getsources is a powerful multi-scale, multi-wavelength source extraction algorithm. It analyzes fine spatial decompositions of original images across a wide range of scales and across all wavebands, cleans those single-scale images of noise and background, and constructs wavelength-independent single-scale detection images that preserve information in both spatial and wavelength dimensions. getsources offers several advantages over other existing methods of source extraction, including the filtering out of irrelevant spatial scales to improve detectability, especially in the crowded regions and for extended sources, the ability to combine data over all wavebands, and the full automation of the extraction process.
Inpainting is a technique for dealing with gaps in time series data, as frequently occurs in asteroseismology data, that may generate spurious peaks in the power spectrum, thus limiting the analysis of the data. The inpainting method, based on a sparsity prior, judiciously fills in gaps in the data, preserving the asteroseismic signal as far as possible. This method can be applied both on ground and space-based data. The inpainting technique improves the oscillation modes detection and estimation, the impact of the observational window function is reduced, and the interpretation of the power spectrum is simplified. K-Inpainting can be used to study very long time series of many stars because its computation is very fast.
DRAMA is a fast, distributed environment for writing instrumentation control systems. It allows low level instrumentation software to be controlled from user interfaces running on UNIX, MS Windows or VMS machines in a consistent manner. Such instrumentation tasks can run either on these machines or on real time systems such as VxWorks. DRAMA uses techniques developed by the AAO while using the Starlink-ADAM environment, but is optimized for the requirements of instrumentation control, portability, embedded systems and speed. A special program is provided which allows seamless communication between ADAM and DRAMA tasks.
FAT (Fully Automated TiRiFiC) is an automated procedure that fits tilted-ring models to Hi data cubes of individual, well-resolved galaxies. The method builds on the 3D Tilted Ring Fitting Code (TiRiFiC, ascl:1208.008). FAT accurately models the kinematics and the morphologies of galaxies with an extent of eight beams across the major axis in the inclination range 20°-90° without the need for priors such as disc inclination. FAT's performance allows us to model the gas kinematics of many thousands of well-resolved galaxies, which is essential for future HI surveys, with the Square Kilometre Array and its pathfinders.
Astrochem computes the abundances of chemical species in the interstellar medium, as function of time. It studies the chemistry in a variety of astronomical objects, including diffuse clouds, dense clouds, photodissociation regions, prestellar cores, protostars, and protostellar disks. Astrochem reads a network of chemical reactions from a text file, builds up a system of kinetic rates equations, and solves it using a state-of-the-art stiff ordinary differential equation (ODE) solver. The Jacobian matrix of the system is computed implicitly, so the resolution of the system is extremely fast: large networks containing several thousands of reactions are usually solved in a few seconds. A variety of gas phase process are considered, as well as simple gas-grain interactions, such as the freeze-out and the desorption via several mechanisms (thermal desorption, cosmic-ray desorption and photo-desorption). The computed abundances are written in a HDF5 file, and can be plotted in different ways with the tools provided with Astrochem. Chemical reactions and their rates are written in a format which is meant to be easy to read and to edit. A tool to convert the chemical networks from the OSU and KIDA databases into this format is also provided. Astrochem is written in C, and its source code is distributed under the terms of the GNU General Public License (GPL).
PPInteractions generates the secondary particle energy spectra produced in proton-proton interactions over the entire chosen energy range for any value of the primary proton spectral index by adjusting the low energy part of the spectra (below 0.1TeV) to the high energy end of the spectra (above 0.1TeV). This code is based on the parametrization of Kelner et al (2006), in which the normalization of the low energy part of the spectra is given only for 3 values of the primary proton spectral indices (2, 2.5, 3).
HLINOP is a collection of codes for computing hydrogen line profiles and opacities in the conditions typical of stellar atmospheres. It includes HLINOP for approximate quick calculation of any line of neutral hydrogen (suitable for model atmosphere calculations), based on the Fortran code of Kurucz and Peterson found in ATLAS9. It also includes HLINPROF, for detailed, accurate calculation of lower Balmer line profiles (suitable for detailed analysis of Balmer lines) and HBOP, to implement the occupation probability formalism of Daeppen, Anderson and Milhalas (1987) and thus account for the merging of bound-bound and bound-free opacity (used often as a wrapper to HLINOP for model atmosphere calculations).
