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

@@ -2,7 +2,17 @@ package space.kscience.kmath.tensors
 
 
 public interface AnalyticTensorAlgebra<T, TensorType : TensorStructure<T>> :
-    TensorPartialDivisionAlgebra<T, TensorType> {
+    TensorPartialDivisionAlgebra<T, TensorType>,
+    OrderedTensorAlgebra<T, TensorType>{
+
+    //https://pytorch.org/docs/stable/generated/torch.quantile.html#torch.quantile
+    public fun TensorType.quantile(q: T, dim: Int, keepDim: Boolean): TensorType
+
+    //https://pytorch.org/docs/stable/generated/torch.std.html#torch.std
+    public fun TensorType.std(dim: Int, unbiased: Boolean, keepDim: Boolean): TensorType
+
+    //https://pytorch.org/docs/stable/generated/torch.var.html#torch.var
+    public fun TensorType.variance(dim: Int, unbiased: Boolean, keepDim: Boolean): TensorType
 
     //https://pytorch.org/docs/stable/generated/torch.exp.html
     public fun TensorType.exp(): TensorType
@@ -109,4 +119,7 @@ public interface AnalyticTensorAlgebra<T, TensorType : TensorStructure<T>> :
     //https://pytorch.org/docs/stable/generated/torch.trapz.html#torch.trapz
     public fun TensorType.trapz(xValues: TensorType, dim: Int): TensorType
 
+    //https://pytorch.org/docs/stable/generated/torch.histc.html#torch.histc
+    public fun TensorType.histc(bins: Int, min: T, max: T): TensorType
+
 }

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

@@ -2,7 +2,7 @@ package space.kscience.kmath.tensors
 
 public class DoubleAnalyticTensorAlgebra:
     AnalyticTensorAlgebra<Double, DoubleTensor>,
-    DoubleTensorAlgebra()
+    DoubleOrderedTensorAlgebra()
 {
     override fun DoubleTensor.exp(): DoubleTensor {
         TODO("Not yet implemented")
@@ -144,6 +144,22 @@ public class DoubleAnalyticTensorAlgebra:
         TODO("Not yet implemented")
     }
 
+    override fun DoubleTensor.quantile(q: Double, dim: Int, keepDim: Boolean): DoubleTensor {
+        TODO("Not yet implemented")
+    }
+
+    override fun DoubleTensor.std(dim: Int, unbiased: Boolean, keepDim: Boolean): DoubleTensor {
+        TODO("Not yet implemented")
+    }
+
+    override fun DoubleTensor.variance(dim: Int, unbiased: Boolean, keepDim: Boolean): DoubleTensor {
+        TODO("Not yet implemented")
+    }
+
+    override fun DoubleTensor.histc(bins: Int, min: Double, max: Double): DoubleTensor {
+        TODO("Not yet implemented")
+    }
+
 }
 
 public inline fun <R> DoubleAnalyticTensorAlgebra(block: DoubleAnalyticTensorAlgebra.() -> R): R =

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

@@ -1,6 +1,6 @@
 package space.kscience.kmath.tensors
 
-public class DoubleOrderedTensorAlgebra:
+public open class DoubleOrderedTensorAlgebra:
     OrderedTensorAlgebra<Double, DoubleTensor>,
     DoubleTensorAlgebra()
 {

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

@@ -0,0 +1,16 @@
+package space.kscience.kmath.tensors
+
+public class DoubleReduceOpsTensorAlgebra:
+    DoubleTensorAlgebra(),
+    ReduceOpsTensorAlgebra<Double, DoubleTensor>  {
+
+    override fun DoubleTensor.value(): Double {
+        check(this.shape contentEquals intArrayOf(1)) {
+            "Inconsistent value for tensor of shape ${shape.toList()}"
+        }
+        return this.buffer.array()[this.bufferStart]
+    }
+}
+
+public inline fun <R> DoubleReduceOpsTensorAlgebra(block: DoubleReduceOpsTensorAlgebra.() -> R): R =
+    DoubleReduceOpsTensorAlgebra().block()

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

@@ -3,13 +3,6 @@ package space.kscience.kmath.tensors
 
 public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double, DoubleTensor> {
 
-    override fun DoubleTensor.value(): Double {
-        check(this.shape contentEquals intArrayOf(1)) {
-            "Inconsistent value for tensor of shape ${shape.toList()}"
-        }
-        return this.buffer.array()[this.bufferStart]
-    }
-
     override operator fun DoubleTensor.get(i: Int): DoubleTensor {
         val lastShape = this.shape.drop(1).toIntArray()
         val newShape = if (lastShape.isNotEmpty()) lastShape else intArrayOf(1)
@@ -257,22 +250,6 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double, Dou
         TODO("Not yet implemented")
     }
 
