Rebinning

This example shows how to rebin a dataset.

Load the data

import lumispy as lum

cl1 = lum.data.asymmetric_peak_map()
cl1 = cl1.remove_background(signal_range=(550.0, 620.0), background_type="Offset")
cl1 = cl1.isig[:-3]
cl1.spikes_removal_tool(interactive=False)

cl3 = cl1.deepcopy()

Display the original data

cl1.inav[0, 0].plot()

The current dataset is quite noisy. As the peak is broad in comparison with the spectral resolution. One way to improve that is by rebinning the data along the signal axis using hyperspy.api.signals.BaseSignal.rebin().

The parameter ‘scale’ specifies the rebinning factor for each axis. Here we rebin by a factor of 2 along the signal axis and keep the resolution along the navigation axes unchanged.

cl2 = cl1.rebin(scale=[1, 1, 2])

Display the rebinned data

cl2.inav[0, 0].plot()

We can alternatively rebin using the parameter new_shape. For each dimension, the new number of pixels has to be specified.

From the old shape of (30, 16|334), we rebin to a new shape of (20, 10|150).

cl3.plot()  # original data

cl4 = cl3.rebin(new_shape=[20, 10, 150])

cl4.plot()  # rebinned data

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