Java Code Examples for org.apache.commons.math3.exception.util.LocalizedFormats#BANDWIDTH

The following examples show how to use org.apache.commons.math3.exception.util.LocalizedFormats#BANDWIDTH . You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may check out the related API usage on the sidebar.
Example 1
Source File: ModifiedLoess.java    From thunderstorm with GNU General Public License v3.0 3 votes vote down vote up 
/**
 * Construct a new {@link LoessInterpolator}
 * with given bandwidth, number of robustness iterations and accuracy.
 *
 * @param bandwidth  when computing the loess fit at
 * a particular point, this fraction of source points closest
 * to the current point is taken into account for computing
 * a least-squares regression.</br>
 * A sensible value is usually 0.25 to 0.5, the default value is
 * {@link #DEFAULT_BANDWIDTH}.
 * @param robustnessIters This many robustness iterations are done.</br>
 * A sensible value is usually 0 (just the initial fit without any
 * robustness iterations) to 4, the default value is
 * {@link #DEFAULT_ROBUSTNESS_ITERS}.
 * @param accuracy If the median residual at a certain robustness iteration
 * is less than this amount, no more iterations are done.
 * @throws OutOfRangeException if bandwidth does not lie in the interval [0,1].
 * @throws NotPositiveException if {@code robustnessIters} is negative.
 * @see #LoessInterpolator(double, int)
 * @since 2.1
 */
public ModifiedLoess(double bandwidth, int robustnessIters, double accuracy)
    throws OutOfRangeException,
           NotPositiveException {
    if (bandwidth < 0 ||
        bandwidth > 1) {
        throw new OutOfRangeException(LocalizedFormats.BANDWIDTH, bandwidth, 0, 1);
    }
    this.bandwidth = bandwidth;
    if (robustnessIters < 0) {
        throw new NotPositiveException(LocalizedFormats.ROBUSTNESS_ITERATIONS, robustnessIters);
    }
    this.robustnessIters = robustnessIters;
    this.accuracy = accuracy;
}
Example 2
Source File: LoessInterpolator.java    From astor with GNU General Public License v2.0 3 votes vote down vote up 
/**
 * Construct a new {@link LoessInterpolator}
 * with given bandwidth, number of robustness iterations and accuracy.
 *
 * @param bandwidth  when computing the loess fit at
 * a particular point, this fraction of source points closest
 * to the current point is taken into account for computing
 * a least-squares regression.</br>
 * A sensible value is usually 0.25 to 0.5, the default value is
 * {@link #DEFAULT_BANDWIDTH}.
 * @param robustnessIters This many robustness iterations are done.</br>
 * A sensible value is usually 0 (just the initial fit without any
 * robustness iterations) to 4, the default value is
 * {@link #DEFAULT_ROBUSTNESS_ITERS}.
 * @param accuracy If the median residual at a certain robustness iteration
 * is less than this amount, no more iterations are done.
 * @throws OutOfRangeException if bandwidth does not lie in the interval [0,1].
 * @throws NotPositiveException if {@code robustnessIters} is negative.
 * @see #LoessInterpolator(double, int)
 * @since 2.1
 */
public LoessInterpolator(double bandwidth, int robustnessIters, double accuracy)
    throws OutOfRangeException,
           NotPositiveException {
    if (bandwidth < 0 ||
        bandwidth > 1) {
        throw new OutOfRangeException(LocalizedFormats.BANDWIDTH, bandwidth, 0, 1);
    }
    this.bandwidth = bandwidth;
    if (robustnessIters < 0) {
        throw new NotPositiveException(LocalizedFormats.ROBUSTNESS_ITERATIONS, robustnessIters);
    }
    this.robustnessIters = robustnessIters;
    this.accuracy = accuracy;
}
Example 3
Source File: LoessInterpolator.java    From astor with GNU General Public License v2.0 3 votes vote down vote up 
/**
 * Construct a new {@link LoessInterpolator}
 * with given bandwidth, number of robustness iterations and accuracy.
