It's easy to initialize a 2D array (or, in fact, any multidimensional array) in Java by putting something like that:
int[][] x = new int[][] {
{ 3, 5, 7, },
{ 0, 4, 9, },
{ 1, 8, 6, },
};
It's easy to read, it resembles a 2D matrix, etc, etc.
But how do I do that in Scala?
The best I could come up with looks, well, much less concise:
val x = Array(
Array(3, 5, 7),
Array(0, 4, 9),
Array(1, 8, 6)
)
The problems I see here:
It repeats "Array" over and over again (like there could be anything else besides Array)
It requires to omit trailing , in every Array invocation
If I screw up and insert something besides Array() in the middle of array, it will go okay with compiler, but type of x would silently become Array[Any] instead of Array[Array[Int]]:
val x = Array(
Array(3, 5, 7),
Array(0, 4), 9, // <= OK with compiler, silently ruins x
Array(1, 8, 6)
)
There is a guard against it, to specify the type directly, but it looks even more overkill than in Java:
val x: Array[Array[Int]] = Array(
Array(3, 5, 7),
Array(0, 4), 9, // <= this one would trigger a compiler error
Array(1, 8, 6)
)
This last example needs Array even 3 times more than I have to say int[][] in Java.
Is there any clear way around this?
Personally I'd suck it up and type out (or cut and paste) "Array" a few times for clarity's sake. Include the type annotation for safety, of course. But if you're really running out of e-ink, a quick easy hack would be simply to provide an alias for Array, for example:
val > = Array
val x: Array[Array[Int]] = >(
>(3, 5, 7),
>(0, 4, 9),
>(1, 8, 6)
)
You could also provide a type alias for Array if you want to shorten the annotation:
type >[T] = Array[T]
val x: >[>[Int]] = ...
I suggest to use Scala 2.10 and macros:
object MatrixMacro {
import language.experimental.macros
import scala.reflect.macros.Context
import scala.util.Try
implicit class MatrixContext(sc: StringContext) {
def matrix(): Array[Array[Int]] = macro matrixImpl
}
def matrixImpl(c: Context)(): c.Expr[Array[Array[Int]]] = {
import c.universe.{ Try => _, _ }
val matrix = Try {
c.prefix.tree match {
case Apply(_, List(Apply(_, List(Literal(Constant(raw: String)))))) =>
def toArrayAST(c: List[TermTree]) =
Apply(Select(Select(Ident("scala"), newTermName("Array")), newTermName("apply")), c)
val matrix = raw split "\n" map (_.trim) filter (_.nonEmpty) map {
_ split "," map (_.trim.toInt)
}
if (matrix.map(_.length).distinct.size != 1)
c.abort(c.enclosingPosition, "rows of matrix do not have the same length")
val matrixAST = matrix map (_ map (i => Literal(Constant(i)))) map (i => toArrayAST(i.toList))
toArrayAST(matrixAST.toList)
}
}
c.Expr(matrix getOrElse c.abort(c.enclosingPosition, "not a matrix of Int"))
}
}
Usage with:
scala> import MatrixMacro._
import MatrixMacro._
scala> matrix"1"
res86: Array[Array[Int]] = Array(Array(1))
scala> matrix"1,2,3"
res87: Array[Array[Int]] = Array(Array(1, 2, 3))
scala> matrix"""
| 1, 2, 3
| 4, 5, 6
| 7, 8, 9
| """
res88: Array[Array[Int]] = Array(Array(1, 2, 3), Array(4, 5, 6), Array(7, 8, 9))
scala> matrix"""
| 1, 2
| 1
| """
<console>:57: error: rows of matrix do not have the same length
matrix"""
^
scala> matrix"a"
<console>:57: error: not a matrix of Int
matrix"a"
^
I don't think you will get it shorter. ;)
If using a mere List of List (which in itself cannot guarantee that every sub list is of the same size) is not a problem for you, and you are only concerned with easy syntax and avoiding errors at creation-time, scala has many ways to create nice syntax constructs.
