PyMca, Hyperspectral Data and HDF5 - ESRF

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

Generic HDF5 Visualization Generic: Select what to plot, how to plot it, and plot it. Slide: 36
The PyMca HDF5 problem PyMca can do a lot more than “just” fully analyze XRF spectra PyMca can read HDF5 data … but often has no clue about what to do without asking Properly defined NXdata groups can provide default visualization and more It would be great to automatically identify the different MCA detectors, with their counts, their energy axis, their preset time, their elapsed time, their calibration, … NeXus NXdetector has almost everything needed to describe an MCA, but still needs user interaction to know that detector is an MCA. It would be very simple to add two attributes to datasets. One defining the “natural” data dimensions and other one defining those dimensions are the first or the last ones of the dataset. Slide: 37
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 and 32: Getting the actual information We c
Page 33 and 34: What have we done? We have used mul
Page 35: PyMca HDF5/NeXus SOLEIL NeXus Data
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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