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HyperSpy v1.4

Francisco de la Peña; Tomas Ostasevicius; Vidar Tonaas Fauske; Pierre Burdet; Eric Prestat; Petras Jokubauskas; Magnus Nord; Katherine E. MacArthur; Mike Sarahan; Duncan N. Johnstone; Joshua Taillon; Alberto Eljarrat; Vadim Migunov; Jan Caron; Tom Furnival; Stefano Mazzucco; Thomas Aarholt; Michael Walls; Tom Slater; Florian Winkler; Ben Martineau; Gaël Donval; Robert McLeod; Eric R. Hoglund; Ivo Alxneit; Ida Hjorth; Trond Henninen; Luiz Fernando Zagonel; Andreas Garmannslund; 5ht2

This is a minor release. Follow the following links for details on all the bugs fixed, enhancements and new features.

NEW

Enhancements


 

  • The cmap option of plot_images() supports iterable types, allowing the user to specify different colormaps for the different images that are plotted by providing a list or other generator.

  • Clicking on an individual image updates it.

  • New customizable keyboard shortcuts to navigate multi-dimensional datasets. See Data visualization.

  • The remove_background() method now operates much faster in multi-dimensional datasets and adds the options to interatively plot the remainder of the operation and to set the removed background to zero. See Background removal for details.

  • The plot() method now takes a norm keyword that can be “linear”, “log”, “auto” or a matplotlib norm. See Customising image plot for details. Moreover, there are three new extra keyword arguments, fft_shift and power_spectrum, that are useful when plotting fourier transforms. See FFT and iFFT.

  • The align2D() and estimate_shift2D() can operate with sub-pixel accuracy using skimage’s upsampled matrix-multiplication DFT. See Two dimensional signal registration (alignment).

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