One such possibility would be a simple helper:
object Matrix {
def apply[X]( elements: Tuple3[X, X, X]* ): List[List[X]] = {
elements.toList.map(_.productIterator.toList.asInstanceOf[List[X]] )
}
// Here you might add other overloads for Tuple4, Tuple5 etc if you need "matrixes" of those sizes
}
val x = Matrix(
(3, 5, 7),
(0, 4, 9),
(1, 8, 6)
)
About your concerns:
It repeats "List" over and over again (like there could be anything else besides List)
Not the case here.
It requires to omit trailing , in every List invocation
Unfortunately that is still true here, not much you can do given scala's syntactic rules.
If I screw up and insert something besides List() in the middle of array, it will go okay with compiler, but type of x would silently become List[Any] instead of List[List[Int]]:
val x = List(
List(3, 5, 7),
List(0, 4), 9, // <= OK with compiler, silently ruins x
List(1, 8, 6)
)
The equivalent code now faile to compile:
scala> val x = Matrix(
| (3, 5, 7),
| (0, 4), 9,
| (1, 8, 6)
| )
<console>:10: error: type mismatch;
found : (Int, Int)
required: (?, ?, ?)
(0, 4), 9,
And finally if you want to explicitly specify the type of elements (say that you want to protect against the possibility of inadvertently mixing Ints and Doubles), you only have to specify Matrix[Int] instead of the ugly List[List[Int]]:
val x = Matrix[Int](
(3, 5, 7),
(0, 4, 9),
(1, 8, 6)
)
EDIT: I see that you replaced List with Array in your question. To use arrays all you have to use is to replace List with Array and toList with toArray in my code above.
Since I'm also in disgust with this trailing comma issue (i.e. I cannot simply exchange the last line with any other) I sometimes use either a fluent API or the constructor syntax trick to get the syntax I like. An example using the constructor syntax would be:
trait Matrix {
// ... and the beast
private val buffer = ArrayBuffer[Array[Int]]()
def >(vals: Int*) = buffer += vals.toArray
def build: Array[Array[Int]] = buffer.toArray
}
Which allows:
// beauty ...
val m = new Matrix {
>(1, 2, 3)
>(4, 5, 6)
>(7, 8, 9)
} build
Unfortunately, this relies on mutable data although it is only used temporarily during the construction. In cases where I want maximal beauty for the construction syntax I would prefer this solution.
In case build is too long/verbose you might want to replace it by an empty apply function.
I don't know if this is the easy way, but I've included some code below for converting nested tuples into '2D' arrays.
First, you need some boiler plate for getting the size of the tuples as well as converting the tuples into [Array[Array[Double]]. The series of steps I used were:
Figure out the number of rows and columns in the tuple
Turn the nested tuple into a one row Array
Reshape the array based on the size of the original tuple.
The code for that is:
object Matrix {
/**
* Returns the size of a series of nested tuples.
*/
def productSize(t: Product): (Int, Int) = {
val a = t.productArity
val one = t.productElement(0)
if (one.isInstanceOf[Product]) {
val b = one.asInstanceOf[Product].productArity
(a, b)
}
else {
(1, a)
}
}
/**
* Flattens out a nested tuple and returns the contents as an iterator.
*/
def flattenProduct(t: Product): Iterator[Any] = t.productIterator.flatMap {
case p: Product => flattenProduct(p)
case x => Iterator(x)
}
/**
* Convert a nested tuple to a flattened row-oriented array.
