From 48d86fac5620b5e663a5dc62618f4f2869e86521 Mon Sep 17 00:00:00 2001 From: Roland Grinis Date: Sat, 1 May 2021 19:55:48 +0100 Subject: [PATCH] invoke refactor --- .../core/algebras/TensorLinearStructure.kt | 6 ----- .../kscience/kmath/tensors/core/linUtils.kt | 2 +- .../kmath/tensors/core/TestBroadcasting.kt | 10 ++++---- .../core/TestDoubleAnalyticTensorAlgebra.kt | 2 +- .../core/TestDoubleLinearOpsAlgebra.kt | 24 +++++++++---------- .../kmath/tensors/core/TestDoubleTensor.kt | 6 ++--- .../tensors/core/TestDoubleTensorAlgebra.kt | 18 +++++++------- 7 files changed, 31 insertions(+), 37 deletions(-) diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/TensorLinearStructure.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/TensorLinearStructure.kt index 08aab5175..5fbc7390f 100644 --- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/TensorLinearStructure.kt +++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/TensorLinearStructure.kt @@ -9,12 +9,6 @@ import space.kscience.kmath.nd.Strides import kotlin.math.max -internal fun offsetFromIndex(index: IntArray, shape: IntArray, strides: IntArray): Int = - index.mapIndexed { i, value -> - if (value < 0 || value >= shape[i]) throw IndexOutOfBoundsException("Index $value out of shape bounds: (0,${shape[i]})") - value * strides[i] - }.sum() - internal fun stridesFromShape(shape: IntArray): IntArray { val nDim = shape.size val res = IntArray(nDim) diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/linUtils.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/linUtils.kt index ba8b823c9..8adbfad39 100644 --- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/linUtils.kt +++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/linUtils.kt @@ -241,7 +241,7 @@ internal fun DoubleLinearOpsTensorAlgebra.qrHelper( } } } - r[j, j] = DoubleAnalyticTensorAlgebra.invoke { (v dot v).sqrt().value() } + r[j, j] = DoubleAnalyticTensorAlgebra { (v dot v).sqrt().value() } for (i in 0 until n) { qM[i, j] = vv[i] / r[j, j] } diff --git a/kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestBroadcasting.kt b/kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestBroadcasting.kt index 1070a1115..1564b85c9 100644 --- a/kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestBroadcasting.kt +++ b/kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestBroadcasting.kt @@ -9,7 +9,7 @@ import kotlin.test.assertTrue internal class TestBroadcasting { @Test - fun broadcastShapes() = DoubleTensorAlgebra.invoke { + fun broadcastShapes() = DoubleTensorAlgebra { assertTrue( broadcastShapes( intArrayOf(2, 3), intArrayOf(1, 3), intArrayOf(1, 1, 1) @@ -24,7 +24,7 @@ internal class TestBroadcasting { } @Test - fun broadcastTo() = DoubleTensorAlgebra.invoke { + fun broadcastTo() = DoubleTensorAlgebra { val tensor1 = fromArray(intArrayOf(2, 3), doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0)) val tensor2 = fromArray(intArrayOf(1, 3), doubleArrayOf(10.0, 20.0, 30.0)) @@ -34,7 +34,7 @@ internal class TestBroadcasting { } @Test - fun broadcastTensors() = DoubleTensorAlgebra.invoke { + fun broadcastTensors() = DoubleTensorAlgebra { val tensor1 = fromArray(intArrayOf(2, 3), doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0)) val tensor2 = fromArray(intArrayOf(1, 3), doubleArrayOf(10.0, 20.0, 30.0)) val tensor3 = fromArray(intArrayOf(1, 1, 