1 files changed, 162 insertions, 0 deletions
diff --git a/test/pending/shootout/fasta.scala b/test/pending/shootout/fasta.scala
new file mode 100644
index 0000000000..16b6f42201
--- /dev/null
+++ b/test/pending/shootout/fasta.scala
@@ -0,0 +1,162 @@
+/* The Computer Language Shootout
+   http://shootout.alioth.debian.org/
+   contributed by Isaac Gouy
+*/
+
+import java.io._
+
+object fasta { 
+   def main(args: Array[String]) = {
+
+      val ALU =
+         "GGCCGGGCGCGGTGGCTCACGCCTGTAATCCCAGCACTTTGG" +
+         "GAGGCCGAGGCGGGCGGATCACCTGAGGTCAGGAGTTCGAGA" +
+         "CCAGCCTGGCCAACATGGTGAAACCCCGTCTCTACTAAAAAT" +
+         "ACAAAAATTAGCCGGGCGTGGTGGCGCGCGCCTGTAATCCCA" +
+         "GCTACTCGGGAGGCTGAGGCAGGAGAATCGCTTGAACCCGGG" +
+         "AGGCGGAGGTTGCAGTGAGCCGAGATCGCGCCACTGCACTCC" +
+         "AGCCTGGGCGACAGAGCGAGACTCCGTCTCAAAAA"
+
+      val _IUB = Array(
+         Pair('a', 0.27), 
+         Pair('c', 0.12), 
+         Pair('g', 0.12), 
+         Pair('t', 0.27), 
+
+         Pair('B', 0.02), 
+         Pair('D', 0.02),
+         Pair('H', 0.02), 
+         Pair('K', 0.02), 
+         Pair('M', 0.02),
+         Pair('N', 0.02), 
+         Pair('R', 0.02), 
+         Pair('S', 0.02),
+         Pair('V', 0.02), 
+         Pair('W', 0.02), 
+         Pair('Y', 0.02)
+      )
+
+      val IUB = makeCumulative(_IUB)
+
+      val _HomoSapiens = Array(
+         Pair('a', 0.3029549426680), 
+         Pair('c', 0.1979883004921),
+         Pair('g', 0.1975473066391), 
+         Pair('t', 0.3015094502008)
+      )
+
+      val HomoSapiens = makeCumulative(_HomoSapiens)
+
+
+      val n = Integer parseInt(args(0))
+      val s = new FastaOutputStream(System.out)
+
+      s.writeDescription("ONE Homo sapiens alu")
+      s.writeRepeatingSequence(ALU,n*2)
+
+      s.writeDescription("TWO IUB ambiguity codes")
+      s.writeRandomSequence(IUB,n*3)
+
+      s.writeDescription("THREE Homo sapiens frequency")
+      s.writeRandomSequence(HomoSapiens,n*5)
+
+      s.close
+   } 
+
+   def makeCumulative(a: Array[Pair[Char,double]]) = {
+      var cp = 0.0
+      a map (frequency =>
+         frequency match { 
+            case Pair(code,percent) => 
+               cp = cp + percent; new Frequency(code.toByte,cp) 
+         } 
+      )
+   }
+
+}
+
+
+// We could use instances of Pair or Tuple2 but specific labels
+// make the code more readable than index numbers
+
+class Frequency(_code: byte, _percent: double){ 
+   var code = _code; var percent = _percent;
+}
+
+
+// extend the Java BufferedOutputStream class
+
+class FastaOutputStream(out: OutputStream) extends BufferedOutputStream(out) {
+
+   private val LineLength = 60
+   private val nl = '\n'.toByte
+
+   def writeDescription(desc: String) = { write( (">" + desc + "\n").getBytes ) }
+
+   def writeRepeatingSequence(_alu: String, length: int) = {
+      val alu = _alu.getBytes
+      var n = length; var k = 0; val kn = alu.length;
+
+      while (n > 0) {
+         val m = if (n < LineLength) n else LineLength
+
+         var i = 0
+         while (i < m){ 
+            if (k == kn) k = 0
+            val b = alu(k)
+            if (count < buf.length){ buf(count) = b; count = count + 1 }
+            else { write(b) } // flush buffer
+            k = k+1
+            i = i+1 
+         }
+
+         write(nl)
+         n = n - LineLength
+      }
+
+   }
+
+   def writeRandomSequence(distribution: Array[Frequency], length: int) = {
+      var n = length
+      while (n > 0) {
+         val m = if (n < LineLength) n else LineLength
+
+         var i = 0
+         while (i < m){ 
+            val b = selectRandom(distribution)
+            if (count < buf.length){ buf(count) = b; count = count + 1 }
+            else { write(b) } // flush buffer
+            i = i+1 
+         }
+
+         if (count < buf.length){ buf(count) = nl; count = count + 1 }
+         else { write(nl) } // flush buffer
+         n = n - LineLength
+      }
+   }
+
+   private def selectRandom(distribution: Array[Frequency]): Byte = {
+      val n = distribution.length
+      val r = RandomNumber scaledTo(1.0)
+
+      var i = 0
+      while (i < n) {
+         if (r < distribution(i).percent) return distribution(i).code
+         i = i+1
+      }
+      return distribution(n-1).code
+   }
+}
+
+
+object RandomNumber {
+   private val IM = 139968
+   private val IA = 3877
+   private val IC = 29573
+   private var seed = 42
+
+   def scaledTo(max: double) = {
+      seed = (seed * IA + IC) % IM
+      max * seed / IM
+   }
+}