Category : fft

I have the following dataset in normal space, lets call it func: I transformed it to fourierspace using the numpy fft algorithm from numpy.fft import fft as fourier, I received the fouriertransform usingfunc_fourier = np.fft.fftshift(fourier(func)) and plotted the absolute values plt.plot(np.abs(func_fourier)), what results in the following plot:. I now want to fit a gaussian model ..

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After reading this excellent answer, which demonstrates the scaling of an FFT-based power spectral density (PSD) for real-valued data vs one computed via scipy.signal.welch, I wondered what difference it would make if the input time domain data were complex. I directly copied the code in the above answer, including the scaling factor ("scale"), and simply ..

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I have got the following function , the central peak is approximately gaussianlike. I used the numpy library for the FFT algorithm from numpy.fft import fft as fourier, ifft as ifourier and transformed my function into fourierspacefunc_fourier = fourier(func), I expected a gaussianlike function in fourier space aswell, but I got this result, while plotting ..

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I followed the example from https://pytorch.org/docs/stable/generated/torch.fft.fftshift.html#torch.fft.fftshift import torch.fft f = torch.fft.fftfreq(4) a = torch.fft.fftshift(f) print(a) and got the error AttributeError: module ‘torch.fft’ has no attribute ‘fftfreq’ I tried pip torch==1.7.0+cu110 and pip torch==1.7.1+cu110 and also conda pytorch==1.7.1 with cudatoolkit=11.0. Others have the same problem https://discuss.pytorch.org/t/unable-to-use-correctly-the-new-torch-fft-module/104560/6 But changing to torch1.7.0 didn’t solve the problem. How to ..

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