aistudio-wpf-diagram/zxing.core/xx/common/reedsolomon/ReedSolomonDecoder.cs

/*
* 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.
* You may obtain a copy of the License at
*
*      http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/

namespace ZXing.Common.ReedSolomon
{
   /// <summary> <p>Implements Reed-Solomon decoding, as the name implies.</p>
   /// 
   /// <p>The algorithm will not be explained here, but the following references were helpful
   /// in creating this implementation:</p>
   /// 
   /// <ul>
   /// <li>Bruce Maggs.
   /// <a href="http://www.cs.cmu.edu/afs/cs.cmu.edu/project/pscico-guyb/realworld/www/rs_decode.ps">
   /// "Decoding Reed-Solomon Codes"</a> (see discussion of Forney's Formula)</li>
   /// <li>J.I. Hall. <a href="www.mth.msu.edu/~jhall/classes/codenotes/GRS.pdf">
   /// "Chapter 5. Generalized Reed-Solomon Codes"</a>
   /// (see discussion of Euclidean algorithm)</li>
   /// </ul>
   /// 
   /// <p>Much credit is due to William Rucklidge since portions of this code are an indirect
   /// port of his C++ Reed-Solomon implementation.</p>
   /// 
   /// </summary>
   /// <author>Sean Owen</author>
   /// <author>William Rucklidge</author>
   /// <author>sanfordsquires</author>
   public sealed class ReedSolomonDecoder
   {
      private readonly GenericGF field;

      public ReedSolomonDecoder(GenericGF field)
      {
         this.field = field;
      }

      /// <summary>
      ///   <p>Decodes given set of received codewords, which include both data and error-correction
      /// codewords. Really, this means it uses Reed-Solomon to detect and correct errors, in-place,
      /// in the input.</p>
      /// </summary>
      /// <param name="received">data and error-correction codewords</param>
      /// <param name="twoS">number of error-correction codewords available</param>
      /// <returns>false: decoding fails</returns>
      public bool decode(int[] received, int twoS)
      {
         var poly = new GenericGFPoly(field, received);
         var syndromeCoefficients = new int[twoS];
         var noError = true;
         for (var i = 0; i < twoS; i++)
         {
            var eval = poly.evaluateAt(field.exp(i + field.GeneratorBase));
            syndromeCoefficients[syndromeCoefficients.Length - 1 - i] = eval;
            if (eval != 0)
            {
               noError = false;
            }
         }
         if (noError)
         {
            return true;
         }
         var syndrome = new GenericGFPoly(field, syndromeCoefficients);

         var sigmaOmega = runEuclideanAlgorithm(field.buildMonomial(twoS, 1), syndrome, twoS);
         if (sigmaOmega == null)
            return false;

         var sigma = sigmaOmega[0];
         var errorLocations = findErrorLocations(sigma);
         if (errorLocations == null)
            return false;

         var omega = sigmaOmega[1];
         var errorMagnitudes = findErrorMagnitudes(omega, errorLocations);
         for (var i = 0; i < errorLocations.Length; i++)
         {
            var position = received.Length - 1 - field.log(errorLocations[i]);
            if (position < 0)
            {
               // throw new ReedSolomonException("Bad error location");
               return false;
            }
            received[position] = GenericGF.addOrSubtract(received[position], errorMagnitudes[i]);
         }

         return true;
      }

      internal GenericGFPoly[] runEuclideanAlgorithm(GenericGFPoly a, GenericGFPoly b, int R)
      {
         // Assume a's degree is >= b's
         if (a.Degree < b.Degree)
         {
            GenericGFPoly temp = a;
            a = b;
            b = temp;
         }

         GenericGFPoly rLast = a;
         GenericGFPoly r = b;
         GenericGFPoly tLast = field.Zero;
         GenericGFPoly t = field.One;

         // Run Euclidean algorithm until r's degree is less than R/2
         while (r.Degree >= R / 2)
         {
            GenericGFPoly rLastLast = rLast;
            GenericGFPoly tLastLast = tLast;
            rLast = r;
            tLast = t;

            // Divide rLastLast by rLast, with quotient in q and remainder in r
            if (rLast.isZero)
            {
               // Oops, Euclidean algorithm already terminated?
               // throw new ReedSolomonException("r_{i-1} was zero");
               return null;
            }
            r = rLastLast;
            GenericGFPoly q = field.Zero;
            int denominatorLeadingTerm = rLast.getCoefficient(rLast.Degree);
            int dltInverse = field.inverse(denominatorLeadingTerm);
            while (r.Degree >= rLast.Degree && !r.isZero)
            {
               int degreeDiff = r.Degree - rLast.Degree;
               int scale = field.multiply(r.getCoefficient(r.Degree), dltInverse);
               q = q.addOrSubtract(field.buildMonomial(degreeDiff, scale));
               r = r.addOrSubtract(rLast.multiplyByMonomial(degreeDiff, scale));
            }

            t = q.multiply(tLast).addOrSubtract(tLastLast);

            if (r.Degree >= rLast.Degree)
            {
               // throw new IllegalStateException("Division algorithm failed to reduce polynomial?");
               return null;
            }
         }

         int sigmaTildeAtZero = t.getCoefficient(0);
         if (sigmaTildeAtZero == 0)
         {
            // throw new ReedSolomonException("sigmaTilde(0) was zero");
            return null;
         }

         int inverse = field.inverse(sigmaTildeAtZero);
         GenericGFPoly sigma = t.multiply(inverse);
         GenericGFPoly omega = r.multiply(inverse);
         return new GenericGFPoly[] { sigma, omega };
      }

      private int[] findErrorLocations(GenericGFPoly errorLocator)
      {
         // This is a direct application of Chien's search
         int numErrors = errorLocator.Degree;
         if (numErrors == 1)
         {
            // shortcut
            return new int[] { errorLocator.getCoefficient(1) };
         }
         int[] result = new int[numErrors];
         int e = 0;
         for (int i = 1; i < field.Size && e < numErrors; i++)
         {
            if (errorLocator.evaluateAt(i) == 0)
            {
               result[e] = field.inverse(i);
               e++;
            }
         }
         if (e != numErrors)
         {
            // throw new ReedSolomonException("Error locator degree does not match number of roots");
            return null;
         }
         return result;
      }

      private int[] findErrorMagnitudes(GenericGFPoly errorEvaluator, int[] errorLocations)
      {
         // This is directly applying Forney's Formula
         int s = errorLocations.Length;
         int[] result = new int[s];
         for (int i = 0; i < s; i++)
         {
            int xiInverse = field.inverse(errorLocations[i]);
            int denominator = 1;
            for (int j = 0; j < s; j++)
            {
               if (i != j)
               {
                  //denominator = field.multiply(denominator,
                  //    GenericGF.addOrSubtract(1, field.multiply(errorLocations[j], xiInverse)));
                  // Above should work but fails on some Apple and Linux JDKs due to a Hotspot bug.
                  // Below is a funny-looking workaround from Steven Parkes
                  int term = field.multiply(errorLocations[j], xiInverse);
                  int termPlus1 = (term & 0x1) == 0 ? term | 1 : term & ~1;
                  denominator = field.multiply(denominator, termPlus1);

                  // removed in java version, not sure if this is right
                  // denominator = field.multiply(denominator, GenericGF.addOrSubtract(1, field.multiply(errorLocations[j], xiInverse)));
               }
            }
            result[i] = field.multiply(errorEvaluator.evaluateAt(xiInverse), field.inverse(denominator));
            if (field.GeneratorBase != 0)
            {
               result[i] = field.multiply(result[i], xiInverse);
            }
         }
         return result;
      }
   }
}