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src/a/s/astroML-0.2/book_figures/chapter10/fig_line_wavelet_PSD.py   astroML(Download)
from matplotlib import pyplot as plt
 
from astroML.fourier import FT_continuous, IFT_continuous
 
#----------------------------------------------------------------------
f, H = FT_continuous(t, hN)
W = np.conj(wavelet_FT(f, 0, f0[:, None], Q))
t, HW = IFT_continuous(f, H * W)
 
#------------------------------------------------------------

src/a/s/astroML-0.2/book_figures/appendix/fig_LIGO_wavelets.py   astroML(Download)
 
from astroML.datasets import fetch_LIGO_bigdog
from astroML.fourier import FT_continuous, IFT_continuous
 
#----------------------------------------------------------------------
W = np.conj(wavelet_FT(f, 0, f0[:, None], Q))
 
t, HW = IFT_continuous(f, H * W)
 
t = t[::100]

src/a/s/astroML-HEAD/book_figures/chapter10/fig_line_wavelet_PSD.py   astroML(Download)
from matplotlib import pyplot as plt
 
from astroML.fourier import FT_continuous, IFT_continuous
 
#----------------------------------------------------------------------
f, H = FT_continuous(t, hN)
W = np.conj(wavelet_FT(f, 0, f0[:, None], Q))
t, HW = IFT_continuous(f, H * W)
 
#------------------------------------------------------------

src/a/s/astroML-HEAD/book_figures/appendix/fig_LIGO_wavelets.py   astroML(Download)
 
from astroML.datasets import fetch_LIGO_bigdog
from astroML.fourier import FT_continuous, IFT_continuous
 
#----------------------------------------------------------------------
W = np.conj(wavelet_FT(f, 0, f0[:, None], Q))
 
t, HW = IFT_continuous(f, H * W)
 
t = t[::100]

src/a/s/astroML-0.2/book_figures/chapter10/fig_wiener_kernel.py   astroML(Download)
 
from scipy import optimize, fftpack, interpolate
from astroML.fourier import IFT_continuous
from astroML.filters import wiener_filter
 
#------------------------------------------------------------
# inverse fourier transform Phi to find the effective kernel
t_plot, kernel = IFT_continuous(f, Phi)
 
#------------------------------------------------------------

src/a/s/astroML-HEAD/book_figures/chapter10/fig_wiener_kernel.py   astroML(Download)
 
from scipy import optimize, fftpack, interpolate
from astroML.fourier import IFT_continuous
from astroML.filters import wiener_filter
 
#------------------------------------------------------------
# inverse fourier transform Phi to find the effective kernel
t_plot, kernel = IFT_continuous(f, Phi)
 
#------------------------------------------------------------

src/a/s/astroML-0.2/book_figures/chapter10/fig_wavelet_PSD.py   astroML(Download)
from matplotlib import pyplot as plt
 
from astroML.fourier import\
    FT_continuous, IFT_continuous, sinegauss, sinegauss_FT, wavelet_PSD
 

src/a/s/astroML-HEAD/book_figures/chapter10/fig_wavelet_PSD.py   astroML(Download)
from matplotlib import pyplot as plt
 
from astroML.fourier import\
    FT_continuous, IFT_continuous, sinegauss, sinegauss_FT, wavelet_PSD
 

src/a/s/astroML-0.2/book_figures/chapter10/fig_wavelets.py   astroML(Download)
from matplotlib import pyplot as plt
 
from astroML.fourier import FT_continuous, IFT_continuous, sinegauss
 
#----------------------------------------------------------------------

src/a/s/astroML-HEAD/book_figures/chapter10/fig_wavelets.py   astroML(Download)
from matplotlib import pyplot as plt
 
from astroML.fourier import FT_continuous, IFT_continuous, sinegauss
 
#----------------------------------------------------------------------

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