transitr

KO | EN

gitlite — search

#python #react #typescript #llm #android #rust #deep-learning #docker #windows #cli #vue #awesome-list #pytorch #ios

(★ 23)

An R package for constructing and modelling a transit network in real time to obtain vehicle ETAs

transitr 최신버젼 다운로드

최종 버전 다운로드 (.zip)

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# transitr

[![Travis build status](https://travis-ci.org/tmelliott/transitr.svg?branch=develop)](https://travis-ci.org/tmelliott/transitr)
[![codecov](https://codecov.io/gh/tmelliott/transitr/branch/develop/graph/badge.svg)](https://codecov.io/gh/tmelliott/transitr)

The goals of `transitr` are to make it easy to __load GTFS data__ into a database,
construct a __transit network__ of roads and intersections,
and __model vehicles in real-time__ from an API feed to update the network
and __generate ETAs__.

# install

`transitr` is not (yet) on CRAN, so for you would need to use `devtools`:
```r
devtools::install_github('tmelliott/transitr')
```

# usage

__Still under development!__
This here is just for demonstration of what it could be like at some point
in the future.

```r
library(transitr)
library(magrittr)

## Create a database, construct network, and connect to a realtime feed
dbname <- "realtime.db"
nw <- create_gtfs("https://cdn01.at.govt.nz/data/gtfs.zip", db = dbname) %>%
    construct() %>%
    realtime_feed("https://api.at.govt.nz/v2/public/realtime/vehiclelocations",
                  with_headers("Ocp-Apim-Subscription-Key" = "mykey"),
                  response = "protobuf")

## Set the parameters and then run the model
nw %>% 
    set_parameters(n_core = 2, 
                   n_particles = 500, 
                   gps_error = 5) %>%
    model()
```

Once running, you can launch a new R session and view the shiny app:
```r
transitr::view_realtime("realtime.db")
```

# mock data server

In order to facilitate model development and checking, there's also a mock data server
in the `simulations` directory.

To install:
```bash
cd simulations
yarn

## or if you don't use yarn
npm install
```

To start the server, you need first an archive of vehicle position feeds,
```bash
ls archive | grep vehicle | head -n 5
# vehicle_locations_20180911050001.pb
# vehicle_locations_20180911050031.pb
# vehicle_locations_20180911050102.pb
# vehicle_locations_20180911050132.pb
# vehicle_locations_20180911050201.pb

yarn start
# yarn run v1.9.4
# $ node mock_server.js
# Mock GTFS server running on port 3000!
```

Now you can run the model with the local server, which will automatically serve 
the next file with each request.
```r
## assumeing you've constructed with simulation flag:
## $ make FLAGS="-DSIMULATION"
## simulation history will be saved in a `history` directory
dir.create("history")

## set some process ID for the server to recognise (allows running multiple simulations simultaneously)
pid <- "test1"
nw <- load_gtfs("fulldata.db") %>%
    realtime_feed(sprintf("http://localhost:3000/%s/vehicle_positions", pid),
                  response = "protobuf") %>%
    set_parameters(n_core = 1,
                   n_particles = 2000,
                   gps_error = 10)

nw %>% model()
```

transitr

transitr 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

transitr

transitr 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

Download README