Astrophysics Source Code Library

Making codes discoverable since 1999

Welcome to the ASCL

The Astrophysics Source Code Library (ASCL) is a free online registry for source codes of interest to astronomers and astrophysicists and lists codes that have been used in research that has appeared in, or been submitted to, peer-reviewed publications. The ASCL is indexed by the SAO/NASA Astrophysics Data System (ADS) and is citable by using the unique ascl ID assigned to each code. The ascl ID can be used to link to the code entry by prefacing the number with (i.e.,

Most Recently Added Codes

2016 Aug 29

[submitted] ExoPlanet

ExoPlanet is a Machine Learning toolkit that provides a graphical interface for the construction,
evaluation and application of a machine learning model in predictive analysis. With the back-end
built using the numpy and scikit-learn libraries, ExoPlanet couples fast and well tested
algorithms, a UI designed over the PyQt framework, and graphs rendered using Matplotlib. This
serves to provide the user with a rich interface, rapid analytics and interactive visuals.

Machine Learning as a field has found immense practical applications in many research domains.
This has increased the need for techniques to analyze and predict patterns in various forms of
data. However, owing to their increased complexity, the implementation of these algorithms may
introduce significant programming overheads to potential users.

ExoPlanet aims to reach out to this widening demographic by ensuring the software needs a minimal
learning curve. This allows researchers to focus more on the applicative aspect of machine learning
algorithms rather than their implementation details. In terms of functionality, ExoPlanet supports
both methods of learning, providing algorithms for unsupervised and supervised training, which may
be done with continuous or discrete labels. The parameters of each of these algorithms can be
adjusted to ensure the best fit for the data. This data to train the model with is read from a
comma-separated values, or CSV, file. After training is complete, the software then automates the
process of building the visual representations for the trained model. This results in an easier and
faster method to evaluate the performance of the algorithm. Once training and evaluation yield
satisfactory results, the model may be used to make data based predictions on a new data set.

These features ensure ExoPlanet provides quick and easy-to-use support for most research projects.
ExoPlanet is still a work in progress with the development following a incremental model. Each
release will add new functionality, file support, algorithms and visual representations of data.
The software will be released as Open Source under the GNU General Public License version 3.

[ascl:1608.012] OBERON: OBliquity and Energy balance Run on N-body systems

OBERON (OBliquity and Energy balance Run on N-body systems) models the climate of Earthlike planets under the effects of an arbitrary number and arrangement of other bodies, such as stars, planets and moons. The code, written in C++, simultaneously computes N body motions using a 4th order Hermite integrator, simulates climates using a 1D latitudinal energy balance model, and evolves the orbital spin of bodies using the equations of Laskar (1986a,b).

[ascl:1608.011] PROFFIT: Analysis of X-ray surface-brightness profiles

PROFFIT analyzes X-ray surface-brightness profiles for data from any X-ray instrument. It can extract surface-brightness profiles in circular or elliptical annuli, using constant or logarithmic bin size, from the image centroid, the surface-brightness peak, or any user-given center, and provides surface-brightness profiles in any circular or elliptical sectors. It offers background map support to extract background profiles, can excise areas using SAO DS9-compatible (ascl:0003.002) region files to exclude point sources, provides fitting with a number of built-in models, including the popular beta model, double beta, cusp beta, power law, and projected broken power law, uses chi-squared or C statistic, and can fit on the surface-brightness or counts data. It has a command-line interface similar to HEASOFT’s XSPEC (ascl:9910.005) package, provides interactive help with a description of all the commands, and results can be saved in FITS, ROOT or TXT format.

[ascl:1608.010] pvextractor: Position-Velocity Diagram Extractor

Given a path defined in sky coordinates and a spectral cube, pvextractor extracts a slice of the cube along that path and along the spectral axis to produce a position-velocity or position-frequency slice. The path can be defined programmatically in pixel or world coordinates, and can also be drawn interactively using a simple GUI. Pvextractor is the main function, but also includes a few utilities related to header trimming and parsing.

