Min max refactor

kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/AnalyticTensorAlgebra.kt

@@ -14,43 +14,6 @@ package space.kscience.kmath.tensors.api
 public interface AnalyticTensorAlgebra<T> :
     TensorPartialDivisionAlgebra<T> {
 
-
-    /**
-     * @return the minimum value of all elements in the input tensor.
-     */
-    public fun Tensor<T>.min(): T
-
-    /**
-     * Returns the minimum value of each row of the input tensor in the given dimension [dim].
-     *
-     * If [keepDim] is true, the output tensor is of the same size as
-     * input except in the dimension [dim] where it is of size 1.
-     * Otherwise, [dim] is squeezed, resulting in the output tensor having 1 fewer dimension.
-     *
-     * @param dim the dimension to reduce.
-     * @param keepDim whether the output tensor has [dim] retained or not.
-     * @return the minimum value of each row of the input tensor in the given dimension [dim].
-     */
-    public fun Tensor<T>.min(dim: Int, keepDim: Boolean): Tensor<T>
-
-    /**
-     * @return the maximum value of all elements in the input tensor.
-     */
-    public fun Tensor<T>.max(): T
-
-    /**
-     * Returns the maximum value of each row of the input tensor in the given dimension [dim].
-     *
-     * If [keepDim] is true, the output tensor is of the same size as
-     * input except in the dimension [dim] where it is of size 1.
-     * Otherwise, [dim] is squeezed, resulting in the output tensor having 1 fewer dimension.
-     *
-     * @param dim the dimension to reduce.
-     * @param keepDim whether the output tensor has [dim] retained or not.
-     * @return the maximum value of each row of the input tensor in the given dimension [dim].
-     */
-    public fun Tensor<T>.max(dim: Int, keepDim: Boolean): Tensor<T>
-
     /**
      * @return the mean of all elements in the input tensor.
      */

kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/TensorAlgebra.kt

@@ -269,6 +269,41 @@ public interface TensorAlgebra<T>: Algebra<Tensor<T>> {
      */
     public fun Tensor<T>.sum(dim: Int, keepDim: Boolean): Tensor<T>
 
+    /**
+     * @return the minimum value of all elements in the input tensor.
+     */
+    public fun Tensor<T>.min(): T
+
+    /**
+     * Returns the minimum value of each row of the input tensor in the given dimension [dim].
+     *
+     * If [keepDim] is true, the output tensor is of the same size as
+     * input except in the dimension [dim] where it is of size 1.
+     * Otherwise, [dim] is squeezed, resulting in the output tensor having 1 fewer dimension.
+     *
+     * @param dim the dimension to reduce.
+     * @param keepDim whether the output tensor has [dim] retained or not.
+     * @return the minimum value of each row of the input tensor in the given dimension [dim].
+     */
+    public fun Tensor<T>.min(dim: Int, keepDim: Boolean): Tensor<T>
+
+    /**
+     * @return the maximum value of all elements in the input tensor.
+     */
+    public fun Tensor<T>.max(): T
+
+    /**
+     * Returns the maximum value of each row of the input tensor in the given dimension [dim].
+     *
+     * If [keepDim] is true, the output tensor is of the same size as
+     * input except in the dimension [dim] where it is of size 1.
+     * Otherwise, [dim] is squeezed, resulting in the output tensor having 1 fewer dimension.
+     *
+     * @param dim the dimension to reduce.
+     * @param keepDim whether the output tensor has [dim] retained or not.
+     * @return the maximum value of each row of the input tensor in the given dimension [dim].
+     */
+    public fun Tensor<T>.max(dim: Int, keepDim: Boolean): Tensor<T>
 
 
 }

kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/DoubleAnalyticTensorAlgebra.kt

@@ -15,16 +15,6 @@ public object DoubleAnalyticTensorAlgebra :
     AnalyticTensorAlgebra<Double>,
     DoubleTensorAlgebra() {
 
