Jama.Matrix.get()方法的使用及代码示例

x33g5p2x  于2022-01-24 转载在 其他  
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本文整理了Java中Jama.Matrix.get()方法的一些代码示例，展示了Matrix.get()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。Matrix.get()方法的具体详情如下：
包路径：Jama.Matrix
类名称：Matrix
方法名：get

Matrix.get介绍

暂无

代码示例

代码示例来源：origin: marytts/marytts

public void printPricipalComponents(Vector<String> factors) {
  System.out.println("PCs:");
  for (int j = 0; j < PC.getColumnDimension(); j++) {
    System.out.println("PC(" + j + ")");
    for (int i = 0; i < PC.getRowDimension(); i++)
      System.out.format(" %s %.5f\n", factors.elementAt(i), PC.get(i, j));
  }
}

代码示例来源：origin: h2oai/h2o-3

final Matrix inv_hessian = new Matrix(cs._hessian).inverse();
for (int j = 0; j < n_coef; ++j) {
 for (int k = 0; k <= j; ++k) {
  final double elem = -inv_hessian.get(j, k);
  o._var_coef[j][k] = elem;
  o._var_coef[k][j] = elem;

代码示例来源：origin: marytts/marytts

y = datay;
b = X.solve(y);
coeffs = new double[b.getRowDimension()];
for (int j = 0; j < b.getRowDimension(); j++) {
  coeffs[j] = b.get(j, 0);

代码示例来源：origin: marytts/marytts

int M = data.getRowDimension();
int N = data.getColumnDimension();
      data.set(i, j, ((data.get(i, j) - mn) / sd));
  } else {
      data.set(i, j, (data.get(i, j) - mn));
  data.print(data.getRowDimension(), 3);
V = new double[svd.getS().getRowDimension()];
for (int i = 0; i < svd.getS().getRowDimension(); i++) {
  V[i] = svd.getS().get(i, i);
  if (debug)
    System.out.println(V[i]);
double sumPropVar = 0.0; // sum of the proportion of variance
for (int j = 0; j < covProjectedData.getColumnDimension(); j++) {
  varianceProportion[j] = covProjectedData.get(j, j);
  sumPropVar += varianceProportion[j];

代码示例来源：origin: us.ihmc/IHMCRoboticsToolkit

private void copyArray(Matrix vectorIn, double[] out) {
  for (int i = 0; i < vectorIn.getRowDimension(); i++) {
    out[i] = vectorIn.get(i, 0);
  }
}

代码示例来源：origin: openimaj/openimaj

private void alignWithFrame(int frame) {
  Vector3D i1 = new Vector3D(R.get(frame, 0), R.get(frame, 1), R.get(frame, 2));
  i1 = i1.scalarMultiply(1 / i1.getNorm());
  final int f = R.getRowDimension() / 2;
  Vector3D j1 = new Vector3D(R.get(frame + f, 0), R.get(frame + f, 1), R.get(frame + f, 2));
  j1 = j1.scalarMultiply(1 / j1.getNorm());
  final Vector3D k1 = Vector3D.crossProduct(i1, j1);
  k1.scalarMultiply(1 / k1.getNorm());
  final Matrix R0 = new Matrix(new double[][] {
      { i1.getX(), j1.getX(), k1.getX() },
      { i1.getY(), j1.getY(), k1.getY() },
      { i1.getZ(), j1.getZ(), k1.getZ() },
  });
  R = R.times(R0);
  S = R0.inverse().times(S);
}

代码示例来源：origin: openimaj/openimaj

@Override
public double estimateProbability(double[] sample) {
  final int N = mean.getColumnDimension();
  final Matrix inv_covar = getCovariance().inverse();
  final double pdf_const_factor = 1.0 / Math.sqrt((Math.pow((2 * Math.PI), N) * getCovariance().det()));
  final Matrix xm = new Matrix(1, N);
  for (int i = 0; i < N; i++)
    xm.set(0, i, sample[i] - mean.get(0, i));
  final Matrix xmt = xm.transpose();
  final double v = xm.times(inv_covar.times(xmt)).get(0, 0);
  return pdf_const_factor * Math.exp(-0.5 * v);
}

