From 6be5caa93f4086e222677a55d15edaca707b16f0 Mon Sep 17 00:00:00 2001
From: Roland Grinis <roland.grinis@grinisrit.com>
Date: Fri, 30 Apr 2021 14:44:42 +0100
Subject: [PATCH] No secondary constructors

---
 .../kmath/tensors/core/BufferedTensor.kt      | 25 +++----
 .../algebras/BroadcastDoubleTensorAlgebra.kt  | 28 ++++----
 .../algebras/DoubleLinearOpsTensorAlgebra.kt  |  2 +-
 .../core/algebras/DoubleTensorAlgebra.kt      | 68 +++++++++----------
 .../kmath/tensors/core/broadcastUtils.kt      | 10 +--
 .../kscience/kmath/tensors/core/linUtils.kt   | 14 ++--
 .../kmath/tensors/core/TestBroadcasting.kt    | 20 +++---
 .../core/TestDoubleAnalyticTensorAlgebra.kt   |  2 +-
 .../core/TestDoubleLinearOpsAlgebra.kt        |  4 +-
 .../kmath/tensors/core/TestDoubleTensor.kt    |  5 +-
 .../tensors/core/TestDoubleTensorAlgebra.kt   | 34 +++++-----
 11 files changed, 103 insertions(+), 109 deletions(-)

diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/BufferedTensor.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/BufferedTensor.kt
index 6e1cab11a..fae59804d 100644
--- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/BufferedTensor.kt
+++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/BufferedTensor.kt
@@ -8,7 +8,7 @@ import space.kscience.kmath.tensors.core.algebras.TensorLinearStructure
 
 public open class BufferedTensor<T>(
     override val shape: IntArray,
-    internal val buffer: MutableBuffer<T>,
+    internal val mutableBuffer: MutableBuffer<T>,
     internal val bufferStart: Int
 ) : TensorStructure<T> {
     public val linearStructure: TensorLinearStructure
@@ -17,10 +17,10 @@ public open class BufferedTensor<T>(
     public val numElements: Int
         get() = linearStructure.size
 
-    override fun get(index: IntArray): T = buffer[bufferStart + linearStructure.offset(index)]
+    override fun get(index: IntArray): T = mutableBuffer[bufferStart + linearStructure.offset(index)]
 
     override fun set(index: IntArray, value: T) {
-        buffer[bufferStart + linearStructure.offset(index)] = value
+        mutableBuffer[bufferStart + linearStructure.offset(index)] = value
     }
 
     override fun elements(): Sequence<Pair<IntArray, T>> = linearStructure.indices().map {
@@ -37,33 +37,28 @@ public class IntTensor internal constructor(
     shape: IntArray,
     buffer: IntArray,
     offset: Int = 0
-) : BufferedTensor<Int>(shape, IntBuffer(buffer), offset) {
-    internal constructor(bufferedTensor: BufferedTensor<Int>) :
-            this(bufferedTensor.shape, bufferedTensor.buffer.array(), bufferedTensor.bufferStart)
-}
+) : BufferedTensor<Int>(shape, IntBuffer(buffer), offset)
 
 public class DoubleTensor internal constructor(
     shape: IntArray,
     buffer: DoubleArray,
     offset: Int = 0
 ) : BufferedTensor<Double>(shape, DoubleBuffer(buffer), offset) {
-    internal constructor(bufferedTensor: BufferedTensor<Double>) :
-            this(bufferedTensor.shape, bufferedTensor.buffer.array(), bufferedTensor.bufferStart)
-
     override fun toString(): String = toPrettyString()
-
 }
 
-internal inline fun BufferedTensor<Int>.asTensor(): IntTensor = IntTensor(this)
-internal inline fun BufferedTensor<Double>.asTensor(): DoubleTensor = DoubleTensor(this)
+internal fun BufferedTensor<Int>.asTensor(): IntTensor =
+    IntTensor(this.shape, this.mutableBuffer.array(), this.bufferStart)
+internal fun BufferedTensor<Double>.asTensor(): DoubleTensor =
+    DoubleTensor(this.shape, this.mutableBuffer.array(), this.bufferStart)
 
-internal inline fun <T> TensorStructure<T>.copyToBufferedTensor(): BufferedTensor<T> =
+internal fun <T> TensorStructure<T>.copyToBufferedTensor(): BufferedTensor<T> =
     BufferedTensor(
         this.shape,
         TensorLinearStructure(this.shape).indices().map(this::get).toMutableList().asMutableBuffer(), 0
     )
 
