Surrogate (IQM 3.5 API)

java.lang.Object
- at.mug.iqm.commons.util.plot.Surrogate

```
public class Surrogate
extends Object
```
This class calculates surrogate data Options: Shuffle, Gaussian, Phase randomized, AAFT, Pseudo-Periodic, Multivariate see e.g. Mark Shelhammer, Nonlinear Dynamics in Physiology, World Scientific 2007

Since:

2012 11

Author:

Helmut Ahammer

Field Summary

Fields
Modifier and Type	Field and Description
`private AbstractOperator`	`operator`
`private int`	`progressBarMax`
`private int`	`progressBarMin`
`static int`	`SURROGATE_AAFT`
`static int`	`SURROGATE_GAUSSIAN`
`static int`	`SURROGATE_MULTIVARIATE`
`static int`	`SURROGATE_PSEUDOPERIODIC`
`static int`	`SURROGATE_RANDOMPHASE`
`static int`	`SURROGATE_SHUFFLE`

Constructor Summary

Constructors
Constructor and Description
`Surrogate()` This is the standard constructor
`Surrogate(AbstractOperator operator)` This is the standard constructor with the possibility to import calling class This is useful for progress bar and canceling functionality

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`Double`	`calcMean(double[] doubleArray)` This method calculates the mean of a data series
`Double`	`calcMean(Vector<Double> data1D)` This method calculates the mean of a data series
`private double`	`calcStandardDeviation(double[] doubleArray)` This method calculates the standard deviation of a data series
`private double`	`calcStandardDeviation(Vector<Double> data1D)` This method calculates the standard deviation of a data series
`double[]`	`calcSurrogateAAFT(double[] signal)` This method calculates a surrogate data double array using the AAFT (amplitude adjusted FT) method A Gaussian signal y is constructed y is ranked according to the original signal then y is FFT converted, phase randomized and inverse FFT back converted yielding y' the original signal is ranked according to y'
`double[]`	`calcSurrogateGaussian(double[] signal)` This method calculates a surrogate data double array using the Gaussian method A Gaussian signal with identical mean and standard deviation as the original signal is constructed
`Vector<Double>`	`calcSurrogateGaussian(Vector<Double> data1D)` This method calculates a surrogate data vector using the Gaussian method A Gaussian signal with identical mean and standard deviation as the original signal is constructed
`double[]`	`calcSurrogateMultivariate(double[] signal)` This method calculates a surrogate data double array using the multivariate method Not implemented yet
`double[]`	`calcSurrogatePseudoPeriodic(double[] signal)` This method calculates a surrogate data double array using the pseudo periodic method Not implented yet
`double[]`	`calcSurrogateRandomPhase(double[] signal)` This method calculates a surrogate data double array using the phase randomized method The signal is FFT converted, phase randomized and inverse FFT back converted
`Vector<Vector<Double>>`	`calcSurrogateSeries(Vector<Double> data1D, int method, int times)` This method calculates new surrogate series
`double[]`	`calcSurrogateShuffle(double[] signal)` This method calculates a surrogate data double array using the shuffle method The signal is randomly shuffled
`private double`	`calcVariance(double[] doubleArray)` This method calculates the variance of a data series
`private double`	`calcVariance(Vector<Double> data1D)` This method calculates the variance of a data series
`private Vector<Double>`	`convertDoubleArrayToVector(double[] doubleArray)` This method constructs a Vector from a double[] array
`private double[]`	`convertVectorToDoubleArray(Vector<Double> data1D)` This method constructs a double[] array from a Vector
`int`	`getProgressBarMax()`
`int`	`getProgressBarMin()`
`void`	`setProgressBarMax(int progressBarMax)`
`void`	`setProgressBarMin(int progressBarMin)`

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Field Detail
  - SURROGATE_SHUFFLE
```
public static final int SURROGATE_SHUFFLE
```
    See Also:
    
    Constant Field Values
  - SURROGATE_GAUSSIAN
```
public static final int SURROGATE_GAUSSIAN
```
    See Also:
    
    Constant Field Values
  - SURROGATE_RANDOMPHASE
```
public static final int SURROGATE_RANDOMPHASE
```
    See Also:
    
    Constant Field Values
  - SURROGATE_AAFT
```
public static final int SURROGATE_AAFT
```
    See Also:
    
    Constant Field Values
  - SURROGATE_PSEUDOPERIODIC
```
public static final int SURROGATE_PSEUDOPERIODIC
```
    See Also:
    
    Constant Field Values
  - SURROGATE_MULTIVARIATE
```
public static final int SURROGATE_MULTIVARIATE
```
    See Also:
    
    Constant Field Values
  - operator
```
private AbstractOperator operator
```
  - progressBarMin
```
private int progressBarMin
```
  - progressBarMax
```
private int progressBarMax
```
- Constructor Detail
  - Surrogate
```
public Surrogate(AbstractOperator operator)
```
    This is the standard constructor with the possibility to import calling class This is useful for progress bar and canceling functionality
    
    Parameters:
    
    operator -
  - Surrogate
```
public Surrogate()
```
    This is the standard constructor
- Method Detail
  - getProgressBarMin
```
public int getProgressBarMin()
```
  - setProgressBarMin
```
public void setProgressBarMin(int progressBarMin)
```
  - getProgressBarMax
```
public int getProgressBarMax()
```
  - setProgressBarMax
```
public void setProgressBarMax(int progressBarMax)
```
  - convertVectorToDoubleArray
```
private double[] convertVectorToDoubleArray(Vector<Double> data1D)
```
    This method constructs a double[] array from a Vector
    