代码示例来源：origin: marytts/marytts

int M = data.getRowDimension();
int N = data.getColumnDimension();
      data.set(i, j, ((data.get(i, j) - mn) / sd));
  } else {
      data.set(i, j, (data.get(i, j) - mn));
  data.print(data.getRowDimension(), 3);
V = new double[svd.getS().getRowDimension()];
for (int i = 0; i < svd.getS().getRowDimension(); i++) {
  V[i] = svd.getS().get(i, i);
  if (debug)
    System.out.println(V[i]);
double sumPropVar = 0.0; // sum of the proportion of variance
for (int j = 0; j < covProjectedData.getColumnDimension(); j++) {
  varianceProportion[j] = covProjectedData.get(j, j);
  sumPropVar += varianceProportion[j];

代码示例来源：origin: marytts/marytts

public void printPricipalComponents(Vector<String> factors) {
  System.out.println("PCs:");
  for (int j = 0; j < PC.getColumnDimension(); j++) {
    System.out.println("PC(" + j + ")");
    for (int i = 0; i < PC.getRowDimension(); i++)
      System.out.format(" %s %.5f\n", factors.elementAt(i), PC.get(i, j));
  }
}

代码示例来源：origin: h2oai/h2o-2

protected void calcModelStats(final double[] newCoef, final double newLoglik) {
 final int n_coef = coef.length;
 final Matrix inv_hessian = new Matrix(hessian).inverse();
 for (int j = 0; j < n_coef; ++j) {
  for (int k = 0; k <= j; ++k) {
   final double elem = -inv_hessian.get(j, k);
   var_coef[j][k] = elem;
   var_coef[k][j] = elem;

代码示例来源：origin: us.ihmc/ihmc-robotics-toolkit

private void copyArray(Matrix vectorIn, double[] out) {
  for (int i = 0; i < vectorIn.getRowDimension(); i++) {
    out[i] = vectorIn.get(i, 0);
  }
}

代码示例来源：origin: org.openimaj/sandbox

private void alignWithFrame(int frame) {
  Vector3D i1 = new Vector3D(R.get(frame, 0), R.get(frame, 1), R.get(frame, 2));
  i1 = i1.scalarMultiply(1 / i1.getNorm());
  final int f = R.getRowDimension() / 2;
  Vector3D j1 = new Vector3D(R.get(frame + f, 0), R.get(frame + f, 1), R.get(frame + f, 2));
  j1 = j1.scalarMultiply(1 / j1.getNorm());
  final Vector3D k1 = Vector3D.crossProduct(i1, j1);
  k1.scalarMultiply(1 / k1.getNorm());
  final Matrix R0 = new Matrix(new double[][] {
      { i1.getX(), j1.getX(), k1.getX() },
      { i1.getY(), j1.getY(), k1.getY() },
      { i1.getZ(), j1.getZ(), k1.getZ() },
  });
  R = R.times(R0);
  S = R0.inverse().times(S);
}

代码示例来源：origin: openimaj/openimaj

@Override
public double estimateLogProbability(double[] sample) {
  final int N = mean.getColumnDimension();
  final Matrix inv_covar = getCovariance().inverse();
  final double cov_det = getCovariance().det();
  final double pdf_const_factor = 1.0 / Math.sqrt((Math.pow((2 * Math.PI), N) * cov_det));
  final Matrix xm = new Matrix(1, N);
  for (int i = 0; i < N; i++)
    xm.set(0, i, sample[i] - mean.get(0, i));
  final Matrix xmt = xm.transpose();
  final double v = xm.times(inv_covar.times(xmt)).get(0, 0);
  return Math.log(pdf_const_factor) + (-0.5 * v);
}

