cern.colt.matrix.linalg.Algebra类的使用及代码示例

x33g5p2x  于2022-01-17 转载在 其他  
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本文整理了Java中cern.colt.matrix.linalg.Algebra类的一些代码示例，展示了Algebra类的具体用法。这些代码示例主要来源于Github/Stackoverflow/Maven等平台，是从一些精选项目中提取出来的代码，具有较强的参考意义，能在一定程度帮忙到你。Algebra类的具体详情如下：
包路径：cern.colt.matrix.linalg.Algebra
类名称：Algebra

Algebra介绍

[英]Linear algebraic matrix operations operating on DoubleMatrix2D; concentrates most functionality of this package.
[中]双矩阵上的线性代数矩阵运算；集中此软件包的大部分功能。

代码示例

代码示例来源：origin: cmu-phil/tetrad

private double lik(DoubleMatrix2D K, DoubleMatrix2D S, int n, int k) {
  Algebra algebra = new Algebra();
  DoubleMatrix2D SK = algebra.mult(S, K);
  return (algebra.trace(SK) - Math.log(algebra.det(SK)) - k) * n;
}

代码示例来源：origin: com.blazegraph/colt

transposeMatrix     = Algebra.DEFAULT.transpose (patternMatrix);
QMatrix             = Algebra.DEFAULT.mult (transposeMatrix,patternMatrix);
inverseQMatrix      = Algebra.DEFAULT.inverse (QMatrix);
pseudoInverseMatrix = Algebra.DEFAULT.mult (inverseQMatrix,transposeMatrix);
weightMatrix        = Algebra.DEFAULT.mult (patternMatrix,pseudoInverseMatrix);
System.out.println("done.");

代码示例来源：origin: stackoverflow.com

Algebra algebra = new Algebra();
DoubleMatrix2D X = algebra.solve(matrix, D);

代码示例来源：origin: blazegraph/database

/**
 * Solves X*A = B, which is also A'*X' = B'.
 * @return X; a new independent matrix; solution if A is square, least squares solution otherwise.
 */
public DoubleMatrix2D solveTranspose(DoubleMatrix2D A, DoubleMatrix2D B) {
  return solve(transpose(A), transpose(B));
}
/**

代码示例来源：origin: cmu-phil/tetrad

Algebra algebra = new Algebra();
DoubleMatrix2D K = algebra.inverse(factory.diagonal(factory.diagonal(S)));
    int[] b = complement(all, a);
    DoubleMatrix2D a1 = S.viewSelection(a, a);
    DoubleMatrix2D a2 = algebra.inverse(a1);
    DoubleMatrix2D a3 = K.viewSelection(a, b);
    DoubleMatrix2D a4 = K.viewSelection(b, b);
    DoubleMatrix2D a5 = algebra.inverse(a4);
    DoubleMatrix2D a6 = K.viewSelection(b, a).copy();
    DoubleMatrix2D a7 = algebra.mult(a3, a5);
    DoubleMatrix2D a8 = algebra.mult(a7, a6);
    a2.assign(a8, PlusMult.plusMult(1));
    DoubleMatrix2D a9 = K.viewSelection(a, a);
  double diff = algebra.norm1(a32);
DoubleMatrix2D V = algebra.inverse(K);
double dev = lik(algebra.inverse(V), S, n, k);

代码示例来源：origin: com.blazegraph/colt

/**
 * Returns the two-norm (aka <i>euclidean norm</i>) of vector <tt>x</tt>; equivalent to <tt>mult(x,x)</tt>.
 */
public double norm2(DoubleMatrix1D x) {
  return mult(x,x);
}
/**

代码示例来源：origin: blazegraph/database

try { values.add(String.valueOf(cond(matrix)));} 
catch (IllegalArgumentException exc) { values.add(unknown+exc.getMessage()); }
try { values.add(String.valueOf(det(matrix)));} 
catch (IllegalArgumentException exc) { values.add(unknown+exc.getMessage()); }
try { values.add(String.valueOf(norm1(matrix)));} 
catch (IllegalArgumentException exc) { values.add(unknown+exc.getMessage()); }
try { values.add(String.valueOf(norm2(matrix)));} 
catch (IllegalArgumentException exc) { values.add(unknown+exc.getMessage()); }
try { values.add(String.valueOf(normF(matrix)));} 
catch (IllegalArgumentException exc) { values.add(unknown+exc.getMessage()); }
try { values.add(String.valueOf(normInfinity(matrix)));} 
catch (IllegalArgumentException exc) { values.add(unknown+exc.getMessage()); }
try { values.add(String.valueOf(rank(matrix)));} 
catch (IllegalArgumentException exc) { values.add(unknown+exc.getMessage()); }
try { values.add(String.valueOf(trace(matrix)));} 
catch (IllegalArgumentException exc) { values.add(unknown+exc.getMessage()); }

