public class HStatAnalysis extends Object
Constructor and Description |
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HStatAnalysis(HStatData hdata)
Initialize analyser
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Modifier and Type | Method and Description |
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P0D |
autoCorrelation(int column,
int windowlength)
Autocorrelation.
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P0D |
crossCorrelation(int column1,
int column2,
int N,
int startLag,
int endLag)
Cross-correlation.
Return a new array that is the cross-correlation of the two argument arrays, starting and ending at user-specified lag values. |
P0D |
filterGaussian(int column,
double width)
Perform Gaussian filtering.
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H1D |
getH1D(int column,
int nbins,
double min,
double max)
Return a histogram for column.
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P0D |
peakFinder(int column,
double sensitivity,
double width)
Identify peaks in the time series.
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void |
smoothColumn(int column,
boolean isWeighted,
int k)
Smooth a column of the original data.
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void |
transformColumn(int column,
String function)
Transform a column inside the time series using an analytic function.
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public HStatAnalysis(HStatData hdata)
hdata
- public P0D autoCorrelation(int column, int windowlength)
column
- - column of the data seriesint
- windowlength - the length of correlation build with the
summaration loop. Corresponds to lag-maxpublic P0D crossCorrelation(int column1, int column2, int N, int startLag, int endLag)
column1
- The first column of doubles.column2
- The second column of doubles.N
- An integer indicating the number of samples to sum over.startLag
- An int indicating at which lag to start (may be negative).endLag
- An int indicating at which lag to end.public P0D filterGaussian(int column, double width)
column
- column numberwidth
- Gaussian width for filteringpublic P0D peakFinder(int column, double sensitivity, double width)
column
- column numbersensitivity
- larger numbers (typical=3) require better defined peakswidth
- typical FWHM of peaks in spectrumpublic void transformColumn(int column, String function)
column
- column number.function
- functional form.
The function may have one independent variable: x
Operators and functions
the following operators are supported:
public void smoothColumn(int column, boolean isWeighted, int k)
column
- column to be smoothed.isWeighted
- Whether values in X or Y will be weighted using a triangular
weighting scheme favoring bins near the central bin.k
- The smoothing parameter which must be non-negative. If zero,
the histogram object will be returned with no smoothing
applied.public H1D getH1D(int column, int nbins, double min, double max)
column
- a colimn index to be converted to a histogram.nbins
- number of bins.min
- min value of histogrammax
- max value of histogramSCaVis 1.0 ©