 *
 * @param bandwidth  when computing the loess fit at
 * a particular point, this fraction of source points closest
 * to the current point is taken into account for computing
 * a least-squares regression.</br>
 * A sensible value is usually 0.25 to 0.5, the default value is
 * {@link #DEFAULT_BANDWIDTH}.
 * @param robustnessIters This many robustness iterations are done.</br>
 * A sensible value is usually 0 (just the initial fit without any
 * robustness iterations) to 4, the default value is
 * {@link #DEFAULT_ROBUSTNESS_ITERS}.
 * @param accuracy If the median residual at a certain robustness iteration
 * is less than this amount, no more iterations are done.
 * @throws OutOfRangeException if bandwidth does not lie in the interval [0,1].
 * @throws NotPositiveException if {@code robustnessIters} is negative.
 * @see #LoessInterpolator(double, int)
 * @since 2.1
 */
public LoessInterpolator(double bandwidth, int robustnessIters, double accuracy)
    throws OutOfRangeException,
           NotPositiveException {
    if (bandwidth < 0 ||
        bandwidth > 1) {
        throw new OutOfRangeException(LocalizedFormats.BANDWIDTH, bandwidth, 0, 1);
    }
    this.bandwidth = bandwidth;
    if (robustnessIters < 0) {
        throw new NotPositiveException(LocalizedFormats.ROBUSTNESS_ITERATIONS, robustnessIters);
    }
    this.robustnessIters = robustnessIters;
    this.accuracy = accuracy;
}
Example 4
Source File: LoessInterpolator.java    From astor with GNU General Public License v2.0 3 votes vote down vote up 
/**
 * Construct a new {@link LoessInterpolator}
 * with given bandwidth, number of robustness iterations and accuracy.
 *
 * @param bandwidth  when computing the loess fit at
 * a particular point, this fraction of source points closest
 * to the current point is taken into account for computing
 * a least-squares regression.</br>
 * A sensible value is usually 0.25 to 0.5, the default value is
 * {@link #DEFAULT_BANDWIDTH}.
 * @param robustnessIters This many robustness iterations are done.</br>
 * A sensible value is usually 0 (just the initial fit without any
 * robustness iterations) to 4, the default value is
 * {@link #DEFAULT_ROBUSTNESS_ITERS}.
 * @param accuracy If the median residual at a certain robustness iteration
 * is less than this amount, no more iterations are done.
 * @throws OutOfRangeException if bandwidth does not lie in the interval [0,1].
 * @throws NotPositiveException if {@code robustnessIters} is negative.
 * @see #LoessInterpolator(double, int)
 * @since 2.1
 */
public LoessInterpolator(double bandwidth, int robustnessIters, double accuracy) {
    if (bandwidth < 0 ||
        bandwidth > 1) {
        throw new OutOfRangeException(LocalizedFormats.BANDWIDTH, bandwidth, 0, 1);
    }
    this.bandwidth = bandwidth;
    if (robustnessIters < 0) {
        throw new NotPositiveException(LocalizedFormats.ROBUSTNESS_ITERATIONS, robustnessIters);
    }
    this.robustnessIters = robustnessIters;
    this.accuracy = accuracy;
}
Example 5
Source File: LoessInterpolator.java    From astor with GNU General Public License v2.0 3 votes vote down vote up 
/**
 * Construct a new {@link LoessInterpolator}
 * with given bandwidth, number of robustness iterations and accuracy.
 *
 * @param bandwidth  when computing the loess fit at
 * a particular point, this fraction of source points closest
 * to the current point is taken into account for computing
 * a least-squares regression.</br>
 * A sensible value is usually 0.25 to 0.5, the default value is
 * {@link #DEFAULT_BANDWIDTH}.
 * @param robustnessIters This many robustness iterations are done.</br>
 * A sensible value is usually 0 (just the initial fit without any
 * robustness iterations) to 4, the default value is
 * {@link #DEFAULT_ROBUSTNESS_ITERS}.
