\n",
       " first\\_leg & second\\_leg & fare\\\\\n",
       " <chr> & <chr> & <dbl>\\\\\n",
       "\\hline\n",
       "\t BUS  & BUS  & 4.8\\\\\n",
       "\t RAIL & BUS  & 4.8\\\\\n",
       "\t BUS  & RAIL & 4.8\\\\\n",
       "\t RAIL & RAIL & 4.8\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.table: 4 × 3\n",
       "\n",
       "| first_leg &lt;chr&gt; | second_leg &lt;chr&gt; | fare &lt;dbl&gt; |\n",
       "|---|---|---|\n",
       "| BUS  | BUS  | 4.8 |\n",
       "| RAIL | BUS  | 4.8 |\n",
       "| BUS  | RAIL | 4.8 |\n",
       "| RAIL | RAIL | 4.8 |\n",
       "\n"
      ],
      "text/plain": [
       "  first_leg second_leg fare\n",
       "1 BUS       BUS        4.8 \n",
       "2 RAIL      BUS        4.8 \n",
       "3 BUS       RAIL       4.8 \n",
       "4 RAIL      RAIL       4.8 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fare_structure$fares_per_transfer"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2b2c961c",
   "metadata": {},
   "source": [
    "Let's update `fare_per_transfer` to account for the actual integration rules in \n",
    "Porto Alegre.\n",
    "-   The fare for \"BUS\" to \"BUS\" integration is composed of 4.80 for the first leg plus 2.40 for the second leg, which equals to a total fare of 7.20.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "dc2eedf6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# conditional update fare value\n",
    "fare_structure$fares_per_transfer[first_leg == \"BUS\" & second_leg == \"BUS\", fare := 7.2]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7b6b5bd7",
   "metadata": {},
   "source": [
    "- Transfers between \"BUS\" and \"RAIL\" (in any direction) cost 8.37, once the 10% discount is applied. Let's make a final update in the data.frame to account for that.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "4365c894",
   "metadata": {},
   "outputs": [],
   "source": [
    "# conditional update fare value\n",
    "fare_structure$fares_per_transfer[first_leg != second_leg, fare := 8.37]\n",
    "\n",
    "# use fcase instead ?\n",
    "fare_structure$fares_per_transfer[, fare := fcase(first_leg == \"BUS\" & second_leg == \"BUS\", 7.2,\n",
    "                                                 first_leg != second_leg, 8.37)]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a6cd222d",
   "metadata": {},
   "source": [
    "-   Transfers between \"RAIL\" and \"RAIL\" are free and unlimited, which is already \n",
    "accounted for in the field `unlimited_transfers` of the `fare_per_mode` table. \n",
    "Thus, the equivalent row of the `fare_per_transfer` data.frame needs to be removed. \n",
    "If we leave the that row in `fare_per_transfer`, transfers between \"RAIL\" and \"RAIL\" \n",
    "will count to the global `max_discounted_transfers` allowance.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "da953def",
   "metadata": {},
   "outputs": [],
   "source": [
    "# remove row\n",
    "fare_structure$fares_per_transfer <- fare_structure$fares_per_transfer[!(first_leg == \"RAIL\" & second_leg == \"RAIL\")]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7520c7c3",
   "metadata": {},
   "source": [
    "Once all changes are applied, the `fare_per_transfer` data.frame should look like \n",
    "this:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "837a3731",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.table: 3 × 3</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>first_leg</th><th scope=col>second_leg</th><th scope=col>fare</th></tr>\n",
       "\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>BUS </td><td>BUS </td><td>7.20</td></tr>\n",
       "\t<tr><td>RAIL</td><td>BUS </td><td>8.37</td></tr>\n",
       "\t<tr><td>BUS </td><td>RAIL</td><td>8.37</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.table: 3 × 3\n",
       "\\begin{tabular}{lll}\n",
       " first\\_leg & second\\_leg & fare\\\\\n",
       " <chr> & <chr> & <dbl>\\\\\n",
       "\\hline\n",
       "\t BUS  & BUS  & 7.20\\\\\n",
       "\t RAIL & BUS  & 8.37\\\\\n",
       "\t BUS  & RAIL & 8.37\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.table: 3 × 3\n",
       "\n",
       "| first_leg &lt;chr&gt; | second_leg &lt;chr&gt; | fare &lt;dbl&gt; |\n",
       "|---|---|---|\n",
