Package flanagan.math

Examples of flanagan.math.ArrayMaths.sort()


        // Calculate standardized transformed data statistics
        this.standardizedTransformedDataStatistics(this.standardizedTransformedData);

        // Obtain the intercept and gradient of the Gaussian probabilty plot
        ArrayMaths st4 = new ArrayMaths(this.standardizedTransformedData);
        st4 = st4.sort();
        double[] ordered = st4.array();
        Regression reg = new Regression(this.gaussianOrderMedians, ordered);
        reg.linear();
        coeff = reg.getBestEstimates();
        this.transformedIntercept = coeff[0];
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        // Calculate standardized transformed data statistics
        this.standardizedTransformedDataStatistics(this.standardizedTransformedData);

        // Obtain the intercept and gradient of the Gaussian probabilty plot
        ArrayMaths st4 = new ArrayMaths(this.standardizedTransformedData);
        st4 = st4.sort();
        double[] ordered = st4.array();
        Regression reg = new Regression(this.gaussianOrderMedians, ordered);
        reg.linear();
        double[] coeff = reg.getBestEstimates();
        this.transformedIntercept = coeff[0];
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    // Return ordered transformed data
    public double[] orderedTransformedData(){
        if(!this.transformDone)this.transform();
        ArrayMaths am = new ArrayMaths(this.transformedData);
        double[] ordered = (am.sort()).array();
        return ordered;
    }

    // Return ordered scaled transformed data
    public double[] orderedScaledTransformedData(){
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        super.nXarrays = 1;
        super.nYarrays = 1;

        // Sort analyte concns into ascending order
        ArrayMaths am = new ArrayMaths(this.analyteConcns);
        am = am.sort();
        int[] indices = am.originalIndices();
        double[] hold = new double[this.nAnalyteConcns];
        hold = Conv.copy(this.analyteConcns);
        for(int i=0; i<this.nAnalyteConcns; i++)this.analyteConcns[i] = hold[indices[i]];
        hold = Conv.copy(this.responses);
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    // Return ordered transformed data
    public double[] orderedTransformedData(){
        if(!this.transformDone)this.transform();
        ArrayMaths am = new ArrayMaths(this.transformedData);
        double[] ordered = (am.sort()).array();
        return ordered;
    }

    // Return ordered scaled transformed data
    public double[] orderedScaledTransformedData(){
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          if(mPoints!=y[0].length)throw new IllegalArgumentException("Arrays x2 and y-column are of different length "+ mPoints + " " + y[0].length);
            if(nPoints<2 || mPoints<2)throw new IllegalArgumentException("The data matrix must have a minimum size of 2 X 2");

            // order data
            ArrayMaths am = new ArrayMaths(x1);
            am = am.sort();
            this.x1indices = am.originalIndices();
            x1 = am.array();
            double[][] hold = new double[nPoints][mPoints];
            double[][] hold1 = null;
            double[][] hold2 = null;
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                  }
              }
            }

          am = new ArrayMaths(x2);
            am = am.sort();
            this.x2indices = am.originalIndices();
            double[] xh = am.array();
            for(int i=0; i<mPoints; i++)x2[i] = xh[mPoints-1-i];
            for(int i=0; i<mPoints; i++){
              for(int j=0; j<nPoints; j++){
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          if(nPoints!=y.length)throw new IllegalArgumentException("Arrays x and y-row are of different length " + nPoints + " " + y.length);
            if(nPoints<nl)throw new IllegalArgumentException("The data matrix must have a minimum size of " + nl + " X " + nl);

            // order data
            ArrayMaths am = new ArrayMaths(x);
            am = am.sort();
            this.xIndices = am.originalIndices();
            x = am.array();
            double[] hold = new double[nPoints];

            for(int i=0; i<nPoints; i++){
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            // Calculate weighting matrix
            this.calcWeights();

            // order data
            ArrayMaths am = new ArrayMaths(x1);
            am = am.sort();
            this.x1indices = am.originalIndices();
            x1 = am.array();
            double[][][] hold = new double[lPoints][mPoints][nPoints];
            double[][][] hold1 = null;
            double[][][] hold2 = null;
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                  }
              }
            }

          am = new ArrayMaths(x2);
            am = am.sort();
            this.x2indices = am.originalIndices();
            x2 = am.array();

            for(int i=0; i<lPoints; i++){
              for(int j=0; j<mPoints; j++){
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