Line broadening cross sections for the broadening of spectral lines by collisions with neutral hydrogen atoms have been tabulated by Anstee & O’Mara (1995), Barklem & O’Mara (1997) and Barklem, O’Mara & Ross (1998) for s–p, p–s, p–d, d–p, d–f and f–d transitions. abo-cross, written in Fortran, interpolates in these tabulations to make these data more accessible to the end user. This code can be incorporated into existing spectrum synthesis programs or used it in a stand-alone mode to compute line broadening cross sections for specific transitions.
Toyz is a python web framework that allows scientists to interact with large images and data sets stored on a remote server. A web application is run on the server containing the data and clients are run from web browsers on the user's computer. Toyz displays large FITS images also also renders any image format supported by Pillow (a fork of the Python Imaging Library), contains a GUI to interact with linked plots, and offers a customizable framework that allows students and researchers to create their own work spaces inside a Toyz environment. Astro-Toyz extends the features of the Toyz image viewer, allowing users to view world coordinates and align images based on their WCS.
slimplectic is a python implementation of a numerical integrator that uses a fixed time-step variational integrator formalism applied to the principle of stationary nonconservative action. It allows nonconservative effects to be included in the numerical evolution while preserving the major benefits of normally conservative symplectic integrators, particularly the accurate long-term evolution of momenta and energy. slimplectic is appropriate for exploring cosmological or celestial N-body dynamics problems where nonconservative interactions, e.g. dynamical friction or dissipative tides, can play an important role.
L-PICOLA generates and evolves a set of initial conditions into a dark matter field and can include primordial non-Gaussianity in the simulation and simulate the past lightcone at run-time, with optional replication of the simulation volume. It is a fast, distributed-memory, planar-parallel code. L-PICOLA is extremely useful for both current and next generation large-scale structure surveys.
Pelican is an efficient, lightweight C++ library for quasi-real time data processing. The library provides a framework to separate the acquisition and processing of data, allowing the scalability and flexibility to fit a number of scenarios. Though its origin was in radio astronomy, processing data as it arrives from a telescope, the framework is sufficiently generic to be useful to any application that requires the efficient processing of incoming data streams.
SUPERBOX is a particle-mesh code that uses moving sub-grids to track and resolve high-density peaks in the particle distribution and a nearest grid point force-calculation scheme based on the second derivatives of the potential. The code implements a fast low-storage FFT-algorithm and allows a highly resolved treatment of interactions in clusters of galaxies, such as high-velocity encounters between elliptical galaxies and the tidal disruption of dwarf galaxies, as sub-grids follow the trajectories of individual galaxies. SUPERBOX is efficient in that the computational overhead is kept as slim as possible and is also memory efficient since it uses only one set of grids to treat galaxies in succession.
3D-Barolo (3D-Based Analysis of Rotating Object via Line Observations) or BBarolo is a tool for fitting 3D tilted-ring models to emission-line datacubes. BBarolo works with 3D FITS files, i.e. image arrays with two spatial and one spectral dimensions. BBarolo recovers the true rotation curve and estimates the intrinsic velocity dispersion even in barely resolved galaxies (about 2 resolution elements) if the signal to noise of the data is larger than 2-3. It has source-detection and first-estimate modules, making it suitable for analyzing large 3D datasets automatically, and is a useful tool for deriving reliable kinematics for both local and high-redshift galaxies.
VAPID (Voigt Absorption Profile [Interstellar] Dabbler) models interstellar absorption lines. It predicts profiles and optimizes model parameters by least-squares fitting to observed spectra. VAPID allows cloud parameters to be optimized with respect to several different data set simultaneously; those data sets may include observations of different transitions of a given species, and may have different S/N ratios and resolutions.
HEATCVB is a stand-alone Fortran 77 subroutine that estimates the local volumetric coronal heating rate with four required inputs: the radial distance r, the wind speed u, the mass density ρ, and the magnetic field strength |B0|. The primary output is the heating rate Qturb at the location defined by the input parameters. HEATCVB also computes the local turbulent dissipation rate of the waves, γ = Qturb/(2UA).
SPRITE (Sparse Recovery of InstrumenTal rEsponse) computes a well-resolved compact source image from several undersampled and noisy observations. The algorithm is based on sparse regularization; adding a sparse penalty in the recovery leads to far better accuracy in terms of ellipticity error, especially at low S/N.