       "| BUS  | BUS  | 7.20 |\n",
       "| RAIL | BUS  | 8.37 |\n",
       "| BUS  | RAIL | 8.37 |\n",
       "\n"
      ],
      "text/plain": [
       "  first_leg second_leg fare\n",
       "1 BUS       BUS        7.20\n",
       "2 RAIL      BUS        8.37\n",
       "3 BUS       RAIL       8.37"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fare_structure$fares_per_transfer"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d024dfeb",
   "metadata": {},
   "source": [
    "### 3.4 Routes configuration\n",
    "\n",
    "The information on the fare price for each route is stored in the `fares_per_route` \n",
    "data.frame. Below, we can see a sample of the bus and train routes in Porto Alegre. \n",
    "In case there a few special routes (e.g. express services) with specific fares, \n",
    "these values can be updated in this `fares_per_route` data.frame.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "71c7584f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.table: 6 × 8</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>agency_id</th><th scope=col>agency_name</th><th scope=col>route_id</th><th scope=col>route_short_name</th><th scope=col>route_long_name</th><th scope=col>mode</th><th scope=col>route_fare</th><th scope=col>fare_type</th></tr>\n",
       "\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;chr&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>EPTC </td><td>Empresa Publica de Transportes e Circulação</td><td>T8       </td><td>T8    </td><td>CAMPUS  /  FARRAPOS                      </td><td>BUS </td><td>4.8</td><td>BUS </td></tr>\n",
       "\t<tr><td>EPTC </td><td>Empresa Publica de Transportes e Circulação</td><td>T9       </td><td>T9    </td><td>PUC                                      </td><td>BUS </td><td>4.8</td><td>BUS </td></tr>\n",
       "\t<tr><td>EPTC </td><td>Empresa Publica de Transportes e Circulação</td><td>TR60     </td><td>TR60  </td><td>TRONCAL TRI‘NGULO                        </td><td>BUS </td><td>4.8</td><td>BUS </td></tr>\n",
       "\t<tr><td>EPTC </td><td>Empresa Publica de Transportes e Circulação</td><td>TR62     </td><td>TR62  </td><td>TRONCAL BALTAZAR                         </td><td>BUS </td><td>4.8</td><td>BUS </td></tr>\n",
       "\t<tr><td>TRENS</td><td>TRENSURB                                   </td><td>LINHA1   </td><td>LINHA1</td><td>ESTACAO MERCADO ATE ESTACAO NOVO HAMBURGO</td><td>RAIL</td><td>4.8</td><td>RAIL</td></tr>\n",
       "\t<tr><td>TRENS</td><td>TRENSURB                                   </td><td>LINHAAERO</td><td>AREO  </td><td>AEROMOVEL TRENSURB                       </td><td>RAIL</td><td>4.8</td><td>RAIL</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.table: 6 × 8\n",
       "\\begin{tabular}{llllllll}\n",
       " agency\\_id & agency\\_name & route\\_id & route\\_short\\_name & route\\_long\\_name & mode & route\\_fare & fare\\_type\\\\\n",
       " <chr> & <chr> & <chr> & <chr> & <chr> & <chr> & <dbl> & <chr>\\\\\n",
       "\\hline\n",
       "\t EPTC  & Empresa Publica de Transportes e Circulação & T8        & T8     & CAMPUS  /  FARRAPOS                       & BUS  & 4.8 & BUS \\\\\n",
       "\t EPTC  & Empresa Publica de Transportes e Circulação & T9        & T9     & PUC                                       & BUS  & 4.8 & BUS \\\\\n",
       "\t EPTC  & Empresa Publica de Transportes e Circulação & TR60      & TR60   & TRONCAL TRI‘NGULO                         & BUS  & 4.8 & BUS \\\\\n",
       "\t EPTC  & Empresa Publica de Transportes e Circulação & TR62      & TR62   & TRONCAL BALTAZAR                          & BUS  & 4.8 & BUS \\\\\n",
       "\t TRENS & TRENSURB                                    & LINHA1    & LINHA1 & ESTACAO MERCADO ATE ESTACAO NOVO HAMBURGO & RAIL & 4.8 & RAIL\\\\\n",
       "\t TRENS & TRENSURB                                    & LINHAAERO & AREO   & AEROMOVEL TRENSURB                        & RAIL & 4.8 & RAIL\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.table: 6 × 8\n",
       "\n",
       "| agency_id &lt;chr&gt; | agency_name &lt;chr&gt; | route_id &lt;chr&gt; | route_short_name &lt;chr&gt; | route_long_name &lt;chr&gt; | mode &lt;chr&gt; | route_fare &lt;dbl&gt; | fare_type &lt;chr&gt; |\n",
       "|---|---|---|---|---|---|---|---|\n",
