Merge remote-tracking branch 'origin/dev-pk' into dev

# Conflicts:
#	settings.gradle.kts
This commit is contained in:
Alexander Nozik 2020-01-12 10:50:43 +03:00
commit 9d1ba1b78b
9 changed files with 211 additions and 30 deletions

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@ -6,21 +6,6 @@ import kotlin.test.assertEquals
class MatrixTest {
@Test
fun testSum() {
val vector1 = RealVector(5) { it.toDouble() }
val vector2 = RealVector(5) { 5 - it.toDouble() }
val sum = vector1 + vector2
assertEquals(5.0, sum[2])
}
@Test
fun testVectorToMatrix() {
val vector = RealVector(5) { it.toDouble() }
val matrix = vector.asMatrix()
assertEquals(4.0, matrix[4, 0])
}
@Test
fun testTranspose() {
val matrix = MatrixContext.real.one(3, 3)
@ -28,21 +13,6 @@ class MatrixTest {
assertEquals(matrix, transposed)
}
@Test
fun testDot() {
val vector1 = RealVector(5) { it.toDouble() }
val vector2 = RealVector(5) { 5 - it.toDouble() }
val matrix1 = vector1.asMatrix()
val matrix2 = vector2.asMatrix().transpose()
val product = MatrixContext.real.run { matrix1 dot matrix2 }
assertEquals(5.0, product[1, 0])
assertEquals(6.0, product[2, 2])
}
@Test
fun testBuilder() {
val matrix = Matrix.build<Double>(2, 3)(

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@ -0,0 +1,11 @@
plugins {
id("scientifik.mpp")
}
kotlin.sourceSets {
commonMain {
dependencies {
api(project(":kmath-core"))
}
}
}

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@ -0,0 +1,146 @@
package scientifik.kmath.real
import scientifik.kmath.linear.MatrixContext
import scientifik.kmath.linear.RealMatrixContext.elementContext
import scientifik.kmath.linear.VirtualMatrix
import scientifik.kmath.operations.sum
import scientifik.kmath.structures.Buffer
import scientifik.kmath.structures.Matrix
import scientifik.kmath.structures.asSequence
import kotlin.math.pow
/*
* Functions for convenient "numpy-like" operations with Double matrices.
*
* Initial implementation of these functions is taken from:
* https://github.com/thomasnield/numky/blob/master/src/main/kotlin/org/nield/numky/linear/DoubleOperators.kt
*
*/
/*
* Functions that help create a real (Double) matrix
*/
fun realMatrix(rowNum: Int, colNum: Int, initializer: (i: Int, j: Int) -> Double) =
MatrixContext.real.produce(rowNum, colNum, initializer)
fun Sequence<DoubleArray>.toMatrix() = toList().let {
MatrixContext.real.produce(it.size, it[0].size) { row, col -> it[row][col] }
}
fun Matrix<Double>.repeatStackVertical(n: Int) = VirtualMatrix(rowNum*n, colNum) {
row, col -> get(if (row == 0) 0 else row % rowNum, col)
}
/*
* Operations for matrix and real number
*/
operator fun Matrix<Double>.times(double: Double) = MatrixContext.real.produce(rowNum, colNum) {
row, col -> this[row, col] * double
}
operator fun Matrix<Double>.plus(double: Double) = MatrixContext.real.produce(rowNum, colNum) {
row, col -> this[row, col] + double
}
operator fun Matrix<Double>.minus(double: Double) = MatrixContext.real.produce(rowNum, colNum) {
row, col -> this[row, col] - double
}
operator fun Matrix<Double>.div(double: Double) = MatrixContext.real.produce(rowNum, colNum) {
row, col -> this[row, col] / double
}
operator fun Double.times(matrix: Matrix<Double>) = MatrixContext.real.produce(matrix.rowNum, matrix.colNum) {
row, col -> this * matrix[row, col]
}
operator fun Double.plus(matrix: Matrix<Double>) = MatrixContext.real.produce(matrix.rowNum, matrix.colNum) {
row, col -> this * matrix[row, col]
}
operator fun Double.minus(matrix: Matrix<Double>) = MatrixContext.real.produce(matrix.rowNum, matrix.colNum) {
row, col -> this - matrix[row, col]
}
// TODO: does this operation make sense? Should it be 'this/matrix[row, col]'?
//operator fun Double.div(matrix: Matrix<Double>) = MatrixContext.real.produce(matrix.rowNum, matrix.colNum) {
// row, col -> matrix[row, col] / this
//}
/*
* Per-element (!) square and power operations
*/
fun Matrix<Double>.square() = MatrixContext.real.produce(rowNum, colNum) {
row, col -> this[row, col].pow(2)
}
fun Matrix<Double>.pow(n: Int) = MatrixContext.real.produce(rowNum, colNum) {
i, j -> this[i, j].pow(n)
}
/*
* Operations on two matrices (per-element!)
*/
operator fun Matrix<Double>.times(other: Matrix<Double>) = MatrixContext.real.produce(rowNum, colNum) {
row, col -> this[row, col] * other[row, col]
}
operator fun Matrix<Double>.plus(other: Matrix<Double>) = MatrixContext.real.add(this, other)
operator fun Matrix<Double>.minus(other: Matrix<Double>) = MatrixContext.real.produce(rowNum, colNum) {
row, col -> this[row,col] - other[row,col]
}
/*
* Operations on columns
*/
inline fun Matrix<Double>.appendColumn(crossinline mapper: (Buffer<Double>) -> Double) =
MatrixContext.real.produce(rowNum,colNum+1) {
row, col ->
if (col < colNum)
this[row, col]
else
mapper(rows[row])
}
fun Matrix<Double>.extractColumns(columnRange: IntRange) = MatrixContext.real.produce(rowNum, columnRange.count()) {
row, col -> this[row, columnRange.first + col]
}
fun Matrix<Double>.extractColumn(columnIndex: Int) = extractColumns(columnIndex..columnIndex)
fun Matrix<Double>.sumByColumn() = MatrixContext.real.produce(1, colNum) { _, j ->
val column = columns[j]
with(elementContext) {
sum(column.asSequence())
}
}
fun Matrix<Double>.minByColumn() = MatrixContext.real.produce(1, colNum) {
_, j -> columns[j].asSequence().min() ?: throw Exception("Cannot produce min on empty column")
}
fun Matrix<Double>.maxByColumn() = MatrixContext.real.produce(1, colNum) {
_, j -> columns[j].asSequence().max() ?: throw Exception("Cannot produce min on empty column")
}
fun Matrix<Double>.averageByColumn() = MatrixContext.real.produce(1, colNum) {
_, j -> columns[j].asSequence().average()
}
/*
* Operations processing all elements
*/
fun Matrix<Double>.sum() = elements().map { (_, value) -> value }.sum()
fun Matrix<Double>.min() = elements().map { (_, value) -> value }.min()
fun Matrix<Double>.max() = elements().map { (_, value) -> value }.max()
fun Matrix<Double>.average() = elements().map { (_, value) -> value }.average()

