Butterfly Wings, Benedykt R. Jany, Marian SmoluchowskiInstitute of Physics - Jagiellonian University, Poland PbI2 Crystallization, TESCANLeaf Fract, TESCAN
Powder metallurgy substrate, TESCANScenedesmus quadricauda - Viktor Sykora, Charles University , Věda je krásná1- Diatom, Magdalena Parlinska, University of Rzeszow, Poland
Pollen grain of Hyoseris radiata, TESCANOrchid root with Mycorrhiza, S. R. Senthilkumar, St. Joseph´s College, India Offretite Scagno, TESCAN
Polymer fibers, TESCANRotaviruses, Electronmicroscopy, Elisabeth M. Schraner, Institutes of Vet. Anatomy and Virology, Switzerland Uniform core shell Fe nanoparticles, S. Bandyopadhyay, NTNU, Trondheim
SEM image of ink-bottle silica nanopores, A. Sterczynska,NanoBioMediacl Centre (CNBM), Poznan, Poland Cross section of an Abutilon leaf, Adriana Dominguez and Eduardo Favret, CNEA - INTA, Argentina Paulinella chromatophora - Yvonne Nemcova, Charles University, Věda je krásná
Orchid root showing with idioblastic cells, S. R. Senthilkumar, St. Joseph´s College, India Salt, TESCANEudorina - Pavel Skaloud, Charles University, Věda je krásná
2- Gel beads coated with a RuC13 coatings, Magdalena Parlinska, University of Rzeszow, Poland Energy filtered TEM micrograph of yttria (in green) - zirconia (in red) multilayers, Chanchal Ghosh,  IGCAR, Kalpakkam, India  Phragmites communis - Jan Martinek, Charles University, Věda je krásná

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Interactive Data Analysis with Python/Hyperspy  

0rganizer: Francisco de la Peña, Michael Walls

Contact: fjd29@cam.ac.uk

Abstract: In all forms of microscopy, as in many other fields, several technological breakthroughs have dramatically increased the amount, rate and precision of experimental data that can be recorded. In parallel, there have been important advances in the field of data analysis which can greatly assist in the task of extracting information from multi-dimensional datasets. In this context, the Python programming language is rapidly establishing itself as the *lingua franca* in most areas of scientific computing, including microscopy.
In this workshop, brief introductory lectures will be followed by hands-on tutorials on microscopy data analysis using Hyperspy (a Python package for interactive multidimensional data analysis) and Swift (a Python package for live data acquisition and analysis). The topics covered will range from multidimensional data visualization to blind source separation methods and will have a strong emphasis on spectroscopic data analysis. Most examples will be taken from the field of electron microscopy but the same methodology can be applied to other domains. No previous knowledge of the Python programming language is required.

Date: one day workshop, September 7, 2014 from 9AM to 4:30PM

Venue: Faculty of Science, Charles University in Prague, Viničná 7, Prague 2 (computer classroom B5, 1st floor)

Minimal number of participants: 20

Registration fee: 60 EUR (included coffee breaks, one lunch and workshop materials)

 

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