Butterfly Wings, Benedykt R. Jany, Marian SmoluchowskiInstitute of Physics - Jagiellonian University, Poland Pollen grain of Hyoseris radiata, TESCANDiatoms World, Mostafa Moonir Shawrav, Institute of Solid State Electronics, Austria
Scenedesmus quadricauda - Viktor Sykora, Charles University , Věda je krásná1- Diatom, Magdalena Parlinska, University of Rzeszow, Poland Gold on Germanium, Benedykt R. Jany, Marian SmoluchowskiInstitute of Physics - Jagiellonian University, Poland
Chroococcus giganteus - Jan Stastny, Charles University, Věda je krásná2- Diatom, Magdalena Parlinska, University of Rzeszow, Poland Cross section of an Abutilon leaf, Adriana Dominguez and Eduardo Favret, CNEA - INTA, Argentina
Paulinella chromatophora - Yvonne Nemcova, Charles University, Věda je krásnáCoral, TESCANPollen of Lavatera arborea, TESCAN
Eudorina - Pavel Skaloud, Charles University, Věda je krásná3- Diatom, Magdalena Parlinska, University of Rzeszow, Poland 2- Gel beads coated with a RuC13 coatings, Magdalena Parlinska, University of Rzeszow, Poland
2- CVD grown diamond film, Magdalena Parlinska, University of Rzeszow, Poland Rotaviruses, Electronmicroscopy, Elisabeth M. Schraner, Institutes of Vet. Anatomy and Virology, Switzerland Scabiosa columbaria - Viktor Sykora, Charles University, Věda je krásná
Rust fungus spore,Adriana Dominguez and Eduardo Favret, CNEA - INTA, Argentina.jpg Plasma coating crossection, TESCANOffretite Scagno, TESCAN

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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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