-    override fun Tensor<Double>.min(): Double = this.fold { it.minOrNull()!! }
-
-    override fun Tensor<Double>.min(dim: Int, keepDim: Boolean): DoubleTensor =
-        foldDim({ x -> x.minOrNull()!! }, dim, keepDim)
-
-    override fun Tensor<Double>.max(): Double = this.fold { it.maxOrNull()!! }
-
-    override fun Tensor<Double>.max(dim: Int, keepDim: Boolean): DoubleTensor =
-        foldDim({ x -> x.maxOrNull()!! }, dim, keepDim)
-
     override fun Tensor<Double>.mean(): Double = this.fold { it.sum() / tensor.numElements }
 
     override fun Tensor<Double>.mean(dim: Int, keepDim: Boolean): DoubleTensor =

kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/DoubleTensorAlgebra.kt

@@ -9,6 +9,8 @@ import space.kscience.kmath.nd.as2D
 import space.kscience.kmath.tensors.api.TensorPartialDivisionAlgebra
 import space.kscience.kmath.tensors.api.Tensor
 import space.kscience.kmath.tensors.core.*
+import space.kscience.kmath.tensors.core.algebras.DoubleAnalyticTensorAlgebra.fold
+import space.kscience.kmath.tensors.core.algebras.DoubleAnalyticTensorAlgebra.foldDim
 import space.kscience.kmath.tensors.core.broadcastOuterTensors
 import space.kscience.kmath.tensors.core.checkBufferShapeConsistency
 import space.kscience.kmath.tensors.core.checkEmptyDoubleBuffer
@@ -447,4 +449,16 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
 
     override fun Tensor<Double>.sum(dim: Int, keepDim: Boolean): DoubleTensor =
         foldDim({ x -> x.sum() }, dim, keepDim)
+
+
+    override fun Tensor<Double>.min(): Double = this.fold { it.minOrNull()!! }
+
+    override fun Tensor<Double>.min(dim: Int, keepDim: Boolean): DoubleTensor =
+        foldDim({ x -> x.minOrNull()!! }, dim, keepDim)
+
+    override fun Tensor<Double>.max(): Double = this.fold { it.maxOrNull()!! }
+
+    override fun Tensor<Double>.max(dim: Int, keepDim: Boolean): DoubleTensor =
+        foldDim({ x -> x.maxOrNull()!! }, dim, keepDim)
+
 }

kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleAnalyticTensorAlgebra.kt

@@ -2,7 +2,7 @@ package space.kscience.kmath.tensors.core
 
 import space.kscience.kmath.operations.invoke
 import space.kscience.kmath.tensors.core.algebras.DoubleAnalyticTensorAlgebra
-import space.kscience.kmath.tensors.core.algebras.DoubleAnalyticTensorAlgebra.tan
+import space.kscience.kmath.tensors.core.algebras.DoubleTensorAlgebra
 import kotlin.math.*
 import kotlin.test.Test
 import kotlin.test.assertTrue
@@ -106,7 +106,7 @@ internal class TestDoubleAnalyticTensorAlgebra {
     val tensor2 = DoubleTensor(shape2, buffer2)
 
     @Test
-    fun testMin() = DoubleAnalyticTensorAlgebra {
+    fun testMin() = DoubleTensorAlgebra {
         assertTrue { tensor2.min() == -3.0 }
         assertTrue { tensor2.min(0, true) eq fromArray(
             intArrayOf(1, 2),
@@ -119,7 +119,7 @@ internal class TestDoubleAnalyticTensorAlgebra {
     }
 
     @Test
-    fun testMax() = DoubleAnalyticTensorAlgebra {
+    fun testMax() = DoubleTensorAlgebra {
         assertTrue { tensor2.max() == 4.0 }
         assertTrue { tensor2.max(0, true) eq fromArray(
             intArrayOf(1, 2),
@@ -132,7 +132,7 @@ internal class TestDoubleAnalyticTensorAlgebra {
     }
 
     @Test
-    fun testSum() = DoubleAnalyticTensorAlgebra {
+    fun testSum() = DoubleTensorAlgebra {
         assertTrue { tensor2.sum() == 4.0 }
         assertTrue { tensor2.sum(0, true) eq fromArray(
             intArrayOf(1, 2),