* Usage is:
* {{{
* val t = ((1, 2, 3), (4, 5, 6))
* val a = Matrix.toArray(t)
* // a: Array[Double] = Array(1, 2, 3, 4, 5, 6)
* }}}
*
* #param t The tuple to convert to an array
*/
def toArray(t: Product): Array[Double] = flattenProduct(t).map(v =>
v match {
case c: Char => c.toDouble
case b: Byte => b.toDouble
case sh: Short => sh.toDouble
case i: Int => i.toDouble
case l: Long => l.toDouble
case f: Float => f.toDouble
case d: Double => d
case s: String => s.toDouble
case _ => Double.NaN
}
).toArray[Double]
def rowArrayTo2DArray[#specialized(Int, Long, Float, Double) A: Numeric](m: Int, n: Int,
rowArray: Array[A]) = {
require(rowArray.size == m * n)
val numeric = implicitly[Numeric[A]]
val newArray = Array.ofDim[Double](m, n)
for (i <- 0 until m; j <- 0 until n) {
val idx = i * n + j
newArray(i)(j) = numeric.toDouble(rowArray(idx))
}
newArray
}
/**
* Factory method for turning tuples into 2D arrays
*/
def apply(data: Product): Array[Array[Double]] = {
def size = productSize(data)
def array = toArray(data)
rowArrayTo2DArray(size._1, size._2, array)
}
}
Now to use this, you could just do the following:
val a = Matrix((1, 2, 3))
// a: Array[Array[Double]] = Array(Array(1.0, 2.0, 3.0))
val b = Matrix(((1, 2, 3), (4, 5, 6), (7, 8, 9)))
// b: Array[Array[Double]] = Array(Array(1.0, 2.0, 3.0),
// Array(4.0, 5.0, 6.0),
// Array(7.0, 8.0, 9.0))
val c = Matrix((1L, 2F, "3")) // Correctly handles mixed types
// c: Array[Array[Double]] = Array(Array(1.0, 2.0, 3.0))
val d = Matrix((1L, 2F, new java.util.Date())) // Non-numeric types convert to NaN
// d: Array[Array[Double]] = Array(Array(1.0, 2.0, NaN))
Alternatively, if you could just call the rowArrayTo2DArray directly using the size of the array you want and a 1D array of values:
val e = Matrix.rowArrayTo2DArray(1, 3, Array(1, 2, 3))
// e: Array[Array[Double]] = Array(Array(1.0, 2.0, 3.0))
val f = Matrix.rowArrayTo2DArray(3, 1, Array(1, 2, 3))
// f: Array[Array[Double]] = Array(Array(1.0), Array(2.0), Array(3.0))
val g = Matrix.rowArrayTo2DArray(3, 3, Array(1, 2, 3, 4, 5, 6, 7, 8, 9))
// g: Array[Array[Double]] = Array(Array(1.0, 2.0, 3.0),
// Array(4.0, 5.0, 6.0),
// Array(7.0, 8.0, 9.0))
glancing through the answers, i did not find what to me seems the most obvious & simple way to do it. instead of Array, you can use a tuple.
would look something like that:
scala> val x = {(
| (3,5,7),
| (0,4,9),
| (1,8,6)
| )}
x: ((Int, Int, Int), (Int, Int, Int), (Int, Int, Int)) = ((3,5,7),(0,4,9),(1,8,6))
seems clean & elegant?
i think so :)
Related
I understand how to use if in map. For example, val result = list.map(x => if (x % 2 == 0) x * 2 else x / 2).
However, I want to use if for only part of the arguments.
val inputColumns = List(
List(1, 2, 3, 4, 5, 6), // first "column"
List(4, 6, 5, 7, 12, 15) // second "column"
)
inputColumns.zipWithIndex.map{ case (col, idx) => if (idx == 0) col * 2 else col / 10}
<console>:1: error: ';' expected but integer literal found.
inputColumns.zipWithIndex
res4: List[(List[Int], Int)] = List((List(1, 2, 3, 4, 5, 6),0), (List(4, 6, 5, 7, 12, 15),1))
I have searched the error info but have not found a solution.
Why my code is not 'legal' in Scala? Is there a better way to write it? Basically, I want to do a pattern matching and then do something on other arguments.
