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199 lines
5.3 KiB
JavaScript
199 lines
5.3 KiB
JavaScript
var approx = require('../../../../tools/approx'),
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math = require('../../../../index'),
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market = require('../../../../tools/matrixmarket');
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describe('slu', function () {
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it('should decompose matrix, 4 x 4, natural ordering (order=0), partial pivoting', function () {
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var m = math.sparse(
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[
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[4.5, 0, 3.2, 0],
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[3.1, 2.9, 0, 0.9],
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[0, 1.7, 3, 0],
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[3.5, 0.4, 0, 1]
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]);
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// partial pivoting
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var r = math.slu(m, 0, 1);
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// verify M[p,q]=L*U
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approx.deepEqual(_permute(m, r.p, r.q).valueOf(), math.multiply(r.L, r.U).valueOf());
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});
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it('should decompose matrix, 4 x 4, amd(A+A\') (order=1)', function () {
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var m = math.sparse(
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[
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[4.5, 0, 3.2, 0],
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[3.1, 2.9, 0, 0.9],
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[0, 1.7, 3, 0],
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[3.5, 0.4, 0, 1]
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]);
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// partial pivoting
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var r = math.slu(m, 1, 1);
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// verify M[p,q]=L*U
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approx.deepEqual(_permute(m, r.p, r.q).valueOf(), math.multiply(r.L, r.U).valueOf());
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});
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it('should decompose matrix, 4 x 4, amd(A\'*A) (order=2), partial pivoting', function () {
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var m = math.sparse(
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[
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[4.5, 0, 3.2, 0],
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[3.1, 2.9, 0, 0.9],
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[0, 1.7, 3, 0],
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[3.5, 0.4, 0, 1]
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]);
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// partial pivoting
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var r = math.slu(m, 2, 1);
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// verify M[p,q]=L*U
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approx.deepEqual(_permute(m, r.p, r.q).valueOf(), math.multiply(r.L, r.U).valueOf());
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});
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it('should decompose matrix, 4 x 4, amd(A\'*A) (order=3), partial pivoting', function () {
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var m = math.sparse(
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[
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[4.5, 0, 3.2, 0],
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[3.1, 2.9, 0, 0.9],
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[0, 1.7, 3, 0],
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[3.5, 0.4, 0, 1]
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]);
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// partial pivoting
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var r = math.slu(m, 3, 1);
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// verify M[p,q]=L*U
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approx.deepEqual(_permute(m, r.p, r.q).valueOf(), math.multiply(r.L, r.U).valueOf());
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});
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it('should decompose matrix, 48 x 48, natural ordering (order=0), full pivoting, matrix market', function (done) {
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// import matrix
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market.import('tools/matrices/bcsstk01.tar.gz', ['bcsstk01/bcsstk01.mtx'])
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.then(function (matrices) {
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// matrix
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var m = matrices[0];
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// full pivoting
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var r = math.slu(m, 0, 0.001);
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// verify M[p,q]=L*U
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approx.deepEqual(_permute(m, r.p, r.q).valueOf(), math.multiply(r.L, r.U).valueOf());
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// indicate test has completed
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done();
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})
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.fail(function (error) {
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// indicate test has completed
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done(error);
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});
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});
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it('should decompose matrix, 48 x 48, amd(A+A\') (order=1), full pivoting, matrix market', function (done) {
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// import matrix
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market.import('tools/matrices/bcsstk01.tar.gz', ['bcsstk01/bcsstk01.mtx'])
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.then(function (matrices) {
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// matrix
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var m = matrices[0];
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// full pivoting
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var r = math.slu(m, 1, 0.001);
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// verify M[p,q]=L*U
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approx.deepEqual(_permute(m, r.p, r.q).valueOf(), math.multiply(r.L, r.U).valueOf());
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// indicate test has completed
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done();
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})
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.fail(function (error) {
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// indicate test has completed
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done(error);
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});
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});
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it('should decompose matrix, 48 x 48, amd(A\'*A) (order=2), full pivoting, matrix market', function (done) {
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// import matrix
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market.import('tools/matrices/bcsstk01.tar.gz', ['bcsstk01/bcsstk01.mtx'])
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.then(function (matrices) {
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// matrix
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var m = matrices[0];
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// full pivoting
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var r = math.slu(m, 2, 0.001);
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// verify M[p,q]=L*U
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approx.deepEqual(_permute(m, r.p, r.q).valueOf(), math.multiply(r.L, r.U).valueOf());
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// indicate test has completed
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done();
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})
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.fail(function (error) {
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// indicate test has completed
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done(error);
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});
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});
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it('should decompose matrix, 48 x 48, amd(A\'*A) (order=3), full pivoting, matrix market', function (done) {
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// import matrix
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market.import('tools/matrices/bcsstk01.tar.gz', ['bcsstk01/bcsstk01.mtx'])
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.then(function (matrices) {
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// matrix
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var m = matrices[0];
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// full pivoting
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var r = math.slu(m, 3, 0.001);
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// verify M[p,q]=L*U
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approx.deepEqual(_permute(m, r.p, r.q).valueOf(), math.multiply(r.L, r.U).valueOf());
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// indicate test has completed
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done();
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})
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.fail(function (error) {
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// indicate test has completed
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done(error);
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});
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});
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/**
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* C = A(p,q) where p is the row permutation vector and q the column permutation vector.
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*/
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var _permute = function (A, pinv, q) {
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// matrix arrays
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var values = A._values;
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var index = A._index;
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var ptr = A._ptr;
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var size = A._size;
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// columns
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var n = size[1];
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// c arrays
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var cvalues = [];
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var cindex = [];
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var cptr = [];
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// loop columns
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for (var k = 0 ; k < n ; k++) {
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cptr[k] = cindex.length;
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// column in C
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var j = q ? (q[k]) : k;
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// values in column j
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for (var t = ptr[j]; t < ptr[j + 1]; t++) {
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cvalues.push(values[t]);
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cindex.push(pinv ? (pinv[index[t]]) : index[t]);
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}
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}
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cptr[n] = cindex.length;
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// return matrix
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return new math.type.SparseMatrix({
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values: cvalues,
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index: cindex,
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ptr: cptr,
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size: size,
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datatype: A._datatype
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});
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};
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}); |