StackGenVis: Alignment of Data, Algorithms, and Models for Stacking Ensemble Learning Using Performance Metrics
https://doi.org/10.1109/TVCG.2020.3030352
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83 lines
2.0 KiB
83 lines
2.0 KiB
var fs = require('fs');
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var browserify = require('browserify');
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var watchify = require('watchify');
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var prettySize = require('prettysize');
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var constants = require('./constants');
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var common = require('./common');
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var strictD3 = require('./strict_d3');
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/**
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* Make a plotly.js browserify bundle function watched by watchify.
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*
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* N.B. This module is meant for dev builds; the output bundle is placed
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* in plotly.js/build/
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* Use `npm run build` for dist builds.
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*
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* @param {function} onFirstBundleCallback executed when first bundle is completed
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*
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*/
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module.exports = function makeWatchifiedBundle(onFirstBundleCallback) {
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var b = browserify(constants.pathToPlotlyIndex, {
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debug: true,
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standalone: 'Plotly',
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transform: [strictD3],
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cache: {},
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packageCache: {},
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plugin: [watchify]
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});
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var firstBundle = true;
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if(firstBundle) {
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console.log([
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'***',
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'Building the first bundle, this should take ~10 seconds',
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'***\n'
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].join(' '));
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}
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b.on('update', bundle);
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formatBundleMsg(b, 'plotly.js');
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function bundle() {
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b.bundle(function(err) {
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if(err) console.error(JSON.stringify(String(err)));
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if(firstBundle) {
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onFirstBundleCallback();
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firstBundle = false;
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}
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})
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.pipe(
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fs.createWriteStream(constants.pathToPlotlyBuild)
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);
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}
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return bundle;
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};
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function formatBundleMsg(b, bundleName) {
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var msgParts = [
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bundleName, ':', '',
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'written', 'in', '', 'sec',
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'[', '', ']'
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];
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b.on('bytes', function(bytes) {
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msgParts[2] = prettySize(bytes, true);
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});
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b.on('time', function(time) {
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msgParts[5] = (time / 1000).toFixed(2);
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});
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b.on('log', function() {
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var formattedTime = common.formatTime(new Date());
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msgParts[msgParts.length - 2] = formattedTime;
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console.log(msgParts.join(' '));
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});
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}
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