代码示例来源：origin: marytts/marytts

y = datay;
b = X.solve(y);
coeffs = new double[b.getRowDimension()];
for (int j = 0; j < b.getRowDimension(); j++) {
  coeffs[j] = b.get(j, 0);

代码示例来源：origin: marytts/marytts

int M = data.getRowDimension();
int N = data.getColumnDimension();
      data.set(i, j, ((data.get(i, j) - mn) / sd));
  } else {
      data.set(i, j, (data.get(i, j) - mn));
  data.print(data.getRowDimension(), 3);
if (debug) {
  System.out.println("Covariance");
  covariance.print(covariance.getRowDimension(), 3);
double values[] = new double[pc.getD().getRowDimension()];
for (int i = 0; i < pc.getD().getRowDimension(); i++)
  values[i] = pc.getD().get(i, i);
  V[j] = values[k];
  for (int i = 0; i < pc.getV().getRowDimension(); i++)
    d[i][j] = pc.getV().get(i, k);
double sumPropVar = 0.0; // sum of the proportion of variance
for (int j = 0; j < covProjectedData.getColumnDimension(); j++) {
  varianceProportion[j] = covProjectedData.get(j, j);
  sumPropVar += varianceProportion[j];

代码示例来源：origin: marytts/marytts

System.out.println("Ordered PC(" + numPCA + ")");
numPCA = numPCA - 1;
double loadings[] = new double[PC.getRowDimension()];
for (int i = 0; i < PC.getRowDimension(); i++)
  loadings[i] = Math.abs(PC.get(i, numPCA));
for (int i = PC.getRowDimension() - 1; i >= 0; i--) {
  index = indices[i];
  System.out.format(" %s %.5f\n", factors[index], PC.get(index, numPCA));
for (int i = PC.getRowDimension() - 1; i >= 0; i--) {

代码示例来源：origin: marytts/marytts

Matrix x = new Matrix(A).solve(new Matrix(b));
double[] coeffs = new double[order + 1];
for (int j = 0; j <= order; j++) {
  coeffs[j] = x.get(j, 0);

代码示例来源：origin: openimaj/openimaj

/**
 * @param mat
 * @return trace of the matrix
 */
public static double trace(Matrix mat) {
  double sum = 0;
  for (int i = 0; i < mat.getRowDimension(); i++) {
    sum += mat.get(i, i);
  }
  return sum;
}

代码示例来源：origin: marytts/marytts

int M = data.getRowDimension();
int N = data.getColumnDimension();
      data.set(i, j, ((data.get(i, j) - mn) / sd));
  } else {
      data.set(i, j, (data.get(i, j) - mn));
  data.print(data.getRowDimension(), 3);
if (debug) {
  System.out.println("Covariance");
  covariance.print(covariance.getRowDimension(), 3);
double values[] = new double[pc.getD().getRowDimension()];
for (int i = 0; i < pc.getD().getRowDimension(); i++)
  values[i] = pc.getD().get(i, i);
  V[j] = values[k];
  for (int i = 0; i < pc.getV().getRowDimension(); i++)
    d[i][j] = pc.getV().get(i, k);
double sumPropVar = 0.0; // sum of the proportion of variance
for (int j = 0; j < covProjectedData.getColumnDimension(); j++) {
  varianceProportion[j] = covProjectedData.get(j, j);
  sumPropVar += varianceProportion[j];

代码示例来源：origin: marytts/marytts

System.out.println("Ordered PC(" + numPCA + ")");
numPCA = numPCA - 1;
double loadings[] = new double[PC.getRowDimension()];
for (int i = 0; i < PC.getRowDimension(); i++)
  loadings[i] = Math.abs(PC.get(i, numPCA));
for (int i = PC.getRowDimension() - 1; i >= 0; i--) {
  index = indices[i];
  System.out.format(" %s %.5f\n", factors[index], PC.get(index, numPCA));
for (int i = PC.getRowDimension() - 1; i >= 0; i--) {

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