-internal inline fun <T> TensorStructure<T>.toBufferedTensor(): BufferedTensor<T> = when (this) {
+internal fun <T> TensorStructure<T>.toBufferedTensor(): BufferedTensor<T> = when (this) {
     is BufferedTensor<T> -> this
     is MutableBufferND<T> -> if (this.strides.strides.toIntArray() contentEquals TensorLinearStructure(this.shape).strides)
         BufferedTensor(this.shape, this.mutableBuffer, 0) else this.copyToBufferedTensor()
diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/BroadcastDoubleTensorAlgebra.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/BroadcastDoubleTensorAlgebra.kt
index fa64092d6..350d939af 100644
--- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/BroadcastDoubleTensorAlgebra.kt
+++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/BroadcastDoubleTensorAlgebra.kt
@@ -21,7 +21,7 @@ public object BroadcastDoubleTensorAlgebra : DoubleTensorAlgebra() {
         val newThis = broadcast[0]
         val newOther = broadcast[1]
         val resBuffer = DoubleArray(newThis.linearStructure.size) { i ->
-            newThis.buffer.array()[i] + newOther.buffer.array()[i]
+            newThis.mutableBuffer.array()[i] + newOther.mutableBuffer.array()[i]
         }
         return DoubleTensor(newThis.shape, resBuffer)
     }
@@ -29,8 +29,8 @@ public object BroadcastDoubleTensorAlgebra : DoubleTensorAlgebra() {
     override fun TensorStructure<Double>.plusAssign(other: TensorStructure<Double>) {
         val newOther = broadcastTo(other.tensor, tensor.shape)
         for (i in 0 until tensor.linearStructure.size) {
-            tensor.buffer.array()[tensor.bufferStart + i] +=
-                newOther.buffer.array()[tensor.bufferStart + i]
+            tensor.mutableBuffer.array()[tensor.bufferStart + i] +=
+                newOther.mutableBuffer.array()[tensor.bufferStart + i]
         }
     }
 
@@ -39,7 +39,7 @@ public object BroadcastDoubleTensorAlgebra : DoubleTensorAlgebra() {
         val newThis = broadcast[0]
         val newOther = broadcast[1]
         val resBuffer = DoubleArray(newThis.linearStructure.size) { i ->
-            newThis.buffer.array()[i] - newOther.buffer.array()[i]
+            newThis.mutableBuffer.array()[i] - newOther.mutableBuffer.array()[i]
         }
         return DoubleTensor(newThis.shape, resBuffer)
     }
@@ -47,8 +47,8 @@ public object BroadcastDoubleTensorAlgebra : DoubleTensorAlgebra() {
     override fun TensorStructure<Double>.minusAssign(other: TensorStructure<Double>) {
         val newOther = broadcastTo(other.tensor, tensor.shape)
         for (i in 0 until tensor.linearStructure.size) {
-            tensor.buffer.array()[tensor.bufferStart + i] -=
-                newOther.buffer.array()[tensor.bufferStart + i]
+            tensor.mutableBuffer.array()[tensor.bufferStart + i] -=
+                newOther.mutableBuffer.array()[tensor.bufferStart + i]
         }
     }
 
@@ -57,8 +57,8 @@ public object BroadcastDoubleTensorAlgebra : DoubleTensorAlgebra() {
         val newThis = broadcast[0]
         val newOther = broadcast[1]
         val resBuffer = DoubleArray(newThis.linearStructure.size) { i ->
-            newThis.buffer.array()[newThis.bufferStart + i] *
-                    newOther.buffer.array()[newOther.bufferStart + i]
+            newThis.mutableBuffer.array()[newThis.bufferStart + i] *
+                    newOther.mutableBuffer.array()[newOther.bufferStart + i]
         }
         return DoubleTensor(newThis.shape, resBuffer)
     }
@@ -66,8 +66,8 @@ public object BroadcastDoubleTensorAlgebra : DoubleTensorAlgebra() {
     override fun TensorStructure<Double>.timesAssign(other: TensorStructure<Double>) {
         val newOther = broadcastTo(other.tensor, tensor.shape)
         for (i in 0 until tensor.linearStructure.size) {
-            tensor.buffer.array()[tensor.bufferStart + i] *=
-                newOther.buffer.array()[tensor.bufferStart + i]
+            tensor.mutableBuffer.array()[tensor.bufferStart + i] *=
+                newOther.mutableBuffer.array()[tensor.bufferStart + i]
         }
     }
 
@@ -76,8 +76,8 @@ public object BroadcastDoubleTensorAlgebra : DoubleTensorAlgebra() {
         val newThis = broadcast[0]
         val newOther = broadcast[1]
         val resBuffer = DoubleArray(newThis.linearStructure.size) { i ->
-            newThis.buffer.array()[newOther.bufferStart + i] /
-                    newOther.buffer.array()[newOther.bufferStart + i]
+            newThis.mutableBuffer.array()[newOther.bufferStart + i] /
+                    newOther.mutableBuffer.array()[newOther.bufferStart + i]
         }
         return DoubleTensor(newThis.shape, resBuffer)
     }
@@ -85,8 +85,8 @@ public object BroadcastDoubleTensorAlgebra : DoubleTensorAlgebra() {
     override fun TensorStructure<Double>.divAssign(other: TensorStructure<Double>) {
         val newOther = broadcastTo(other.tensor, tensor.shape)
         for (i in 0 until tensor.linearStructure.size) {
-            tensor.buffer.array()[tensor.bufferStart + i] /=
-                newOther.buffer.array()[tensor.bufferStart + i]
+            tensor.mutableBuffer.array()[tensor.bufferStart + i] /=
+                newOther.mutableBuffer.array()[tensor.bufferStart + i]
         }
     }
 }
\ No newline at end of file
diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/DoubleLinearOpsTensorAlgebra.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/DoubleLinearOpsTensorAlgebra.kt
index 975755656..ab73b25b1 100644
--- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/DoubleLinearOpsTensorAlgebra.kt
+++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/DoubleLinearOpsTensorAlgebra.kt
@@ -106,7 +106,7 @@ public object DoubleLinearOpsTensorAlgebra :
             val matrixSize = matrix.shape.reduce { acc, i -> acc * i }
             val curMatrix = DoubleTensor(
                 matrix.shape,
-                matrix.buffer.array().slice(matrix.bufferStart until matrix.bufferStart + matrixSize).toDoubleArray()
+                matrix.mutableBuffer.array().slice(matrix.bufferStart until matrix.bufferStart + matrixSize).toDoubleArray()
             )
             svdHelper(curMatrix, USV, m, n, epsilon)
         }
diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/DoubleTensorAlgebra.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/DoubleTensorAlgebra.kt
index 8729358cc..f428b9d2e 100644
--- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/DoubleTensorAlgebra.kt
+++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/DoubleTensorAlgebra.kt
@@ -29,7 +29,7 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
         check(tensor.shape contentEquals intArrayOf(1)) {
             "Inconsistent value for tensor of shape ${shape.toList()}"
         }
-        return tensor.buffer.array()[tensor.bufferStart]
+        return tensor.mutableBuffer.array()[tensor.bufferStart]
     }
 
