Racing Data Converter

Converts time series data into popular motorsport Data Logger formats.

This library was developed at B'Energy Racing, a Formula SAE Electric Team from the Facens University Center.

Formats supported

Format	Extension	Software	Support
Pro Tune	.dlf	Pro Tune Analyzer	Writer
MegaSquirt ASCII	.msl	MegaLogViewer	Writer
MoTeC CSV	.csv	MoTeC i2	Writer
Pi ASCII	.txt	Cosworth Pi Toolbox	Writer
BOSCH Darab ASCII	.txt	Bosch WinDarab	Writer
RacePak ASCII	.txt	RacePak DataLink II	Writer
Excel CSV	.csv	Microsoft Excel	Writer
CSV	.csv, .tsv	-	Reader/Writer
B'Energy Meteor Log	.met	-	Reader/Writer
JSON (raw data frames)	.json	-	Reader/Writer

Command Line Interface

The CLI allows converting without writing a single line of code.

By default, it reads CSV files and outputs any format. The CSV file must have the first column as the timestamp in seconds. Columns can follow the format Name (unit) or Name (unit) [key].

Install

You need NodeJS (16+ is recommended) installed first.

npm install -g racing-data-converter

Usage

Type racing-data-converter --help for a list of options.

Example

racing-data-converter ./input.csv ./output.dlf --output-format protune

Application Programming Interface

1. Create an input stream. This can be a simple passthrough stream such as DataFrameStream or read from a CsvReader, MeteorReader or a JsonReader.
2. Define the list of channels that you will work with, including information such as the unit of measure.
3. Create a writer. This can be a CsvWriter, MeteorWriter, ExcelCsvWriter, MegaSquirtWriter, MotecCsvWriter, PiToolboxAsciiWriter, ProtuneWriter, RacePakWriter, WinDarabWriter or a JsonWriter.
4. Create a writer stream from the writer class, receiving the input stream created earlier.
5. The file is successfully converted!

Install

npm install racing-data-converter

Sample

import { DataFrameStream, ProtuneWriter, SensorChannel } from 'racing-data-converter';
import * as fs from 'node:fs';

// Creates a plain data frame stream. This will be the input
const dataFrameStream = new DataFrameStream();

// Creates a Protune writer with two channels
const writer = new ProtuneWriter({
  channels: [
    {
      key: SensorChannel.GPS_SPEED,
      name: 'Speed',
      unit: 'Km/h',
    },
    {
      key: 'happy-sensor',
      name: 'Happy Sensor',
      unit: 'm',
      decimalPlaces: 2,
    }
  ]
});

// Creates a Protune stream using the data frame stream as the input
const protuneStream = writer.createStream(dataFrameStream);

// Pipes the Protune stream into the output file
protuneStream.pipe(fs.createWriteStream('sample-output.dlf'));

// Writes a few data frames
dataFrameStream.write({
  channel: SensorChannel.GPS_SPEED,
  value: 53,
  timestamp: 10,
});

dataFrameStream.write({
  channel: 'happy-sensor',
  value: 3925,
  timestamp: 15,
});

dataFrameStream.write({
  channel: SensorChannel.GPS_SPEED,
  value: 59,
  timestamp: 20,
});

// Finishes writing
dataFrameStream.end();

There are more samples available.