forked from kscience/kmath
complete qr + test qr and lu
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@ -118,7 +118,8 @@ public class DoubleLinearOpsTensorAlgebra :
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//todo checks
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//todo checks
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checkSquareMatrix(luTensor.shape)
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checkSquareMatrix(luTensor.shape)
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check(
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check(
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luTensor.shape.dropLast(1).toIntArray() contentEquals pivotsTensor.shape
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luTensor.shape.dropLast(2).toIntArray() contentEquals pivotsTensor.shape.dropLast(1).toIntArray() ||
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luTensor.shape.last() == pivotsTensor.shape.last() - 1
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) { "Bed shapes ((" } //todo rewrite
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) { "Bed shapes ((" } //todo rewrite
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val n = luTensor.shape.last()
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val n = luTensor.shape.last()
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@ -173,16 +174,56 @@ public class DoubleLinearOpsTensorAlgebra :
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return lTensor
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return lTensor
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}
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}
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private fun matrixQR(
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private fun MutableStructure1D<Double>.dot(other: MutableStructure1D<Double>): Double {
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matrix: Structure2D<Double>,
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var res = 0.0
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for (i in 0 until size) {
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res += this[i] * other[i]
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}
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return res
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}
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private fun MutableStructure1D<Double>.l2Norm(): Double {
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var squareSum = 0.0
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for (i in 0 until size) {
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squareSum += this[i] * this[i]
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}
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return sqrt(squareSum)
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}
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fun qrHelper(
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matrix: MutableStructure2D<Double>,
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q: MutableStructure2D<Double>,
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q: MutableStructure2D<Double>,
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r: MutableStructure2D<Double>
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r: MutableStructure2D<Double>
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) {
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) {
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//todo check square
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val n = matrix.colNum
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for (j in 0 until n) {
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val v = matrix.columns[j]
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if (j > 0) {
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for (i in 0 until j) {
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r[i, j] = q.columns[i].dot(matrix.columns[j])
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for (k in 0 until n) {
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v[k] = v[k] - r[i, j] * q.columns[i][k]
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}
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}
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}
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r[j, j] = v.l2Norm()
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for (i in 0 until n) {
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q[i, j] = v[i] / r[j, j]
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}
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}
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}
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}
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override fun DoubleTensor.qr(): Pair<DoubleTensor, DoubleTensor> {
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override fun DoubleTensor.qr(): Pair<DoubleTensor, DoubleTensor> {
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TODO("ANDREI")
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checkSquareMatrix(shape)
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val qTensor = zeroesLike()
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val rTensor = zeroesLike()
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val seq = matrixSequence().zip((qTensor.matrixSequence().zip(rTensor.matrixSequence())))
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for ((matrix, qr) in seq) {
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val (q, r) = qr
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qrHelper(matrix.as2D(), q.as2D(), r.as2D())
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}
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return Pair(qTensor, rTensor)
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}
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}
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override fun DoubleTensor.svd(): Triple<DoubleTensor, DoubleTensor, DoubleTensor> {
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override fun DoubleTensor.svd(): Triple<DoubleTensor, DoubleTensor, DoubleTensor> {
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@ -76,4 +76,50 @@ class TestDoubleLinearOpsTensorAlgebra {
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val b = fromArray(intArrayOf(3), doubleArrayOf(5.5, 2.6, 6.4))
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val b = fromArray(intArrayOf(3), doubleArrayOf(5.5, 2.6, 6.4))
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assertEquals(a.dot(b).value(), 59.92)
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assertEquals(a.dot(b).value(), 59.92)
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}
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}
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@Test
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fun testQR() = DoubleLinearOpsTensorAlgebra {
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val shape = intArrayOf(2, 2, 2)
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val buffer = doubleArrayOf(
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1.0, 3.0,
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1.0, 2.0,
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1.5, 1.0,
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10.0, 2.0
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)
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val tensor = fromArray(shape, buffer)
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val (q, r) = tensor.qr()
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assertTrue { q.shape contentEquals shape }
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assertTrue { r.shape contentEquals shape }
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assertTrue { q.dot(r).buffer.array().epsEqual(buffer) }
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//todo check orthogonality/upper triang.
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}
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@Test
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fun testLU() = DoubleLinearOpsTensorAlgebra {
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val shape = intArrayOf(2, 2, 2)
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val buffer = doubleArrayOf(
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1.0, 3.0,
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1.0, 2.0,
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1.5, 1.0,
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10.0, 2.0
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)
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val tensor = fromArray(shape, buffer)
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val (lu, pivots) = tensor.lu()
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// todo check lu
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val (p, l, u) = luPivot(lu, pivots)
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assertTrue { p.shape contentEquals shape }
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assertTrue { l.shape contentEquals shape }
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assertTrue { u.shape contentEquals shape }
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assertTrue { p.dot(tensor).buffer.array().epsEqual(l.dot(u).buffer.array()) }
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}
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}
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}
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