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

@inb/oeb-chart-scatter

v1.1.4

Published

benchmarkingChart_scatter

Downloads

121

Readme

OpenEBench Scientific Benchmarking visualizer

Repository that contains the code required to visualize results from scientific benchmarking experiments in plot format, and apply several classification methods in order to transform them to tabular format.

NPM Package

NPM Package @inb/oeb-chart-scatter published to: https://www.npmjs.com/package/@inb/oeb-chart-scatter

Data Input

The visualizer uses as input the results of one challenge stored in the OpenEBench database in the format of the official Benchmarking Data Model.

Per default it consumes the OpenEBench Sci-API (deprecated).

It is also able to consume the new API OpenEBench API Scientific. The API can be set by supplying the following attribute: data-api-url="{{ API_URL }}"

Branches

  • master: Python visualizer scripts
  • js: JavaScript visualizer project

Classification methods

  • Square quartiles - divide the plotting area in four squares by getting the 2nd quartile of the X and Y metrics. squares
  • Diagonal quartiles - divide the plotting area with diagonal lines by assigning a score to each participant based in the distance to the 'optimal performance'. diagonals
  • Clustering - group the participants using the K-means clustering algorithm and sort the clusters according to the performance. clusters

How to use

The component can be imported in two way: As npm package (preferred), or via the build file from the git repository (see bottom).

Use the npm package

npm i @inb/oeb-chart-scatter

In your frontend component: import { load_scatter_visualization } from "@inb/oeb-chart-scatter";

          <div
              data-id="{{ ID }}"
              class="benchmarkingChart_scatter"
              data-api-url="{{ API_URL }}"
              toTable="true"
          ></div>

You can then call the load_scatter_visualization() function.

Attributes that can be set on the <div> tag

  • data-id : the official OEB id of the aggregation dataset you want to visualize.
  • toTable: should be set to true/false depending whether you want to view the classification table in the right or not.
  • class: should always be 'benchmarkingChart_scatter'
  • data-api-url: Should always contain the full API URL e.g. https://openebench.bsc.es/api/scientific/graphql

Alternative way: Clone from repository

Requirements:

-npm -http server

Clone the repo to your document root :

git clone https://github.com/inab/OpenEBench_scientific_visualizer.git

Install dependencies from package.json :

npm install 

Export node moodules :

export PATH="${PWD}/node_modules/.bin/:$PATH"

Compile with webpack and visualize sample results in your localhost :

./node_modules/.bin/webpack-cli src/app.js --output=build/build.js -d -w

Add JS cdn for D3 and jquery and the build file which you can download from build/build.js and tag it into your html. You can then call the load_scatter_visualization() function.

The HTML file should look like this

Live Demo

See a demo of how this visualizer works here