teldufalsari/kmath
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Reformat code

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This commit is contained in:
Alexander Nozik 2021-03-15 14:26:59 +03:00
parent 0e0deaeb72
commit d9743978ab
18 changed files with 30 additions and 29 deletions
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2
kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/DifferentiableExpression.kt
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@ -28,7 +28,7 @@ public fun <T, R : Expression<T>> DifferentiableExpression<T, R>.derivative(name
/**
* A [DifferentiableExpression] that defines only first derivatives
*/
public abstract class FirstDerivativeExpression<T, R : Expression<T>> : DifferentiableExpression<T,R> {
public abstract class FirstDerivativeExpression<T, R : Expression<T>> : DifferentiableExpression<T, R> {
/**
* Returns first derivative of this expression by given [symbol].
*/

2
kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/Expression.kt
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@ -95,7 +95,7 @@ public fun <T, E> ExpressionAlgebra<T, E>.bindSymbol(symbol: Symbol): E =
/**
* A delegate to create a symbol with a string identity in this scope
*/
public val symbol: ReadOnlyProperty<Any?, Symbol> = ReadOnlyProperty { _, property ->
public val symbol: ReadOnlyProperty<Any?, Symbol> = ReadOnlyProperty { _, property ->
StringSymbol(property.name)
}

2
kmath-core/src/commonMain/kotlin/space/kscience/kmath/expressions/FunctionalExpressionAlgebra.kt
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@ -98,7 +98,7 @@ public open class FunctionalExpressionRing<T, A : Ring<T>>(
super<FunctionalExpressionGroup>.binaryOperationFunction(operation)
}
public open class FunctionalExpressionField<T, A: Field<T>>(
public open class FunctionalExpressionField<T, A : Field<T>>(
algebra: A,
) : FunctionalExpressionRing<T, A>(algebra), Field<Expression<T>>,
ScaleOperations<Expression<T>> {

2
kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/BufferedLinearSpace.kt
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@ -48,7 +48,7 @@ public class BufferedLinearSpace<T : Any, A : Ring<T>>(
override fun Matrix<T>.dot(other: Matrix<T>): Matrix<T> {
require(colNum == other.rowNum) { "Matrix dot operation dimension mismatch: ($rowNum, $colNum) x (${other.rowNum}, ${other.colNum})" }
return elementAlgebra {
val rows = this@dot.rows.map{it.linearize()}
val rows = this@dot.rows.map { it.linearize() }
val columns = other.columns.map { it.linearize() }
buildMatrix(rowNum, other.colNum) { i, j ->
val r = rows[i]

2
kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/LinearSpace.kt
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@ -175,7 +175,7 @@ public interface LinearSpace<T : Any, out A : Ring<T>> {
public fun <T : Any, A : Ring<T>> buffered(
algebra: A,
bufferFactory: BufferFactory<T> = Buffer.Companion::boxing,
): LinearSpace<T, A> = BufferedLinearSpace(algebra,bufferFactory)
): LinearSpace<T, A> = BufferedLinearSpace(algebra, bufferFactory)
public val real: LinearSpace<Double, RealField> = buffered(RealField, ::RealBuffer)

2
kmath-core/src/commonMain/kotlin/space/kscience/kmath/linear/VirtualMatrix.kt
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@ -10,7 +10,7 @@ import space.kscience.kmath.nd.NDStructure
public class VirtualMatrix<T : Any>(
override val rowNum: Int,
override val colNum: Int,
public val generator: (i: Int, j: Int) -> T
public val generator: (i: Int, j: Int) -> T,
) : Matrix<T> {
override val shape: IntArray get() = intArrayOf(rowNum, colNum)