REALMAF is a maximum-a-posteriori code to measure magnetic power spectra from Faraday rotation data. It uses a sophisticated model for the magnetic autocorrelation in real space, thus alleviating the need for simplifying assumptions in the processing. REALMAF treats the divergence relation of the magnetic field with a multiplicative factor in Fourier space, which allows modeling the magnetic autocorrelation as a spherically symmetric function.
Fsclean produces 3D Faraday spectra using the Faraday synthesis method, transforming directly from multi-frequency visibility data to the Faraday depth-sky plane space. Deconvolution is accomplished using the CLEAN algorithm, and the package includes Clark and Högbom style CLEAN algorithms. Fsclean reads in MeasurementSet visibility data and produces HDF5 formatted images; it handles images and data of arbitrary size, using scratch HDF5 files as buffers for data that is not being immediately processed, and is limited only by available disk space.
PyMC is a python module that implements Bayesian statistical models and fitting algorithms, including Markov chain Monte Carlo. Its flexibility and extensibility make it applicable to a large suite of problems. Along with core sampling functionality, PyMC includes methods for summarizing output, plotting, goodness-of-fit and convergence diagnostics.
The multiband periodogram is a general extension of the well-known Lomb-Scargle approach for detecting periodic signals in time-domain data. In addition to advantages of the Lomb-Scargle method such as treatment of non-uniform sampling and heteroscedastic errors, the multiband periodogram significantly improves period finding for randomly sampled multiband light curves (e.g., Pan-STARRS, DES and LSST). The light curves in each band are modeled as arbitrary truncated Fourier series, with the period and phase shared across all bands.
PLATO Simulator is an end-to-end simulation software tool designed for the performance of realistic simulations of the expected observations of the PLATO mission but easily adaptable to similar types of missions. It models and simulates photometric time-series of CCD images by including models of the CCD and its electronics, the telescope optics, the stellar field, the jitter movements of the spacecraft, and all important natural noise sources.
The dmdd package enables simple simulation and Bayesian posterior analysis of recoil-event data from dark-matter direct-detection experiments under a wide variety of scattering theories. It enables calculation of the nuclear-recoil rates for a wide range of non-relativistic and relativistic scattering operators, including non-standard momentum-, velocity-, and spin-dependent rates. It also accounts for the correct nuclear response functions for each scattering operator and takes into account the natural abundances of isotopes for a variety of experimental target elements.
pyKLIP subtracts out the stellar PSF to search for directly-imaged exoplanets and disks using a Python implementation of the Karhunen-Loève Image Projection (KLIP) algorithm. pyKLIP supports ADI, SDI, and ADI+SDI to model the stellar PSF and offers a large array of PSF subtraction parameters to optimize the reduction. pyKLIP relies on a minimal amount of dependencies (numpy, scipy, and astropy) and parallelizes the KLIP algorithm to speed up the reduction. pyKLIP supports GPI and P1640 data and can interface with other data sources with the addition of new modules. It also can inject simulated planets and disks as well as automatically search for point sources in PSF-subtracted data.
dStar is a collection of modules for computing neutron star structure and evolution, and uses the numerical, utility, and equation of state libraries of MESA (ascl:1010.083).
SNEC (SuperNova Explosion Code) is a spherically-symmetric Lagrangian radiation-hydrodynamics code that follows supernova explosions through the envelope of their progenitor star, produces bolometric (and approximate multi-color) light curve predictions, and provides input to spectral synthesis codes for spectral modeling. SNEC's features include 1D (spherical) Lagrangian Newtonian hydrodynamics with artificial viscosity, stellar equation of state with a Saha solver ionization/recombination, equilibrium flux-limited photon diffusion with OPAL opacities and low-temperature opacities, and prediction of bolometric light curves and multi-color lightcurves (in the blackbody approximation).
The Planck simulation package takes a cosmological model specified by the user and calculates a potential CMB sky consistent with this model, including astrophysical foregrounds, and then performs a simulated observation of this sky. This Simulation embraces many instrumental effects such as beam convolution and noise. Alternatively, the package can simulate the observation of a provided sky model, generated by another program such as the Planck Sky Model software. The Planck simulation package does not only provide Planck-like data, it can also be easily adopted to mimic the properties of other existing and upcoming CMB experiments.
TEA (Thermal Equilibrium Abundances) calculates gaseous molecular abundances under thermochemical equilibrium conditions. Given a single T,P point or a list of T,P pairs (the thermal profile of an atmosphere) and elemental abundances, TEA calculates mole fractions of the desired molecular species. TEA uses 84 elemental species and thermodynamical data for more then 600 gaseous molecular species, and can adopt any initial elemental abundances.