1), doubleArrayOf(500.0)) @@ -51,7 +51,7 @@ internal class TestBroadcasting { } @Test - fun broadcastOuterTensors() = DoubleTensorAlgebra.invoke { + fun broadcastOuterTensors() = DoubleTensorAlgebra { val tensor1 = fromArray(intArrayOf(2, 3), doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0)) val tensor2 = fromArray(intArrayOf(1, 3), doubleArrayOf(10.0, 20.0, 30.0)) val tensor3 = fromArray(intArrayOf(1, 1, 1), doubleArrayOf(500.0)) @@ -68,7 +68,7 @@ internal class TestBroadcasting { } @Test - fun broadcastOuterTensorsShapes() = DoubleTensorAlgebra.invoke { + fun broadcastOuterTensorsShapes() = DoubleTensorAlgebra { val tensor1 = fromArray(intArrayOf(2, 1, 3, 2, 3), DoubleArray(2 * 1 * 3 * 2 * 3) {0.0}) val tensor2 = fromArray(intArrayOf(4, 2, 5, 1, 3, 3), DoubleArray(4 * 2 * 5 * 1 * 3 * 3) {0.0}) val tensor3 = fromArray(intArrayOf(1, 1), doubleArrayOf(500.0)) diff --git a/kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleAnalyticTensorAlgebra.kt b/kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleAnalyticTensorAlgebra.kt index 66959a0de..835b8a08a 100644 --- a/kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleAnalyticTensorAlgebra.kt +++ b/kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleAnalyticTensorAlgebra.kt @@ -27,7 +27,7 @@ internal class TestDoubleAnalyticTensorAlgebra { } @Test - fun testExp() = DoubleAnalyticTensorAlgebra.invoke { + fun testExp() = DoubleAnalyticTensorAlgebra { tensor.exp().let { assertTrue { shape contentEquals it.shape } assertTrue { buffer.fmap(::exp).epsEqual(it.mutableBuffer.array())} diff --git a/kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleLinearOpsAlgebra.kt b/kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleLinearOpsAlgebra.kt index 6689e893a..65070af7f 100644 --- a/kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleLinearOpsAlgebra.kt +++ b/kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleLinearOpsAlgebra.kt @@ -10,7 +10,7 @@ import kotlin.test.assertTrue internal class TestDoubleLinearOpsTensorAlgebra { @Test - fun testDetLU() = DoubleLinearOpsTensorAlgebra.invoke { + fun testDetLU() = DoubleLinearOpsTensorAlgebra { val tensor = fromArray( intArrayOf(2, 2, 2), doubleArrayOf( @@ -35,7 +35,7 @@ internal class TestDoubleLinearOpsTensorAlgebra { } @Test - fun testDet() = DoubleLinearOpsTensorAlgebra.invoke { + fun testDet() = DoubleLinearOpsTensorAlgebra { val expectedValue = 0.019827417 val m = fromArray( intArrayOf(3, 3), doubleArrayOf( @@ -49,7 +49,7 @@ internal class TestDoubleLinearOpsTensorAlgebra { } @Test - fun testDetSingle() = DoubleLinearOpsTensorAlgebra.invoke { + fun testDetSingle() = DoubleLinearOpsTensorAlgebra { val expectedValue = 48.151623 val m = fromArray( intArrayOf(1, 1), doubleArrayOf( @@ -61,7 +61,7 @@ internal class TestDoubleLinearOpsTensorAlgebra { } @Test - fun testInvLU() = DoubleLinearOpsTensorAlgebra.invoke { + fun testInvLU() = DoubleLinearOpsTensorAlgebra { val tensor = fromArray( intArrayOf(2, 2, 2), doubleArrayOf( @@ -86,14 +86,14 @@ internal class TestDoubleLinearOpsTensorAlgebra { } @Test - fun testScalarProduct() = DoubleLinearOpsTensorAlgebra.invoke { + fun testScalarProduct() = DoubleLinearOpsTensorAlgebra { val a = fromArray(intArrayOf(3), doubleArrayOf(1.8, 2.5, 6.8)) val b = fromArray(intArrayOf(3), doubleArrayOf(5.5, 2.6, 6.4)) assertEquals(a.dot(b).value(), 