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Astrophysics Source Code Library

Making codes discoverable since 1999

Searching for codes credited to 'Ginsburg, A.'

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Found 3 codes.

[ascl:1704.004] STATCONT: Statistical continuum level determination method for line-rich sources
Sanchez-Monge, A.; Schilke, P.; Ginsburg, A.; Cesaroni, R.; Schmiedeke, A.
STATCONT determines the continuum emission level in line-rich spectral data by inspecting the intensity distribution of a given spectrum by using different statistical approaches. The sigma-clipping algorithm provides the most accurate continuum level determination, together with information on the uncertainty in its determination; this uncertainty is used to correct the final continuum emission level. In general, STATCONT obtains accuracies of < 10 % in the continuum determination, and < 5 % in most cases. The main products of the software are the continuum emission level, together with its uncertainty, and data cubes containing only spectral line emission, i.e. continuum-subtracted data cubes. STATCONT also includes the option to estimate the spectral index or variation of the continuum emission with frequency.
[ascl:1601.003] SCOUSE: Semi-automated multi-COmponent Universal Spectral-line fitting Engine
Henshaw, J. D.; Longmore, S. N.; Kruijssen, J. M. D.; Davies, B.; Bally, J.; Barnes, A.; Battersby, C.; Burton, M.; Cunningham, M. R.; Dale, J. E.; Ginsburg, A.; Immer, K.; Jones, P. A.; Kendrew, S.; Mills, E. A. C.; Molinari, S.; Moore, T. J. T.; Ott, J.; Pillai, T.; Rathborne, J.; Schilke, P.; Schmiedeke, A.; Testi, L.; Walker, D.; Walsh, A.; Zhang, Q.
The Semi-automated multi-COmponent Universal Spectral-line fitting Engine (SCOUSE) is a spectral line fitting algorithm that fits Gaussian files to spectral line emission. It identifies the spatial area over which to fit the data and generates a grid of spectral averaging areas (SAAs). The spatially averaged spectra are fitted according to user-provided tolerance levels, and the best fit is selected using the Akaike Information Criterion, which weights the chisq of a best-fitting solution according to the number of free-parameters. A more detailed inspection of the spectra can be performed to improve the fit through an iterative process, after which SCOUSE integrates the new solutions into the solution file.
[ascl:2405.024] ndcube: Multi-dimensional contiguous and non-contiguous coordinate-aware arrays
Ryan, Daniel F.; Mumford, Stuart; Barnes, Will T.; Baruah, Ankit Kumar; Bhope, Adwait; Buchlin, Éric; Freij, Nabil; Ginsburg, Adam; Hayes, Laura A.; Homeier, Derek; Hughes, J. Marcus; Lowder, Chris; O'Steen, Richard; Pellorce, Baptiste; Robitaille, Thomas; Sharma, Yash; Stansby, David; Shih, Albert Y.; Tollerud, Erik; Weberg, Micah J.; West, Matthew J.
ndcube manipulates, inspects, and visualizes multi-dimensional contiguous and non-contiguous coordinate-aware data arrays. A sunpy (ascl:1401.010) affiliated package, it combines data, uncertainties, units, metadata, masking, and coordinate transformations into classes with unified slicing and generic coordinate transformations and plotting and animation capabilities. ndcube handles data of any number of dimensions and axis types (e.g., spatial, temporal, and spectral) whose relationship between the array elements and the real world can be described by World Coordinate System (WCS) translations.