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it("should make test number 2", function () {
// import the modules
var la = require('qminer').la;
// create a random matrix
var A = new la.Matrix({ rows: 10, cols: 5, random: true });
// set the parameters for the calculation
var k = 2; // number of singular vectors
var param = { iter: 1000, tol: 1e-4 };
// calculate the svd
la.svd(A, k, param, function (err, result) {
if (err) { console.log(err); }
// successful calculation
var U = result.U;
var V = result.V;
var s = result.s;
});
});
});
require('qminer').la.Vector.prototype.print = function () { };require('qminer').la.SparseVector.prototype.print = function () { };require('qminer').la.SparseMatrix.prototype.print = function () { };require('qminer').la.Matrix.prototype.print = function () { };describe('example tests for the ladoc.js file', function () {
describe("Linear algebra module, number 1", function () {
it("should make test number 1", function () {
// import module, create a random matrix and a vector, multiply. find svd of the matrix
});
});
describe("Computes the truncated SVD decomposition, number 2", function () {
it("should make test number 2", function () {
// import the modules
var la = require('qminer').la;
// create a random matrix
var A = new la.Matrix({ rows: 10, cols: 5, random: true });
// set the parameters for the calculation
var k = 2; // number of singular vectors
it("should make test number 49", function () {
// import la module
var la = require('qminer').la;
// create a new sparse matrix
var mat = new la.SparseMatrix([[[0, 1], [1, 3]], [[0, 2], [1, 4]]]);
// get the frobenious norm of sparse matrix
var norm = mat.frob(); // returns sqrt(30)
});
});
require('qminer').la.Vector.prototype.print = function () { };require('qminer').la.SparseVector.prototype.print = function () { };require('qminer').la.SparseMatrix.prototype.print = function () { };require('qminer').la.Matrix.prototype.print = function () { };describe('example tests for the statdoc.js file', function () {
describe("Statistics module, number 1", function () {
it("should make test number 1", function () {
// TODO
});
});
});
it("should make test number 103", function () {
// import fs module
var fs = require('qminer').fs;
var la = require('qminer').la;
// create a new vector
var vec = new la.BoolVector([true, true, false]);
// open write stream
var fout = fs.openWrite('vec.dat');
// save vector and close write stream
vec.save(fout).close();
});
});
it("should make test number 17", function () {
// import modules
la = require('qminer').la;
analytics = require('qminer').analytics;
// create a new model with gamma = 1.0
var regmod = new analytics.RidgeReg({ gamma: 1.0 });
// generate a random feature matrix
var A = la.randn(10,100);
// generate a random model
var w = la.randn(10);
// generate noise
var n = la.randn(100).multiply(0.01);
// generate responses (model'*data + noise)
var b = A.transpose().multiply(w).plus(n);
// fit model
regmod.fit(A, b);
// compare
// true model
w.print();
/**
* Copyright (c) 2015, Jozef Stefan Institute, Quintelligence d.o.o. and contributors
* All rights reserved.
*
* This source code is licensed under the FreeBSD license found in the
* LICENSE file in the root directory of this source tree.
*/
var assert = require('../../src/nodejs/scripts/assert.js');
var analytics = require('qminer').analytics;
var la = require('qminer').la;
describe('RecursiveLinearRegression Tests', function () {
describe('Constructor Tests', function () {
it('should not throw an exception', function () {
assert.doesNotThrow(function () {
var linreg = new analytics.RecLinReg({ dim: 10, regFact: 1.0, forgetFact: 1.0 });
});
})
it('should create an object with mostly default params', function () {
var linreg = new analytics.RecLinReg({ dim: 10 });
var param = linreg.getParams();
assert.equal(param.dim, 10);
assert.equal(param.regFact, 1.0);
assert.equal(param.forgetFact, 1.0);
})
exports.Matrix.prototype.getRow = function (rowIdx) { return Object.create(require('qminer').la.Vector.prototype); }
/**
exports.mean = function (input) { return input instanceof Object.create(require('qminer').la.Vector) ? 0.0 : Object.create(require('qminer').la.Vector.prototype); }
/**
exports.SparseVector = function(arg, dim) { return Object.create(require('qminer').la.SparseVector.prototype); }
/**