Plasma coating crossection, TESCANButterfly Wings, Benedykt R. Jany, Marian SmoluchowskiInstitute of Physics - Jagiellonian University, Poland Salt, TESCAN
Cross section of an Abutilon leaf, Adriana Dominguez and Eduardo Favret, CNEA - INTA, Argentina Rust fungus spore,Adriana Dominguez and Eduardo Favret, CNEA - INTA, Argentina.jpg Gold on Germanium, Benedykt R. Jany, Marian SmoluchowskiInstitute of Physics - Jagiellonian University, Poland
Pollen grain of Hyoseris radiata, TESCANSEM image of ink-bottle silica nanopores, A. Sterczynska,NanoBioMediacl Centre (CNBM), Poznan, Poland 1- CVD grown diamond film, Magdalena Parlinska, University of Rzeszow, Poland
Offretite Scagno, TESCANRotaviruses, Electronmicroscopy, Elisabeth M. Schraner, Institutes of Vet. Anatomy and Virology, Switzerland 1- Gel beads coated with a RuC13 coatings, Magdalena Parlinska, University of Rzeszow, Poland
Powder metallurgy substrate, TESCAN2- Diatom, Magdalena Parlinska, University of Rzeszow, Poland Phragmites communis - Jan Martinek, Charles University, Věda je krásná
Energy filtered TEM micrograph of yttria (in green) - zirconia (in red) multilayers, Chanchal Ghosh,  IGCAR, Kalpakkam, India  Collagen fibers in cartilage, E. I. Romijn, NTNU, Trondheim Paulinella chromatophora - Yvonne Nemcova, Charles University, Věda je krásná
Polymer fibers, TESCAN1- Diatom, Magdalena Parlinska, University of Rzeszow, Poland Eudorina - Pavel Skaloud, 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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