CANDID finds faint companion around star in interferometric data in the OIFITS format. It allows systematically searching for faint companions in OIFITS data, and if not found, estimates the detection limit. The tool is based on model fitting and Chi2 minimization, with a grid for the starting points of the companion position. It ensures all positions are explored by estimating a-posteriori if the grid is dense enough, and provides an estimate of the optimum grid density.
fits2hdf ports FITS files to Hierarchical Data Format (HDF5) files in the HDFITS format. HDFITS allows faster reading of data, higher compression ratios, and higher throughput. HDFITS formatted data can be presented transparently as an in-memory FITS equivalent by changing the import lines in Python-based FITS utilities. fits2hdf includes a utility to port MeasurementSets (MS) to HDF5 files.
RESOLVE is a Bayesian inference algorithm for image reconstruction in radio interferometry. It is optimized for extended and diffuse sources. Features include parameter-free Bayesian reconstruction of radio continuum data with a focus on extended and weak diffuse sources, reconstruction with uncertainty propagation dependent on measurement noise, and estimation of the spatial correlation structure of the radio astronomical source. RESOLVE provides full support for measurement sets and includes a simulation tool (if uv-coverage is provided).
The great majority of X-ray measurements of cluster masses in the literature assume parametrized functional forms for the radial distribution of two independent cluster thermodynamic properties, such as electron density and temperature, to model the X-ray surface brightness. These radial profiles (e.g. β-model) have an amplitude normalization parameter and two or more shape parameters. BAYES-X uses a cluster model to parametrize the radial X-ray surface brightness profile and explore the constraints on both model parameters and physical parameters. Bayes-X is programmed in Fortran and uses MultiNest (ascl:1109.006) as the Bayesian inference engine.
Lensed performs forward parametric modelling of strong lenses. Using a provided model, Lensed renders the expected image of the lensing event for a large number of parameter settings, thereby exploring the space of possible realizations of the observation. It compares the expectation to the observed image by calculating the likelihood that the observation was indeed produced by the assumed model, thus reconstructing the probability distribution over the parameter space of the model. Written in C, the code uses a massively parallel ray-tracing kernel to perform the necessary calculations on a graphics processing unit (GPU), making the precise rendering of the background lensed sources fast and allowing the simultaneous optimization of tens of parameters for the selected model.
pyMCZ calculates metallicity according to a number of strong line metallicity diagnostics from spectroscopy line measurements and obtain uncertainties from the line flux errors in a Monte Carlo framework. Given line flux measurements and their uncertainties, pyMCZ produces synthetic distributions for the oxygen abundance in up to 13 metallicity scales simultaneously, as well as for E(B-V), and estimates their median values and their 68% confidence regions. The code can output the full MC distributions and their kernel density estimates.
PyTransit implements optimized versions of the Giménez and Mandel & Agol transit models for exoplanet transit light-curves. The two models are implemented natively in Fortran with OpenMP parallelization, and are accessed by an object-oriented python interface. PyTransit facilitates the analysis of photometric time series of exoplanet transits consisting of hundreds of thousands of data points, and of multipassband transit light curves from spectrophotometric observations. It offers efficient model evaluation for multicolour observations and transmission spectroscopy, built-in supersampling to account for extended exposure times, and routines to calculate the projected planet-to-star distance for circular and eccentric orbits, transit durations, and more.
The SNooPy package (also known as SNpy), written in Python, contains tools for the analysis of TypeIa supernovae. It offers interactive plotting of light-curve data and models (and spectra), computation of reddening laws and K-corrections, LM non-linear least-squares fitting of light-curve data, and various types of spline fitting, including Diercx and tension. The package also includes a SNIa lightcurve template generator in the CSP passbands, estimates of Milky-Way Extinction, and a module for dealing with filters and spectra.
Snoopy is a spectral 3D code that solves the MHD and Boussinesq equations, such as compressibility, particles, and Braginskii viscosity, and several other physical effects. It's useful for turbulence study involving shear and rotation. Snoopy requires the FFTW library (ascl:1201.015), and can run on parallel machine using MPI OpenMP or both at the same time.
rvfit, developed in IDL 7.0, fits non-precessing keplerian radial velocity (RV) curves for double-line and single-line binary stars or exoplanets. It fits a simple keplerian model to the observed RV and computes the seven parameters (six for a single-line system) from the model. Some parameters can be fixed beforehand if they are known, for instance, if photometric observations are available. The fit is done using an Adaptive Simulated Annealing algorithm optimized for this specific task. Simulated Annealing methods are powerful heuristic algorithms to minimize functions in multiparametric spaces.
