npm package discovery and stats viewer.

Discover Tips

  • General search

    [free text search, go nuts!]

  • Package details

    pkg:[package-name]

  • User packages

    @[username]

Sponsor

Optimize Toolset

I’ve always been into building performant and accessible sites, but lately I’ve been taking it extremely seriously. So much so that I’ve been building a tool to help me optimize and monitor the sites that I build to make sure that I’m making an attempt to offer the best experience to those who visit them. If you’re into performant, accessible and SEO friendly sites, you might like it too! You can check it out at Optimize Toolset.

About

Hi, 👋, I’m Ryan Hefner  and I built this site for me, and you! The goal of this site was to provide an easy way for me to check the stats on my npm packages, both for prioritizing issues and updates, and to give me a little kick in the pants to keep up on stuff.

As I was building it, I realized that I was actually using the tool to build the tool, and figured I might as well put this out there and hopefully others will find it to be a fast and useful way to search and browse npm packages as I have.

If you’re interested in other things I’m working on, follow me on Twitter or check out the open source projects I’ve been publishing on GitHub.

I am also working on a Twitter bot for this site to tweet the most popular, newest, random packages from npm. Please follow that account now and it will start sending out packages soon–ish.

Open Software & Tools

This site wouldn’t be possible without the immense generosity and tireless efforts from the people who make contributions to the world and share their work via open source initiatives. Thank you 🙏

© 2024 – Pkg Stats / Ryan Hefner

@eagle-io/timeseries

v1.0.6

Published

Time Series data construction, manipulation and serialisation

Downloads

22

Readme

Time Series

npm version npm

Time Series data construction, manipulation and serialisation.

Installation

Install for use in NodeJS

npm install @eagle-io/timeseries

Import or require module

// ESM import
import { TimeSeries, JtsDocument } from '@eagle-io/timeseries'

// CommonJS 
const { TimeSeries, JtsDocument } = require('@eagle-io/timeseries')

Usage

// Create Time Series
const timeseries = new TimeSeries({
    type: 'NUMBER',
    records: [
        {
            timestamp: new Date(),
            value: 10,
            quality: 192,
            annotation: 'example comment'
        },
        { 
            timestamp: new Date('2022-04-13T00:00:00.000Z'),
            value: 20
        }
    ]
})

// Add record(s)
timeseries.insert({ timestamp: new Date('2022-04-14T00:00:00.000Z'), value: 30 })

// Output in JSON Time Series document format
const jtsDocument = new JtsDocument({ series: [timeseries] })
jtsDocument.toJSON()

TimeSeries

TimeSeries is a class for constructing and manipulating a single dataset.

const timeseries = new TimeSeries({
    type: 'NUMBER',
    id: 'series_1',
    name: 'My Series',
    units: 'm/s',
    records: [
        {
            timestamp: new Date(),
            value: 1.23,
            quality: 0,
            annotation: 'example comment'
        }
    ]
})

Options

Optionally provide configuration used for certain output formats such as JTS Document.

  • type: data type of record value attribute. NUMBER | TEXT | TIME | COORDINATES
  • id: string or number to uniquely identify the series to use instead of the automatically assigned id.
  • name: string
  • units: string
  • records: array of data records

Alternatively set later:

timeseries.type = 'NUMBER'
timeseries.id = 'Series_1'
timeseries.name = 'My Series'
timeseries.units = 'm/s'

Record attributes

Records require a timestamp and at least one attribute: value, quality or annotation

  • timestamp: date object. Strings must be converted as required. e.g.new Date('2022-03-29T00:00:00.000Z')
  • value (optional): number, string, date, array, null
  • quality (optional): number (quality code) associated with value
  • annotation (optional): string description or comment related to the record

Methods

// Output as JSON
timeseries.toJSON()

// Insert single record
timeseries.insert({timestamp: new Date(), value: 30})

// Insert multiple records
timeseries.insert([{timestamp: new Date('2022-03-28T03:45:59.000Z'), value: 30}, {timestamp: new Date(), value: 40}])

// Sort records in ascending chronological order
timeseries.sort()

// Clone timeseries
const timeseriesCopy = timeseries.clone()

Properties

// Record count
timeseries.length

// First record
timeseries.first

// Last record
timeseries.last

// Array of timestamps
timeseries.timestamps // [Date, Date]

// Array of values
timeseries.values // [10, 20]

// Array of qualities
timeseries.qualities // [192]

// Array of annotations
timeseries.annotations // ['example comment']

JTS Document

JtsDocument is a class for outputting TimeSeries in JSON Time Series document format.

// Create a JTS Document from one or more timeseries
const jtsDocument = new JtsDocument({ series: [timeseries1, timeseries2] })
// Output series in JTS Document format
jtsDocument.toJSON()

Options

  • series: array of TimeSeries to include in JTS Document

Methods

// Output as formatted JSON
jtsDocument.toJSON()

// Output as stringified JSON
jtsDocument.toString()

// Add single series
jtsDocument.addSeries(timeseries1)

// Add multiple series
jtsDocument.addSeries([timeseries1, timeseries2])

// Get series by id
jtsDocument.getSeries('series_2') // timeseries2

// Clone document (also clones series)
jtsDocument.clone()

// Create a new jtsDocument from JSON
const jtsDocument = JtsDocument.from('{"docType": "jts", ...}')

Properties

// Get JTS specification version number
jtsDocument.version // 1

// Get array of timeseries
jtsDocument.series // [timeseries1, timeseries2]

License

MIT