C# Class MCAEmotiv.Analysis.AnalysisExtensions

Provides extensions related to data analysis?
显示文件 Open project: madelson/Emotiv-Experimenter

Public Methods

Method Description
Averages ( this data ) : IArray

Computes the average of each "feature"
Downsample ( this values, int binWidth ) : IArrayView

Averages together adjacent bins in values
HasMotionArtifact ( this trial, double round1Alpha = 0.025, double round1Threshold = 40.0, double round2Alpha = 0.5, double round2Threshold = 40.0, Channel channel = Channel.AF3, bool useMirror = false ) : bool

Implements an artifact-detection algorithm
NearestPowerOfTwo ( this value, bool canReturnGreaterValues = true ) : int

Returns the power of two nearest to value
StandardDevations ( this examples, IArrayView &means ) : IArrayView

Computes the mean and standard deviation of each feature.
ZScored ( this examples, IArrayView stddevs, IArrayView means ) : IArrayView>

ZScores each feature based on stddevs and means.

Method Details

Averages() public static method

Computes the average of each "feature"
public static Averages ( this data ) : IArray
data this
return IArray

Downsample() public static method

Averages together adjacent bins in values
public static Downsample ( this values, int binWidth ) : IArrayView
values this
binWidth int
return IArrayView

HasMotionArtifact() public static method

Implements an artifact-detection algorithm
public static HasMotionArtifact ( this trial, double round1Alpha = 0.025, double round1Threshold = 40.0, double round2Alpha = 0.5, double round2Threshold = 40.0, Channel channel = Channel.AF3, bool useMirror = false ) : bool
trial this
round1Alpha double
round1Threshold double
round2Alpha double
round2Threshold double
channel Channel
useMirror bool
return bool

NearestPowerOfTwo() public static method

Returns the power of two nearest to value
public static NearestPowerOfTwo ( this value, bool canReturnGreaterValues = true ) : int
value this
canReturnGreaterValues bool
return int

StandardDevations() public static method

Computes the mean and standard deviation of each feature.
public static StandardDevations ( this examples, IArrayView &means ) : IArrayView
examples this
means IArrayView
return IArrayView

ZScored() public static method

ZScores each feature based on stddevs and means.
public static ZScored ( this examples, IArrayView stddevs, IArrayView means ) : IArrayView>
examples this
stddevs IArrayView
means IArrayView
return IArrayView>