To explain your problem another way, inputColumns has type List[List[Int]]. You can verify this in the Scala REPL:
$ scala
Welcome to Scala 2.12.4 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_161).
Type in expressions for evaluation. Or try :help.
scala> val inputColumns = List(
| List(1, 2, 3, 4, 5, 6), // first "column"
| List(4, 6, 5, 7, 12, 15) // second "column"
| )
inputColumns: List[List[Int]] = List(List(1, 2, 3, 4, 5, 6), List(4, 6, 5, 7, 12, 15))
Now, when you call .zipWithIndex on that list, you end up with a List[(List[Int], Int)] - that is, a list of a tuple, in which the first tuple type is a List[Int] (the column) and the second is an Int (the index):
scala> inputColumns.zipWithIndex
res0: List[(List[Int], Int)] = List((List(1, 2, 3, 4, 5, 6),0), (List(4, 6, 5, 7, 12, 15),1))
Consequently, when you try to apply a map function to this list, col is a List[Int] and not an Int, and so col * 2 makes no sense - you're multiplying a List[Int] by 2. You then also try to divide the list by 10, obviously.
scala> inputColumns.zipWithIndex.map{ case(col, idx) => if(idx == 0) col * 2 else col / 10 }
<console>:13: error: value * is not a member of List[Int]
inputColumns.zipWithIndex.map{ case(col, idx) => if(idx == 0) col * 2 else col / 10 }
^
<console>:13: error: value / is not a member of List[Int]
inputColumns.zipWithIndex.map{ case(col, idx) => if(idx == 0) col * 2 else col / 10 }
^
In order to resolve this, it depends what you're trying to achieve. If you want a single list of integers, and then zip those so that each value has an associated index, you should call flatten on inputColumns before calling zipWithIndex. This will result in List[(Int, Int)], where the first value in the tuple is the column value, and the second is the index. Your map function will then work correctly without modification:
scala> inputColumns.flatten.zipWithIndex.map{ case(col, idx) => if(idx == 0) col * 2 else col / 10 }
res3: List[Int] = List(2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1)
Of course, you no longer have separate columns.
If you wish each value in each list to have an associated index, you need to firstly map inputColumns into two zipped lists, using inputColumns.map(_.zipWithIndex) to create a List[List[(Int, Int)]] - a list of a list of (Int, Int) tuples:
scala> inputColumns.map(_.zipWithIndex)
res4: List[List[(Int, Int)]] = List(List((1,0), (2,1), (3,2), (4,3), (5,4), (6,5)), List((4,0), (6,1), (5,2), (7,3), (12,4), (15,5)))
We can now apply your original map function to the result of the zipWithIndex operation:
scala> inputColumns.map(_.zipWithIndex.map { case (col, idx) => if(idx == 0) col * 2 else col / 10 })
res5: List[List[Int]] = List(List(2, 0, 0, 0, 0, 0), List(8, 0, 0, 0, 1, 1))
The result is another List[List[Int]] with each internal list being the results of your map operation on the original two input columns.
On the other hand, if idx is meant to be the index of the column, and not of each value, and you want to multiply all of the values in the first column by 2 and divide all of the values in the other columns by 10, then you need to change your original map function to map across each column, as follows:
scala> inputColumns.zipWithIndex.map {
| case (col, idx) => {
| if(idx == 0) col.map(_ * 2) // Multiply values in first column by 1
| else col.map(_ / 10) // Divide values in all other columns by 10
| }
| }
res5: List[List[Int]] = List(List(2, 4, 6, 8, 10, 12), List(0, 0, 0, 0, 1, 1))
Let me know if you require any further clarification...
UPDATE:
The use of case in map is a common Scala shorthand. If a higher-order function takes a single argument, something such as this:
def someHOF[A, B](x: A => B) = //...
and you call that function like this (with what Scala terms a partial function - a function consisting solely of a list of case statements):
someHOF {
case expr1 => //...
case expr2 => //...
...