TFIT measures galaxy photometry using prior knowledge of sources in a deep, high‐resolution image (HRI) to improve photometric measurements of objects in a corresponding low‐resolution image (LRI) of the same field, usually at a different wavelength. For background‐limited data, this technique produces optimally weighted photometry that maximizes signal‐to‐noise ratio (S/N). For objects not significantly detected in the low‐resolution image, it provides useful and quantitative information for setting upper limits.
This code is no longer updated and has been superseded by T-PHOT (ascl:1609.001).
POKER (P Of K EstimatoR) estimates the angular power spectrum of a 2D map or the cross-power spectrum of two 2D maps in the flat sky limit approximation in a realistic data context: steep power spectrum, non periodic boundary conditions, arbitrary pixel resolution, non trivial masks and observation patch geometry.
HALOGEN generates approximate synthetic halo catalogs. Written in C, it decomposes the problem of generating cosmological tracer distributions (eg. halos) into four steps: generating an approximate density field, generating the required number of tracers from a CDF over mass, placing the tracers on field particles according to a bias scheme dependent on local density, and assigning velocities to the tracers based on velocities of local particles. It also implements a default set of four models for these steps. HALOGEN uses 2LPTic (ascl:1201.005) and CUTE (ascl:1505.016); the software is flexible and can be adapted to varying cosmologies and simulation specifications.
CUTE (Correlation Utilities and Two-point Estimation) extracts any two-point statistic from enormous datasets with hundreds of millions of objects, such as large galaxy surveys. The computational time grows with the square of the number of objects to be correlated; technology provides multiple means to massively parallelize this problem and CUTE is specifically designed for these kind of calculations. Two implementations are provided: one for execution on shared-memory machines using OpenMP and one that runs on graphical processing units (GPUs) using CUDA.
2dfdr is an automatic data reduction pipeline dedicated to reducing multi-fibre spectroscopy data, with current implementations for AAOmega (fed by the 2dF, KOALA-IFU, SAMI Multi-IFU or older SPIRAL front-ends), HERMES, 2dF (spectrograph), 6dF, and FMOS. A graphical user interface is provided to control data reduction and allow inspection of the reduced spectra.
FCLC (Featureless Classification of Light Curves) software describes the static behavior of a light curve in a probabilistic way. Individual data points are converted to densities and consequently probability density are compared instead of features. This gives rise to an independent classification which can corroborate the usefulness of the selected features.
Approximate Bayesian Computation (ABC) enables parameter inference for complex physical systems in cases where the true likelihood function is unknown, unavailable, or computationally too expensive. It relies on the forward simulation of mock data and comparison between observed and synthetic catalogs. cosmoabc is a Python Approximate Bayesian Computation (ABC) sampler featuring a Population Monte Carlo variation of the original ABC algorithm, which uses an adaptive importance sampling scheme. The code can be coupled to an external simulator to allow incorporation of arbitrary distance and prior functions. When coupled with the numcosmo library, it has been used to estimate posterior probability distributions over cosmological parameters based on measurements of galaxy clusters number counts without computing the likelihood function.
LSSGALPY provides visualization tools to compare the 3D positions of a sample (or samples) of isolated systems with respect to the locations of the large-scale structures galaxies in their local and/or large scale environments. The interactive tools use different projections in the 3D space (right ascension, declination, and redshift) to study the relation of the galaxies with the LSS. The tools permit visualization of the locations of the galaxies for different values of redshifts and redshift ranges; the relationship of isolated galaxies, isolated pairs, and isolated triplets to the galaxies in the LSS can be visualized for different values of the declinations and declination ranges.
missForest imputes missing values particularly in the case of mixed-type data. It uses a random forest trained on the observed values of a data matrix to predict the missing values. It can be used to impute continuous and/or categorical data including complex interactions and non-linear relations. It yields an out-of-bag (OOB) imputation error estimate without the need of a test set or elaborate cross-validation and can be run in parallel to save computation time. missForest has been used to, among other things, impute variable star colors in an All-Sky Automated Survey (ASAS) dataset of variable stars with no NOMAD match.