       "| EPTC  | Empresa Publica de Transportes e Circulação | T8        | T8     | CAMPUS  /  FARRAPOS                       | BUS  | 4.8 | BUS  |\n",
       "| EPTC  | Empresa Publica de Transportes e Circulação | T9        | T9     | PUC                                       | BUS  | 4.8 | BUS  |\n",
       "| EPTC  | Empresa Publica de Transportes e Circulação | TR60      | TR60   | TRONCAL TRI‘NGULO                         | BUS  | 4.8 | BUS  |\n",
       "| EPTC  | Empresa Publica de Transportes e Circulação | TR62      | TR62   | TRONCAL BALTAZAR                          | BUS  | 4.8 | BUS  |\n",
       "| TRENS | TRENSURB                                    | LINHA1    | LINHA1 | ESTACAO MERCADO ATE ESTACAO NOVO HAMBURGO | RAIL | 4.8 | RAIL |\n",
       "| TRENS | TRENSURB                                    | LINHAAERO | AREO   | AEROMOVEL TRENSURB                        | RAIL | 4.8 | RAIL |\n",
       "\n"
      ],
      "text/plain": [
       "  agency_id agency_name                                 route_id \n",
       "1 EPTC      Empresa Publica de Transportes e Circulação T8       \n",
       "2 EPTC      Empresa Publica de Transportes e Circulação T9       \n",
       "3 EPTC      Empresa Publica de Transportes e Circulação TR60     \n",
       "4 EPTC      Empresa Publica de Transportes e Circulação TR62     \n",
       "5 TRENS     TRENSURB                                    LINHA1   \n",
       "6 TRENS     TRENSURB                                    LINHAAERO\n",
       "  route_short_name route_long_name                           mode route_fare\n",
       "1 T8               CAMPUS  /  FARRAPOS                       BUS  4.8       \n",
       "2 T9               PUC                                       BUS  4.8       \n",
       "3 TR60             TRONCAL TRI‘NGULO                         BUS  4.8       \n",
       "4 TR62             TRONCAL BALTAZAR                          BUS  4.8       \n",
       "5 LINHA1           ESTACAO MERCADO ATE ESTACAO NOVO HAMBURGO RAIL 4.8       \n",
       "6 AREO             AEROMOVEL TRENSURB                        RAIL 4.8       \n",
       "  fare_type\n",
       "1 BUS      \n",
       "2 BUS      \n",
       "3 BUS      \n",
       "4 BUS      \n",
       "5 RAIL     \n",
       "6 RAIL     "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tail(fare_structure$fares_per_route)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e9b21079",
   "metadata": {},
   "source": [
    "Basic route information is taken directly from the GTFS data (agency, route id \n",
    "and names, mode, etc), but the `route_fare` and `fare_type` columns were added \n",
    "specifically for the `r5r` fare structure.\n",
    "\n",
    "-   `route_fare`: is used to set a specific fare for each route. This field can \n",
    "be used to represent services that have many unique fares, such as metropolitan \n",
    "/ suburban trains and buses. This is used together with the `use_route_fare` \n",
    "column in the `fares_per_type` table: the `route_fare` field is only considered \n",
    "by the `r5r` fare structure when `use_route_fare` of that mode is set to `TRUE`.\n",
    "\n",
    "-   `fare_type`: is used to link each route with information in the `fares_per_type` \n",
    "and `fares_per_transfer` tables. In this example, `fare_type` is always the same \n",
    "as `mode`, because that was what we chose in the `by` parameter when calling `setup_fare_structure` earlier (we could have chosen to discriminate fares by \n",
    "agency, for example).\n",
    "\n",
    "We actually don't have any change do to in the `fares_per_route` table, in this \n",
    "example. It does not matter that the `route_fare` value is wrong for the \"RAIL\" \n",
    "lines, because we are using the fares set in `fares_per_type` and `fares_per_transfer` \n",
    "which we already set up correctly before.\n",
    "Now that our `fare_structure` is complete, we can use it to calculate travel time \n",
    "matrices and accessibility while accounting for monetary cost cutoffs. Let's see \n",
    "how it's done in the next sections.\n",
    "\n",
    "## 4. Calculating travel time and accessibiilty accounting for monetary costs\n",
    "The `travel_time_matrix()` and `accessibility()` functions have two new parameters \n",
