Editing User:Josiah425:TISEAN Package:Table of functions
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The choice whether a program exist in Octave is based only on comparing package/octave documentation with the TISEAN documentation. As of now I have not compared any code, nor checked if any sample data gives the same results from both functions (the octave ones and the TISEAN ones). | The choice whether a program exist in Octave is based only on comparing package/octave documentation with the TISEAN documentation. As of now I have not compared any code, nor checked if any sample data gives the same results from both functions (the octave ones and the TISEAN ones). | ||
{| class="wikitable" | {| class="wikitable" | ||
|- | |- | ||
| | ! Program Name !! Program Description !! Corresponding Octave Function !! Comments | ||
| | |- | ||
| arima-model || Fit and possibly iterate an ARIMA model || generalizes TSA arma functions || This is a c-file that can be wrapped in C++/mfile/octfile code | |||
|- | |||
|ar-model || Fit and possibly iterate an Autoregessive model || 'aar' in TSA || C; see also: aarmam, adim, amarma, mvaar from TSA | |||
|- | |||
|ar-run || Iterate an Autoregessive model || Same as above || FORTRAN | |||
|- | |||
|av-d2 || Simply smooth output of d2 || Can be implemented with filter in core || C | |||
|- | |||
|boxcount || Renyi Entopies of Qth order || None in GNU Octave (maybe in info-theory but it is not worth the pain) || C | |||
|- | |||
|c1 || Fixed mass estimation of D1 || None in GNU Octave || FORTRAN | |||
|- | |||
|c2d || Get local slopes from correlation integral || None in GNU Octave || FORTRAN | |||
|- | |||
|c2g || Gaussian kernel of C2 || None in GNU Octave || FORTRAN | |||
|- | |||
|c2t || Takens estimator of D2 || None in GNU Octave || FORTRAN | |||
|- | |||
|choose || Choose rows and/or columns from a data file || Does not need to be ported || ------ | |||
|- | |||
|compare || Compares two data sets || Does not need to be ported || FORTRAN | |||
|- | |||
|corr, autocorr || Autocorrelation function || xcorr in signal || corr -C, autocorr (faster according to documentation) - FORTRAN | |||
|- | |||
|d2 || Correlation dimension d2 || None in GNU Octave || c | |||
|- | |||
|delay || Creates delay embedding || None in GNU Octave (easy to implement in Octave but not worth the effort) || C | |||
|- | |||
|endtoend || Determine end-to-end mismatch || None in GNU Octave || FORTRAN | |||
|- | |||
|events || Interval/event conversion || None in GNU Octave || FORTRAN to be implemented as mfile | |||
|- | |||
|extrema || Determine the extrema of a time series || findpeaks in signal (but maybe is just easier to port) || C | |||
|- | |||
|false_nearest || The false nearest neighbor algorithm || None in GNU Octave || C | |||
|- | |||
|ghkss || Nonlinear noise reduction || None in GNU Octave || C | |||
|- | |||
|henon || Create a Hénon time series || There is not || To m-file; already ported | |||
|- | |||
|histogram || Creates histograms || hist in core || C | |||
|- | |||
|ikeda || Create an Ikeda time series || None in GNU Octave || FORTRAN to be reimplemented as mfile | |||
|- | |||
|intervals || Event/intervcal conversion || Might exist under different name || FORTRAN to be reimplemented as mfile | |||
|- | |||
|lazy || Simple nonlinear noise reduction || None in GNU Octave || FORTRAN | |||
|- | |||
|lfo-ar || Locally first order model vs. global AR model (old ll-ar) || Does not exist || C | |||
|- | |||
|lfo-run || Iterate a locally first order model (old nstep) || Does not exist || C | |||
|- | |||
|lfo-test || Test a locally first order model (old onestep) || Does not exist || C | |||
|- | |||
|lorenz || Create a Lorenz time series || Does not exist || FORTRAN | |||
|- | |||
|low121 || Time domain low pass filter || There are lowpass filters in Octave: buttap, cheb1ap, cheb2ap, ellipap, sftrans, but I don't think they perform this task || C, might be ok to implement as mfile | |||
|- | |||
|lyap_k || Maximal Lyapunov exponent with the Kantz algorithm || Does not exist || C | |||
|- | |||
|lyap_r || Maximal Lyapunov exponent with the Rosenstein algorithm || Does not exist || C | |||
|- | |||
