2021
DOI: 10.5281/zenodo.4683076
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hyperspy/hyperspy: Release v1.6.2

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Cited by 6 publications
(5 citation statements)
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“…EDS data processing was conducted with Hyperspy. [45] Diffraction data was analyzed with the support of CrysTBox. [46] In Situ Scattering Measurements: Combined SAXS and WAXS measurements during flash-annealing of samples (i)-(iv) were carried out at beamline P21.2, Petra III, Desy, Hamburg [47] with a photon energy of 52.7keV.…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…EDS data processing was conducted with Hyperspy. [45] Diffraction data was analyzed with the support of CrysTBox. [46] In Situ Scattering Measurements: Combined SAXS and WAXS measurements during flash-annealing of samples (i)-(iv) were carried out at beamline P21.2, Petra III, Desy, Hamburg [47] with a photon energy of 52.7keV.…”
Section: Methodsmentioning
confidence: 99%
“…EDS data processing was conducted with Hyperspy. [ 45 ] Diffraction data was analyzed with the support of CrysTBox. [ 46 ]…”
Section: Methodsmentioning
confidence: 99%
“…The total of 93 s of acquisition was sliced into 232 hyperspectral images with intervals of 400 ms, which corresponds to, roughly, 100 complete ADF frames and an exposition time, per pixel, of 400 µs. As we shall see, this temporal sampling is more than enough to unveil the calcite decomposition dynamics but at the same time allowing us to have sufficient electrons per slice to perform meaningful principal component analysis (PCA) on each one of them using the Hyperspy package [34].…”
Section: Study Of Calcite Decompositionmentioning
confidence: 99%
“…As ParticleSpy is written in python, it can be easily expanded upon and integrated into workflows, particularly those using the Hyper-Spy ecosystem. 27 Previous studies have successfully used trainable segmentation to segment inorganic nanoparticles from electron microscopy data, 28,29 but these studies have not investigated the parameters used in trainable segmentation. To produce accurate and effective segmentation results, the mechanisms behind trainable segmentation, and the filter kernels and classifiers used, need to be understood.…”
Section: Introductionmentioning
confidence: 99%