}
then Scala treats it as a kind-of shorthand for:
someHOF {a =>
a match {
case expr1 => //...
case expr2 => //...
...
}
}
or, being slightly more terse,
someHOF {
_ match {
case expr1 => //...
case expr2 => //...
...
}
}
For a List, for example, you can use it with functions such as map, flatMap, filter, etc.
In the case of your map function, the sole argument is a tuple, and the sole case statement acts to break open the tuple and expose its contents. That is:
val l = List((1, 2), (3, 4), (5, 6))
l.map { case(a, b) => println(s"First is $a, second is $b") }
is equivalent to:
l.map {x =>
x match {
case (a, b) => println(s"First is $a, second is $b")
}
}
and both will output:
First is 1, second is 2
First is 3, second is 4
First is 5, second is 6
Note: This latter is a bit of a dumb example, since map is supposed to map (i.e. change) the values in the list into new values in a new list. If all you were doing was printing the values, this would be better:
val l = List((1, 2), (3, 4), (5, 6))
l.foreach { case(a, b) => println(s"First is $a, second is $b") }
You are trying to multiply a list by 2 when you do col * 2 as col is List(1, 2, 3, 4, 5, 6) when idx is 0, which is not possible and similar is the case with else part col / 10
If you are trying to multiply the elements of first list by 2 and devide the elements of rest of the list by 10 then you should be doing the following
inputColumns.zipWithIndex.map{ case (col, idx) => if (idx == 0) col.map(_*2) else col.map(_/10)}
Even better approach would be to use match case
inputColumns.zipWithIndex.map(x => x._2 match {
case 0 => x._1.map(_*2)
case _ => x._1.map(_/10)
})
I have the following hashmap, where each element should be mapped to a stack:
var pos = new HashMap[Int, Stack[Int]] withDefaultValue Stack.empty[Int]
for(i <- a.length - 1 to 0 by -1) {
pos(a(i)).push(i)
}
If a will have elements {4, 6, 6, 4, 6, 6},
and if I add the following lines after the code above:
println("pos(0) is " + pos(0))
println("pos(4) is " + pos(4))
The output will be:
pos(0) is Stack(0, 1, 2, 3, 4, 5)
pos(4) is Stack(0, 1, 2, 3, 4, 5)
Why is this happening?
I don't want to add elements to pos(0), but only to pos(4) and pos(6) (the lements of a).
It looks like there is only one stack mapped to all the keys. I want a stack for each key.
Check the docs:
http://www.scala-lang.org/api/current/index.html#scala.collection.mutable.HashMap
method withDefaultValue takes this value as a regular parameter, it won't be recalculated so all your entries share the same mutable stack.
def withDefaultValue(d: B): Map[A, B]
You should use withDefault method instead.
val pos = new HashMap[Int, Stack[Int]] withDefault (_ => Stack.empty[Int])
Edit
Above solution doesn't seem to work, I get empty stacks. Checking with sources shows that the default value is returned but never put into map
override def apply(key: A): B = {
val result = findEntry(key)
if (result eq null) default(key)
else result.value
}
I guess one solution might be to override apply or default method to add the entry to map before returning it. Example for default method:
val pos = new mutable.HashMap[Int, mutable.Stack[Int]]() {
override def default(key: Int) = {
val newValue = mutable.Stack.empty[Int]
this += key -> newValue
newValue
}
}
Btw. that is punishment for being mutable, I encourage you to use immutable data structures.
