8-12 May 2023
Haus H, Telegrafenberg
Europe/Berlin timezone

COCOPLOT: Using color to view 3D data as a 2D image

Not scheduled
20m
Haus H, Telegrafenberg

Haus H, Telegrafenberg

Potsdam, Germany
Poster presentation 5) Innovative ways of data analysis, data handling, machine learning, and big data Innovative ways of data analysis, data handling, machine learning, and big data

Speakers

Malcolm Druett (KU Leuven) Alex Pietrow (AIP)

Description

Although applicable to any 3D datacube, this software was inspired by a single thought: what would the Sun look like if we could only see light from one spectral line? In an absorption line, with low emission in the central wavelengths, and high wings on either side, the blue and red cone receptors of our thought experiment would be triggered, making the Sun appear purple. For a strong, narrow emission line the converse is true, and so the line would appear green. A red or blue Doppler-shifted emission would appear in those colors respectively.

COlor COllapsed PLOTting software (COCOPLOT) generates quick-look and context images. The aim is to convey spectral profile information from all of the spatial pixels in a 3D datacube via a single 2D image, using color. Filters for red, green, and blue channels are convolved with the datacube to produce an RGB a color image. This process avoids the user needing to scan through many different wavelengths when searching for regions in the datacube that satisfy multiple criteria.

A selection of useful images are presented to illustrate the capabilities of this method. We make the code publicly available, currently in IDL and PYTHON.

Submit to 'solar physics' topical issue? No

Primary authors

Malcolm Druett (KU Leuven) Alex Pietrow (AIP) Dr Gregal Vissers (Stockholm University) Dr Carolina Robustini (Stockholm University) Dr Flavio Calvo (Stockholm University)

Presentation Materials

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