59.92) } @Test - fun testQR() = DoubleLinearOpsTensorAlgebra.invoke { + fun testQR() = DoubleLinearOpsTensorAlgebra { val shape = intArrayOf(2, 2, 2) val buffer = doubleArrayOf( 1.0, 3.0, @@ -114,7 +114,7 @@ internal class TestDoubleLinearOpsTensorAlgebra { } @Test - fun testLU() = DoubleLinearOpsTensorAlgebra.invoke { + fun testLU() = DoubleLinearOpsTensorAlgebra { val shape = intArrayOf(2, 2, 2) val buffer = doubleArrayOf( 1.0, 3.0, @@ -134,7 +134,7 @@ internal class TestDoubleLinearOpsTensorAlgebra { } @Test - fun testCholesky() = DoubleLinearOpsTensorAlgebra.invoke { + fun testCholesky() = DoubleLinearOpsTensorAlgebra { val tensor = randomNormal(intArrayOf(2, 5, 5), 0) val sigma = (tensor dot tensor.transpose()) + diagonalEmbedding( fromArray(intArrayOf(2, 5), DoubleArray(10) { 0.1 }) @@ -145,7 +145,7 @@ internal class TestDoubleLinearOpsTensorAlgebra { } @Test - fun testSVD1D() = DoubleLinearOpsTensorAlgebra.invoke { + fun testSVD1D() = DoubleLinearOpsTensorAlgebra { val tensor2 = fromArray(intArrayOf(2, 3), doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0)) val res = svd1d(tensor2) @@ -156,13 +156,13 @@ internal class TestDoubleLinearOpsTensorAlgebra { } @Test - fun testSVD() = DoubleLinearOpsTensorAlgebra.invoke{ + fun testSVD() = DoubleLinearOpsTensorAlgebra{ testSVDFor(fromArray(intArrayOf(2, 3), doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0))) testSVDFor(fromArray(intArrayOf(2, 2), doubleArrayOf(-1.0, 0.0, 239.0, 238.0))) } @Test - fun testBatchedSVD() = DoubleLinearOpsTensorAlgebra.invoke { + fun testBatchedSVD() = DoubleLinearOpsTensorAlgebra { val tensor = randomNormal(intArrayOf(2, 5, 3), 0) val (tensorU, tensorS, tensorV) = tensor.svd() val tensorSVD = tensorU dot (diagonalEmbedding(tensorS) dot tensorV.transpose()) @@ -170,7 +170,7 @@ internal class TestDoubleLinearOpsTensorAlgebra { } @Test - fun testBatchedSymEig() = DoubleLinearOpsTensorAlgebra.invoke { + fun testBatchedSymEig() = DoubleLinearOpsTensorAlgebra { val tensor = randomNormal(shape = intArrayOf(2, 3, 3), 0) val tensorSigma = tensor + tensor.transpose() val (tensorS, tensorV) = tensorSigma.symEig() diff --git a/kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleTensor.kt b/kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleTensor.kt index 333a7bdec..ed5f8e780 100644 --- a/kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleTensor.kt +++ b/kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleTensor.kt @@ -15,14 +15,14 @@ import kotlin.test.assertTrue internal class TestDoubleTensor { @Test - fun valueTest() = DoubleTensorAlgebra.invoke { + fun valueTest() = DoubleTensorAlgebra { val value = 12.5 val tensor = fromArray(intArrayOf(1), doubleArrayOf(value)) assertEquals(tensor.value(), value) } @Test - fun stridesTest() = DoubleTensorAlgebra.invoke { + fun stridesTest() = DoubleTensorAlgebra { val tensor = fromArray(intArrayOf(2, 2), doubleArrayOf(3.5, 5.8, 58.4, 2.4)) assertEquals(tensor[intArrayOf(0, 1)], 5.8) assertTrue( @@ -31,7 +31,7 @@ internal class TestDoubleTensor { } @Test - fun getTest() = DoubleTensorAlgebra.invoke { + fun getTest() = DoubleTensorAlgebra { val tensor = fromArray(intArrayOf(1, 2, 2), doubleArrayOf(3.5, 5.8, 58.4, 2.4)) val matrix = tensor[0].as2D() assertEquals(matrix[0, 1], 5.8) diff --git a/kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleTensorAlgebra.kt