If you are looking for a more idiomatic Scala, functional-style solution without those mutable collections, consider this:
scala> val a = List(4, 6, 6, 4, 6, 6)
a: List[Int] = List(4, 6, 6, 4, 6, 6)
scala> val pos = a.zipWithIndex groupBy {_._1} mapValues { _ map (_._2) }
pos: scala.collection.immutable.Map[Int,List[Int]] = Map(4 -> List(0, 3), 6 -> List(1, 2, 4, 5))
It may look confusing at first, but if you break it down, zipWithIndex gets pairs of values and their positions, groupBy makes a map from each value to a list of entries, and mapValues is then used to turn the lists of (value, position) pairs into just lists of positions.
scala> val pairs = a.zipWithIndex
pairs: List[(Int, Int)] = List((4,0), (6,1), (6,2), (4,3), (6,4), (6,5))
scala> val pairsByValue = pairs groupBy (_._1)
pairsByValue: scala.collection.immutable.Map[Int,List[(Int, Int)]] = Map(4 -> List((4,0), (4,3)), 6 -> List((6,1), (6,2), (6,4), (6,5)))
scala> val pos = pairsByValue mapValues (_ map (_._2))
pos: scala.collection.immutable.Map[Int,List[Int]] = Map(4 -> List(0, 3), 6 -> List(1, 2, 4, 5))
I was trying to perform multiply operation on list in Scala like:
val list = List(1,2,3,4,5)
list.map(_*2)
res0: List[Int] = List(2, 4, 6, 8, 10) // Output
Now, I have created a separate method for the multiply operation like:
val list = List(1,2,3,4,5)
def multiplyListContents(x: Int) = {
x * 2
}
list.map(multiplyListContents)
res1: List[Int] = List(2, 4, 6, 8, 10) // Output
Now I want to pass custom multiplier instead of using default multiplier 2 like:
val list = List(1,2,3,4,5)
val multiplier = 3
def multiplyListContents(x: Int, multiplier: Int) = {
x * multiplier
}
list.map(multiplyListContents(multiplier))
res1: List[Int] = List(3, 6, 9, 12, 15) // Output should be this
Any idea how to do this?
scala> list.map(multiplyListContents(_, multiplier))
res0: List[Int] = List(3, 6, 9, 12, 15)
This translates to list.map(x => multiplyListContents(x, multiplier)).
(see scala placeholder syntax for more information).
And I have a comparison function "compr" already in the code to compare two values.
I want something like this:
Sorting.stableSort(arr[i,j] , compr)
where arr[i,j] is a range of element in array.
Take the slice as a view, sort and copy it back (or take a slice as a working buffer).
scala> val vs = Array(3,2,8,5,4,9,1,10,6,7)
vs: Array[Int] = Array(3, 2, 8, 5, 4, 9, 1, 10, 6, 7)
scala> vs.view(2,5).toSeq.sorted.copyToArray(vs,2)
scala> vs
res31: Array[Int] = Array(3, 2, 4, 5, 8, 9, 1, 10, 6, 7)
Outside the REPL, the extra .toSeq isn't needed:
vs.view(2,5).sorted.copyToArray(vs,2)
Updated:
scala 2.13.8> val vs = Array(3, 2, 8, 5, 4, 9, 1, 10, 6, 7)
val vs: Array[Int] = Array(3, 2, 8, 5, 4, 9, 1, 10, 6, 7)
scala 2.13.8> vs.view.slice(2,5).sorted.copyToArray(vs,2)
val res0: Int = 3
scala 2.13.8> vs
val res1: Array[Int] = Array(3, 2, 4, 5, 8, 9, 1, 10, 6, 7)
Split array into three parts, sort middle part and then concat them, not the most efficient way, but this is FP who cares about performance =)
val sorted =
for {
first <- l.take(FROM)
sortingPart <- l.slice(FROM, UNTIL)
lastPart <- l.takeRight(UNTIL)
} yield (first ++ Sorter.sort(sortingPart) ++ lastPart)
Something like that:
def stableSort[T](x: Seq[T], i: Int, j: Int, comp: (T,T) => Boolean ):Seq[T] = {
x.take(i) ++ x.slice(i,j).sortWith(comp) ++ x.drop(i+j-1)
}
def comp: (Int,Int) => Boolean = { case (x1,x2) => x1 < x2 }
val x = Array(1,9,5,6,3)
stableSort(x,1,4, comp)
// > res0: Seq[Int] = ArrayBuffer(1, 5, 6, 9, 3)
If your class implements Ordering it would be less cumbersome.
