Pollen of Lavatera arborea, TESCANOrchid root showing with idioblastic cells, S. R. Senthilkumar, St. Joseph´s College, India Rust fungus spore,Adriana Dominguez and Eduardo Favret, CNEA - INTA, Argentina.jpg
4- Gel beads coated with a RuC13 coatings, Magdalena Parlinska, University of Rzeszow, Poland Chroococcus giganteus - Jan Stastny, Charles University, Věda je krásná3- Diatom, Magdalena Parlinska, University of Rzeszow, Poland
Plasma coating crossection, TESCANOrchid root stained with Acridine orange, S. R. Senthilkumar, St. Joseph´s College, India Phragmites communis - Jan Martinek, Charles University, Věda je krásná
Uniform core shell Fe nanoparticles, S. Bandyopadhyay, NTNU, Trondheim Offretite Scagno, TESCANPolymer fibers, TESCAN
1- Diatom, Magdalena Parlinska, University of Rzeszow, Poland 3- Gel beads coated with a RuC13 coatings, Magdalena Parlinska, University of Rzeszow, Poland 2- CVD grown diamond film, Magdalena Parlinska, University of Rzeszow, Poland
Butterfly Wings, Benedykt R. Jany, Marian SmoluchowskiInstitute of Physics - Jagiellonian University, Poland Orchid root with Mycorrhiza, S. R. Senthilkumar, St. Joseph´s College, India Scabiosa columbaria - Viktor Sykora, Charles University, Věda je krásná
Scenedesmus quadricauda - Viktor Sykora, Charles University , Věda je krásnáEnergy filtered TEM micrograph of yttria (in green) - zirconia (in red) multilayers, Chanchal Ghosh,  IGCAR, Kalpakkam, India  Powder metallurgy substrate, 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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