     public fun fromArray(shape: IntArray, buffer: DoubleArray): DoubleTensor {
@@ -43,7 +43,7 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
         val lastShape = tensor.shape.drop(1).toIntArray()
         val newShape = if (lastShape.isNotEmpty()) lastShape else intArrayOf(1)
         val newStart = newShape.reduce(Int::times) * i + tensor.bufferStart
-        return DoubleTensor(newShape, tensor.buffer.array(), newStart)
+        return DoubleTensor(newShape, tensor.mutableBuffer.array(), newStart)
     }
 
     public fun full(value: Double, shape: IntArray): DoubleTensor {
@@ -77,12 +77,12 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
     }
 
     public fun TensorStructure<Double>.copy(): DoubleTensor {
-        return DoubleTensor(tensor.shape, tensor.buffer.array().copyOf(), tensor.bufferStart)
+        return DoubleTensor(tensor.shape, tensor.mutableBuffer.array().copyOf(), tensor.bufferStart)
     }
 
     override fun Double.plus(other: TensorStructure<Double>): DoubleTensor {
         val resBuffer = DoubleArray(other.tensor.numElements) { i ->
-            other.tensor.buffer.array()[other.tensor.bufferStart + i] + this
+            other.tensor.mutableBuffer.array()[other.tensor.bufferStart + i] + this
         }
         return DoubleTensor(other.shape, resBuffer)
     }
@@ -92,35 +92,35 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
     override fun TensorStructure<Double>.plus(other: TensorStructure<Double>): DoubleTensor {
         checkShapesCompatible(tensor, other.tensor)
         val resBuffer = DoubleArray(tensor.numElements) { i ->
-            tensor.buffer.array()[i] + other.tensor.buffer.array()[i]
+            tensor.mutableBuffer.array()[i] + other.tensor.mutableBuffer.array()[i]
         }
         return DoubleTensor(tensor.shape, resBuffer)
     }
 
     override fun TensorStructure<Double>.plusAssign(value: Double) {
         for (i in 0 until tensor.numElements) {
-            tensor.buffer.array()[tensor.bufferStart + i] += value
+            tensor.mutableBuffer.array()[tensor.bufferStart + i] += value
         }
     }
 
     override fun TensorStructure<Double>.plusAssign(other: TensorStructure<Double>) {
         checkShapesCompatible(tensor, other.tensor)
         for (i in 0 until tensor.numElements) {
-            tensor.buffer.array()[tensor.bufferStart + i] +=
-                other.tensor.buffer.array()[tensor.bufferStart + i]
+            tensor.mutableBuffer.array()[tensor.bufferStart + i] +=
+                other.tensor.mutableBuffer.array()[tensor.bufferStart + i]
         }
     }
 
     override fun Double.minus(other: TensorStructure<Double>): DoubleTensor {
         val resBuffer = DoubleArray(other.tensor.numElements) { i ->
-            this - other.tensor.buffer.array()[other.tensor.bufferStart + i]
+            this - other.tensor.mutableBuffer.array()[other.tensor.bufferStart + i]
         }
         return DoubleTensor(other.shape, resBuffer)
     }
 
     override fun TensorStructure<Double>.minus(value: Double): DoubleTensor {
         val resBuffer = DoubleArray(tensor.numElements) { i ->
-            tensor.buffer.array()[tensor.bufferStart + i] - value
+            tensor.mutableBuffer.array()[tensor.bufferStart + i] - value
         }
         return DoubleTensor(tensor.shape, resBuffer)
     }
@@ -128,28 +128,28 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
     override fun TensorStructure<Double>.minus(other: TensorStructure<Double>): DoubleTensor {
         checkShapesCompatible(tensor, other)
         val resBuffer = DoubleArray(tensor.numElements) { i ->
-            tensor.buffer.array()[i] - other.tensor.buffer.array()[i]
+            tensor.mutableBuffer.array()[i] - other.tensor.mutableBuffer.array()[i]
         }
         return DoubleTensor(tensor.shape, resBuffer)
     }
 
