PyMca, Hyperspectral Data and HDF5 - ESRF

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$Experiment title: (Long term report) X-ray diffractive ... - Index of - ESRF$

We could have easily missed the presence of one element if we would have just analyzed the sum spectrum via ROIs. Slide: 32
What have we done? We have used multivariate analysis (PCA in this case) to know what sample regions were worth to take a closer look. Not bad when you have a lot of data … This This data data treatment treatment is is totally totally generic generic <strong>and</strong> <strong>and</strong> applicable applicable to to other other techniques t echniques Slide: 33
Page 1 and 2: PyMca, Hyperspectral Data and HDF5
Page 3 and 4: Integration into our acquisition sy
Page 5 and 6: Multiplatform Slide: 5
Page 7 and 8: PyMca Visualization Data courtesy o
Page 9 and 10: Use of (sub-)shell mass attenuation
Page 11 and 12: XRF Spectrum Analysis Typical proce
Page 13 and 14: Fit Configuration Dialog (II) Slide
Page 15 and 16: Quantification (II) Nominal concent
Page 17 and 18: Is it easy to embed? For the previo
Page 19 and 20: Advanced Fit Batch processing Selec
Page 21 and 22: Copyright C2RMF S Pb Ca Sb We wante
Page 23 and 24: … and their correlations as shown
Page 25 and 26: Eigenimages and Eigenvectors Slide:
Page 31: Getting the actual information We c
Page 35 and 36: PyMca HDF5/NeXus SOLEIL NeXus Data
Page 37 and 38: The PyMca HDF5 problem PyMca can do
Page 39 and 40: The alternative looks ugly, doesn
Page 41: Acknowledgements My ESRF colleagues

PyMca, Hyperspectral Data and HDF5 - ESRF

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