Astronomy and Computing

ISSN: 2213-1337
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Datasets associated with articles published in Astronomy and Computing
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  • Machine and Deep Learning morphological classification for 670,560 galaxies from Sloan Digital Sky Survey Data Release 7 (SDSS-DR7). Classifications are provided for 2 classes problem (0: elliptical; or, 1: spiral galaxy) and 3 classes problem (0: elliptical, 1: non-barred spiral, or 2: barred spiral galaxy). ML2classes classification is obtained by Traditional Machine Learning Approach, using Morphological non-parametric parameters and Decision Tree. Classifications using Deep Learning are obtained using a Convolutional Neural Network (CNN). Morphological non-parametric parameters are provided as well: Concentration (C), Asymmetry (A), Smoothness (S), Gradient Pattern Analysis (G2) parameter and Entropy (H). We also provide the Error from CyMorph processing. All error flags are mapped as follows: Error = 0: success (no errors); Error = 1: many objects of significant brightness inside 2 Rp of the galaxy; Error = 2: not possible to calculate the galaxy's Rp; Error = 3: problem calculating GPA; Error = 4: problem calculating H; Error = 5: problem calculating C; Error = 6: problem calculating A; Error = 7: problem calculating S.
    Data Types:
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    • File Set
  • Run times of the LOFAR prefactor pipeline obtained by scaling the Number of CPUs, Data size and skymodel size. The prefactor version used for this data was https://github.com/apmechev/prefactor/commit/da4ac885bce9b24e604c9aac6bf649992065326f
    Data Types:
    • Dataset
    • File Set
  • Code and self-downloading data of the paper "Unsupervised Learning of Structure in Spectroscopic Cubes" in Jupyter notebooks format.
    Data Types:
    • Software/Code
    • Dataset
  • MAPLE worksheets. edge.mw: contains the full derivation of the Edgeworth decomposition for the false alarm probability of a sample wavelet transform qij.mw: contains only the final expressions for the coefficients of the normality test
    Data Types:
    • Other
    • Dataset