    "to account for monetary costs thresholds:\n",
    "-   `fare_structure`: the settings object that we've been working on.\n",
    "-   `max_fare`: the maximum total fare that can be used in the trip.\n",
    "\n",
    "### 4.1 Travel time with monetary cost\n",
    "\n",
    "The following example shows travel time differences when monetary costs are \n",
    "accounted for, using the `travel_time_matrix()` function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "76310e04",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Loading required namespace: testthat\n",
      "\n"
     ]
    }
   ],
   "source": [
    "## load input data\n",
    "points <- read.csv(system.file(\"extdata/poa/poa_hexgrid.csv\", package = \"r5r\"))\n",
    "\n",
    "# calculate travel times function\n",
    "calculate_travel_times <- function(fare) {\n",
    "\n",
    "  ttm_df <- travel_time_matrix(r5r_core,\n",
    "                               origins = points,\n",
    "                               destinations = points,\n",
    "                               departure_datetime = as.POSIXct(\"13-05-2019 14:00:00\",\n",
    "                                                               format = \"%d-%m-%Y %H:%M:%S\"),\n",
    "                               mode = c(\"WALK\", \"TRANSIT\"),\n",
    "                               fare_structure = fare_structure,\n",
    "                               max_fare = fare,\n",
    "                               max_trip_duration = 45,\n",
    "                               max_walk_time = 30)\n",
    "\n",
    "  return(ttm_df)\n",
    "}\n",
    "\n",
    "\n",
    "# calculate travel times, and combine results\n",
    "ttm <- calculate_travel_times(fare = Inf)\n",
    "ttm_500 <- calculate_travel_times(fare = 5)\n",
    "\n",
    "# merge results\n",
    "ttm[ttm_500, on = .(from_id, to_id), travel_time_500 := i.travel_time_p50]\n",
    "ttm[, travel_time_unl := travel_time_p50]\n",
    "ttm[, travel_time_p50 := NULL]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dd6af560",
   "metadata": {},
   "source": [
    "Below, we can see a sample of the travel time differences with and without monetary \n",
    "cost restriction. We can see that some trips are not affected at all (`travel_time_unl == travel_time_500`), some trips take a little longer to complete (`travel_time_500 > travel_time_unl`), and other trips cannot be completed at all (`travel_time_500 == NA`).\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "55091023",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.table: 10 × 4</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>from_id</th><th scope=col>to_id</th><th scope=col>travel_time_500</th><th scope=col>travel_time_unl</th></tr>\n",
       "\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>89a90166da7ffff</td><td>89a90129c2bffff</td><td>38</td><td>36</td></tr>\n",
       "\t<tr><td>89a90166da7ffff</td><td>89a90129aa7ffff</td><td>33</td><td>30</td></tr>\n",
       "\t<tr><td>89a90166da7ffff</td><td>89a90e93497ffff</td><td>32</td><td>32</td></tr>\n",
       "\t<tr><td>89a90166da7ffff</td><td>89a90129807ffff</td><td>39</td><td>38</td></tr>\n",
       "\t<tr><td>89a90166da7ffff</td><td>89a90129b5bffff</td><td>34</td><td>34</td></tr>\n",
       "\t<tr><td>89a90166da7ffff</td><td>89a90129dd7ffff</td><td>37</td><td>37</td></tr>\n",
       "\t<tr><td>89a90166da7ffff</td><td>89a90129bbbffff</td><td>33</td><td>33</td></tr>\n",
       "\t<tr><td>89a90166da7ffff</td><td>89a90129bd7ffff</td><td>26</td><td>26</td></tr>\n",
       "\t<tr><td>89a90166da7ffff</td><td>89a90129a47ffff</td><td>19</td><td>19</td></tr>\n",
       "\t<tr><td>89a90166da7ffff</td><td>89a90166da7ffff</td><td> 0</td><td> 0</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.table: 10 × 4\n",
       "\\begin{tabular}{llll}\n",
       " from\\_id & to\\_id & travel\\_time\\_500 & travel\\_time\\_unl\\\\\n",
       " <chr> & <chr> & <int> & <int>\\\\\n",
       "\\hline\n",
       "\t 89a90166da7ffff & 89a90129c2bffff & 38 & 36\\\\\n",
       "\t 89a90166da7ffff & 89a90129aa7ffff & 33 & 30\\\\\n",
       "\t 89a90166da7ffff & 89a90e93497ffff & 32 & 32\\\\\n",
       "\t 89a90166da7ffff & 89a90129807ffff & 39 & 38\\\\\n",
       "\t 89a90166da7ffff & 89a90129b5bffff & 34 & 34\\\\\n",
