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https://github.com/datasciencecampus/propeR

A repository for the R tool propeR, which analyses travel time and cost using an OTP graph (see datasciencecampus/graphite)
https://github.com/datasciencecampus/propeR

docker dsc-projects opentripplanner otp r transport travel

Last synced: about 2 months ago
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A repository for the R tool propeR, which analyses travel time and cost using an OTP graph (see datasciencecampus/graphite)

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README

        

# p r o p e R

**prope** [latin] _verb_
**Definitions:**
1. near, nearby;
2. almost;
3. close by

## Contents

* [Introduction](#introduction)
* [Software Prerequisites](#software-prerequisites)
* [Installing propeR](#installing-proper)
* [R installation](#r-installation)
* [Docker installation](#docker-installation)
* [Running propeR](#running-proper)
* [Data prerequisites](#data-prerequisites)
* [Using R](#using-rstudio)
* [Using Docker](#using-docker)
* [FAQ](#faq)
* [Acknowledgments](#acknowledgments)
* [Contributions and Bug Reports](#contributions-and-bug-reports)
* [Licence](#licence)

## Introduction

This R package ([propeR](https://github.com/datasciencecampus/proper)) was created to analyse multimodal transport for a number of research projects at the [Data Science Campus, Office for National Statistics](https://datasciencecampus.ons.gov.uk/). This repository is for the installation and use of propeR only, for all OTP graph related guidance, please see [graphite](https://github.com/datasciencecampus/graphite).

## Software Prerequisites

* [R](https://www.r-project.org/) and your GUI of choice, such as [RStudio](https://www.rstudio.com/), OR
* [Docker](https://www.docker.com/)

## Installing propeR

### R installation

The easiest method is to install direct from this GitHub repository using:

```
library(devtools)
install_github("datasciencecampus/propeR/propeR")
```

Failing this, you can pull this repository and install locally using:

```
install("path/to/propeR/dir")
```

#### R building

If neither method above works. Or you wish to make changes to the package. Then you will need to build the package. Building propeR requires devtools and roxygen2:

```
# R
install.packages("devtools")
install.packages("roxygen2")
```

Then:

```
build("path/to/propeR/dir")
install("path/to/propeR/dir")
```

Once you have installed propeR using RStudio you can now [start using it in RStudio](#using-rstudio).

### Docker installation

For those who want to run propeR through Docker, we have created a Docker image. The propeR R package can be built from the parent directory as follows:

```
cd path/to/propeR/dir
docker build . --tag=dsc_proper
```

Or you can build from the [online docker image](https://hub.docker.com/u/datasciencecampus), using:

```
docker run datasciencecampus/dsc_proper:1.0
```

See [Dockerfile](Dockerfile) for more information and dependencies. Once you have installed propeR using Docker you can now [start using it in Docker](#using-docker).

## Running propeR

Function examples are [available in this example.md file](https://github.com/datasciencecampus/proper/tree/develop/example.md).

### Data prerequisites

All location data (origin and destination) must be in comma separated (CSV) format and contain the following columns:
* A unique ID column
* A latitude column, where data is in decimal degrees (or a postcode column)
* A longitude column, where data is in decimal degrees (or a postcode column)

The CSV file must contain headers, the header names can be specified in **`importLocationData()`**.

### Using RStudio

As with any R package, it can be loaded in an R session using:

```
#R
library(propeR)
```

Then you can use the functions, such as:

```
#R
pointToPoint(
output.dir="path/to/output/dir",
originPoints=originPointsdf,
destinationPoints=destinationPointsdf,
startDateAndTime="2019-08-02 12:00:00"
)
```

Outputs will be saved to `path/to/output/dir`.

### Using Docker

Alternatively. If you have installed propeR using Docker you can use Docker to run propeR. Put source and destination `.csv` data in a directory, e.g., `/tmp/data/`. Example data files `origin.csv` and `destination.csv` can be found in `propeR/inst/extdata/`, then:

```
docker run -v path/to/output/dir:/mnt datasciencecampus/dsc_proper:1.0 'otp.host="XXX.XXX.X.X", fun="pointToPoint", src_file="/mnt/origin.csv", dst_file="/mnt/destination.csv", output.dir="/mnt", startDateAndTime="2019-08-02 12:00:00"'
```

where `otp.host` is your inet address, which can be found using:

```
/sbin/ifconfig |grep inet |awk '{print $2}'

```

Output data will be in `path/to/output/dir`.

## FAQ

Q: How accurate is the cost calculation in the point to point functions?

>A: The tool currently cannot ingest fare information. Therefore `costEstimate` can be used in the point to point functions. This provides an *estimate* based on the values given in the parameters `busTicketPrice`, `busTicketPriceMax`, `trainTicketPriceKm` and `trainTicketPriceMin`.

Q: How to I stop propeR printing to the R console:

>A: All functions have a parameter called `infoPrint`. This by default is set to `T`, please set to `F` if you want to prevent console printing.

Q: I found a bug!

>A: Please use the [GitHub issues](https://github.com/datasciencecampus/proper/issues) form to provide us with the information.

### Common errors

Q: Why am I receiving the following error when running propeR?

```
Error in curl::curl_fetch_memory(url, handle = handle) :
Failed to connect to localhost port 8080: Connection refused
Called from: curl::curl_fetch_memory(url, handle = handle)
```

> A: The OTP server has not been initiated. Please see [graphite](https://github.com/datasciencecampus/graphite) of this guide.

Q: Why am I receiving the following error when running propeR?

```
Error in paste0(otpcon, "/plan") : object 'otpcon' not found
```

> A: The OTP connection has not been established. Please see [graphite](https://github.com/datasciencecampus/graphite) of this guide.

## Acknowledgments

* [TransXChange2GTFS](https://github.com/danbillingsley/TransXChange2GTFS)
* [transxchange2gtfs](https://github.com/planarnetwork/transxchange2gtfs)
* [dtd2mysql](https://github.com/open-track/dtd2mysql)
* [OpenTripPlanner](http://www.opentripplanner.org/)
* functions `otpConnect()`, `otpTripTime()`, `otpTripDistance()`, `otpIsochrone()` are modified from Marcus Young's repo [here](https://github.com/marcusyoung/opentripplanner/blob/master/Rscripts/otp-api-fn.R). Permission to use Marcus Young's code can be found here: https://github.com/marcusyoung/opentripplanner/pull/15

## Authors / Contributors

#### Data Science Campus - Office for National Statistics
* [Michael Hodge](https://github.com/mshodge)
* [Phillip Stubbings](https://github.com/phil8192)
* [Ioannis Tsalamanis](https://github.com/IoannisTsalamanis)

## Contributions and Bug Reports

We welcome contributions and bug reports. Please do this on this repo and we will endeavour to review pull requests and fix bugs in a prompt manner.

Built and tested on OS and Windows using R version 3.5.2.

## Licence

The Open Government Licence (OGL) Version 3

Copyright (c) 2018 Office of National Statistics

This source code is licensed under the Open Government Licence v3.0. To view this licence, visit [www.nationalarchives.gov.uk/doc/open-government-licence/version/3](www.nationalarchives.gov.uk/doc/open-government-licence/version/3) or write to the Information Policy Team, The National Archives, Kew, Richmond, Surrey, TW9 4DU.