October 2014
Beginner to intermediate
348 pages
6h 55m
English
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SciPy
This section shows useful SciPy functions:
scipy.fftpack
fftshift(x, axes=None): This function shifts the zero-frequency component to the center of the spectrumrfft(x, n=None, axis=-1, overwrite_x=0): This function performs a discrete Fourier transform of an array containing real values
scipy.signal
detrend(data, axis=-1, type='linear', bp=0): This function removes the linear trend or a constant from the datamedfilt(volume, kernel_size=None): This function applies a median filter on an arraywiener(im, mysize=None, noise=None): This function applies a Wiener filter on an array
scipy.stats
anderson(x, dist='norm'): This function performs the Anderson-Darling test for data coming from a specified distributionkruskal(*args): This function performs ...
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