Class RemoveNoise<T extends DataContainer & Mergeable>

  • Type Parameters:
    T - the data to process
    All Implemented Interfaces:
    CleanUpHandler, Destroyable, GlobalInfoSupporter, LoggingLevelHandler, LoggingSupporter, OptionHandler, ShallowCopySupporter<Filter>, SizeOfHandler, Filter<T>, Serializable, Comparable

    public class RemoveNoise<T extends DataContainer & Mergeable>
    extends AbstractFilter<T>
    A filter that removes noise from the data with a user-supplied noise level algorithm.

    Valid options are:

    -D (property: debug)
             If set to true, scheme may output additional info to the console.
     
    -denoiser <gcms.data.noise.AbstractDenoiser [options]> (property: denoiser)
             The denoiser algorithm to use for removing the noise from the data.
             default: gcms.data.noise.MedianHeightDifference -factor-sd 2.0 -thr2 -1.0 -savitzky "gcms.data.filter.SavitzkyGolay -polynomial 2 -derivative 0 -left 3 -right 3 -optimize 15" -derivative "gcms.data.filter.Derivative -order 2 -scaling -1.0"
     
    -invert (property: invert)
             If set to true, non-noise will be removed instead of noise.
     
    Default options for gcms.data.noise.MedianHeightDifference (-denoiser/denoiser):
    -D (property: debug)
             If set to true, scheme may output additional info to the console.
     
    -zero (property: zeroNoise)
             If set to true, the abundances of noisy points will be set to zero instead
              of being completely removed from the data.
     
    -factor-sd <double> (property: thresholdSdFactor)
             The factor to multiply the height median (thr_sd) with in order to obtain
              the threshold below signals are considered being noise.
             default: 2
     
    -thr2 <double> (property: threshold2)
             A user-supplied threshold (= thr_2) that is applied to the abundances of
              the original input data, use -1 to disable.
             default: -1.0
     
    -savitzky <gcms.data.filter.AbstractFilter [options]> (property: savitzkyGolay)
             The Savitzky-Golay filter setup to use in smoothing the data beforehand.
             default: gcms.data.filter.SavitzkyGolay -polynomial 2 -derivative 0 -left 3 -right 3 -optimize 15
     
    -derivative <gcms.data.filter.AbstractFilter [options]> (property: derivative)
             The Derivative filter to use (always uses 2nd derivative).
             default: gcms.data.filter.Derivative -order 2 -scaling -1.0
     
    -regions (property: recordRegions)
             If set to true, the elution regions will be recorded as well.
     
    Default options for gcms.data.filter.SavitzkyGolay (-savitzky/savitzkyGolay):
     
    -D (property: debug)
             If set to true, scheme may output additional info to the console.
     
    -polynomial <int> (property: polynomialOrder)
             The polynomial order to use, must be at least 2.
             default: 2
     
    -derivative <int> (property: derivativeOrder)
             The order of the derivative to use, >= 0.
             default: 1
     
    -left <int> (property: numPointsLeft)
             The number of points left of a data point, >= 0.
             default: 3
     
    -right <int> (property: numPointsRight)
             The number of points right of a data point, >= 0.
             default: 3
     
    -optimize <int> (property: optimizeWindowSize)
             The maximum window size to optimize (odd, positive number); uses the Durbin-Watson
              statistic to determine the best window size, ie, number of points left
             and right of the points being smoothed; the data must be oscillating around
              zero, ie, passed through the Derivative filter.
             default: -1
     
    
    
     
    Default options for gcms.data.filter.Derivative (-derivative/derivative):
     
    -D (property: debug)
             If set to true, scheme may output additional info to the console.
     
    -order <int> (property: order)
             The order of the derivative to calculate.
             default: 1
     
    -scaling <double> (property: scalingRange)
             The range to scale the abundances to after each derivation step; use 0 to
              turn off and -1 to set it to the input range.
             default: 0.0
     
    Version:
    $Revision$
    Author:
    fracpete (fracpete at waikato dot ac dot nz)
    See Also:
    Serialized Form
    • Field Detail

      • m_Invert

        protected boolean m_Invert
        indicates whether to invert behavior, i.e., to remove non-noise instead of noise.
    • Constructor Detail

      • RemoveNoise

        public RemoveNoise()
    • Method Detail

      • setDenoiser

        public void setDenoiser​(AbstractDenoiser value)
        Sets the denoiser algorithm.
        Parameters:
        value - the algorithm
      • getDenoiser

        public AbstractDenoiser getDenoiser()
        Returns the current denoiser algorithm.
        Returns:
        the algorithm
      • denoiserTipText

        public String denoiserTipText()
        Returns the tip text for this property.
        Returns:
        tip text for this property suitable for displaying in the GUI or for listing the options.
      • setInvert

        public void setInvert​(boolean value)
        Sets whether the behavior should be inverted, i.e., removing non-noise.
        Parameters:
        value - true if non-noise should be removed
      • getInvert

        public boolean getInvert()
        Returns whether non-noise is removed (= true) or the actual noise.
        Returns:
        true if non-noise is removed
      • invertTipText

        public String invertTipText()
        Returns the tip text for this property.
        Returns:
        tip text for this property suitable for displaying in the GUI or for listing the options.