     override fun TensorStructure<Double>.minusAssign(value: Double) {
         for (i in 0 until tensor.numElements) {
-            tensor.buffer.array()[tensor.bufferStart + i] -= value
+            tensor.mutableBuffer.array()[tensor.bufferStart + i] -= value
         }
     }
 
     override fun TensorStructure<Double>.minusAssign(other: TensorStructure<Double>) {
         checkShapesCompatible(tensor, other)
         for (i in 0 until tensor.numElements) {
-            tensor.buffer.array()[tensor.bufferStart + i] -=
-                other.tensor.buffer.array()[tensor.bufferStart + i]
+            tensor.mutableBuffer.array()[tensor.bufferStart + i] -=
+                other.tensor.mutableBuffer.array()[tensor.bufferStart + i]
         }
     }
 
     override fun Double.times(other: TensorStructure<Double>): DoubleTensor {
         val resBuffer = DoubleArray(other.tensor.numElements) { i ->
-            other.tensor.buffer.array()[other.tensor.bufferStart + i] * this
+            other.tensor.mutableBuffer.array()[other.tensor.bufferStart + i] * this
         }
         return DoubleTensor(other.shape, resBuffer)
     }
@@ -159,36 +159,36 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
     override fun TensorStructure<Double>.times(other: TensorStructure<Double>): DoubleTensor {
         checkShapesCompatible(tensor, other)
         val resBuffer = DoubleArray(tensor.numElements) { i ->
-            tensor.buffer.array()[tensor.bufferStart + i] *
-                    other.tensor.buffer.array()[other.tensor.bufferStart + i]
+            tensor.mutableBuffer.array()[tensor.bufferStart + i] *
+                    other.tensor.mutableBuffer.array()[other.tensor.bufferStart + i]
         }
         return DoubleTensor(tensor.shape, resBuffer)
     }
 
     override fun TensorStructure<Double>.timesAssign(value: Double) {
         for (i in 0 until tensor.numElements) {
-            tensor.buffer.array()[tensor.bufferStart + i] *= value
+            tensor.mutableBuffer.array()[tensor.bufferStart + i] *= value
         }
     }
 
     override fun TensorStructure<Double>.timesAssign(other: TensorStructure<Double>) {
         checkShapesCompatible(tensor, other)
         for (i in 0 until tensor.numElements) {
-            tensor.buffer.array()[tensor.bufferStart + i] *=
-                other.tensor.buffer.array()[tensor.bufferStart + i]
+            tensor.mutableBuffer.array()[tensor.bufferStart + i] *=
+                other.tensor.mutableBuffer.array()[tensor.bufferStart + i]
         }
     }
 
     override fun Double.div(other: TensorStructure<Double>): DoubleTensor {
         val resBuffer = DoubleArray(other.tensor.numElements) { i ->
-            this / other.tensor.buffer.array()[other.tensor.bufferStart + i]
+            this / other.tensor.mutableBuffer.array()[other.tensor.bufferStart + i]
         }
         return DoubleTensor(other.shape, resBuffer)
     }
 
     override fun TensorStructure<Double>.div(value: Double): DoubleTensor {
         val resBuffer = DoubleArray(tensor.numElements) { i ->
-            tensor.buffer.array()[tensor.bufferStart + i] / value
+            tensor.mutableBuffer.array()[tensor.bufferStart + i] / value
         }
         return DoubleTensor(shape, resBuffer)
     }
@@ -196,29 +196,29 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
     override fun TensorStructure<Double>.div(other: TensorStructure<Double>): DoubleTensor {
         checkShapesCompatible(tensor, other)
         val resBuffer = DoubleArray(tensor.numElements) { i ->
-            tensor.buffer.array()[other.tensor.bufferStart + i] /
-                    other.tensor.buffer.array()[other.tensor.bufferStart + i]
+            tensor.mutableBuffer.array()[other.tensor.bufferStart + i] /
+                    other.tensor.mutableBuffer.array()[other.tensor.bufferStart + i]
         }
         return DoubleTensor(tensor.shape, resBuffer)
     }
 
     override fun TensorStructure<Double>.divAssign(value: Double) {
         for (i in 0 until tensor.numElements) {
-            tensor.buffer.array()[tensor.bufferStart + i] /= value
+            tensor.mutableBuffer.array()[tensor.bufferStart + i] /= value
         }
     }
 
     override fun TensorStructure<Double>.divAssign(other: TensorStructure<Double>) {
         checkShapesCompatible(tensor, other)
         for (i in 0 until tensor.numElements) {
-            tensor.buffer.array()[tensor.bufferStart + i] /=
-                other.tensor.buffer.array()[tensor.bufferStart + i]
+            tensor.mutableBuffer.array()[tensor.bufferStart + i] /=
+                other.tensor.mutableBuffer.array()[tensor.bufferStart + i]
         }
     }
 
     override fun TensorStructure<Double>.unaryMinus(): DoubleTensor {
         val resBuffer = DoubleArray(tensor.numElements) { i ->
-            tensor.buffer.array()[tensor.bufferStart + i].unaryMinus()
+            tensor.mutableBuffer.array()[tensor.bufferStart + i].unaryMinus()
         }
         return DoubleTensor(tensor.shape, resBuffer)
     }
@@ -241,8 +241,8 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
             newMultiIndex[ii] = newMultiIndex[jj].also { newMultiIndex[jj] = newMultiIndex[ii] }
 
