Updates from sanfordsquires to fix RS decoding for Datamatrix

[zxing.git] / core / src / com / google / zxing / common / reedsolomon / ReedSolomonDecoder.java

diff --git a/core/src/com/google/zxing/common/reedsolomon/ReedSolomonDecoder.java b/core/src/com/google/zxing/common/reedsolomon/ReedSolomonDecoder.java
index 9188c79..4c000d3 100644 (file)
--- a/core/src/com/google/zxing/common/reedsolomon/ReedSolomonDecoder.java
+++ b/core/src/com/google/zxing/common/reedsolomon/ReedSolomonDecoder.java
@@ -1,5 +1,5 @@
 /*
- * Copyright 2007 Google Inc.
+ * Copyright 2007 ZXing authors
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -36,6 +36,7 @@ package com.google.zxing.common.reedsolomon;
  *
  * @author srowen@google.com (Sean Owen)
  * @author William Rucklidge
+ * @author sanfordsquires
  */
 public final class ReedSolomonDecoder {
 
@@ -52,14 +53,16 @@ public final class ReedSolomonDecoder {
    *
    * @param received data and error-correction codewords
    * @param twoS number of error-correction codewords available
-   * @throws ReedSolomonException if decoding fails for any reaosn
+   * @throws ReedSolomonException if decoding fails for any reason
    */
   public void decode(int[] received, int twoS) throws ReedSolomonException {
     GF256Poly poly = new GF256Poly(field, received);
     int[] syndromeCoefficients = new int[twoS];
+    boolean dataMatrix = field.equals(GF256.DATA_MATRIX_FIELD);
     boolean noError = true;
     for (int i = 0; i < twoS; i++) {
-      int eval =  poly.evaluateAt(field.exp(i));
+      // Thanks to sanfordsquires for this fix:
+      int eval = poly.evaluateAt(field.exp(dataMatrix ? i + 1 : i));
       syndromeCoefficients[syndromeCoefficients.length - 1 - i] = eval;
       if (eval != 0) {
         noError = false;
@@ -71,10 +74,15 @@ public final class ReedSolomonDecoder {
     GF256Poly syndrome = new GF256Poly(field, syndromeCoefficients);
     GF256Poly[] sigmaOmega =
         runEuclideanAlgorithm(field.buildMonomial(twoS, 1), syndrome, twoS);
-    int[] errorLocations = findErrorLocations(sigmaOmega[0]);
-    int[] errorMagnitudes = findErrorMagnitudes(sigmaOmega[1], errorLocations);
+    GF256Poly sigma = sigmaOmega[0];
+    GF256Poly omega = sigmaOmega[1];
+    int[] errorLocations = findErrorLocations(sigma);
+    int[] errorMagnitudes = findErrorMagnitudes(omega, errorLocations, dataMatrix);
     for (int i = 0; i < errorLocations.length; i++) {
       int position = received.length - 1 - field.log(errorLocations[i]);
+      if (position < 0) {
+        throw new ReedSolomonException("Bad error location");
+      }
       received[position] = GF256.addOrSubtract(received[position], errorMagnitudes[i]);
     }
   }
@@ -155,12 +163,9 @@ public final class ReedSolomonDecoder {
     return result;
   }
 
-  private int[] findErrorMagnitudes(GF256Poly errorEvaluator, int[] errorLocations) {
+  private int[] findErrorMagnitudes(GF256Poly errorEvaluator, int[] errorLocations, boolean dataMatrix) {
     // This is directly applying Forney's Formula
     int s = errorLocations.length;
-    if (s == 1) { // shortcut
-      return new int[] { errorEvaluator.getCoefficient(0) };
-    }
     int[] result = new int[s];
     for (int i = 0; i < s; i++) {
       int xiInverse = field.inverse(errorLocations[i]);
@@ -173,6 +178,10 @@ public final class ReedSolomonDecoder {
       }
       result[i] = field.multiply(errorEvaluator.evaluateAt(xiInverse),
           field.inverse(denominator));
+      // Thanks to sanfordsquires for this fix:
+      if (dataMatrix) {
+        result[i] = field.multiply(result[i], xiInverse);
+      }
     }
     return result;
   }