コード例 #1
0
ファイル: StatCalculator.java プロジェクト: cjfuller/imglib
 /**
  * Computes an alpha trimmed mean upon the current region of the current function. Note that this
  * method uses memory to make a copy of the input values. Larger input regions might require a lot
  * of memory.
  *
  * @param alpha A number between 0 and 0.5 specifying the proportion of samples to ignore on each
  *     end.
  * @return The measured value
  */
 public double alphaTrimmedMean(double alpha) {
   if ((alpha < 0) || (alpha >= 0.5))
     throw new IllegalArgumentException("alpha value must be >= 0 and < 0.5");
   T tmp = func.createOutput();
   values.clear();
   iter.reset();
   while (iter.hasNext()) {
     long[] pos = iter.next();
     func.compute(pos, tmp);
     values.add(tmp.getRealDouble());
   }
   values.sortValues();
   double tailSize = alpha * values.size();
   // can we avoid interpolation?
   if (tailSize == Math.floor(tailSize)) {
     // yes, trim count is exactly an integer
     return calcTrimmedMean(values, (int) tailSize);
   }
   // no, trim count is a float value
   // calc two trimmed means and interpolate to find the value between them
   double mean1 = calcTrimmedMean(values, (int) Math.floor(tailSize));
   double mean2 = calcTrimmedMean(values, (int) Math.ceil(tailSize));
   double fraction = tailSize - Math.floor(tailSize);
   double interpolation = ((1 - fraction) * mean1) + (fraction * mean2);
   return interpolation;
 }
コード例 #2
0
ファイル: StatCalculator.java プロジェクト: cjfuller/imglib
 private double calcTrimmedMean(PrimitiveDoubleArray vals, int halfTrim) {
   final int trimSize = halfTrim * 2;
   final int numElements = vals.size();
   if (numElements <= trimSize)
     throw new IllegalArgumentException(
         "number of samples must be greater than number of trimmed values");
   final int top = numElements - halfTrim;
   double sum = 0;
   for (int i = halfTrim; i < top; i++) {
     sum += vals.get(i);
   }
   return sum / (numElements - trimSize);
 }
コード例 #3
0
ファイル: StatCalculator.java プロジェクト: cjfuller/imglib
  /**
   * Computes the median upon the current region of the current function. Note that this method uses
   * memory to make a copy of the input values. Larger input regions might require a lot of memory.
   *
   * @return The measured value
   */
  public double median() {
    T tmp = func.createOutput();
    values.clear();
    iter.reset();
    while (iter.hasNext()) {
      long[] pos = iter.next();
      func.compute(pos, tmp);
      values.add(tmp.getRealDouble());
    }
    final int numElements = values.size();
    if (numElements <= 0)
      throw new IllegalArgumentException("number of samples must be greater than 0");

    values.sortValues();

    // odd number of elements
    if ((numElements % 2) == 1) return values.get(numElements / 2);

    // else an even number of elements
    double value1 = values.get((numElements / 2) - 1);
    double value2 = values.get((numElements / 2));
    return (value1 + value2) / 2;
  }