COBS (COnstrained B-Splines), written in R, creates constrained regression smoothing splines via linear programming and sparse matrices. The method has two important features: the number and location of knots for the spline fit are established using the likelihood-based Akaike Information Criterion (rather than a heuristic procedure); and fits can be made for quantiles (e.g. 25% and 75% as well as the usual 50%) in the response variable, which is valuable when the scatter is asymmetrical or non-Gaussian. This code is useful for, for example, estimating cluster ages when there is a wide spread in stellar ages at a chosen absorption, as a standard regression line does not give an effective measure of this relationship.
stellaR accesses and manipulates publicly available stellar evolutionary tracks and isochrones from the Pisa low-mass database. It retrieves and plots the required calculations from CDS, constructs by interpolation tracks or isochrones of compositions different to the ones available in the database, constructs isochrones for age not included in the database, and extracts relevant evolutionary points from tracks or isochrones.
SCEPtER (Stellar CharactEristics Pisa Estimation gRid) estimates the stellar mass and radius given a set of observable quantities; the results are obtained by adopting a maximum likelihood technique over a grid of pre-computed stellar models. The code is quite flexible since different observables can be used, depending on their availability, as well as different grids of models.
Starfish is a set of tools used for spectroscopic inference. It robustly determines stellar parameters using high resolution spectral models and uses Markov Chain Monte Carlo (MCMC) to explore the full posterior probability distribution of the stellar parameters. Additional potential applications include other types of spectra, such as unresolved stellar clusters or supernovae spectra.
Written in FORTRAN, Athena3D, based on Athena (ascl:1010.014), is an implementation of a flux-conservative Godunov-type algorithm for compressible magnetohydrodynamics. Features of the Athena3D code include compressible hydrodynamics and ideal MHD in one, two or three spatial dimensions in Cartesian coordinates; adiabatic and isothermal equations of state; 1st, 2nd or 3rd order reconstruction using the characteristic variables; and numerical fluxes computed using the Roe scheme. In addition, it offers the ability to add source terms to the equations and is parallelized based on MPI.
The ARoMe (Analytical Rossiter-McLaughlin Effects) library generates analytical Rossiter-McLaughlin (RM) effects. It models the Doppler-shift of a star during a transit measured by the fit of a cross-correlation function by a Gaussian function, fit of an observed spectrum by a modeled one, and the weighted mean.
KS Intergration solves for mutual photometric effects produced by planets and spots allowing for analysis of planetary occultations of spots and spots regions. It proceeds by identifying integrable and non integrable arcs on the objects profiles and analytically calculates the solution exploiting the power of Kelvin-Stokes theorem. It provides the solution up to the second degree of the limb darkening law.
caret (Classification And REgression Training) provides functions for training and plotting classification and regression models. It contains tools for data splitting, pre-processing, feature selection, model tuning using resampling, and variable importance estimation, as well as other functionality.
ASteCA (Automated Stellar Cluster Analysis), written in Python, fully automates standard tests applied on star clusters in order to determine their characteristics, including center, radius, and stars' membership probabilities. It also determines associated intrinsic/extrinsic parameters, including metallicity, age, reddening, distance, total mass, and binarity fraction, among others.
CALCEPH accesses binary planetary ephemeris files, including INPOPxx, JPL DExxx ,and SPICE ephemeris files. It provides a C Application Programming Interface (API) and, optionally, a Fortran 77 or 2003 interface to be called by the application. Two groups of functions enable the access to the ephemeris files, single file access functions, provided to make transition easier from the JPL functions, such as PLEPH, to this library, and many ephemeris file at the same time. Although computers have different endianess (order in which integers are stored as bytes in computer memory), CALCEPH can handles the binary ephemeris files with any endianess by automatically swaps the bytes when it performs read operations on the ephemeris file.
SOAP (Spot Oscillation And Planet) 2.0 simulates the effects of dark spots and bright plages on the surface of a rotating star, computing their expected radial velocity and photometric signatures. It includes the convective blueshift and its inhibition in active regions.
BGLS calculates the Bayesian Generalized Lomb-Scargle periodogram. It takes as input arrays with a time series, a dataset and errors on those data, and returns arrays with sampled periods and the periodogram values at those periods.
LineProf implements a series of line-profile analysis indicators and evaluates its correlation with RV data. It receives as input a list of Cross-Correlation Functions and an optional list of associated RV. It evaluates the line-profile according to the indicators and compares it with the computed RV if no associated RV is provided, or with the provided RV otherwise.