[ascl:1608.009] FilFinder: Filamentary structure in molecular clouds

FilFinder extracts and analyzes filamentary structure in molecular clouds. In particular, it is capable of uniformly extracting structure over a large dynamical range in intensity. It returns the main filament properties: local amplitude and background, width, length, orientation and curvature. FilFinder offers additional tools to, for example, create a filament-only image based on the properties of the radial fits. The resulting mask and skeletons may be saved in FITS format, and property tables may be saved as a CSV, FITS or LaTeX table.

2016 Aug 28

[ascl:1608.008] Cuba: Multidimensional numerical integration library

The Cuba library offers four independent routines for multidimensional numerical integration: Vegas, Suave, Divonne, and Cuhre. The four algorithms work by very different methods, and can integrate vector integrands and have very similar Fortran, C/C++, and Mathematica interfaces. Their invocation is very similar, making it easy to cross-check by substituting one method by another. For further safeguarding, the output is supplemented by a chi-square probability which quantifies the reliability of the error estimate.

[ascl:1608.007] BASE-9: Bayesian Analysis for Stellar Evolution with nine variables

The BASE-9 (Bayesian Analysis for Stellar Evolution with nine variables) software suite recovers star cluster and stellar parameters from photometry and is useful for analyzing single-age, single-metallicity star clusters, binaries, or single stars, and for simulating such systems. BASE-9 uses a Markov chain Monte Carlo (MCMC) technique along with brute force numerical integration to estimate the posterior probability distribution for the age, metallicity, helium abundance, distance modulus, line-of-sight absorption, and parameters of the initial-final mass relation (IFMR) for a cluster, and for the primary mass, secondary mass (if a binary), and cluster probability for every potential cluster member. The MCMC technique is used for the cluster quantities (the first six items listed above) and numerical integration is used for the stellar quantities (the last three items in the above list).

2016 Aug 22

[ascl:1608.006] Gemini IRAF: Data reduction software for the Gemini telescopes

The Gemini IRAF package processes observational data obtained with the Gemini telescopes. It is an external package layered upon IRAF and supports data from numerous instruments, including FLAMINGOS-2, GMOS-N, GMOS-S, GNIRS, GSAOI, NIFS, and NIRI. The Gemini IRAF package is organized into sub-packages; it contains a generic tools package, "gemtools", along with instrument-specific packages. The raw data from the Gemini facility instruments are stored as Multi-Extension FITS (MEF) files. Therefore, all the tasks in the Gemini IRAF package, intended for processing data from the Gemini facility instruments, are capable of handling MEF files.

2016 Aug 21

[ascl:1608.005] AstroVis: Visualizing astronomical data cubes

AstroVis enables rapid visualization of large data files on platforms supporting the OpenGL rendering library. Radio astronomical observations are typically three dimensional and stored as data cubes. AstroVis implements a scalable approach to accessing these files using three components: a File Access Component (FAC) that reduces the impact of reading time, which speeds up access to the data; the Image Processing Component (IPC), which breaks up the data cube into smaller pieces that can be processed locally and gives a representation of the whole file; and Data Visualization, which implements an approach of Overview + Detail to reduces the dimensions of the data being worked with and the amount of memory required to store it. The result is a 3D display paired with a 2D detail display that contains a small subsection of the original file in full resolution without reducing the data in any way.

2016 Aug 15

[ascl:1608.004] BART: Bayesian Atmospheric Radiative Transfer fitting code

BART implements a Bayesian, Monte Carlo-driven, radiative-transfer scheme for extracting parameters from spectra of planetary atmospheres. BART combines a thermochemical-equilibrium code, a one-dimensional line-by-line radiative-transfer code, and the Multi-core Markov-chain Monte Carlo statistical module to constrain the atmospheric temperature and chemical-abundance profiles of exoplanets.