       "\t 89a90166da7ffff & 89a90129dd7ffff & 37 & 37\\\\\n",
       "\t 89a90166da7ffff & 89a90129bbbffff & 33 & 33\\\\\n",
       "\t 89a90166da7ffff & 89a90129bd7ffff & 26 & 26\\\\\n",
       "\t 89a90166da7ffff & 89a90129a47ffff & 19 & 19\\\\\n",
       "\t 89a90166da7ffff & 89a90166da7ffff &  0 &  0\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.table: 10 × 4\n",
       "\n",
       "| from_id &lt;chr&gt; | to_id &lt;chr&gt; | travel_time_500 &lt;int&gt; | travel_time_unl &lt;int&gt; |\n",
       "|---|---|---|---|\n",
       "| 89a90166da7ffff | 89a90129c2bffff | 38 | 36 |\n",
       "| 89a90166da7ffff | 89a90129aa7ffff | 33 | 30 |\n",
       "| 89a90166da7ffff | 89a90e93497ffff | 32 | 32 |\n",
       "| 89a90166da7ffff | 89a90129807ffff | 39 | 38 |\n",
       "| 89a90166da7ffff | 89a90129b5bffff | 34 | 34 |\n",
       "| 89a90166da7ffff | 89a90129dd7ffff | 37 | 37 |\n",
       "| 89a90166da7ffff | 89a90129bbbffff | 33 | 33 |\n",
       "| 89a90166da7ffff | 89a90129bd7ffff | 26 | 26 |\n",
       "| 89a90166da7ffff | 89a90129a47ffff | 19 | 19 |\n",
       "| 89a90166da7ffff | 89a90166da7ffff |  0 |  0 |\n",
       "\n"
      ],
      "text/plain": [
       "   from_id         to_id           travel_time_500 travel_time_unl\n",
       "1  89a90166da7ffff 89a90129c2bffff 38              36             \n",
       "2  89a90166da7ffff 89a90129aa7ffff 33              30             \n",
       "3  89a90166da7ffff 89a90e93497ffff 32              32             \n",
       "4  89a90166da7ffff 89a90129807ffff 39              38             \n",
       "5  89a90166da7ffff 89a90129b5bffff 34              34             \n",
       "6  89a90166da7ffff 89a90129dd7ffff 37              37             \n",
       "7  89a90166da7ffff 89a90129bbbffff 33              33             \n",
       "8  89a90166da7ffff 89a90129bd7ffff 26              26             \n",
       "9  89a90166da7ffff 89a90129a47ffff 19              19             \n",
       "10 89a90166da7ffff 89a90166da7ffff  0               0             "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tail(ttm, 10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2f3d4522",
   "metadata": {},
   "source": [
    "The plots below show the overall distribution of the travel time differences and \n",
    "unreachable destinations:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "a2f317ea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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AR5eXm6WDMR6Wi12dnZulgzN4ywjo5kExMTTcZNZFm2xO8KDDvY4QoyADB02dc3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GnkoyWUD0qk7+OvEI7TN9+ebt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\nVF3NoDWd7MXjve1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ZyNnRWrV7LqDqPv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\nAABoxP8B+J45/d9JzNsAAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot of overall travel time differences between limited and unlimited cost travel time matrices \n",
    "time_difference = ttm[!is.na(travel_time_500), .(count = .N), \n",
    "                      by = .(travel_time_unl, travel_time_500)]\n",
    "\n",
    "p1 <- ggplot(time_difference, aes(y = travel_time_unl, x = travel_time_500)) +\n",
    "  geom_point(size = 0.7) +\n",
    "  coord_fixed() +\n",
    "  scale_x_continuous(breaks = seq(0, 45, 5)) +\n",
    "  scale_y_continuous(breaks = seq(0, 45, 5)) +\n",
    "  theme_light() +\n",
    "  theme(legend.position = \"none\") +\n",
    "  labs(y = \"travel time (minutes)\\nunestricted monetary cost\",\n",
    "       x = \"travel time (minutes)\\nmonetary cost restricted to BRL 5.00\"\n",
    "       )\n",
    "\n",
    "# plot of unreachable destinations when the monetary cost limit is too low\n",
    "unreachable <- ttm[, .(count = .N), by = .(travel_time_unl, is.na(travel_time_500))]\n",
    "unreachable[, perc := count / sum(count, na.rm = T), by = .(travel_time_unl)]\n",
    "unreachable <- unreachable[is.na == TRUE]\n",
    "unreachable <- na.omit(unreachable)\n",
    "\n",
    "p2 <- ggplot(unreachable, aes(x=travel_time_unl, y=perc)) +\n",
    "  geom_col() +\n",
    "  coord_flip() +\n",
    "  scale_x_continuous(breaks = seq(0, 45, 5)) +\n",