代码示例来源：origin: org.ujmp/ujmp-colt

public Matrix inv() {
  return new ColtDenseDoubleMatrix2D((DenseDoubleMatrix2D) new Algebra().inverse(matrix));
}

代码示例来源：origin: ca.umontreal.iro/ssj

Algebra alge = new Algebra();
final double mu = alge.trace(B) / n;
double x;
final double norm = alge.norm1(B) / THETA9;
int s;
if (norm > 1)
final DoubleMatrix2D B2 = alge.mult(B, B);    // B^2
final DoubleMatrix2D B4 = alge.mult(B2, B2);  // B^4
DoubleMatrix2D U = alge.mult(B4, W);   // U <-- B4*W
W.assign (B0, F.plusMult(cPade[1]));   // W <-- W + B0*cPade[1]
U = alge.mult(B, U);                   // U <-- B*U
W.assign (F.mult(cPade[8]));           // W <-- W*cPade[8]
W.assign (T, F. plusMult(cPade[6]));   // W <-- W + T*cPade[6]
DoubleMatrix2D V = alge.mult(B4, W);   // V <-- B4*W
  B.assign (F.mult(r));
  for (int i = 0; i < s; i++)
   B = alge.mult(B, B);

代码示例来源：origin: cmu-phil/tetrad

private static double norm2(DoubleMatrix2D mat){
  //return Math.sqrt(mat.copy().assign(Functions.pow(2)).zSum());
  Algebra al = new Algebra();
  //norm found by svd so we need rows >= cols
  if(mat.rows() < mat.columns()){
    return al.norm2(al.transpose(mat));
  }
  return al.norm2(mat);
}

代码示例来源：origin: ca.umontreal.iro/ssj

DoubleMatrix2D coltN = Algebra.ZERO.subMatrix(DoubleFactory2D.dense.make(N), 1, x.length-1, 1, h-1).copy();
DoubleMatrix2D coltM = Algebra.ZERO.mult(Algebra.ZERO.transpose(coltN), coltN);
DoubleMatrix2D coltP;
coltP = Algebra.ZERO.solve(coltM, coltQ);
double[] pxTemp = coltP.viewColumn(0).toArray();
double[] pyTemp = coltP.viewColumn(1).toArray();

代码示例来源：origin: ujmp/universal-java-matrix-package

public Matrix inv() {
  return new ColtDenseDoubleMatrix2D((DenseDoubleMatrix2D) Algebra.DEFAULT.inverse(matrix));
}

代码示例来源：origin: cmu-phil/tetrad

par.beta.assign(alg.transpose(par.beta), Functions.plus);
par.phi.assign(alg.transpose(par.phi), Functions.plus);
DoubleMatrix2D xBeta = alg.mult(xDat,alg.mult(par.beta, divBetaD));
DoubleMatrix2D dTheta = alg.mult(alg.mult(dDat, par.theta), divBetaD);
DoubleMatrix2D wxProd = alg.mult(xDat, alg.transpose(par.theta));
wxProd.assign(alg.mult(dDat, par.phi), Functions.plus);
for(int i = 0; i < n; i++){
  if (Thread.currentThread().isInterrupted()) {
    .5 * Math.pow(alg.normF(alg.mult(tempLoss, factory2D.diagonal(par.betad.copy().assign(Functions.sqrt)))), 2);
gradOut.beta = alg.mult(alg.transpose(xDat), tempLoss);
DoubleMatrix2D lowerBeta = alg.transpose(lowerTri(gradOut.beta.copy(), -1));
upperTri(gradOut.beta, 1).assign(lowerBeta, Functions.plus);
gradOut.alpha1 = alg.mult(factory2D.diagonal(par.betad),margSum(tempLoss, 1));
gradOut.theta = alg.mult(alg.transpose(dDat), tempLoss);
  wxTemp.assign(alg.mult(factory2D.diagonal(invDenom), wxTemp));
  for(int k = 0; k < n; k++){
    if (Thread.currentThread().isInterrupted()) {
DoubleMatrix2D gradW = alg.mult(alg.transpose(xDat), wxProd);

