kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/Structure1D.kt

@@ -52,7 +52,7 @@ private inline class MutableStructure1DWrapper<T>(val structure: MutableNDStruct
 
     override fun get(index: Int): T = structure[index]
     override fun set(index: Int, value: T) {
-        set(index, value)
+        structure[intArrayOf(index)] = value
     }
 
     override fun copy(): MutableBuffer<T> =

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

@@ -11,9 +11,6 @@ public interface AnalyticTensorAlgebra<T, TensorType : TensorStructure<T>> :
     //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
 
@@ -23,9 +20,6 @@ public interface AnalyticTensorAlgebra<T, TensorType : TensorStructure<T>> :
     //https://pytorch.org/docs/stable/generated/torch.sqrt.html
     public fun TensorType.sqrt(): TensorType
 
-    //https://pytorch.org/docs/stable/generated/torch.square.html
-    public fun TensorType.square(): TensorType
-
     //https://pytorch.org/docs/stable/generated/torch.acos.html#torch.cos
     public fun TensorType.cos(): TensorType
 

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

@@ -16,10 +16,6 @@ public class DoubleAnalyticTensorAlgebra:
         TODO("Not yet implemented")
     }
 
-    override fun DoubleTensor.square(): DoubleTensor {
-        TODO("Not yet implemented")
-    }
-
     override fun DoubleTensor.cos(): DoubleTensor {
         TODO("Not yet implemented")
     }
@@ -152,10 +148,6 @@ public class DoubleAnalyticTensorAlgebra:
         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")
     }

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

@@ -254,6 +254,14 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double, Dou
         TODO("Not yet implemented")
     }
 
+    override fun DoubleTensor.square(): DoubleTensor {
+        TODO("Not yet implemented")
+    }
+
+    override fun DoubleTensor.variance(dim: Int, unbiased: Boolean, keepDim: Boolean): DoubleTensor {
+        TODO("Not yet implemented")
+    }
+
 }
 
 public inline fun <R> DoubleTensorAlgebra(block: DoubleTensorAlgebra.() -> R): R =

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

@@ -40,6 +40,9 @@ public interface TensorAlgebra<T, TensorType : TensorStructure<T>> {
     public operator fun TensorType.timesAssign(other: TensorType): Unit
     public operator fun TensorType.unaryMinus(): TensorType
 
+    //https://pytorch.org/docs/stable/generated/torch.square.html
+    public fun TensorType.square(): TensorType
+
     //https://pytorch.org/cppdocs/notes/tensor_indexing.html
     public operator fun TensorType.get(i: Int): TensorType
 

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

@@ -10,4 +10,7 @@ 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.var.html#torch.var
+    public fun TensorType.variance(dim: Int, unbiased: Boolean, keepDim: Boolean): TensorType
 }

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

@@ -36,7 +36,7 @@ class TestDoubleTensor {
         matrix[0,1] = 77.89
         assertEquals(tensor[intArrayOf(0,0,1)], 77.89)
 
-        //vector[0] = 109.56
+        vector[0] = 109.56
-        //println(tensor[intArrayOf(0,1,0)])
+        assertEquals(tensor[intArrayOf(0,1,0)], 109.56)
     }
 }