             val linearIndex = resTensor.linearStructure.offset(newMultiIndex)
-            resTensor.buffer.array()[linearIndex] =
-                tensor.buffer.array()[tensor.bufferStart + offset]
+            resTensor.mutableBuffer.array()[linearIndex] =
+                tensor.mutableBuffer.array()[tensor.bufferStart + offset]
         }
         return resTensor
     }
@@ -250,7 +250,7 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
 
     override fun TensorStructure<Double>.view(shape: IntArray): DoubleTensor {
         checkView(tensor, shape)
-        return DoubleTensor(shape, tensor.buffer.array(), tensor.bufferStart)
+        return DoubleTensor(shape, tensor.mutableBuffer.array(), tensor.bufferStart)
     }
 
     override fun TensorStructure<Double>.viewAs(other: TensorStructure<Double>): DoubleTensor {
@@ -259,7 +259,7 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
 
     override infix fun TensorStructure<Double>.dot(other: TensorStructure<Double>): DoubleTensor {
         if (tensor.shape.size == 1 && other.shape.size == 1) {
-            return DoubleTensor(intArrayOf(1), doubleArrayOf(tensor.times(other).tensor.buffer.array().sum()))
+            return DoubleTensor(intArrayOf(1), doubleArrayOf(tensor.times(other).tensor.mutableBuffer.array().sum()))
         }
 
         var newThis = tensor.copy()
@@ -361,7 +361,7 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
     public fun TensorStructure<Double>.map(transform: (Double) -> Double): DoubleTensor {
         return DoubleTensor(
             tensor.shape,
-            tensor.buffer.array().map { transform(it) }.toDoubleArray(),
+            tensor.mutableBuffer.array().map { transform(it) }.toDoubleArray(),
             tensor.bufferStart
         )
     }
@@ -382,7 +382,7 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
             return false
         }
         for (i in 0 until n) {
-            if (!eqFunction(tensor.buffer[tensor.bufferStart + i], other.tensor.buffer[other.tensor.bufferStart + i])) {
+            if (!eqFunction(tensor.mutableBuffer[tensor.bufferStart + i], other.tensor.mutableBuffer[other.tensor.bufferStart + i])) {
                 return false
             }
         }
diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/broadcastUtils.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/broadcastUtils.kt
index 71ccbf97b..2d4d6f0f7 100644
--- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/broadcastUtils.kt
+++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/broadcastUtils.kt
@@ -18,8 +18,8 @@ internal inline fun multiIndexBroadCasting(tensor: DoubleTensor, resTensor: Doub
         }
 
         val curLinearIndex = tensor.linearStructure.offset(curMultiIndex)
-        resTensor.buffer.array()[linearIndex] =
-            tensor.buffer.array()[tensor.bufferStart + curLinearIndex]
+        resTensor.mutableBuffer.array()[linearIndex] =
+            tensor.mutableBuffer.array()[tensor.bufferStart + curLinearIndex]
     }
 }
 
@@ -113,7 +113,7 @@ internal inline fun broadcastOuterTensors(vararg tensors: DoubleTensor): List<Do
             var curMultiIndex = tensor.shape.sliceArray(0..tensor.shape.size - 3).copyOf()
             curMultiIndex = IntArray(totalMultiIndex.size - curMultiIndex.size) { 1 } + curMultiIndex
 
-            val newTensor = DoubleTensor(curMultiIndex + matrixShape, tensor.buffer.array())
+            val newTensor = DoubleTensor(curMultiIndex + matrixShape, tensor.mutableBuffer.array())
 
             for (i in curMultiIndex.indices) {
                 if (curMultiIndex[i] != 1) {
@@ -133,8 +133,8 @@ internal inline fun broadcastOuterTensors(vararg tensors: DoubleTensor): List<Do
                             matrix.linearStructure.index(i)
                 )
 
-                resTensor.buffer.array()[resTensor.bufferStart + newLinearIndex] =
-                    newTensor.buffer.array()[newTensor.bufferStart + curLinearIndex]
+                resTensor.mutableBuffer.array()[resTensor.bufferStart + newLinearIndex] =
+                    newTensor.mutableBuffer.array()[newTensor.bufferStart + curLinearIndex]
             }
         }
         res += resTensor
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 c7a730018..776a5e4d5 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
@@ -18,7 +18,7 @@ internal inline fun <T> BufferedTensor<T>.vectorSequence(): Sequence<BufferedTen
     val vectorOffset = shape[n - 1]
     val vectorShape = intArrayOf(shape.last())
     for (offset in 0 until numElements step vectorOffset) {
-        val vector = BufferedTensor(vectorShape, buffer, offset)
+        val vector = BufferedTensor(vectorShape, mutableBuffer, offset)
         yield(vector)
     }
 }
@@ -29,7 +29,7 @@ internal inline fun <T> BufferedTensor<T>.matrixSequence(): Sequence<BufferedTen
     val matrixOffset = shape[n - 1] * shape[n - 2]
     val matrixShape = intArrayOf(shape[n - 2], shape[n - 1])
     for (offset in 0 until numElements step matrixOffset) {
-        val matrix = BufferedTensor(matrixShape, buffer, offset)
+        val matrix = BufferedTensor(matrixShape, mutableBuffer, offset)
         yield(matrix)
     }
 }
@@ -322,16 +322,16 @@ internal inline fun DoubleLinearOpsTensorAlgebra.svdHelper(
     }
 