-    override fun DoubleTensor.quantile(q: Double, dim: Int, keepDim: Boolean): DoubleTensor {
-        TODO("Not yet implemented")
-    }
-
-    override fun DoubleTensor.std(dim: Int, unbiased: Boolean, keepDim: Boolean): DoubleTensor {
-        TODO("Not yet implemented")
-    }
-
-    override fun DoubleTensor.variance(dim: Int, unbiased: Boolean, keepDim: Boolean): DoubleTensor {
-        TODO("Not yet implemented")
-    }
-
-    override fun DoubleTensor.histc(bins: Int, min: Double, max: Double): DoubleTensor {
-        TODO("Not yet implemented")
-    }
-
     override fun DoubleTensor.det(): DoubleTensor {
         TODO("Not yet implemented")
     }

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

@@ -0,0 +1,7 @@
+package space.kscience.kmath.tensors
+
+public interface ReduceOpsTensorAlgebra<T, TensorType : TensorStructure<T>> :
+    TensorAlgebra<T, TensorType> {
+    public fun TensorType.value(): T
+
+}

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

@@ -3,7 +3,6 @@ package space.kscience.kmath.tensors
 // https://proofwiki.org/wiki/Definition:Algebra_over_Ring
 public interface TensorAlgebra<T, TensorType : TensorStructure<T>> {
 
-    public fun TensorType.value(): T
 
     public fun zeros(shape: IntArray): TensorType
     public fun TensorType.zeroesLike(): TensorType

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

@@ -3,7 +3,6 @@ package space.kscience.kmath.tensors
 // https://proofwiki.org/wiki/Definition:Division_Algebra
 public interface TensorPartialDivisionAlgebra<T, TensorType : TensorStructure<T>> :
     TensorAlgebra<T, TensorType> {
-
     public operator fun TensorType.div(value: T): TensorType
     public operator fun TensorType.div(other: TensorType): TensorType
     public operator fun TensorType.divAssign(value: T)
@@ -11,17 +10,4 @@ public interface TensorPartialDivisionAlgebra<T, TensorType : TensorStructure<T>
 
     //https://pytorch.org/docs/stable/generated/torch.mean.html#torch.mean
     public fun TensorType.mean(dim: Int, keepDim: Boolean): TensorType
-
-    //https://pytorch.org/docs/stable/generated/torch.quantile.html#torch.quantile
-    public fun TensorType.quantile(q: T, dim: Int, keepDim: Boolean): TensorType
-
-    //https://pytorch.org/docs/stable/generated/torch.std.html#torch.std
-    public fun TensorType.std(dim: Int, unbiased: Boolean, keepDim: Boolean): TensorType
-
-    //https://pytorch.org/docs/stable/generated/torch.var.html#torch.var
-    public fun TensorType.variance(dim: Int, unbiased: Boolean, keepDim: Boolean): TensorType
-
-    //https://pytorch.org/docs/stable/generated/torch.histc.html#torch.histc
-    public fun TensorType.histc(bins: Int, min: T, max: T): TensorType
-
 }

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

@@ -1,6 +1,7 @@
 package space.kscience.kmath.tensors
 
 
+import space.kscience.kmath.nd.as1D
 import space.kscience.kmath.nd.as2D
 import space.kscience.kmath.structures.toDoubleArray
 import kotlin.test.Test
@@ -10,7 +11,7 @@ import kotlin.test.assertTrue
 class TestDoubleTensor {
 
     @Test
-    fun valueTest() = DoubleTensorAlgebra {
+    fun valueTest() = DoubleReduceOpsTensorAlgebra {
         val value = 12.5
         val tensor = DoubleTensor(intArrayOf(1), doubleArrayOf(value))
         assertEquals(tensor.value(), value)
@@ -28,5 +29,14 @@ class TestDoubleTensor {
         val tensor = DoubleTensor(intArrayOf(1,2,2), doubleArrayOf(3.5,5.8,58.4,2.4))
         val matrix = tensor[0].as2D()
         assertEquals(matrix[0,1], 5.8)
+
+        val vector = tensor[0][1].as1D()
+        assertEquals(vector[0], 58.4)
+
+        matrix[0,1] = 77.89
+        assertEquals(tensor[intArrayOf(0,0,1)], 77.89)
+
+        //vector[0] = 109.56
+        //println(tensor[intArrayOf(0,1,0)])
     }
 }