Namespace com.ibm.streams.timeseries.analysis
Specialized toolkits - release 4.3.1.0-prod20190605 > com.ibm.streams.timeseries 5.0.1 > com.ibm.streams.timeseries.analysis
Operators
- AnomalyDetector: The AnomalyDetector operator can detect anomalous subsequences in an incoming data stream.
- CrossCorrelate2: In signal processing, cross-correlation is a measure of similarity of two time series as a function of a time-lag applied to one of them.
- CrossCorrelateMulti: In signal processing, cross-correlation is a measure of similarity of two time series as a function of a time-lag applied to one of them.
- DSPFilter2: The Digital Signal Processing (DSP) filter operator performs a digital filtering operation on an input time series.
- DSPFilterFinite: The Digital Signal Processing (DSP) filter operator performs a digital filtering operation on an input time series.
- DWT2: The DWT2 operator applies a discrete wavelet transform (DWT) on a vector time series.
- Distribution: The Distribution operator calculates the quartile distribution for an input time series.
- FFT: The FFT operator applies a transformation of a time series from time domain into frequency domain.
- FunctionEvaluator: The FunctionEvaluator operator applies a function to each value in a time series.
- Normalize: The Normalize operator incrementally estimates the means and variance and can normalize the time series to zero means and unit variance.
- PSAX: The PSAX operator is capable of providing a symbolic representation of real-valued time series data.
- STD2: The Seasonal Trend Decomposition (STD) operator uses the Loess algorithm to decompose an input time series into three components: the season, the trend and the residuals.
Functions
- convolve(list<float64>, list<float64>): The convolve function generates the convolution of two time series input signals.
- crosscorrelate(list<float64>, list<float64>): The crosscorrelate function generates the crosscorrelation of two time series input signals.
- laggedConvolve(list<float64>, list<float64>, enum{STANDARD, FFT}): The laggedConvolve function generates the convolution of two time series input signals.
- laggedCrosscorrelate(list<float64>, list<float64>, int32, enum{STANDARD, FFT}): The laggedCrosscorrelate function generates the lagged crosscorrelation of two time series input signals.
- rms(list<T>): The rms function generates the root mean square value from a list of numerical values.
Types
- ConvolveAlgorithmTypes.ConvolveAlgorithmType: An enum type that allows for specifying the algorithm to use when performing convolution.
- CrossCorrelateTypes.CrossCorrelateAlgorithmType: An enum type that allows for specifying the algorithm to use when performing cross correlation.
- CrossCorrelateTypes.CrossCorrelateMultiOutputType: This type can hold the results of the CrossCorrelate operator when using the PEARSON algorithm.
- DSPFilterTypes.DSPFilterType: An enum type that can be passed to the DSPFilter operator as an input attribute to enable dynamically setting the filter type to use (either highPass or lowPass)