 * @param accuracy If the median residual at a certain robustness iteration
 * is less than this amount, no more iterations are done.
 * @throws OutOfRangeException if bandwidth does not lie in the interval [0,1].
 * @throws NotPositiveException if {@code robustnessIters} is negative.
 * @see #LoessInterpolator(double, int)
 * @since 2.1
 */
public LoessInterpolator(double bandwidth, int robustnessIters, double accuracy)
    throws OutOfRangeException,
           NotPositiveException {
    if (bandwidth < 0 ||
        bandwidth > 1) {
        throw new OutOfRangeException(LocalizedFormats.BANDWIDTH, bandwidth, 0, 1);
    }
    this.bandwidth = bandwidth;
    if (robustnessIters < 0) {
        throw new NotPositiveException(LocalizedFormats.ROBUSTNESS_ITERATIONS, robustnessIters);
    }
    this.robustnessIters = robustnessIters;
    this.accuracy = accuracy;
}
Example 6
Source File: LoessInterpolator.java    From astor with GNU General Public License v2.0 3 votes vote down vote up 
/**
 * Construct a new {@link LoessInterpolator}
 * with given bandwidth, number of robustness iterations and accuracy.
 *
 * @param bandwidth  when computing the loess fit at
 * a particular point, this fraction of source points closest
 * to the current point is taken into account for computing
 * a least-squares regression.</br>
 * A sensible value is usually 0.25 to 0.5, the default value is
 * {@link #DEFAULT_BANDWIDTH}.
 * @param robustnessIters This many robustness iterations are done.</br>
 * A sensible value is usually 0 (just the initial fit without any
 * robustness iterations) to 4, the default value is
 * {@link #DEFAULT_ROBUSTNESS_ITERS}.
 * @param accuracy If the median residual at a certain robustness iteration
 * is less than this amount, no more iterations are done.
 * @throws OutOfRangeException if bandwidth does not lie in the interval [0,1].
 * @throws NotPositiveException if {@code robustnessIters} is negative.
 * @see #LoessInterpolator(double, int)
 * @since 2.1
 */
public LoessInterpolator(double bandwidth, int robustnessIters, double accuracy) {
    if (bandwidth < 0 ||
        bandwidth > 1) {
        throw new OutOfRangeException(LocalizedFormats.BANDWIDTH, bandwidth, 0, 1);
    }
    this.bandwidth = bandwidth;
    if (robustnessIters < 0) {
        throw new NotPositiveException(LocalizedFormats.ROBUSTNESS_ITERATIONS, robustnessIters);
    }
    this.robustnessIters = robustnessIters;
    this.accuracy = accuracy;
}
Example 7
Source File: LoessInterpolator.java    From astor with GNU General Public License v2.0 3 votes vote down vote up 
/**
 * Construct a new {@link LoessInterpolator}
 * with given bandwidth, number of robustness iterations and accuracy.
 *
 * @param bandwidth  when computing the loess fit at
 * a particular point, this fraction of source points closest
 * to the current point is taken into account for computing
 * a least-squares regression.</br>
 * A sensible value is usually 0.25 to 0.5, the default value is
 * {@link #DEFAULT_BANDWIDTH}.
 * @param robustnessIters This many robustness iterations are done.</br>
 * A sensible value is usually 0 (just the initial fit without any
 * robustness iterations) to 4, the default value is
 * {@link #DEFAULT_ROBUSTNESS_ITERS}.
 * @param accuracy If the median residual at a certain robustness iteration
 * is less than this amount, no more iterations are done.
 * @throws OutOfRangeException if bandwidth does not lie in the interval [0,1].
 * @throws NotPositiveException if {@code robustnessIters} is negative.
