Welcome to p4TSA and pyTSA documentation¶
This library is a ‘spin-off’ of C++ Noise Analysis Package (NAP) written together with Giancarlo Cella (giancarlo.cella@pi.infn.it)
The core library is written in C++ and should be compiled before using the python interface.
The Python interface to the library is pyTSA (you can call it pi’za)
Features¶
p4TSA is a minimal package containing ad hoc function to work with time series. It contains
Modern Spectral Analysis Estimators
Whitening in Time domain
Wavelet Decomposition
Wavelet Detection Filter (WDF)
Contents:
- Installation
- Contact
- Documentation
- ARMAView
- BaseView
- LatticeView
- tsaLog
- tsaTraits
- tsaTypes
- tsaUtilityFunctions
- SeqView
- TFView
- ViewUtil
- AlgoBase
- AlgoExceptions
- ArBurgEstimator
- ArDurbinEstimator
- Arma2Psd
- Arma2TF
- AR2
- AR2Parcor
- ARMAFilter
- ARMAfit
- BartlettWindow
- BaseFFT
- BaseWindow
- BisquareWindow
- ButterworthFilter
- BLInterpolation
- ComplexFFT
- CreateDvector
- Cs2HammingWindow
- Cs2HannWindow
- DCT
- IDCT
- DST
- DoubleWhitening
- EventDescription
- EventFullFeatured
- ClusterizedEventFullFeatured
- InverseRealFFT
- KaiserWindow
- LatticeFilter
- LeastSquaresLattice
- LSLfilter
- LSLLearning
- MYWE
- NotchWidrow
- Parcor2AR
- RealFFT
- RLSCanceler
- SelectionOrderCriteria
- TF2Psd
- TukeyWindow
- TukeyHannWindow
- WaveletThreshold
- WaveletTransform
- WavReconstruction
- WDF2Classify
- WDF2Reconstruct
- WelchWindow
- WindowFactory
- Util
- eternity
- fparser
- fpconfig
- fptypes
- FrameIStream
- FrameIChannel
- WDFpipe