    "  scale_y_continuous(limits = c(0, 1), breaks = seq(0, 1, 0.2), \n",
    "                     labels = paste0(seq(0, 100, 20), \"%\")) +\n",
    "  theme_light() +\n",
    "  labs(x = \"travel time (minutes)\\nwithout monetary cost restriction\",\n",
    "       y = \"% of unreachable destinations\\nconsidering a R$ 5.00 monetary cost limit\")\n",
    "\n",
    "# combine both plots using patchwork\n",
    "p1 + p2 + plot_annotation(subtitle = \"Comparing travel times with and without monetary cost restriction\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "55214556",
   "metadata": {},
   "source": [
    "### 4.2 Calculating accessibility with monetary cost\n",
    "\n",
    "Now, we can answer questions like \"how many health care facilities one can access \n",
    "in 60 minutes using public transport, on a R\\$5.00 budget?\". We'll do that below, \n",
    "and compare the results the accessibility unconstrained by monetary costs: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "3de24a52",
   "metadata": {},
   "outputs": [],
   "source": [
    "# calculate accessibility function\n",
    "calculate_accessibility <- function(fare, fare_string) {\n",
    "  access_df <- accessibility(r5r_core,\n",
    "                             origins = points,\n",
    "                             destinations = points,\n",
    "                             departure_datetime = as.POSIXct(\"13-05-2019 14:00:00\",\n",
    "                                                             format = \"%d-%m-%Y %H:%M:%S\"),\n",
    "                             opportunities_colname = \"healthcare\",\n",
    "                             mode = c(\"WALK\", \"TRANSIT\"),\n",
    "                             cutoffs = c(60),\n",
    "                             fare_structure = fare_structure,\n",
    "                             max_fare = fare,\n",
    "                             max_trip_duration = 45,\n",
    "                             max_walk_time = 30,\n",
    "                             progress = FALSE)\n",
    "  access_df$max_fare <- fare_string\n",
    "  return(access_df)\n",
    "}\n",
    "# calculate accessibility, combine results, and convert to SF\n",
    "access_500 <- calculate_accessibility(fare=5, fare_string=\"R$ 5.00 budget\")\n",
    "access_unl <- calculate_accessibility(fare=Inf, fare_string=\"Unlimited budget\")\n",
    "access <- rbind(access_500, access_unl)\n",
    "# bring geometry\n",
    "access$geometry <- h3jsr::cell_to_polygon(access$id)\n",
    "access <- st_as_sf(access)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a9954f6c",
   "metadata": {},
   "source": [
    "Finally, we can plot the results and see how accessibility levels can differ \n",
    "quite substantially when we account for monetary costs. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "6ba88c46",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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QAAAIBHINgBAAAAeASCHQAAAIBHINgBAAAAeASCHQAAAIBHBGq9AwDg1q0rrjt9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\nXFKdkx4Nrol62/JcRcewFoIBI1vlqGovevx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S+s9r/Xd3vdgvIeW6pYWhNnGy84N7ho7623r/3U2PniPN7vhSa704u6ZnxPvR9c9h25h1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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot accessibility maps\n",
    "ggplot(data = access) +\n",
    "  geom_sf(aes(fill = accessibility), color=NA, size = 0.2) +\n",
    "  scale_fill_distiller(palette = \"Spectral\") +\n",
    "  facet_wrap(~max_fare) +\n",
    "  labs(subtitle = \"Effect of monetary cost on accessibility\") +\n",
    "  theme_minimal() +\n",
    "  theme(legend.position = \"bottom\",\n",
    "        axis.text = element_blank())\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2a58ad1c",
   "metadata": {},
   "source": [
    "If you have any suggestions or want to report an error, please visit [the package GitHub page](https://github.com/ipeaGIT/r5r)."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "R",
   "language": "R",
   "name": "ir"
  },
  "language_info": {
   "codemirror_mode": "r",
   "file_extension": ".r",
   "mimetype": "text/x-r-source",
   "name": "R",
   "pygments_lexer": "r",
   "version": "4.2.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}