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    <p>I don't know if this is the easy way, but I've included some code below for converting nested tuples into '2D' arrays.</p> <p>First, you need some boiler plate for getting the size of the tuples as well as converting the tuples into <code>[Array[Array[Double]]</code>. The series of steps I used were:</p> <ol> <li>Figure out the number of rows and columns in the tuple</li> <li>Turn the nested tuple into a one row Array</li> <li>Reshape the array based on the size of the original tuple.</li> </ol> <p>The code for that is:</p> <pre><code>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 =&gt; flattenProduct(p) case x =&gt; 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 =&gt; v match { case c: Char =&gt; c.toDouble case b: Byte =&gt; b.toDouble case sh: Short =&gt; sh.toDouble case i: Int =&gt; i.toDouble case l: Long =&gt; l.toDouble case f: Float =&gt; f.toDouble case d: Double =&gt; d case s: String =&gt; s.toDouble case _ =&gt; 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 &lt;- 0 until m; j &lt;- 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) } } </code></pre> <p>Now to use this, you could just do the following:</p> <pre><code>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)) </code></pre> <p>Alternatively, if you could just call the rowArrayTo2DArray directly using the size of the array you want and a 1D array of values:</p> <pre><code>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)) </code></pre>
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    1. POInitializing a 2D (multi-dimensional) array in Scala
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    1. COOne problem I can see with this approach is that you can still pass any kind of tuple (by example a Tuple2[SomeType, AnotherType]), which is clearly not good and will compile fine (only to blow at runtime)
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      1. USRégis Jean-Gilles
    2. CO@Régis Jean-Gilles: 'Tis true ... Product doesn't expose the type of it's content. One could, however, just use the `rowArrayTo2DArray` method directly, which is type safe. I added an example to illustrate that.
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    3. CO@Régis Jean-Gilles: Also, to prevent runtime blowups, one could change the line `case _ => throw new UnsupportedOperationException(...` to `case _ => Double.NaN` which would prevent blowups and provide a 'correct' way to handle non-numeric values. I'm going to change the code to reflect that.
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