Rogelio J. Baucells 8fb42ee11b fix tests
2015-05-29 21:34:29 -04:00

199 lines
5.3 KiB
JavaScript

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