PeakDetection (FSharp.Stats)

PeakDetection Module

Namespace: FSharp.Stats.Signal
Assembly: FSharp.Stats.dll

Types and nested modules

Type/Module	Description
SecondDerivative
Extrema
IdentifiedPeak
PeakFeature
Tag<'t, 'v>

Functions and values

Function or value	Description
`createIdentifiedPeak apex leftLiftOff leftEnd rightLiftOff rightEnd leftSidedConvolved rightSidedConvolved xData yData` Full Usage: `createIdentifiedPeak apex leftLiftOff leftEnd rightLiftOff rightEnd leftSidedConvolved rightSidedConvolved xData yData` Parameters: apex : `PeakFeature` leftLiftOff : `PeakFeature option` leftEnd : `PeakFeature` rightLiftOff : `PeakFeature option` rightEnd : `PeakFeature` leftSidedConvolved : `bool` rightSidedConvolved : `bool` xData : `float[]` yData : `float[]` Returns: `IdentifiedPeak`	apex : `PeakFeature` leftLiftOff : `PeakFeature option` leftEnd : `PeakFeature` rightLiftOff : `PeakFeature option` rightEnd : `PeakFeature` leftSidedConvolved : `bool` rightSidedConvolved : `bool` xData : `float[]` yData : `float[]` Returns: `IdentifiedPeak`
`createPeakFeature index xVal yVal` Full Usage: `createPeakFeature index xVal yVal` Parameters: index : `int` xVal : `float` yVal : `float` Returns: `PeakFeature`	index : `int` xVal : `float` yVal : `float` Returns: `PeakFeature`
`idxOfClosestLabeledPeak labeledData labelV x` Full Usage: `idxOfClosestLabeledPeak labeledData labelV x` Parameters: labeledData : `Tag<Extrema, (float * float)>[]` labelV : `Extrema` x : `float` Returns: `(int * Tag<Extrema, (float * float)>) option`	labeledData : `Tag<Extrema, (float * float)>[]` labelV : `Extrema` x : `float` Returns: `(int * Tag<Extrema, (float * float)>) option`
`idxOfClosestPeakBy xData yData xt` Full Usage: `idxOfClosestPeakBy xData yData xt` Parameters: xData : `float[]` - yData : `float[]` - xt : `float` - Returns: `int`	Returns Index of the highestPeak flanking a given mzValue xData : `float[]` yData : `float[]` xt : `float` Returns: `int` Example
`idxOfHighestLabeledPeakBy labeledData labelV` Full Usage: `idxOfHighestLabeledPeakBy labeledData labelV` Parameters: labeledData : `Tag<Extrema, (float * float)>[]` labelV : `Extrema` Returns: `(int * Tag<Extrema, (float * float)>) option`	labeledData : `Tag<Extrema, (float * float)>[]` labelV : `Extrema` Returns: `(int * Tag<Extrema, (float * float)>) option`
`idxOfHighestPeakBy xData yData xt` Full Usage: `idxOfHighestPeakBy xData yData xt` Parameters: xData : `float[]` - yData : `float[]` - xt : `float` - Returns: `int`	Returns Index of the highestPeak flanking a given x value (xt) xData : `float[]` yData : `float[]` xt : `float` Returns: `int` Example
`iterUntil predicate stepSize startIdx arr` Full Usage: `iterUntil predicate stepSize startIdx arr` Parameters: predicate : `'T -> bool` - stepSize : `int` - startIdx : `int` - arr : `'T[]` - Returns: `int option`	TODO: Add FSharpAux reference Iterates the data array beginning from the startIdx. The step size and direction are implied by magnitude and sign of stepSize. The function returns the idx of the first value for which predicate returns true or the end/start of the collection is reached (returning None). predicate : `'T -> bool` stepSize : `int` startIdx : `int` arr : `'T[]` Returns: `int option` Example
`iterUntili predicate stepSize startIdx arr` Full Usage: `iterUntili predicate stepSize startIdx arr` Parameters: predicate : `int -> 'T -> bool` - stepSize : `int` - startIdx : `int` - arr : `'T[]` - Returns: `int option`	TODO: Add FSharpAux reference Iterates the data array beginning from the startIdx. The step size and direction are implied by magnitude and sign of stepSize. The function returns the idx of the first value for which predicate returns true or the end/start of the collection is reached (returning None). The predicate function takes the idx of the current value as an additional parameter. predicate : `int -> 'T -> bool` stepSize : `int` startIdx : `int` arr : `'T[]` Returns: `int option` Example
`labelPeaks negYThreshold posYThreshold xData smoothYData` Full Usage: `labelPeaks negYThreshold posYThreshold xData smoothYData` Parameters: negYThreshold : `float` - posYThreshold : `float` - xData : `float[]` - smoothYData : `float[]` - Returns: `Tag<Extrema, (float * float)>[]`	Returns a collection of local Maxima and Minima. Attention: The algorithm is very sensitive to noise negYThreshold : `float` posYThreshold : `float` xData : `float[]` smoothYData : `float[]` Returns: `Tag<Extrema, (float * float)>[]` Example
`localMaxima yThreshold xData smoothYData` Full Usage: `localMaxima yThreshold xData smoothYData` Parameters: yThreshold : `float` - xData : `float[]` - smoothYData : `float[]` - Returns: `(float * float)[]`	Returns a collection local maxima. Attention: The algorithm is very sensitive to noise and behaves irregulary for negative Y-values. yThreshold : `float` xData : `float[]` smoothYData : `float[]` Returns: `(float * float)[]` Example
`localMaximaIdx yThreshold xData smoothYData` Full Usage: `localMaximaIdx yThreshold xData smoothYData` Parameters: yThreshold : `float` - xData : `float[]` - smoothYData : `float[]` - Returns: `int[]`	Returns a collection of indices corresponding to local maxima. Attention: The algorithm is very sensitive to noise and behaves irregulary for negative Y-values. yThreshold : `float` xData : `float[]` smoothYData : `float[]` Returns: `int[]` Example
`localMinima xData smoothYData` Full Usage: `localMinima xData smoothYData` Parameters: xData : `float[]` - smoothYData : `float[]` - Returns: `(float * float)[]`	Returns a collection of local minima. Attention: The algorithm is very sensitive to noise xData : `float[]` smoothYData : `float[]` Returns: `(float * float)[]` Example
`localMinimaIdx xData smoothYData` Full Usage: `localMinimaIdx xData smoothYData` Parameters: xData : `float[]` - smoothYData : `float[]` - Returns: `int[]`	Returns a collection of indices corresponding to local minima. Attention: The algorithm is very sensitive to noise xData : `float[]` smoothYData : `float[]` Returns: `int[]` Example