代码示例来源：origin: lessthanoptimal/Java-Matrix-Benchmark

@Override
  public long process(BenchmarkMatrix[] inputs, BenchmarkMatrix[] outputs, long numTrials) {
    DenseDoubleMatrix2D matA = inputs[0].getOriginal();
    DenseDoubleMatrix2D matB = inputs[1].getOriginal();
    Algebra alg = new Algebra();
    DoubleMatrix2D result = null;
    long prev = System.nanoTime();
    for( long i = 0; i < numTrials; i++ ) {
      result = alg.mult(matA,matB);
    }
    long elapsed = System.nanoTime()-prev;
    if( outputs != null ) {
      outputs[0] = new ColtBenchmarkMatrix(result);
    }
    return elapsed;
  }
}

代码示例来源：origin: com.github.vincentk/joptimizer

/**
 * @TODO: check this!!!
 * @see "http://mathworld.wolfram.com/PositiveDefiniteMatrix.html"
 */
public static DoubleMatrix2D randomValuesPositiveMatrix(int rows, int cols, double min, double max, Long seed) {
  DoubleMatrix2D Q = Utils.randomValuesMatrix(rows, cols, min, max, seed);
  DoubleMatrix2D P = Algebra.DEFAULT.mult(Q, Algebra.DEFAULT.transpose(Q.copy()));
return Algebra.DEFAULT.mult(P, P);
}

代码示例来源：origin: blazegraph/database

/**
Constructs and returns a new LU Decomposition object which uses the given tolerance for singularity detection; 
*/	
public LUDecompositionQuick(double tolerance) {
  this.algebra = new Algebra(tolerance);
}
/**

代码示例来源：origin: cmu-phil/tetrad

par.beta.assign(alg.transpose(par.beta), Functions.plus);
par.phi.assign(alg.transpose(par.phi), Functions.plus);
DoubleMatrix2D xBeta = alg.mult(alg.mult(xDat, par.beta), divBetaD);
DoubleMatrix2D dTheta = alg.mult(alg.mult(dDat, par.theta), divBetaD);
DoubleMatrix2D wxProd = alg.mult(xDat, alg.transpose(par.theta));
wxProd.assign(alg.mult(dDat, par.phi), Functions.plus);
for(int i = 0; i < n; i++){
  if (Thread.currentThread().isInterrupted()) {
grad.beta = alg.mult(alg.transpose(xDat), negLoss);
DoubleMatrix2D lowerBeta = alg.transpose(lowerTri(grad.beta.copy(), -1));
upperTri(grad.beta, 1).assign(lowerBeta, Functions.plus);
grad.alpha1 = alg.mult(factory2D.diagonal(par.betad),margSum(negLoss, 1));
grad.theta = alg.mult(alg.transpose(dDat), negLoss);
  wxTemp.assign(alg.mult(factory2D.diagonal(invDenom), wxTemp));
  for(int k = 0; k < n; k++){
    DoubleMatrix1D curRow = wxTemp.viewRow(k);
DoubleMatrix2D gradW = alg.mult(alg.transpose(xDat), wxProd);
grad.theta.assign(alg.transpose(gradW), Functions.plus);

代码示例来源：origin: com.github.vincentk/joptimizer

public void setAMatrix(DoubleMatrix2D AMatrix) {
  this.A = AMatrix;
  this.AT = ALG.transpose(A);
}

代码示例来源：origin: cmu-phil/tetrad

public static double norm2(DoubleMatrix1D vec){
    //return Math.sqrt(vec.copy().assign(Functions.pow(2)).zSum());
    return Math.sqrt(new Algebra().norm2(vec));
  }
}

代码示例来源：origin: lessthanoptimal/Java-Matrix-Benchmark

@Override
  public long process(BenchmarkMatrix[] inputs, BenchmarkMatrix[] outputs, long numTrials) {
    DenseDoubleMatrix2D matA = inputs[0].getOriginal();
    Algebra alg = new Algebra();
    long prev = System.nanoTime();
    for( long i = 0; i < numTrials; i++ ) {
      alg.det(matA);
    }
    return System.nanoTime()-prev;
  }
}

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Algebra

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