b/kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleTensorAlgebra.kt index a0efa4573..df2d21b96 100644 --- a/kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleTensorAlgebra.kt +++ b/kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleTensorAlgebra.kt @@ -10,21 +10,21 @@ import kotlin.test.assertTrue internal class TestDoubleTensorAlgebra { @Test - fun doublePlus() = DoubleTensorAlgebra.invoke { + fun doublePlus() = DoubleTensorAlgebra { val tensor = fromArray(intArrayOf(2), doubleArrayOf(1.0, 2.0)) val res = 10.0 + tensor assertTrue(res.mutableBuffer.array() contentEquals doubleArrayOf(11.0, 12.0)) } @Test - fun doubleDiv() = DoubleTensorAlgebra.invoke { + fun doubleDiv() = DoubleTensorAlgebra { val tensor = fromArray(intArrayOf(2), doubleArrayOf(2.0, 4.0)) val res = 2.0/tensor assertTrue(res.mutableBuffer.array() contentEquals doubleArrayOf(1.0, 0.5)) } @Test - fun divDouble() = DoubleTensorAlgebra.invoke { + fun divDouble() = DoubleTensorAlgebra { val tensor = fromArray(intArrayOf(2), doubleArrayOf(10.0, 5.0)) val res = tensor / 2.5 assertTrue(res.mutableBuffer.array() contentEquals doubleArrayOf(4.0, 2.0)) @@ -40,7 +40,7 @@ internal class TestDoubleTensorAlgebra { } @Test - fun transpose3x2() = DoubleTensorAlgebra.invoke { + fun transpose3x2() = DoubleTensorAlgebra { val tensor = fromArray(intArrayOf(3, 2), doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0)) val res = tensor.transpose(1, 0) @@ -49,7 +49,7 @@ internal class TestDoubleTensorAlgebra { } @Test - fun transpose1x2x3() = DoubleTensorAlgebra.invoke { + fun transpose1x2x3() = DoubleTensorAlgebra { val tensor = fromArray(intArrayOf(1, 2, 3), doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0)) val res01 = tensor.transpose(0, 1) val res02 = tensor.transpose(-3, 2) @@ -65,7 +65,7 @@ internal class TestDoubleTensorAlgebra { } @Test - fun linearStructure() = DoubleTensorAlgebra.invoke { + fun linearStructure() = DoubleTensorAlgebra { val shape = intArrayOf(3) val tensorA = full(value = -4.5, shape = shape) val tensorB = full(value = 10.9, shape = shape) @@ -97,7 +97,7 @@ internal class TestDoubleTensorAlgebra { } @Test - fun dot() = DoubleTensorAlgebra.invoke { + fun dot() = DoubleTensorAlgebra { val tensor1 = fromArray(intArrayOf(2, 3), doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0)) val tensor11 = fromArray(intArrayOf(3, 2), doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0)) val tensor2 = fromArray(intArrayOf(3), doubleArrayOf(10.0, 20.0, 30.0)) @@ -133,7 +133,7 @@ internal class TestDoubleTensorAlgebra { } @Test - fun diagonalEmbedding() = DoubleTensorAlgebra.invoke { + fun diagonalEmbedding() = DoubleTensorAlgebra { val tensor1 = fromArray(intArrayOf(3), doubleArrayOf(10.0, 20.0, 30.0)) val tensor2 = fromArray(intArrayOf(2, 3), doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0)) val tensor3 = zeros(intArrayOf(2, 3, 4, 5)) @@ -166,7 +166,7 @@ internal class TestDoubleTensorAlgebra { } @Test - fun testEq() = DoubleTensorAlgebra.invoke { + fun testEq() = DoubleTensorAlgebra { val tensor1 = fromArray(intArrayOf(2, 3), doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0)) val tensor2 = fromArray(intArrayOf(2, 3), doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0)) val tensor3 = fromArray(intArrayOf(2, 3), doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 5.0))