     val s = res.map { it.first }.toDoubleArray()
-    val uBuffer = res.map { it.second }.flatMap { it.buffer.array().toList() }.toDoubleArray()
-    val vBuffer = res.map { it.third }.flatMap { it.buffer.array().toList() }.toDoubleArray()
+    val uBuffer = res.map { it.second }.flatMap { it.mutableBuffer.array().toList() }.toDoubleArray()
+    val vBuffer = res.map { it.third }.flatMap { it.mutableBuffer.array().toList() }.toDoubleArray()
     for (i in uBuffer.indices) {
-        matrixU.buffer.array()[matrixU.bufferStart + i] = uBuffer[i]
+        matrixU.mutableBuffer.array()[matrixU.bufferStart + i] = uBuffer[i]
     }
     for (i in s.indices) {
-        matrixS.buffer.array()[matrixS.bufferStart + i] = s[i]
+        matrixS.mutableBuffer.array()[matrixS.bufferStart + i] = s[i]
     }
     for (i in vBuffer.indices) {
-        matrixV.buffer.array()[matrixV.bufferStart + i] = vBuffer[i]
+        matrixV.mutableBuffer.array()[matrixV.bufferStart + i] = vBuffer[i]
     }
 }
 
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 207dd1c98..1070a1115 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
@@ -30,7 +30,7 @@ internal class TestBroadcasting {
 
         val res = broadcastTo(tensor2, tensor1.shape)
         assertTrue(res.shape contentEquals intArrayOf(2, 3))
-        assertTrue(res.buffer.array() contentEquals doubleArrayOf(10.0, 20.0, 30.0, 10.0, 20.0, 30.0))
+        assertTrue(res.mutableBuffer.array() contentEquals doubleArrayOf(10.0, 20.0, 30.0, 10.0, 20.0, 30.0))
     }
 
     @Test
@@ -45,9 +45,9 @@ internal class TestBroadcasting {
         assertTrue(res[1].shape contentEquals intArrayOf(1, 2, 3))
         assertTrue(res[2].shape contentEquals intArrayOf(1, 2, 3))
 
-        assertTrue(res[0].buffer.array() contentEquals doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0))
-        assertTrue(res[1].buffer.array() contentEquals doubleArrayOf(10.0, 20.0, 30.0, 10.0, 20.0, 30.0))
-        assertTrue(res[2].buffer.array() contentEquals doubleArrayOf(500.0, 500.0, 500.0, 500.0, 500.0, 500.0))
+        assertTrue(res[0].mutableBuffer.array() contentEquals doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0))
+        assertTrue(res[1].mutableBuffer.array() contentEquals doubleArrayOf(10.0, 20.0, 30.0, 10.0, 20.0, 30.0))
+        assertTrue(res[2].mutableBuffer.array() contentEquals doubleArrayOf(500.0, 500.0, 500.0, 500.0, 500.0, 500.0))
     }
 
     @Test
@@ -62,9 +62,9 @@ internal class TestBroadcasting {
         assertTrue(res[1].shape contentEquals intArrayOf(1, 1, 3))
         assertTrue(res[2].shape contentEquals intArrayOf(1, 1, 1))
 
-        assertTrue(res[0].buffer.array() contentEquals doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0))
-        assertTrue(res[1].buffer.array() contentEquals doubleArrayOf(10.0, 20.0, 30.0))
-        assertTrue(res[2].buffer.array() contentEquals doubleArrayOf(500.0))
+        assertTrue(res[0].mutableBuffer.array() contentEquals doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0))
+        assertTrue(res[1].mutableBuffer.array() contentEquals doubleArrayOf(10.0, 20.0, 30.0))
+        assertTrue(res[2].mutableBuffer.array() contentEquals doubleArrayOf(500.0))
     }
 
     @Test
@@ -91,16 +91,16 @@ internal class TestBroadcasting {
         val tensor32 = tensor3 - tensor2
 
         assertTrue(tensor21.shape contentEquals intArrayOf(2, 3))
-        assertTrue(tensor21.buffer.array() contentEquals doubleArrayOf(9.0, 18.0, 27.0, 6.0, 15.0, 24.0))
+        assertTrue(tensor21.mutableBuffer.array() contentEquals doubleArrayOf(9.0, 18.0, 27.0, 6.0, 15.0, 24.0))
 
         assertTrue(tensor31.shape contentEquals intArrayOf(1, 2, 3))
         assertTrue(
-            tensor31.buffer.array()
+            tensor31.mutableBuffer.array()
                     contentEquals doubleArrayOf(499.0, 498.0, 497.0, 496.0, 495.0, 494.0)
         )
 
         assertTrue(tensor32.shape contentEquals intArrayOf(1, 1, 3))
-        assertTrue(tensor32.buffer.array() contentEquals doubleArrayOf(490.0, 480.0, 470.0))
+        assertTrue(tensor32.mutableBuffer.array() contentEquals doubleArrayOf(490.0, 480.0, 470.0))
     }
 