    Parameters:
    
    data1D -
    
    Returns:
    
    double array
  - convertDoubleArrayToVector
```
private Vector<Double> convertDoubleArrayToVector(double[] doubleArray)
```
    This method constructs a Vector from a double[] array
    
    Parameters:
    
    doubleArray -
    
    Returns:
    
    a vector of doubles
  - calcMean
```
public Double calcMean(Vector<Double> data1D)
```
    This method calculates the mean of a data series
    
    Parameters:
    
    data1D -
    
    Returns:
    
    Double Mean
  - calcMean
```
public Double calcMean(double[] doubleArray)
```
    This method calculates the mean of a data series
    
    Parameters:
    
    doubleArray -
    
    Returns:
    
    Double Mean
  - calcVariance
```
private double calcVariance(Vector<Double> data1D)
```
    This method calculates the variance of a data series
    
    Parameters:
    
    data1D -
    
    Returns:
    
    Double Variance
  - calcVariance
```
private double calcVariance(double[] doubleArray)
```
    This method calculates the variance of a data series
    
    Parameters:
    
    doubleArray -
    
    Returns:
    
    Double Variance
  - calcStandardDeviation
```
private double calcStandardDeviation(Vector<Double> data1D)
```
    This method calculates the standard deviation of a data series
    
    Parameters:
    
    data1D -
    
    Returns:
    
    Double standard deviation
  - calcStandardDeviation
```
private double calcStandardDeviation(double[] doubleArray)
```
    This method calculates the standard deviation of a data series
    
    Parameters:
    
    doubleArray -
    
    Returns:
    
    Double standard deviation
  - calcSurrogateShuffle
```
public double[] calcSurrogateShuffle(double[] signal)
```
    This method calculates a surrogate data double array using the shuffle method The signal is randomly shuffled
    
    Parameters:
    
    signal -
    
    Returns:
    
    surrogate data
  - calcSurrogateGaussian
```
public Vector<Double> calcSurrogateGaussian(Vector<Double> data1D)
```
    This method calculates a surrogate data vector using the Gaussian method A Gaussian signal with identical mean and standard deviation as the original signal is constructed
    
    Parameters:
    
    data1D -
    
    Returns:
    
    surrogate data
  - calcSurrogateGaussian
```
public double[] calcSurrogateGaussian(double[] signal)
```
    This method calculates a surrogate data double array using the Gaussian method A Gaussian signal with identical mean and standard deviation as the original signal is constructed
    
    Parameters:
    
    signal -
    
    Returns:
    
    surrogate data
  - calcSurrogateRandomPhase
```
public double[] calcSurrogateRandomPhase(double[] signal)
```
    This method calculates a surrogate data double array using the phase randomized method The signal is FFT converted, phase randomized and inverse FFT back converted
    
    Parameters:
    
    signal -
    
    Returns:
    
    surrogate data
  - calcSurrogateAAFT
```
public double[] calcSurrogateAAFT(double[] signal)
```
    This method calculates a surrogate data double array using the AAFT (amplitude adjusted FT) method A Gaussian signal y is constructed y is ranked according to the original signal then y is FFT converted, phase randomized and inverse FFT back converted yielding y' the original signal is ranked according to y'
    
    Parameters:
    
    signal -
    
    Returns:
    
    surrogate data
  - calcSurrogatePseudoPeriodic
```
public double[] calcSurrogatePseudoPeriodic(double[] signal)
```
    This method calculates a surrogate data double array using the pseudo periodic method Not implented yet
    
    Parameters:
    
    signal -
    
    Returns:
    
    surrogate data
  - calcSurrogateMultivariate
```
public double[] calcSurrogateMultivariate(double[] signal)
```
    This method calculates a surrogate data double array using the multivariate method Not implemented yet
    
    Parameters:
    
    signal -
    
    Returns:
    
    surrogate data
  - calcSurrogateSeries
```
public Vector<Vector<Double>> calcSurrogateSeries(Vector<Double> data1D,
                                                  int method,
                                                  int times)
```
    This method calculates new surrogate series
    
    Parameters:
    
    data1D - 1D data vector
    
    method - method of surrogate data generation
    
    times - number of new series
    
    Returns:
    
    Vector of Series (vectors)

Class Surrogate

Field Summary

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Field Detail

SURROGATE_SHUFFLE

SURROGATE_GAUSSIAN

SURROGATE_RANDOMPHASE

SURROGATE_AAFT

SURROGATE_PSEUDOPERIODIC

SURROGATE_MULTIVARIATE

operator

progressBarMin

progressBarMax

Constructor Detail

Surrogate

Surrogate

Method Detail

getProgressBarMin

setProgressBarMin

getProgressBarMax

setProgressBarMax

convertVectorToDoubleArray

convertDoubleArrayToVector

calcMean

calcMean

calcVariance

calcVariance

calcStandardDeviation

calcStandardDeviation

calcSurrogateShuffle

calcSurrogateGaussian

calcSurrogateGaussian

calcSurrogateRandomPhase

calcSurrogateAAFT

calcSurrogatePseudoPeriodic

calcSurrogateMultivariate

calcSurrogateSeries