15
kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/NDAlgebra.kt
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@ -19,7 +19,7 @@ public class ShapeMismatchException(public val expected: IntArray, public val ac
* @param C the type of the element context.
* @param N the type of the structure.
*/
public interface NDAlgebra<T, C: Algebra<T>> {
public interface NDAlgebra<T, C : Algebra<T>> {
/**
* The shape of ND-structures this algebra operates on.
*/
@ -65,11 +65,12 @@ public interface NDAlgebra<T, C: Algebra<T>> {
* @param structures the structures to check.
* @return the array of valid structures.
*/
internal fun <T, C: Algebra<T>> NDAlgebra<T, C>.checkShape(vararg structures: NDStructure<T>): Array<out NDStructure<T>> = structures
.map(NDStructure<T>::shape)
.singleOrNull { !shape.contentEquals(it) }
?.let<IntArray, Array<out NDStructure<T>>> { throw ShapeMismatchException(shape, it) }
?: structures
internal fun <T, C : Algebra<T>> NDAlgebra<T, C>.checkShape(vararg structures: NDStructure<T>): Array<out NDStructure<T>> =
structures
.map(NDStructure<T>::shape)
.singleOrNull { !shape.contentEquals(it) }
?.let<IntArray, Array<out NDStructure<T>>> { throw ShapeMismatchException(shape, it) }
?: structures
/**
* Checks if given element is consistent with this context.
@ -77,7 +78,7 @@ internal fun <T, C: Algebra<T>> NDAlgebra<T, C>.checkShape(vararg structures: ND
* @param element the structure to check.
* @return the valid structure.
*/
internal fun <T, C: Algebra<T>> NDAlgebra<T, C>.checkShape(element: NDStructure<T>): NDStructure<T> {
internal fun <T, C : Algebra<T>> NDAlgebra<T, C>.checkShape(element: NDStructure<T>): NDStructure<T> {
if (!element.shape.contentEquals(shape)) throw ShapeMismatchException(shape, element.shape)
return element
}

2
kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/AlgebraElements.kt
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@ -41,7 +41,7 @@ public interface AlgebraElement<T, C : Algebra<T>> {
*/
@UnstableKMathAPI
public operator fun <T : AlgebraElement<T, S>, S : NumbersAddOperations<T>> T.minus(b: T): T =
context.add(this, context.run { -b})
context.add(this, context.run { -b })
/**
* Adds element to this one.

4
kmath-core/src/commonMain/kotlin/space/kscience/kmath/operations/algebraExtensions.kt
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@ -71,7 +71,7 @@ public fun <T> Sequence<T>.sumWith(space: Group<T>): T = space.sum(this)
* @return the average value.
* @author Iaroslav Postovalov
*/
public fun <T, S> Iterable<T>.averageWith(space: S): T where S : Group<T>, S : ScaleOperations<T> =
public fun <T, S> Iterable<T>.averageWith(space: S): T where S : Group<T>, S : ScaleOperations<T> =
space.average(this)
/**
@ -82,7 +82,7 @@ public fun <T, S> Iterable<T>.averageWith(space: S): T where S : Group<T>, S :
* @return the average value.
* @author Iaroslav Postovalov
*/
public fun <T, S> Sequence<T>.averageWith(space: S): T where S : Group<T>, S : ScaleOperations<T> =
public fun <T, S> Sequence<T>.averageWith(space: S): T where S : Group<T>, S : ScaleOperations<T> =
space.average(this)
//TODO optimized power operation

4
kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/BufferAccessor2D.kt
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@ -13,10 +13,10 @@ internal class BufferAccessor2D<T : Any>(
public val colNum: Int,
val factory: MutableBufferFactory<T>,
) {
public operator fun Buffer<T>.get(i: Int, j: Int): T = get(i*colNum + j)
public operator fun Buffer<T>.get(i: Int, j: Int): T = get(i * colNum + j)
public operator fun MutableBuffer<T>.set(i: Int, j: Int, value: T) {
set(i*colNum + j, value)
set(i * colNum + j, value)
}
public inline fun create(crossinline init: (i: Int, j: Int) -> T): MutableBuffer<T> =

2
kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/FloatBuffer.kt
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@ -38,7 +38,7 @@ public fun FloatBuffer(vararg floats: Float): FloatBuffer = FloatBuffer(floats)
/**
* Returns a new [FloatArray] containing all of the elements of this [Buffer].
*/
public fun Buffer<Float>.toFloatArray(): FloatArray = when(this) {
public fun Buffer<Float>.toFloatArray(): FloatArray = when (this) {
is FloatBuffer -> array.copyOf()
else -> FloatArray(size, ::get)
}

2
kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/IntBuffer.kt
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@ -37,7 +37,7 @@ public fun IntBuffer(vararg ints: Int): IntBuffer = IntBuffer(ints)
/**
* Returns a new [IntArray] containing all of the elements of this [Buffer].
*/
public fun Buffer<Int>.toIntArray(): IntArray = when(this) {
public fun Buffer<Int>.toIntArray(): IntArray = when (this) {
is IntBuffer -> array.copyOf()
else -> IntArray(size, ::get)
}

