本文整理了Java中org.ujmp.core.Matrix.selectColumns()方法的一些代码示例，展示了Matrix.selectColumns()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.selectColumns()方法的具体详情如下：
包路径：org.ujmp.core.Matrix
类名称：Matrix
方法名：selectColumns

Matrix.selectColumns介绍

暂无

代码示例

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

public void actionPerformed(ActionEvent e) {
    try {
      Octave.getInstance().plot(matrix.getMatrix().selectColumns(Ret.NEW, 0),
          matrix.getMatrix().selectColumns(Ret.NEW, 1), "x");
    } catch (Exception e1) {
      e1.printStackTrace();
    }
  }
}

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

public void actionPerformed(ActionEvent e) {
    try {
      Matlab.getInstance().plot(matrix.getMatrix().selectColumns(Ret.NEW, 0),
          matrix.getMatrix().selectColumns(Ret.NEW, 1));
    } catch (Exception e1) {
      e1.printStackTrace();
    }
  }
}

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

public void actionPerformed(ActionEvent e) {
    try {
      Matlab.getInstance().plot(matrix.getMatrix().selectColumns(Ret.NEW, 0),
          matrix.getMatrix().selectColumns(Ret.NEW, 1), "x");
    } catch (Exception e1) {
      e1.printStackTrace();
    }
  }
}

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

public void actionPerformed(ActionEvent e) {
    try {
      Octave.getInstance().plot(matrix.getMatrix().selectColumns(Ret.NEW, 0),
          matrix.getMatrix().selectColumns(Ret.NEW, 1));
    } catch (Exception e1) {
      e1.printStackTrace();
    }
  }
}

代码示例来源：origin: jdmp/java-data-mining-package

public void trainAll(ListDataSet dataSet) {
  reset();
  classCount = getClassCount(dataSet);
  for (int i = 0; i < classCount; i++) {
    System.out.println("Training class " + i);
    Classifier c = singleClassClassifier.emptyCopy();
    singleClassClassifiers.add(c);
    Matrix input = dataSet.getInputMatrix();
    Matrix target = dataSet.getTargetMatrix().selectColumns(Ret.LINK, i);
    if (twoColumns) {
      Matrix target2 = target.minus(1).abs(Ret.NEW);
      target = Matrix.Factory.horCat(target, target2);
    }
    ListDataSet ds = DataSet.Factory.linkToInputAndTarget(input, target);
    c.trainAll(ds);
  }
}

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

private static Matrix replaceInColumn(Matrix original, Matrix firstGuess, long column) {
  Matrix y = original.selectColumns(Ret.NEW, column);

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

private static Matrix replaceInColumn(Matrix original, Matrix firstGuess, long column) {
  Matrix x = firstGuess.deleteColumns(Ret.NEW, column);
  Matrix y = original.selectColumns(Ret.NEW, column);
  List<Long> missingRows = new ArrayList<Long>();
  for (long i = y.getRowCount(); --i >= 0;) {
    double v = y.getAsDouble(i, 0);
    if (MathUtil.isNaNOrInfinite(v)) {
      missingRows.add(i);
    }
  }
  if (missingRows.isEmpty()) {
    return y;
  }
  Matrix xdel = x.deleteRows(Ret.NEW, missingRows);
  DenseDoubleMatrix2D bias1 = DenseDoubleMatrix2D.Factory.ones(xdel.getRowCount(), 1);
  Matrix xtrain = Matrix.Factory.horCat(xdel, bias1);
  Matrix ytrain = y.deleteRows(Ret.NEW, missingRows);
  Matrix xinv = xtrain.pinv();
  Matrix b = xinv.mtimes(ytrain);
  DenseDoubleMatrix2D bias2 = DenseDoubleMatrix2D.Factory.ones(x.getRowCount(), 1);
  Matrix yPredicted = Matrix.Factory.horCat(x, bias2).mtimes(b);
  // set non-missing values back to original values
  for (int row = 0; row < y.getRowCount(); row++) {
    double v = y.getAsDouble(row, 0);
    if (!Double.isNaN(v)) {
      yPredicted.setAsDouble(v, row, 0);
    }
  }
  return yPredicted;
}

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

public ExtractAnnotation(Matrix m, int dim) {
  super(dim, m);
  size = Coordinates.copyOf(m.getSize());
  size[dim]--;
  setMetaData(new DefaultMapMatrix<String, Object>(new TreeMap<String, Object>()));
  getMetaData().put(Matrix.LABEL, m.getLabelObject());
  if (dim == ROW) {
    MapMatrix<String, Object> a = m.getMetaData();
    if (a != null) {
      Matrix ai = (Matrix) a.get(Matrix.DIMENSIONMETADATA + COLUMN);
      if (ai != null) {
        ai = ai.deleteRows(Ret.NEW, 0);
        getMetaData().put(Matrix.DIMENSIONMETADATA + COLUMN, ai);
      }
    }
    getMetaData().put(Matrix.DIMENSIONMETADATA + ROW, m.selectRows(Ret.NEW, 0));
  } else if (dim == COLUMN) {
    MapMatrix<String, Object> a = m.getMetaData();
    if (a != null) {
      Matrix ai = (Matrix) a.get(Matrix.DIMENSIONMETADATA + ROW);
      if (ai != null) {
        ai = ai.selectColumns(Ret.NEW, 0);
        getMetaData().put(Matrix.DIMENSIONMETADATA + ROW, ai);
      }
    }
    getMetaData().put(Matrix.DIMENSIONMETADATA + COLUMN, m.selectColumns(Ret.NEW, 0));
  } else {
    throw new RuntimeException("only supported for 2D matrices");
  }
}