Package mgui.neuro.stats

Class SignalProcessing

java.lang.Object
mgui.interfaces.Utility
mgui.neuro.stats.SignalProcessing
public class SignalProcessing
extends Utility
Utility class for signal processing functions.
Since:
1.0
Version:
1.0
Author:
Andrew Reid

  • Constructor Summary

    Constructors
    Constructor Description
    SignalProcessing()  

  • Method Summary

    Modifier and Type Method Description
    static java.util.ArrayList<java.lang.Double> getDerivative​(java.util.ArrayList<java.lang.Double> curve, int order)
    Returns a set of data points which represent the orderth order derivative of curve.
    static java.util.ArrayList<java.lang.Double> getNormalizedCurve​(java.util.ArrayList<java.lang.Double> curve)
    Normalizes this curve to the max and min of its values.
    static java.util.ArrayList<java.lang.Double> getNormalizedCurve​(java.util.ArrayList<java.lang.Double> curve, double min, double max)
    Normalizes this curve to max and min.
    static java.util.ArrayList<java.lang.Double> getResampledCurve​(java.util.ArrayList<java.lang.Double> curve, int samples, int order)
    Resample (interpolate with order) curve to specified number of samples.
    static java.util.ArrayList<java.lang.Double> smoothCurveMovingAverage​(java.util.ArrayList<java.lang.Double> curve, int n)
    Smooths curve using a moving-average algorithm, with a window width n = 2m + 1; where n is an odd number.

    Methods inherited from class java.lang.Object

    clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

  • Constructor Details

    • SignalProcessing

      public SignalProcessing()

  • Method Details

    • smoothCurveMovingAverage

      public static java.util.ArrayList<java.lang.Double> smoothCurveMovingAverage​(java.util.ArrayList<java.lang.Double> curve, int n)
      Smooths curve using a moving-average algorithm, with a window width n = 2m + 1; where n is an odd number. Each data point is assigned a value according to the function:

      y(k)_s = SUM[i = -m : m](y_k+1) / n

      See http://www.chem.uoa.gr/applets/appletsmooth/appl_smooth2.html

      Parameters:
      curve -
      n -
      Returns:

    • getDerivative

      public static java.util.ArrayList<java.lang.Double> getDerivative​(java.util.ArrayList<java.lang.Double> curve, int order)
      Returns a set of data points which represent the orderth order derivative of curve. The result will have order less elements than curve.
      Parameters:
      curve - the curve for which to compute the derivative
      order - the order of the derivative to compute
      Returns:
      the derivative for curve, with n - 1 elements

    • getResampledCurve

      public static java.util.ArrayList<java.lang.Double> getResampledCurve​(java.util.ArrayList<java.lang.Double> curve, int samples, int order)
      Resample (interpolate with order) curve to specified number of samples. Currently only resamples with linear interpolation.
      Parameters:
      curve - the curve to resample
      samples - the number of samples in the resulting curve
      the - order of the interpolation (currently does nothing as only linear interpolation is implemented.
      Returns:
      the resampled curve

    • getNormalizedCurve

      public static java.util.ArrayList<java.lang.Double> getNormalizedCurve​(java.util.ArrayList<java.lang.Double> curve)
      Normalizes this curve to the max and min of its values.
      Parameters:
      curve - the curve to normalize
      min - the minimum for the normalization
      max - the maximum for the normalization
      Returns:
      the normalized curve

    • getNormalizedCurve

      public static java.util.ArrayList<java.lang.Double> getNormalizedCurve​(java.util.ArrayList<java.lang.Double> curve, double min, double max)
      Normalizes this curve to max and min.
      Parameters:
      curve - the curve to normalize
      min - the minimum for the normalization
      max - the maximum for the normalization
      Returns:
      the normalized curve