Merge pull request #200 from mipt-npm/commandertvis/fix-benchmarks

Fix benchmarks source set

examples/src/benchmarks/kotlin/kscience/kmath/benchmarks/BufferBenchmark.kt

@@ -31,4 +31,4 @@ internal class BufferBenchmark {
     companion object {
         const val size: Int = 100
     }
-}
+}

examples/src/benchmarks/kotlin/kscience/kmath/benchmarks/DotBenchmark.kt

@@ -14,7 +14,7 @@ import org.openjdk.jmh.annotations.State
 import kotlin.random.Random
 
 @State(Scope.Benchmark)
-class DotBenchmark {
+internal class DotBenchmark {
     companion object {
         val random = Random(12224)
         val dim = 1000
@@ -64,4 +64,4 @@ class DotBenchmark {
             matrix1 dot matrix2
         }
     }
-}
+}

examples/src/benchmarks/kotlin/kscience/kmath/benchmarks/ExpressionsInterpretersBenchmark.kt

@@ -1,6 +1,8 @@
-package kscience.kmath.ast
+package kscience.kmath.benchmarks
 
 import kscience.kmath.asm.compile
+import kscience.kmath.ast.MstField
+import kscience.kmath.ast.mstInField
 import kscience.kmath.expressions.Expression
 import kscience.kmath.expressions.expressionInField
 import kscience.kmath.expressions.invoke
@@ -37,7 +39,7 @@ internal class ExpressionsInterpretersBenchmark {
     @Benchmark
     fun asmExpression() {
         val expr = algebra.mstInField {
-            symbol("x") * 2.0 + 2.0 / symbol("x") - 16.0
+            MstField.symbol("x") * 2.0 + 2.0 / MstField.symbol("x") - 16.0
         }.compile()
 
         invokeAndSum(expr)

examples/src/benchmarks/kotlin/kscience/kmath/benchmarks/LinearAlgebraBenchmark.kt

@@ -1,5 +1,4 @@
-package kscience.kmath.linear
+package kscience.kmath.benchmarks
-
 
 import kotlinx.benchmark.Benchmark
 import kscience.kmath.commons.linear.CMMatrixContext
@@ -7,14 +6,17 @@ import kscience.kmath.commons.linear.CMMatrixContext.dot
 import kscience.kmath.commons.linear.inverse
 import kscience.kmath.ejml.EjmlMatrixContext
 import kscience.kmath.ejml.inverse
+import kscience.kmath.linear.Matrix
+import kscience.kmath.linear.MatrixContext
+import kscience.kmath.linear.inverseWithLup
+import kscience.kmath.linear.real
 import kscience.kmath.operations.invoke
-import kscience.kmath.structures.Matrix
 import org.openjdk.jmh.annotations.Scope
 import org.openjdk.jmh.annotations.State
 import kotlin.random.Random
 
 @State(Scope.Benchmark)
-class LinearAlgebraBenchmark {
+internal class LinearAlgebraBenchmark {
     companion object {
         val random = Random(1224)
         val dim = 100
@@ -43,4 +45,4 @@ class LinearAlgebraBenchmark {
             inverse(matrix)
         }
     }
-}
+}

examples/src/benchmarks/kotlin/kscience/kmath/benchmarks/NDFieldBenchmark.kt

@@ -42,4 +42,4 @@ internal class NDFieldBenchmark {
         val specializedField: RealNDField = NDAlgebra.real(dim, dim)
         val genericField = NDAlgebra.field(RealField, Buffer.Companion::boxing, dim, dim)
     }
-}
+}

examples/src/benchmarks/kotlin/kscience/kmath/benchmarks/ViktorBenchmark.kt

@@ -49,4 +49,4 @@ internal class ViktorBenchmark {
         var res = one
         repeat(n) { res = res + one }
     }
-}
+}

examples/src/benchmarks/kotlin/kscience/kmath/benchmarks/ViktorLogBenchmark.kt

@@ -46,4 +46,4 @@ internal class ViktorLogBenchmark {
             res = fortyTwo.log()
         }
     }
-}
+}