Live FFT#

Get interactive fast Fourier transform (FFT) from a subset of a Signal2D using RectangularROI.

import hyperspy.api as hs
import numpy as np

Create a signal:

Add noise to the signal to make it more realistic

s.data *= 1E3
s.data += np.random.default_rng().poisson(s.data)

Create the ROI, here a RectangularROI:

Slice signal with the ROI. By using the interactive function, the output signal sliced_signal will update automatically. The ROI will be added automatically on the signal plot.

s.plot()
sliced_signal = roi.interactive(s, recompute_out_event=None)

# Choose the second figure as gallery thumbnail:
# sphinx_gallery_thumbnail_number = 2
Signal

Get the FFT of this sliced signal, and plot it Apodization is used to smoothen the edge of the image before taking the FFT to remove streaks from the FFT - see the Fast Fourier Transform (FFT) section of the user guide for more details:

s_fft = hs.interactive(sliced_signal.fft, apodization=True, shift=True, recompute_out_event=None)
s_fft.plot(power_spectrum=True)
FFT of  Signal

Total running time of the script: (0 minutes 1.110 seconds)

Gallery generated by Sphinx-Gallery