Package flanagan.math

Examples of flanagan.math.Matrix

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        this.errorType = 3;
        this.preprocessDataThree();
    }

    public RankAnalysis(ArrayList<Object>[] values){
        Matrix matv = new Matrix(values);
        this.values = matv.getArrayCopy();
        this.errorType = 3;
        this.preprocessDataThree();
    }
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        this.errorType = 3;
        this.preprocessDataThree();
    }

    public RankAnalysis(Vector<Object>[] values){
        Matrix matv = new Matrix(values);
        this.values = matv.getArrayCopy();
        this.errorType = 3;
        this.preprocessDataThree();
    }
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        // Matrix reduction

        this.reducedValues = this.values;
        this.reducedErrors = this.errors;
        Matrix matv0 = new Matrix(this.reducedValues);
        Matrix mate0 = new Matrix(this.reducedErrors);
        int nn = this.diagonalLength - 1;

        for(int i=0; i<nn; i++){
            matv0 = new Matrix(this.reducedValues);

            // Isolate sub-matrix
          int nrow = this.numberOfRows-i;
          int ncol = this.numberOfColumns - i;
            Matrix mat1 = matv0.getSubMatrix(i, i, this.numberOfRows-1, numberOfColumns-1);
            double[][] subv = mat1.getArrayCopy();

          // Get pivot indices
          int[] max = mat1.pivot();
          int pivotI = max[0]+i;
          int pivotJ = max[1]+i;

          // Swap rows
          double[] holdv1 = this.reducedValues[i];
          double[] holde1 = this.reducedErrors[i];
          this.reducedValues[i] = this.reducedValues[pivotI];
          this.reducedErrors[i] = this.reducedErrors[pivotI];
          this.reducedValues[pivotI] = holdv1;
          this.reducedErrors[pivotI] = holde1;

          // Swap columns
          double holdv2 = 0.0;
          double holde2 = 0.0;
          for(int j=0; j<numberOfRows; j++){
              holdv2 = this.reducedValues[j][i];
              holde2 = this.reducedErrors[j][i];
              this.reducedValues[j][i] = this.reducedValues[j][pivotJ];
              this.reducedErrors[j][i] = this.reducedErrors[j][pivotJ];
              this.reducedValues[j][pivotJ] = holdv2;
              this.reducedErrors[j][pivotJ] = holde2;
          }

          // Reduce sub-matrix
          Matrix matValueHold = new Matrix(this.reducedValues);
          Matrix matErrorHold = new Matrix(this.reducedErrors);
          double[][] valueHold = matValueHold.getArrayCopy();
          double[][] errorHold = matErrorHold.getArrayCopy();

          for(int j=i+1; j<this.numberOfRows; j++){
              for(int k=i; k<this.numberOfColumns; k++){
                  double ratio1 = 1.0;
                  if(this.reducedValues[j][i]!=this.reducedValues[i][i])ratio1 = this.reducedValues[j][i]/this.reducedValues[i][i];
                  valueHold[j][k] = this.reducedValues[j][k] - ratio1*this.reducedValues[i][k];
                  double hold = this.reducedErrors[j][k] + this.reducedErrors[i][k]*ratio1*ratio1;
                  double ratio2 = 1.0;
                  if(this.reducedValues[i][k]!=this.reducedValues[i][i])ratio2 = this.reducedValues[i][k]/this.reducedValues[i][i];
                  hold += this.reducedErrors[j][i]*ratio2*ratio2;
                  errorHold[j][k] = hold + this.reducedErrors[i][i]*ratio1*ratio1*ratio2*ratio2;
              }
          }
          matValueHold = new Matrix(valueHold);
          matErrorHold = new Matrix(errorHold);
          this.reducedValues = matValueHold.getArrayCopy();
          this.reducedErrors = matErrorHold.getArrayCopy();
        }

        // Convert errors to standard deviations
        for(int i=0; i<this.numberOfRows; i++){
          for(int j=0; j<this.numberOfColumns; j++){
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        this.errorType = 0;
        this.preprocessDataOne();
    }

    public RankAnalysis(float[][] values, float[][] errors){
        Matrix matv = new Matrix(values);
        this.values = matv.getArrayCopy();
        Matrix mate = new Matrix(errors);
        this.errors = mate.getArrayCopy();
        this.errorType = 0;
        this.preprocessDataOne();
    }
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        this.errorType = 0;
        this.preprocessDataOne();
    }

    public RankAnalysis(long[][] values, long[][] errors){
        Matrix matv = new Matrix(values);
        this.values = matv.getArrayCopy();
        Matrix mate = new Matrix(errors);
        this.errors = mate.getArrayCopy();
        this.errorType = 0;
        this.preprocessDataOne();
    }
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        this.errorType = 0;
        this.preprocessDataOne();
    }

    public RankAnalysis(int[][] values, int[][] errors){
        Matrix matv = new Matrix(values);
        this.values = matv.getArrayCopy();
        Matrix mate = new Matrix(errors);
        this.errors = mate.getArrayCopy();
        this.errorType = 0;
        this.preprocessDataOne();
    }
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        this.errorType = 0;
        this.preprocessDataOne();
    }

    public RankAnalysis(BigDecimal[][] values, BigDecimal[][] errors){
        Matrix matv = new Matrix(values);
        this.values = matv.getArrayCopy();
        Matrix mate = new Matrix(errors);
        this.errors = mate.getArrayCopy();
        this.errorType = 0;
        this.preprocessDataOne();
    }
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        this.errorType = 0;
        this.preprocessDataOne();
    }

    public RankAnalysis(float[][] values, float[][] errors){
        Matrix matv = new Matrix(values);
        this.values = matv.getArrayCopy();
        Matrix mate = new Matrix(errors);
        this.errors = mate.getArrayCopy();
        this.errorType = 0;
        this.preprocessDataOne();
    }
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        this.errorType = 0;
        this.preprocessDataOne();
    }

    public RankAnalysis(long[][] values, long[][] errors){
        Matrix matv = new Matrix(values);
        this.values = matv.getArrayCopy();
        Matrix mate = new Matrix(errors);
        this.errors = mate.getArrayCopy();
        this.errorType = 0;
        this.preprocessDataOne();
    }
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        this.errorType = 0;
        this.preprocessDataOne();
    }

    public RankAnalysis(int[][] values, int[][] errors){
        Matrix matv = new Matrix(values);
        this.values = matv.getArrayCopy();
        Matrix mate = new Matrix(errors);
        this.errors = mate.getArrayCopy();
        this.errorType = 0;
        this.preprocessDataOne();
    }
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Related Classes of flanagan.math.Matrix

  • flanagan.analysis.RankAnalysis
  • flanagan.analysis.Regression
  • flanagan.analysis.Stat
  • flanagan.interpolation.TriCubicInterpolation
  • flanagan.math.ArrayMaths
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