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); }
internal GenericGFPoly[] divide(GenericGFPoly other) { if (!field.Equals(other.field)) { throw new ArgumentException("GenericGFPolys do not have same GenericGF field"); } if (other.isZero) { throw new ArgumentException("Divide by 0", "other"); } GenericGFPoly quotient = new GenericGFPoly(field, new int[] { 0 }, encoding); GenericGFPoly remainder = this; int denominatorLeadingTerm = other.getCoefficient(other.Degree); int inverseDenominatorLeadingTerm = field.inverse(denominatorLeadingTerm); while (remainder.Degree >= other.Degree && !remainder.isZero) { int degreeDifference = remainder.Degree - other.Degree; int scale = field.multiply(remainder.getCoefficient(remainder.Degree), inverseDenominatorLeadingTerm); GenericGFPoly term = other.multiplyByMonomial(degreeDifference, scale); GenericGFPoly iterationQuotient = buildMonomial(degreeDifference, scale); quotient = quotient.addOrSubtract(iterationQuotient); remainder = remainder.addOrSubtract(term); } return(new GenericGFPoly[] { quotient, remainder }); }
// Method added by Sonic-The-Hedgehog-LNK1123 (github.com/Sonic-The-Hedgehog-LNK1123) // this method replaces original method "runEuclideanAlgorithm" internal GenericGFPoly runBerlekampMasseyAlgorithm(GenericGFPoly syndrome, int erasureCount) { GenericGFPoly sigma = new GenericGFPoly(field, new int[] { 1 }, false); GenericGFPoly old = new GenericGFPoly(field, new int[] { 1 }, false); for (int i = 0; i < (syndrome.Coefficients.Length - erasureCount); i++) { int delta = syndrome.getCoefficient(i); for (int j = 1; j < sigma.Coefficients.Length; j++) { delta ^= field.multiply(sigma.getCoefficient(j), syndrome.getCoefficient(i - j)); } List <int> oldList = new List <int>(old.Coefficients); oldList.Add(0); old = new GenericGFPoly(field, oldList.ToArray(), false); if (delta != 0) { if (old.Coefficients.Length > sigma.Coefficients.Length) { GenericGFPoly new_loc = old.multiply(delta); old = sigma.multiply(field.inverse(delta)); sigma = new_loc; } sigma = sigma.addOrSubtract(old.multiply(delta)); } } List <int> sigmaList = new List <int>(sigma.Coefficients); while (Convert.ToBoolean(sigmaList.Count) && sigmaList[0] == 0) { sigmaList.RemoveAt(0); } sigma = new GenericGFPoly(field, sigmaList.ToArray(), false); return(sigma); }
// Method added by Sonic-The-Hedgehog-LNK1123 (github.com/Sonic-The-Hedgehog-LNK1123) internal GenericGFPoly calculateForneySyndromes(GenericGFPoly syndromes, int[] positions, int messageLength) { int[] positionsReversed = new int[positions.Length]; for (int i = 0; i < positions.Length; i++) { positionsReversed[i] = messageLength - 1 - positions[i]; } int forneySyndromesLength = syndromes.Coefficients.Length; int[] syndromeCoefficients = new int[syndromes.Coefficients.Length]; Array.Copy(syndromes.Coefficients, 0, syndromeCoefficients, 0, syndromes.Coefficients.Length); GenericGFPoly forneySyndromes = new GenericGFPoly(field, syndromeCoefficients, false); for (int i = 0; i < positions.Length; i++) { int x = field.exp(positionsReversed[i]); for (int j = 0; j < forneySyndromes.Coefficients.Length - 1; j++) { forneySyndromes.Coefficients[forneySyndromesLength - j - 1] = GenericGF.addOrSubtract(field.multiply(forneySyndromes.getCoefficient(j), x), forneySyndromes.getCoefficient(j + 1)); } } return(forneySyndromes); }