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/* xlsx.js (C) 2013-present SheetJS -- http://sheetjs.com *//* eslint-env node */var XLSX = require('xlsx');var tf = require('@tensorflow/tfjs');var linest = require('./linest');
/* generate linreg.xlsx with 100 random points */var N = 100;linest.generate_random_file(N);
/* get the first worksheet as an array of arrays, skip the first row */var wb = XLSX.readFile('linreg.xlsx');var ws = wb.Sheets[wb.SheetNames[0]];var aoa = XLSX.utils.sheet_to_json(ws, {header:1, raw:true}).slice(1);
/* calculate the coefficients in JS */(function(aoa) {	var x_ = 0, y_ = 0, xx = 0, xy = 0, n = aoa.length;	for(var i = 0; i < n; ++i) {		x_ += aoa[i][0] / n;		y_ += aoa[i][1] / n;		xx += aoa[i][0] * aoa[i][0];		xy += aoa[i][0] * aoa[i][1];	}	var m = Math.fround((xy - n * x_ * y_)/(xx - n * x_ * x_));	console.log(m, Math.fround(y_ - m * x_), "JS Post");})(aoa);
/* build X and Y vectors */var tensor = tf.tensor2d(aoa).transpose();console.log(tensor.shape);var xs = tensor.slice([0,0], [1,tensor.shape[1]]).flatten();var ys = tensor.slice([1,0], [1,tensor.shape[1]]).flatten();
/* set up variables with initial guess */var x_ = xs.mean().dataSync()[0];var y_ = ys.mean().dataSync()[0];var a = tf.variable(tf.scalar(y_/x_));var b = tf.variable(tf.scalar(Math.random()));
/* linear predictor */function predict(x) { return tf.tidy(function() { return a.mul(x).add(b); }); }/* mean square scoring */function loss(yh, y) { return yh.sub(y).square().mean(); }
/* train */for(var j = 0; j < 5; ++j) {	var learning_rate = 0.0001 /(j+1), iterations = 1000;	var optimizer = tf.train.sgd(learning_rate);
	for(var i = 0; i < iterations; ++i) optimizer.minimize(function() {		var pred = predict(xs);		var L = loss(pred, ys);		return L	});
	/* compute the coefficient */	var m = a.dataSync()[0], b_ = b.dataSync()[0];	console.log(m, b_, "TF " + iterations * (j+1));}
/* export data to aoa */var yh = predict(xs);var tfdata = tf.stack([xs, ys, yh]).transpose();var shape = tfdata.shape;var tfarr = tfdata.dataSync();var tfaoa = [];for(j = 0; j < shape[0]; ++j) {	tfaoa[j] = [];	for(i = 0; i < shape[1]; ++i) tfaoa[j][i] = tfarr[j * shape[1] + i];}
/* add headers and export */tfaoa.unshift(["x", "y", "pred"]);var new_ws = XLSX.utils.aoa_to_sheet(tfaoa);var new_wb = XLSX.utils.book_new();XLSX.utils.book_append_sheet(new_wb, new_ws, "Sheet1");XLSX.writeFile(new_wb, "tfjs.xls");