D3PO (Denoising, Deconvolving, and Decomposing Photon Observations) addresses the inference problem of denoising, deconvolving, and decomposing photon observations. Its primary goal is the simultaneous but individual reconstruction of the diffuse and point-like photon flux given a single photon count image, where the fluxes are superimposed. A hierarchical Bayesian parameter model is used to discriminate between morphologically different signal components, yielding a diffuse and a point-like signal estimate for the photon flux components.
JWFront visualizes wavefronts and light cones in general relativity. The interactive front-end allows users to enter the initial position values and choose the values for mass and angular momentum per unit mass. The wavefront animations are available in 2D and 3D; the light cones are visualized using the coordinate systems (t, x, y) or (t, z, x). JWFront can be easily modified to simulate wavefronts and light cones for other spacetime by providing the Christoffel symbols in the program.
MRrelation calculates the posterior predictive mass distribution for an individual planet. The probabilistic mass-radius relationship (M-R relation) is evaluated within a Bayesian framework, which both quantifies this intrinsic dispersion and the uncertainties on the M-R relation parameters.
IGMtransmission is a Java graphical user interface that implements Monte Carlo simulations to compute the corrections to colors of high-redshift galaxies due to intergalactic attenuation based on current models of the Intergalactic Medium. The effects of absorption due to neutral hydrogen are considered, with particular attention to the stochastic effects of Lyman Limit Systems. Attenuation curves are produced, as well as colors for a wide range of filter responses and model galaxy spectra. Photometric filters are included for the Hubble Space Telescope, the Keck telescope, the Mt. Palomar 200-inch, the SUBARU telescope and UKIRT; alternative filter response curves and spectra may be readily uploaded.
abcpmc is a Python Approximate Bayesian Computing (ABC) Population Monte Carlo (PMC) implementation based on Sequential Monte Carlo (SMC) with Particle Filtering techniques. It is extendable with k-nearest neighbour (KNN) or optimal local covariance matrix (OLCM) pertubation kernels and has built-in support for massively parallelized sampling on a cluster using MPI.
The kozai Python package evolves hierarchical triple systems in the secular approximation. As its name implies, the kozai package is useful for studying Kozai-Lidov oscillations. The kozai package can represent and evolve hierarchical triples using either the Delaunay orbital elements or the angular momentum and eccentricity vectors. kozai contains functions to calculate the period of Kozai-Lidov oscillations and the maximum eccentricity reached; it also contains a module to study octupole order effects by averaging over individual Kozai-Lidov oscillations.
DPI is a FORTRAN77 library that supplies the symplectic mapping method for binary star systems for the Mercury N-Body software package (ascl:1201.008). The binary symplectic mapping is implemented as a hybrid symplectic method that allows close encounters and collisions between massive bodies and is therefore suitable for planetary accretion simulations.
samiDB is an archive, database, and query engine to serve the spectra, spectral hypercubes, and high-level science products that make up the SAMI Galaxy Survey. Based on the versatile Hierarchical Data Format (HDF5), samiDB does not depend on relational database structures and hence lightens the setup and maintenance load imposed on science teams by metadata tables. The code, written in Python, covers the ingestion, querying, and exporting of data as well as the automatic setup of an HTML schema browser. samiDB serves as a maintenance-light data archive for Big Science and can be adopted and adapted by science teams that lack the means to hire professional archivists to set up the data back end for their projects.
CosmoTransitions analyzes early-Universe finite-temperature phase transitions with multiple scalar fields. The code enables analysis of the phase structure of an input theory, determines the amount of supercooling at each phase transition, and finds the bubble-wall profiles of the nucleated bubbles that drive the transitions.
The self-lensing binary code with Markov chain code was used to analyze the self-lensing binary system KOI-3278. It includes the MCMC modeling and the key figures.
Spearman’s rank correlation test is commonly used in astronomy to discern whether a set of two variables are correlated or not. Unlike most other quantities quoted in astronomical literature, the Spearman’s rank correlation coefficient is generally quoted with no attempt to estimate the errors on its value. This code implements a number of Monte Carlo based methods to estimate the uncertainty on the Spearman’s rank correlation coefficient.
