scipy tutorial - Baustatik-Info-Server

Notes
Number of Fourier components. Default: x.shape[axis]
axis : int, optional
Returns
xa : ndarray
Analytic signal of x, of each 1d array along axis
The analytic signal x_a(t) of x(t) is:
x_a = F^{-1}(F(x) 2U) = x + i y
SciPy Reference Guide, Release 0.8.dev
where F is the Fourier transform, U the unit step function, and y the Hilbert transform of x. [1]
changes in scipy 0.8.0: new axis argument, new default axis=-1
References
[R5]
get_window(window, Nx, fftbins=1)
Return a window of length Nx and type window.
If fftbins is 1, create a “periodic” window ready to use with ifftshift and be multiplied by the result of an fft
(SEE ALSO fftfreq).
Window types: boxcar, triang, blackman, hamming, hanning, bartlett,
parzen, bohman, blackmanharris, nuttall, barthann, kaiser (needs beta), gaussian (needs std), general_gaussian
(needs power, width), slepian (needs width)
If the window requires no parameters, then it can be a string. If the window requires parameters, the window
argument should be a tuple
with the first argument the string name of the window, and the next arguments the needed parameters.
If window is a floating point number, it is interpreted as the beta
parameter of the kaiser window.
detrend(data, axis=-1, type=’linear’, bp=0)
Remove linear trend along axis from data.
If type is ‘constant’ then remove mean only.
If bp is given, then it is a sequence of points at which to
break a piecewise-linear fit to the data.
resample(x, num, t=None, axis=0, window=None)
Resample to num samples using Fourier method along the given axis.
The resampled signal starts at the same value of x but is sampled with a spacing of len(x) / num * (spacing of
x). Because a Fourier method is used, the signal is assumed periodic.
Window controls a Fourier-domain window that tapers the Fourier spectrum before zero-padding to alleviate
ringing in the resampled values for sampled signals you didn’t intend to be interpreted as band-limited.
If window is a function, then it is called with a vector of inputs indicating the frequency bins (i.e. fftfreq(x.shape[axis])
)
3.13. Signal processing (scipy.signal) 333