 * @see #LoessInterpolator(double, int)
 * @since 2.1
 */
public LoessInterpolator(double bandwidth, int robustnessIters, double accuracy)
    throws OutOfRangeException,
           NotPositiveException {
    if (bandwidth < 0 ||
        bandwidth > 1) {
        throw new OutOfRangeException(LocalizedFormats.BANDWIDTH, bandwidth, 0, 1);
    }
    this.bandwidth = bandwidth;
    if (robustnessIters < 0) {
        throw new NotPositiveException(LocalizedFormats.ROBUSTNESS_ITERATIONS, robustnessIters);
    }
    this.robustnessIters = robustnessIters;
    this.accuracy = accuracy;
}
Example 8
Source File: LoessInterpolator.java    From astor with GNU General Public License v2.0 3 votes vote down vote up 
/**
 * Construct a new {@link LoessInterpolator}
 * with given bandwidth, number of robustness iterations and accuracy.
 *
 * @param bandwidth  when computing the loess fit at
 * a particular point, this fraction of source points closest
 * to the current point is taken into account for computing
 * a least-squares regression.</br>
 * A sensible value is usually 0.25 to 0.5, the default value is
 * {@link #DEFAULT_BANDWIDTH}.
 * @param robustnessIters This many robustness iterations are done.</br>
 * A sensible value is usually 0 (just the initial fit without any
 * robustness iterations) to 4, the default value is
 * {@link #DEFAULT_ROBUSTNESS_ITERS}.
 * @param accuracy If the median residual at a certain robustness iteration
 * is less than this amount, no more iterations are done.
 * @throws OutOfRangeException if bandwidth does not lie in the interval [0,1].
 * @throws NotPositiveException if {@code robustnessIters} is negative.
 * @see #LoessInterpolator(double, int)
 * @since 2.1
 */
public LoessInterpolator(double bandwidth, int robustnessIters, double accuracy)
    throws OutOfRangeException,
           NotPositiveException {
    if (bandwidth < 0 ||
        bandwidth > 1) {
        throw new OutOfRangeException(LocalizedFormats.BANDWIDTH, bandwidth, 0, 1);
    }
    this.bandwidth = bandwidth;
    if (robustnessIters < 0) {
        throw new NotPositiveException(LocalizedFormats.ROBUSTNESS_ITERATIONS, robustnessIters);
    }
    this.robustnessIters = robustnessIters;
    this.accuracy = accuracy;
}
Example 9
Source File: LoessInterpolator.java    From astor with GNU General Public License v2.0 3 votes vote down vote up 
/**
 * Construct a new {@link LoessInterpolator}
 * with given bandwidth, number of robustness iterations and accuracy.
 *
 * @param bandwidth  when computing the loess fit at
 * a particular point, this fraction of source points closest
 * to the current point is taken into account for computing
 * a least-squares regression.</br>
 * A sensible value is usually 0.25 to 0.5, the default value is
 * {@link #DEFAULT_BANDWIDTH}.
 * @param robustnessIters This many robustness iterations are done.</br>
 * A sensible value is usually 0 (just the initial fit without any
 * robustness iterations) to 4, the default value is
 * {@link #DEFAULT_ROBUSTNESS_ITERS}.
 * @param accuracy If the median residual at a certain robustness iteration
 * is less than this amount, no more iterations are done.
 * @throws OutOfRangeException if bandwidth does not lie in the interval [0,1].
 * @throws NotPositiveException if {@code robustnessIters} is negative.
 * @see #LoessInterpolator(double, int)
 * @since 2.1
 */
public LoessInterpolator(double bandwidth, int robustnessIters, double accuracy)
    throws OutOfRangeException,
           NotPositiveException {
    if (bandwidth < 0 ||
        bandwidth > 1) {
        throw new OutOfRangeException(LocalizedFormats.BANDWIDTH, bandwidth, 0, 1);
    }
    this.bandwidth = bandwidth;
    if (robustnessIters < 0) {
        throw new NotPositiveException(LocalizedFormats.ROBUSTNESS_ITERATIONS, robustnessIters);
    }
    this.robustnessIters = robustnessIters;
    this.accuracy = accuracy;
}