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voetberg authored Jan 30, 2024
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Expand Up @@ -86,7 +86,7 @@ The **DeepBench** software simulates data for analysis tasks that require precis

# Primary Modules

* Geometry objects: two-dimensional images generated with matplotlib `[@hunterMatplotlib2DGraphics2007b]`. The shapes include $_N_$-sided polygons, arcs, straight lines, and ellipses. They are solid, filled or unfilled two-dimensional shapes with edges of variable thickness.
* Geometry objects: two-dimensional images generated with matplotlib `[@hunterMatplotlib2DGraphics2007b]`. The shapes include $N$-sided polygons, arcs, straight lines, and ellipses. They are solid, filled or unfilled two-dimensional shapes with edges of variable thickness.
* Physics objects: one-dimensional profiles for two types of implementations of pendulums dynamics: one using Newtonian physics, the other using Hamiltonian.
* Astronomy objects: two-dimensional images generated based on radial profiles of typical astronomical objects. The star object is created using the Moffat distribution provided by the AstroPy `[@theastropycollaborationAstropyCommunityPython2013a]` library. The spiral galaxy object is created with the function used to produce a logarithmic spiral `[@ringermacherNewFormulaDescribing2009a]`. The elliptical Galaxy object is created using the Sérsic profile provided by the AstroPy library. Two-dimensional models are representations of astronomical objects commonly found in data sets used for galaxy morphology classification.
* Image: two-dimensional images that are combinations and/or concatenations of Geometry or Astronomy objects. The combined images are within `matplotlib` meshgrid objects. Sky images are composed of any combination of Astronomy objects, while geometric images comprise individual geometric shape objects.
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