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

@@ -1,5 +1,7 @@
 package space.kscience.kmath.tensors.core
 
+import space.kscience.kmath.nd.as1D
+import space.kscience.kmath.nd.as2D
 import space.kscience.kmath.samplers.GaussianSampler
 import space.kscience.kmath.stat.RandomGenerator
 import space.kscience.kmath.structures.*
@@ -57,4 +59,48 @@ internal inline fun minusIndexFrom(n: Int, i: Int) : Int = if (i >= 0) i else {
     ii
 }
 
-internal inline fun <T> BufferedTensor<T>.minusIndex(i: Int): Int =  minusIndexFrom(this.linearStructure.dim, i)
+internal inline fun <T> BufferedTensor<T>.minusIndex(i: Int): Int =  minusIndexFrom(this.linearStructure.dim, i)
+
+public fun DoubleTensor.toPrettyString(): String = buildString {
+    var offset = 0
+    val shape = this@toPrettyString.shape
+    val linearStructure = this@toPrettyString.linearStructure
+    var vectorSize = shape.last()
+    val initString = "DoubleTensor(\n"
+    append(initString)
+    var charOffset = 3
+    for (vector in vectorSequence()) {
+        append(" ".repeat(charOffset))
+        val index = linearStructure.index(offset)
+        for (ind in index.reversed()) {
+            if (ind != 0) {
+                break
+            }
+            append("[")
+            charOffset += 1
+        }
+        // todo refactor
+        val values = mutableListOf<Double>()
+        for (i in 0 until vectorSize) {
+            values.add(vector[intArrayOf(i)])
+        }
+        // todo apply exp formatting
+        append(values.joinToString(", "))
+        append("]")
+        charOffset -= 1
+        for ((ind, maxInd) in index.reversed().zip(shape.reversed()).drop(1)){
+            if (ind != maxInd - 1) {
+                break
+            }
+            append("]")
+            charOffset -=1
+        }
+        offset += vectorSize
+        // todo refactor
+        if (this@toPrettyString.numel == offset) {
+            break
+        }
+        append(",\n")
+    }
+    append("\n)")
+}

kmath-tensors/src/jvmMain/kotlin/tensorPrettyPrinter.kt

@@ -0,0 +1,64 @@
+
+import space.kscience.kmath.tensors.core.DoubleTensor
+import space.kscience.kmath.tensors.core.vectorSequence
+import java.lang.StringBuilder
+
+internal fun format(value: Double, digits: Int = 4): String {
+    val res = "%.${digits}e".format(value).replace(',', '.')
+    if (value < 0.0) {
+        return res
+    }
+    return StringBuilder().append(" ").append(res).toString()
+}
+
+public fun DoubleTensor.toPrettyString(): String {
+    val builder = StringBuilder()
+    with(builder) {
+        var offset = 0
+        val shape = this@toPrettyString.shape
+        val linearStructure = this@toPrettyString.linearStructure
+        var vectorSize = shape.last()
+        val initString = "DoubleTensor(\n"
+        append(initString)
+        var charOffset = 3
+        for (vector in vectorSequence()) {
+            append(" ".repeat(charOffset))
+            val index = linearStructure.index(offset)
+            for (ind in index.reversed()) {
+                if (ind != 0) {
+                    break
+                }
+                append("[")
+                charOffset += 1
+            }
+            // todo refactor
+            val values = mutableListOf<Double>()
+            for (i in 0 until vectorSize) {
+                values.add(vector[intArrayOf(i)])
+            }
+            append(values.map { format(it) }.joinToString(", "))
+            append("]")
+            charOffset -= 1
+            for (i in shape.size - 2 downTo 0){
+                val ind = index[i]
+                val maxInd = shape[i]
+                if (ind != maxInd - 1) {
+                    break
+                }
+                append("]")
+                charOffset -=1
+            }
+            offset += vectorSize
+            // todo refactor
+            if (this@toPrettyString.numel == offset) {
+                break
+            }
+            append(",\n")
+        }
+        append("\n)")
+    }
+    return builder.toString()
+}
+
+
+