Examples of viewDice()


Examples of cern.colt.matrix.DoubleMatrix2D.viewDice()

  { 0       , -0.112952,-0.04932 ,-0.700157,0},
  { 0       , 0        ,0        ,0        ,0}
};
DoubleMatrix2D H = new DenseDoubleMatrix2D( vals ); // see values below...
System.out.println("\nHplus="+H.viewDice().zMult(H,null));

DoubleMatrix2D Hplus = Algebra.DEFAULT.inverse(H.viewDice().zMult( H,null )).zMult(H.viewDice(),null);
Hplus.assign(cern.jet.math.Functions.round(1.0E-10));
System.out.println("\nHplus="+Hplus);
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Examples of cern.colt.matrix.DoubleMatrix2D.viewDice()

System.out.println("\n\ninitializing...");
DoubleFactory2D factory = DoubleFactory2D.dense;
DoubleMatrix2D A = factory.make(values).viewDice();

System.out.println("\nA="+A.viewDice());
System.out.println("\ndist="+distance(A,norm).viewDice());
}
/**
* Constructs and returns the distance matrix of the given matrix.
* The distance matrix is a square, symmetric matrix consisting of nothing but distance coefficients.
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Examples of cern.colt.matrix.DoubleMatrix2D.viewDice()

System.out.println("\n\ninitializing...");
DoubleFactory2D factory = DoubleFactory2D.dense;
DoubleMatrix2D A = factory.make(values).viewDice();

System.out.println("\nA="+A.viewDice());
System.out.println("\ndist="+distance(A,norm).viewDice());
}
/**
* Constructs and returns the distance matrix of the given matrix.
* The distance matrix is a square, symmetric matrix consisting of nothing but distance coefficients.
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Examples of cern.colt.matrix.DoubleMatrix2D.viewDice()

  { 0       , -0.112952,-0.04932 ,-0.700157,0},
  { 0       , 0        ,0        ,0        ,0}
};
DoubleMatrix2D H = new DenseDoubleMatrix2D( vals ); // see values below...
System.out.println("\nHplus="+H.viewDice().zMult(H,null));

DoubleMatrix2D Hplus = Algebra.DEFAULT.inverse(H.viewDice().zMult( H,null )).zMult(H.viewDice(),null);
Hplus.assign(cern.jet.math.Functions.round(1.0E-10));
System.out.println("\nHplus="+Hplus);
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Examples of cern.colt.matrix.DoubleMatrix3D.viewDice()

  for (int j=densities.length; --j >= 0; ) colNames[j]=Double.toString(densities[j]);
  System.out.println("*");
  // show transposed
  String tmp = rowAxisName; rowAxisName = colAxisName; colAxisName = tmp;
  String[] tmp2 = rowNames; rowNames = colNames; colNames = tmp2;
  timings = timings.viewDice(0,2,1);
  System.out.println(new cern.colt.matrix.doublealgo.Formatter("%1.3G").toTitleString(timings,sliceNames,rowNames,colNames,sliceAxisName,rowAxisName,colAxisName,"Performance of "+title,aggr));
  /*
  title = "Speedup of dense over sparse";
  DoubleMatrix2D speedup = cern.colt.matrix.doublealgo.Transform.div(timings.viewSlice(0).copy(),timings.viewSlice(1));
  System.out.println("\n"+new cern.colt.matrix.doublealgo.Formatter("%1.3G").toTitleString(speedup,rowNames,colNames,rowAxisName,colAxisName,title,aggr));
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Examples of org.apache.mahout.math.matrix.DoubleMatrix2D.viewDice()

            }

            final DoubleMatrix2D phraseMatrix = TermDocumentMatrixBuilder
                .buildAlignedMatrix(context, phraseFeatureIndices, termWeighting);
            MatrixUtils.normalizeColumnL2(phraseMatrix, null);
            context.termPhraseMatrix = phraseMatrix.viewDice();
        }
    }

    /**
     * Calculates the boost we should apply to a stem, based on the field indices array.
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