Package com.mockturtlesolutions.snifflib.datatypes

Examples of com.mockturtlesolutions.snifflib.datatypes.DblMatrix.divideBy()

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        DblMatrix[] new_pKa = new DblMatrix[pKa1.length];
       
        for (int n=0;n<pKa1.length;n++)
        {
          DblMatrix temp = weight1.times(pKa1[n]).plus(weight2.times(pKa2[n]));
          new_pKa[n] = temp.divideBy(weight1.plus(weight2));
          //new_pKa[n].show("new_pKa["+n+"]");
        }

        DblMatrix[] pKb1 = out.getEstimatedpKb(comps[m]);
        DblMatrix[] pKb2 = cont_pred.getEstimatedpKb(comps[m]);
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        DblMatrix[] new_pKb = new DblMatrix[pKb1.length];

        for (int n=0;n<pKb1.length;n++)
        {
          DblMatrix temp = weight1.times(pKb1[n]).plus(weight2.times(pKb2[n]));
          new_pKb[n] = temp.divideBy(weight1.plus(weight2));
        }


        out.setEstimatedpKa(comps[m],new_pKa);
        out.setEstimatedpKb(comps[m],new_pKb);
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    //We store the emperical average for the purposes of evaluating the prior as well.
    for (int n=0;n<params.length;n++)
    {
      System.out.println("Setting initial for parameter:"+params[n]);
      DblMatrix pKaSum = (DblMatrix)OUT.get(params[n]);
      this.setParam(params[n],pKaSum.divideBy(((Integer)divisors.get(params[n])).intValue()));
      pKaSum.divideBy(((Integer)divisors.get(params[n])).intValue());
     
      // if (this.avgcoefficients == null)
//       {
//         System.out.println("AVG COEFF IS NULL");
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    for (int n=0;n<params.length;n++)
    {
      System.out.println("Setting initial for parameter:"+params[n]);
      DblMatrix pKaSum = (DblMatrix)OUT.get(params[n]);
      this.setParam(params[n],pKaSum.divideBy(((Integer)divisors.get(params[n])).intValue()));
      pKaSum.divideBy(((Integer)divisors.get(params[n])).intValue());
     
      // if (this.avgcoefficients == null)
//       {
//         System.out.println("AVG COEFF IS NULL");
//       }
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      //this.avgcoefficients.setParam(params[n],pKaSum.divideBy(((Integer)divisors.get(params[n])).intValue()));
     
     
      DblParamSet pparms = this.getPriorParams();
      pparms.setParam(params[n],pKaSum.divideBy(((Integer)divisors.get(params[n])).intValue()));
     
      pKaSum = ((DblMatrix)SUMSQ.get(params[n])).minus((pKaSum.pow(2.0)).divideBy(((Integer)divisors.get(params[n])).intValue()));
      //this.stdcoefficients.setParam(params[n],pKaSum);
      pparms.setParam(params[n]+"_sigma",DblMatrix.sqrt(pKaSum));//Set the standard deviation in the priorParameters.
     
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          nickname = contents[m];
          occurances = (Integer)Navg.get(nickname);
          count = occurances.intValue();
          DblMatrix v = containedSOL.getConcentration(nickname);
          //val = (Double)((DblMatrix)contents.get(nickname)).getDoubleAt(0);
          containedSOL.setConcentration(nickname,v.divideBy(count));
          //contents.put(nickname,val.doubleValue()/count);
        }
      }
     
      //containedSOL is now a solution consisting of all stated components
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        if (buffname.endsWith(".water"))
        {

          
          IonicStr = Kw.divideBy(H).plus(H);
           
        }
        else
        {
       
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