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@ -0,0 +1,16 @@
package scientific.kmath.real
import scientifik.kmath.real.average
import scientifik.kmath.real.realMatrix
import scientifik.kmath.real.sum
import kotlin.test.Test
import kotlin.test.assertEquals
class RealMatrixTest {
@Test
fun testSum() {
val m = realMatrix(10, 10) { i, j -> (i + j).toDouble() }
assertEquals(m.sum(), 900.0)
assertEquals(m.average(), 9.0)
}
}

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@ -0,0 +1,36 @@
package scientifik.kmath.linear
import kotlin.test.Test
import kotlin.test.assertEquals
class VectorTest {
@Test
fun testSum() {
val vector1 = RealVector(5) { it.toDouble() }
val vector2 = RealVector(5) { 5 - it.toDouble() }
val sum = vector1 + vector2
assertEquals(5.0, sum[2])
}
@Test
fun testVectorToMatrix() {
val vector = RealVector(5) { it.toDouble() }
val matrix = vector.asMatrix()
assertEquals(4.0, matrix[4, 0])
}
@Test
fun testDot() {
val vector1 = RealVector(5) { it.toDouble() }
val vector2 = RealVector(5) { 5 - it.toDouble() }
val matrix1 = vector1.asMatrix()
val matrix2 = vector2.asMatrix().transpose()
val product = MatrixContext.real.run { matrix1 dot matrix2 }
assertEquals(5.0, product[1, 0])
assertEquals(6.0, product[2, 2])
}
}

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@ -5,5 +5,6 @@ plugins {
kotlin.sourceSets.commonMain {
dependencies {
api(project(":kmath-core"))
api(project(":kmath-for-real"))
}
}

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@ -39,5 +39,6 @@ include(
":kmath-prob",
":kmath-io",
":kmath-dimensions",
":kmath-for-real",
":examples"
)