|lyap_spec || Full spectrum of Lyapunov exponents || Does not exist || C | |||
|- | |||
|lzo-gm || Locally zeroth order model vs. global mean || Does not exist || C | |||
|- | |||
|lzo-run || Iterate a locally zeroth order model || Does not exist || C | |||
|- | |||
|lzo-test || Test a locally zeroth order model (old zeroth) || Does not exist || C | |||
|- | |||
|makenoise || Produce noise || Rand exists || Should be implemented as mfile using Octave rand functions | |||
|- | |||
|mem_spec || Power spectrum using the maximum entropy principle || Does not exist || C | |||
|- | |||
|mutual || Estimate the mutual information || Does not exist || C | |||
|- | |||
|notch || Notch filter || pei_tseng_notch, needs to be verified || FORTRAN | |||
|- | |||
|nstat_z || Nonstationarity testing via cross-prediction || Does not exist || C | |||
|- | |||
|pca, pc || Principle component analysis || 'pcacov' if likely the equivalent || pca - C, pc - FORTRAN | |||
|- | |||
|poincare || Create Poincaré sections || Does not exist || C | |||
|- | |||
|polyback || Fit a polynomial model (backward elimination) || polyfit, detrend, wpolyfit || I do not know if they work the same way, but it does seem so, written in C | |||
|- | |||
|polynom || Fit a polynomial model || same as above || same as above | |||
|- | |||
|polynomp || Fit a polynomial model (reads terms to fit from file) || same as above || same as above | |||
|- | |||
|polypar || Creates parameter file for polynomp || same as above || same as above | |||
|- | |||
|predict || Forecast discriminating statistics for surrogates || Does not exist || FORTRAN | |||
|- | |- | ||
|randomize || General constraint randomization (surrogates) || There are random function, but I don't think this one exists || FORTRAN | |||
|- | |- | ||
| | |randomize_spikeauto_exp_random || Surrogate data preserving event time autocorrelations || Same as above || Same as above | ||
|- | |- | ||
| | |randomize_spikespec_exp_event || Surrogate data preserving event time power spectrum || Same as above || Same as above | ||
|- | |- | ||
| | |rbf || Radial basis functions fit || Does not exist || C | ||
|- | |- | ||
| | |recurr || Creates a recurrence plot || Does not exist || C | ||
|- | |- | ||
| | |resample || Resamples data || There is 'resample' in Octave, but I believe it does something else || C | ||
|- | |- | ||
| | |rescale || Rescale data set || This should be in Octave, cannot find... || C | ||
|- | |- | ||
| | |rms || Rescale data set and get mean, variance and data interval || This should be in Octave, cannot find... || FORTRNAN | ||
|- | |- | ||
| | |sav_gol || Savitzky-Golay filter || Does not exist || C | ||
|- | |- | ||
| | |spectrum || Power spectrum using FFT || bispec from tsa? || FORTRAN | ||
|- | |- | ||
| | |spikeauto || Autocorrelation function of event times || similar to above || FORTRAN | ||
|- | |- | ||
| | |spikespec || Power spectrum of event times || ar_psd, cpsd is the closest but I do not think they are the same || FORTRAN | ||
|- | |- | ||
| | |stp || Creates a space-time separation plot || Does not exist || FORTRAN | ||
|- | |- | ||
| | |surrogates || Creates surrogate data || Does not exist || FORTRAN | ||
|- | |- | ||
| | |timerev || Time reversal discrimating statistics for surrogates || Does not exist || FORTRAN, to be implemented as mfile | ||
|- | |- | ||
| | |upo || Finds unstable periodic orbits and estimates their stability || No corresponding function in Octave || FORTRAN | ||
|- | |- | ||
| | |upoembed || Takes the output of upo and create data files out of it || Same as above || Same as above | ||
|- | |- | ||
| | |wiener1, wiener2 || Wiener filter || Wiener process exists, might be similar || FORTRAN | ||
|- | |- | ||
| | |xc2 || Cross-correlation integral || xcorr2 || Needs to be verified that works the same way | ||
|- | |- | ||
| | |xcor || Cross-correlations || xcorr || Needs to be verified that works same way | ||
|- | |- | ||
| | |xrecur || Cross-recurrence Plot || xcorr, or xcorr2 or another function might cover this || C | ||
|- | |- | ||
|xzero || Locally zeroth order cross-prediction || Does not exist || C | |||
|xzero || Locally zeroth order cross-prediction || | |||
|} | |} |