 }
\ No newline at end of file
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 3b3e22acc..66959a0de 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
@@ -30,7 +30,7 @@ internal class TestDoubleAnalyticTensorAlgebra {
     fun testExp() = DoubleAnalyticTensorAlgebra.invoke {
         tensor.exp().let {
             assertTrue { shape contentEquals it.shape }
-            assertTrue { buffer.fmap(::exp).epsEqual(it.buffer.array())}
+            assertTrue { buffer.fmap(::exp).epsEqual(it.mutableBuffer.array())}
         }
     }
 }
\ No newline at end of file
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 aa68340d4..1148c0aad 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
@@ -151,8 +151,8 @@ internal class TestDoubleLinearOpsTensorAlgebra {
         val res = svd1d(tensor2)
 
         assertTrue(res.shape contentEquals intArrayOf(2))
-        assertTrue { abs(abs(res.buffer.array()[res.bufferStart]) - 0.386) < 0.01 }
-        assertTrue { abs(abs(res.buffer.array()[res.bufferStart + 1]) - 0.922) < 0.01 }
+        assertTrue { abs(abs(res.mutableBuffer.array()[res.bufferStart]) - 0.386) < 0.01 }
+        assertTrue { abs(abs(res.mutableBuffer.array()[res.bufferStart + 1]) - 0.922) < 0.01 }
     }
 
     @Test
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 20acc0901..eca54f68b 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
@@ -6,7 +6,6 @@ import space.kscience.kmath.nd.as1D
 import space.kscience.kmath.nd.as2D
 import space.kscience.kmath.operations.invoke
 import space.kscience.kmath.structures.DoubleBuffer
-import space.kscience.kmath.structures.asMutableBuffer
 import space.kscience.kmath.structures.toDoubleArray
 import space.kscience.kmath.tensors.core.algebras.DoubleTensorAlgebra
 import kotlin.test.Test
@@ -27,7 +26,7 @@ internal class TestDoubleTensor {
         val tensor = fromArray(intArrayOf(2, 2), doubleArrayOf(3.5, 5.8, 58.4, 2.4))
         assertEquals(tensor[intArrayOf(0, 1)], 5.8)
         assertTrue(
-            tensor.elements().map { it.second }.toList().toDoubleArray() contentEquals tensor.buffer.toDoubleArray()
+            tensor.elements().map { it.second }.toList().toDoubleArray() contentEquals tensor.mutableBuffer.toDoubleArray()
         )
     }
 
@@ -71,7 +70,7 @@ internal class TestDoubleTensor {
         val tensorArrayPublic = ndArray.toTypedTensor() // public API, data copied twice
         val sharedTensorArray = tensorArrayPublic.toTypedTensor() // no data copied by matching type
 
-        assertTrue(tensorArray.buffer.array() contentEquals sharedTensorArray.buffer.array())
+        assertTrue(tensorArray.mutableBuffer.array() contentEquals sharedTensorArray.mutableBuffer.array())
 
         tensorArray[intArrayOf(0)] = 55.9
         assertEquals(tensorArrayPublic[intArrayOf(0)], 1.0)
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 115016974..34fe5d5f1 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
@@ -13,21 +13,21 @@ internal class TestDoubleTensorAlgebra {
     fun doublePlus() = DoubleTensorAlgebra.invoke {
         val tensor = fromArray(intArrayOf(2), doubleArrayOf(1.0, 2.0))
         val res = 10.0 + tensor
-        assertTrue(res.buffer.array() contentEquals doubleArrayOf(11.0, 12.0))
+        assertTrue(res.mutableBuffer.array() contentEquals doubleArrayOf(11.0, 12.0))
     }
 
     @Test
     fun doubleDiv() = DoubleTensorAlgebra.invoke {
         val tensor = fromArray(intArrayOf(2), doubleArrayOf(2.0, 4.0))
         val res = 2.0/tensor
-        assertTrue(res.buffer.array() contentEquals doubleArrayOf(1.0, 0.5))
+        assertTrue(res.mutableBuffer.array() contentEquals doubleArrayOf(1.0, 0.5))
     }
 
     @Test
     fun divDouble() = DoubleTensorAlgebra.invoke {
         val tensor = fromArray(intArrayOf(2), doubleArrayOf(10.0, 5.0))
         val res = tensor / 2.5
-        assertTrue(res.buffer.array() contentEquals doubleArrayOf(4.0, 2.0))
+        assertTrue(res.mutableBuffer.array() contentEquals doubleArrayOf(4.0, 2.0))
     }
 
     @Test
@@ -35,7 +35,7 @@ internal class TestDoubleTensorAlgebra {
         val tensor = fromArray(intArrayOf(1), doubleArrayOf(0.0))
         val res = tensor.transpose(0, 0)
 
-        assertTrue(res.buffer.array() contentEquals doubleArrayOf(0.0))
+        assertTrue(res.mutableBuffer.array() contentEquals doubleArrayOf(0.0))
         assertTrue(res.shape contentEquals intArrayOf(1))
     }
 
@@ -44,7 +44,7 @@ internal class TestDoubleTensorAlgebra {
         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)
 