This should be as good as you can get without reimplementing the sort. Creates just one extra array with the size of the slice to be sorted.
def stableSort[K:reflect.ClassTag](xs:Array[K], from:Int, to:Int, comp:(K,K) => Boolean) : Unit = {
val tmp = xs.slice(from,to)
scala.util.Sorting.stableSort(tmp, comp)
tmp.copyToArray(xs, from)
}
I need to shuffle part of an ArrayBuffer, preferably in-place so no copies are required. For example, if an ArrayBuffer has 10 elements, and I want to shuffle elements 3-7:
// Unshuffled ArrayBuffer of ints numbered 0-9
0, 1, 2, 3, 4, 5, 6, 7, 8, 9
// Region I want to shuffle is between the pipe symbols (3-7)
0, 1, 2 | 3, 4, 5, 6, 7 | 8, 9
// Example of how it might look after shuffling
0, 1, 2 | 6, 3, 5, 7, 4 | 8, 9
// Leaving us with a partially shuffled ArrayBuffer
0, 1, 2, 6, 3, 5, 7, 4, 8, 9
I've written something like shown below, but it requires copies and iterating over loops a couple of times. It seems like there should be a more efficient way of doing this.
def shufflePart(startIndex: Int, endIndex: Int) {
val part: ArrayBuffer[Int] = ArrayBuffer[Int]()
for (i <- startIndex to endIndex ) {
part += this.children(i)
}
// Shuffle the part of the array we copied
val shuffled = this.random.shuffle(part)
var count: Int = 0
// Overwrite the part of the array we chose with the shuffled version of it
for (i <- startIndex to endIndex ) {
this.children(i) = shuffled(count)
count += 1
}
}
I could find nothing about partially shuffling an ArrayBuffer with Google. I assume I will have to write my own method, but in doing so I would like to prevent copies.
If you can use a subtype of ArrayBuffer you can access the underlying array directly, since ResizableArray has a protected member array:
import java.util.Collections
import java.util.Arrays
import collection.mutable.ArrayBuffer
val xs = new ArrayBuffer[Int]() {
def shuffle(a: Int, b: Int) {
Collections.shuffle(Arrays.asList(array: _*).subList(a, b))
}
}
xs ++= (0 to 9) // xs = ArrayBuffer(0, 1, 2, 3, 4, 5, 6, 7, 8, 9)
xs.shuffle(3, 8) // xs = ArrayBuffer(0, 1, 2, 4, 6, 5, 7, 3, 8, 9)
Notes:
The upper bound for java.util.List#subList is exclusive
It's reasonably efficient because Arrays#asList doesn't create a new set of elements: it's backed by the array itself (hence no add or remove methods)
If using for real, you probably want to add bounds-checks on a and b
I'm not entirely sure why it must be in place - you might want to think that over. But, assuming it's the right thing to do, this could do it:
import scala.collection.mutable.ArrayBuffer
implicit def array2Shufflable[T](a: ArrayBuffer[T]) = new {
def shufflePart(start: Int, end: Int) = {
val seq = (start.max(0) until end.min(a.size - 1)).toSeq
seq.zip(scala.util.Random.shuffle(seq)) foreach { t =>
val x = a(t._1)
a.update(t._1, a(t._2))
a(t._2) = x
}
a
}
}
You can use it like:
val a = ArrayBuffer(1,2,3,4,5,6,7,8,9)
println(a)
println(a.shufflePart(2, 7))
edit: If you're willing to pay the extra cost of an intermediate sequence, this is more reasonable, algorithmically speaking:
def shufflePart(start: Int, end: Int) = {
val seq = (start.max(0) until end.min(a.size - 1)).toSeq
seq.zip(scala.util.Random.shuffle(seq) map { i =>
a(i)
}) foreach { t =>
a.update(t._1, t._2)
}
a
}
}