Fast Lomb-Scargle periodogram using Non-equispaced Fast Fourier Transform (NFFT) by B. Leroy
Project description
PyNFFTls
This Python module provides the Fast Lomb-Scargle periodogram
developed by B. Leroy (2012, Astron. Astrophys. 545, A50)
It is based on the Non-equispaced Fast Fourier Transform (NFFTn http://www-user.tu-chemnitz.de/~potts/nfft/download.php) as well as the FFTW3 library (http://www.fftw.org/).
Both libraries must be installed.
Calling sequence:
(f,p) = period(t,y,ofac,hifac)
For more details, see the associated documentation
For a complete example, see nfftls_test.py
This Python module also provides the following methods:
- the Non-equidistant Fast Fourier Transform (NFFT, see http://www-user.tu-chemnitz.de/~potts/nfft/) of a time series:
(f,A) = nfft(t,y,p,d)
For more details, see the associated documentation
- the Discrete Fourier Transform (DFT) of a time series:
A = dft(t,y,f)
For more details, see the associated documentation
For a complete example, see nfftls_test2.py
R. Samadi, LESIA (http://lesia.obspm.fr), Observatoire de Paris, 22 Dec. 2012
This Python module provides the Fast Lomb-Scargle periodogram
developed by B. Leroy (2012, Astron. Astrophys. 545, A50)
It is based on the Non-equispaced Fast Fourier Transform (NFFTn http://www-user.tu-chemnitz.de/~potts/nfft/download.php) as well as the FFTW3 library (http://www.fftw.org/).
Both libraries must be installed.
Calling sequence:
(f,p) = period(t,y,ofac,hifac)
For more details, see the associated documentation
For a complete example, see nfftls_test.py
This Python module also provides the following methods:
- the Non-equidistant Fast Fourier Transform (NFFT, see http://www-user.tu-chemnitz.de/~potts/nfft/) of a time series:
(f,A) = nfft(t,y,p,d)
For more details, see the associated documentation
- the Discrete Fourier Transform (DFT) of a time series:
A = dft(t,y,f)
For more details, see the associated documentation
For a complete example, see nfftls_test2.py
R. Samadi, LESIA (http://lesia.obspm.fr), Observatoire de Paris, 22 Dec. 2012
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