-        assertTrue(res.buffer.array() contentEquals doubleArrayOf(1.0, 3.0, 5.0, 2.0, 4.0, 6.0))
+        assertTrue(res.mutableBuffer.array() contentEquals doubleArrayOf(1.0, 3.0, 5.0, 2.0, 4.0, 6.0))
         assertTrue(res.shape contentEquals intArrayOf(2, 3))
     }
 
@@ -59,9 +59,9 @@ internal class TestDoubleTensorAlgebra {
         assertTrue(res02.shape contentEquals intArrayOf(3, 2, 1))
         assertTrue(res12.shape contentEquals intArrayOf(1, 3, 2))
 
-        assertTrue(res01.buffer.array() contentEquals doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0))
-        assertTrue(res02.buffer.array() contentEquals doubleArrayOf(1.0, 4.0, 2.0, 5.0, 3.0, 6.0))
-        assertTrue(res12.buffer.array() contentEquals doubleArrayOf(1.0, 4.0, 2.0, 5.0, 3.0, 6.0))
+        assertTrue(res01.mutableBuffer.array() contentEquals doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0))
+        assertTrue(res02.mutableBuffer.array() contentEquals doubleArrayOf(1.0, 4.0, 2.0, 5.0, 3.0, 6.0))
+        assertTrue(res12.mutableBuffer.array() contentEquals doubleArrayOf(1.0, 4.0, 2.0, 5.0, 3.0, 6.0))
     }
 
     @Test
@@ -92,8 +92,8 @@ internal class TestDoubleTensorAlgebra {
         assignResult += tensorC
         assignResult += -39.4
 
-        assertTrue(expected.buffer.array() contentEquals result.buffer.array())
-        assertTrue(expected.buffer.array() contentEquals assignResult.buffer.array())
+        assertTrue(expected.mutableBuffer.array() contentEquals result.mutableBuffer.array())
+        assertTrue(expected.mutableBuffer.array() contentEquals assignResult.mutableBuffer.array())
     }
 
     @Test
@@ -104,19 +104,19 @@ internal class TestDoubleTensorAlgebra {
         val tensor3 = fromArray(intArrayOf(1, 1, 3), doubleArrayOf(-1.0, -2.0, -3.0))
 
         val res12 = tensor1.dot(tensor2)
-        assertTrue(res12.buffer.array() contentEquals doubleArrayOf(140.0, 320.0))
+        assertTrue(res12.mutableBuffer.array() contentEquals doubleArrayOf(140.0, 320.0))
         assertTrue(res12.shape contentEquals intArrayOf(2))
 
         val res32 = tensor3.dot(tensor2)
-        assertTrue(res32.buffer.array() contentEquals doubleArrayOf(-140.0))
+        assertTrue(res32.mutableBuffer.array() contentEquals doubleArrayOf(-140.0))
         assertTrue(res32.shape contentEquals intArrayOf(1, 1))
 
         val res22 = tensor2.dot(tensor2)
-        assertTrue(res22.buffer.array() contentEquals doubleArrayOf(1400.0))
+        assertTrue(res22.mutableBuffer.array() contentEquals doubleArrayOf(1400.0))
         assertTrue(res22.shape contentEquals intArrayOf(1))
 
         val res11 = tensor1.dot(tensor11)
-        assertTrue(res11.buffer.array() contentEquals doubleArrayOf(22.0, 28.0, 49.0, 64.0))
+        assertTrue(res11.mutableBuffer.array() contentEquals doubleArrayOf(22.0, 28.0, 49.0, 64.0))
         assertTrue(res11.shape contentEquals intArrayOf(2, 2))
 
         var tensor4 = fromArray(intArrayOf(10, 3, 4), DoubleArray(10 * 3 * 4) {0.0})
@@ -147,17 +147,17 @@ internal class TestDoubleTensorAlgebra {
 
         val diagonal1 = diagonalEmbedding(tensor1, 0, 1, 0)
         assertTrue(diagonal1.shape contentEquals intArrayOf(3, 3))
-        assertTrue(diagonal1.buffer.array() contentEquals
+        assertTrue(diagonal1.mutableBuffer.array() contentEquals
                 doubleArrayOf(10.0, 0.0, 0.0, 0.0, 20.0, 0.0, 0.0, 0.0, 30.0))
 
         val diagonal1Offset = diagonalEmbedding(tensor1, 1, 1, 0)
         assertTrue(diagonal1Offset.shape contentEquals intArrayOf(4, 4))
-        assertTrue(diagonal1Offset.buffer.array() contentEquals
+        assertTrue(diagonal1Offset.mutableBuffer.array() contentEquals
                 doubleArrayOf(0.0, 0.0, 0.0, 0.0, 10.0, 0.0, 0.0, 0.0, 0.0, 20.0, 0.0, 0.0, 0.0, 0.0, 30.0, 0.0))
 
         val diagonal2 = diagonalEmbedding(tensor2, 1, 0, 2)
         assertTrue(diagonal2.shape contentEquals intArrayOf(4, 2, 4))
-        assertTrue(diagonal2.buffer.array() contentEquals
+        assertTrue(diagonal2.mutableBuffer.array() contentEquals
                 doubleArrayOf(
                     0.0, 1.0, 0.0, 0.0, 0.0, 4.0, 0.0, 0.0,
                     0.0, 0.0, 2.0, 0.0, 0.0, 0.0, 5.0, 0.0,