2
kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/LongBuffer.kt
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@ -37,7 +37,7 @@ public fun LongBuffer(vararg longs: Long): LongBuffer = LongBuffer(longs)
/**
* Returns a new [LongArray] containing all of the elements of this [Buffer].
*/
public fun Buffer<Long>.toLongArray(): LongArray = when(this) {
public fun Buffer<Long>.toLongArray(): LongArray = when (this) {
is LongBuffer -> array.copyOf()
else -> LongArray(size, ::get)
}

4
kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/MemoryBuffer.kt
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@ -24,7 +24,7 @@ public open class MemoryBuffer<T : Any>(protected val memory: Memory, protected
public inline fun <T : Any> create(
spec: MemorySpec<T>,
size: Int,
initializer: (Int) -> T
initializer: (Int) -> T,
): MemoryBuffer<T> = MutableMemoryBuffer(Memory.allocate(size * spec.objectSize), spec).also { buffer ->
(0 until size).forEach { buffer[it] = initializer(it) }
}
@ -53,7 +53,7 @@ public class MutableMemoryBuffer<T : Any>(memory: Memory, spec: MemorySpec<T>) :
public inline fun <T : Any> create(
spec: MemorySpec<T>,
size: Int,
initializer: (Int) -> T
initializer: (Int) -> T,
): MutableMemoryBuffer<T> = MutableMemoryBuffer(Memory.allocate(size * spec.objectSize), spec).also { buffer ->
(0 until size).forEach { buffer[it] = initializer(it) }
}

2
kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/RealBuffer.kt
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@ -42,7 +42,7 @@ public fun RealBuffer.contentEquals(vararg doubles: Double): Boolean = array.con
/**
* Returns a new [DoubleArray] containing all of the elements of this [Buffer].
*/
public fun Buffer<Double>.toDoubleArray(): DoubleArray = when(this) {
public fun Buffer<Double>.toDoubleArray(): DoubleArray = when (this) {
is RealBuffer -> array.copyOf()
else -> DoubleArray(size, ::get)
}

2
kmath-core/src/commonMain/kotlin/space/kscience/kmath/structures/ShortBuffer.kt
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@ -35,7 +35,7 @@ public fun ShortBuffer(vararg shorts: Short): ShortBuffer = ShortBuffer(shorts)
/**
* Returns a new [ShortArray] containing all of the elements of this [Buffer].
*/
public fun Buffer<Short>.toShortArray(): ShortArray = when(this) {
public fun Buffer<Short>.toShortArray(): ShortArray = when (this) {
is ShortBuffer -> array.copyOf()
else -> ShortArray(size, ::get)
}

6
kmath-core/src/commonTest/kotlin/space/kscience/kmath/linear/RealLUSolverTest.kt
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@ -17,7 +17,7 @@ class RealLUSolverTest {
@Test
fun testDecomposition() {
LinearSpace.real.run {
val matrix = matrix(2,2)(
val matrix = matrix(2, 2)(
3.0, 1.0,
2.0, 3.0
)
@ -33,14 +33,14 @@ class RealLUSolverTest {
@Test
fun testInvert() {
val matrix = LinearSpace.real.matrix(2,2)(
val matrix = LinearSpace.real.matrix(2, 2)(
3.0, 1.0,
1.0, 3.0
)
val inverted = LinearSpace.real.inverseWithLup(matrix)
val expected = LinearSpace.real.matrix(2,2)(
val expected = LinearSpace.real.matrix(2, 2)(
0.375, -0.125,
-0.125, 0.375
)

2
kmath-core/src/commonTest/kotlin/space/kscience/kmath/structures/NumberNDFieldTest.kt
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@ -11,7 +11,7 @@ import kotlin.test.assertEquals
@Suppress("UNUSED_VARIABLE")
class NumberNDFieldTest {
val algebra = NDAlgebra.real(3,3)
val algebra = NDAlgebra.real(3, 3)
val array1 = algebra.produce { (i, j) -> (i + j).toDouble() }
val array2 = algebra.produce { (i, j) -> (i - j).toDouble() }