106 lines
3.1 KiB
JavaScript

import assert from 'assert'
import approx from '../../../../../tools/approx'
import math from '../../../../../src/bundleAny'
import { csPermute } from '../../../../../src/function/algebra/sparse/csPermute'
import { createCsLu } from '../../../../../src/function/algebra/sparse/csLu'
import { createCsSqr } from '../../../../../src/function/algebra/sparse/csSqr'
const { abs, add, divideScalar, multiply, subtract, larger, largerEq, transpose, SparseMatrix } = math
const csLu = createCsLu({ abs, divideScalar, multiply, subtract, larger, largerEq, SparseMatrix })
const csSqr = createCsSqr({ add, multiply, transpose })
describe('csLu', function () {
it('should decompose matrix, 2 x 2, no symbolic ordering and analysis, partial pivoting', function () {
const m = math.sparse([[2, 1], [1, 4]])
// partial pivoting
const r = csLu(m, null, 1)
// L
assert.deepStrictEqual(r.L.valueOf(), [[1, 0], [0.5, 1]])
// U
assert.deepStrictEqual(r.U.valueOf(), [[2, 1], [0, 3.5]])
// P
assert.deepStrictEqual(r.pinv, [0, 1])
// verify
approx.deepEqual(csPermute(m, r.pinv, null, true), math.multiply(r.L, r.U))
})
it('should decompose matrix, 4 x 4, natural ordering (order=0), partial pivoting', function () {
const 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]
])
// symbolic ordering and analysis, order = 0
const s = csSqr(0, m, false)
// partial pivoting
const r = csLu(m, s, 1)
// verify
approx.deepEqual(csPermute(m, r.pinv, s.q, true).valueOf(), math.multiply(r.L, r.U).valueOf())
})
it('should decompose matrix, 4 x 4, amd(A+A\') (order=1), partial pivoting', function () {
const 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]
])
// symbolic ordering and analysis, order = 1
const s = csSqr(1, m, false)
// partial pivoting
const r = csLu(m, s, 1)
// verify
approx.deepEqual(csPermute(m, r.pinv, s.q, true).valueOf(), math.multiply(r.L, r.U).valueOf())
})
it('should decompose matrix, 4 x 4, amd(A\'*A) (order=2), partial pivoting', function () {
const 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]
])
// symbolic ordering and analysis, order = 2
const s = csSqr(2, m, false)
// partial pivoting
const r = csLu(m, s, 1)
// verify
approx.deepEqual(csPermute(m, r.pinv, s.q, true).valueOf(), math.multiply(r.L, r.U).valueOf())
})
it('should decompose matrix, 4 x 4, amd(A\'*A) (order=3), partial pivoting', function () {
const 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]
])
// symbolic ordering and analysis, order = 3
const s = csSqr(3, m, false)
// partial pivoting
const r = csLu(m, s, 1)
// verify
approx.deepEqual(csPermute(m, r.pinv, s.q, true).valueOf(), math.multiply(r.L, r.U).valueOf())
})
})