WebbPSF provides a PSF simulation tool in a flexible and easy-to-use software package implemented in Python. Functionality includes support for spectroscopic modes of JWST NIRISS, MIRI, and NIRSpec, including modeling of slit losses and diffractive line spread functions.
drive-casa provides a Python interface for scripting of CASA (ascl.net/1107.013) subroutines from a separate Python process, allowing for utilization alongside other Python packages which may not easily be installed into the CASA environment. This is particularly useful for embedding use of CASA subroutines within a larger pipeline. drive-casa runs plain-text casapy scripts directly; alternatively, the package includes a set of convenience routines which try to adhere to a consistent style and make it easy to chain together successive CASA reduction commands to generate a command-script programmatically.
Chimenea implements an heuristic algorithm for automated imaging of multi-epoch radio-synthesis data. It generates a deep image via an iterative Clean subroutine performed on the concatenated visibility set and locates steady sources in the field of view. The code then uses this information to apply constrained and then unconstrained (i.e., masked/open-box) Cleans to the single-epoch observations. This obtains better results than if the single-epoch data had been processed independently without prior knowledge of the sky-model. The chimenea pipeline is built upon CASA (ascl:1107.013) subroutines, interacting with the CASA environment via the drive-casa (ascl:1504.006) interface layer.
HOTPANTS (High Order Transform of PSF ANd Template Subtraction) implements the Alard 1999 algorithm for image subtraction. It photometrically aligns one input image with another after they have been astrometrically aligned.
EsoRex (ESO Recipe Execution Tool) lists, configures, and executes Common Pipeline Library (CPL) (ascl:1402.010) recipes from the command line. Its features include automatically generating configuration files, recursive recipe-path searching, command line and configuration file parameters, and recipe product naming control, among many others.
The Solar Position Algorithm (SPA) calculates the solar zenith and azimuth angles in the period from the year -2000 to 6000, with uncertainties of +/- 0.0003 degrees based on the date, time, and location on Earth. SPA is implemented in C; in addition to being available for download, an online calculator using this code is available at http://www.nrel.gov/midc/solpos/spa.html.
UPMASK, written in R, performs membership assignment in stellar clusters. It uses photometry and spatial positions, but can take into account other types of data. UPMASK takes into account arbitrary error models; the code is unsupervised, data-driven, physical-model-free and relies on as few assumptions as possible. The approach followed for membership assessment is based on an iterative process, principal component analysis, a clustering algorithm and a kernel density estimation.
Validation of Exoplanet Signals using a Probabilistic Algorithm (VESPA) calculates false positive probabilities and statistically validates transiting exoplanets. Written in Python, it uses isochrones [ascl:1503.010] and the package simpledist.
Isochrones, written in Python, simplifies common tasks often done with stellar model grids, such as simulating synthetic stellar populations, plotting evolution tracks or isochrones, or estimating the physical properties of a star given photometric and/or spectroscopic observations.
The GSD library reads data written in the James Clerk Maxwell Telescope GSD format. This format uses the General Single-Dish Data model and was used at the JCMT until 2005. The library provides an API to open GSD files and read their contents. The content of the data files is self-describing and the library can return the type and name of any component. The library is used by SPECX (ascl:1310.008), JCMTDR (ascl:1406.019) and COADD (ascl:1411.020). The SMURF (ascl:1310.007) package can convert GSD heterodyne data files to ACSIS format using this library.
The pYSOVAR code calculates properties for a stack of lightcurves, including simple descriptive statistics (mean, max, min, ...), timing (e.g. Lomb-Scargle periodograms), variability indixes (e.g. Stetson), and color properties (e.g. slope in the color-magnitude diagram). The code is written in python and is closely integrated with astropy tables. Initially, pYSOVAR was written specifically for the analysis of two clusters in the YSOVAR project, using the (not publicly released) YSOVAR database as an input. Additional functionality has been added and the code has become more general; it is now useful for other clusters in the YSOVAR dataset or for other projects that have similar data (lightcurves in one or more bands with a few hundred points for a few thousand objects), though may not work out-of-the-box for different datasets.
UniPOPS, a suite of programs and utilities developed at the National Radio Astronomy Observatory (NRAO), reduced data from the observatory's single-dish telescopes: the Tucson 12-m, the Green Bank 140-ft, and archived data from the Green Bank 300-ft. The primary reduction programs, 'line' (for spectral-line reduction) and 'condar' (for continuum reduction), used the People-Oriented Parsing Service (POPS) as the command line interpreter. UniPOPS unified previous analysis packages and provided new capabilities; development of UniPOPS continued within the NRAO until 2004 when the 12-m was turned over to the Arizona Radio Observatory (ARO). The submitted code is version 3.5 from 2004, the last supported by the NRAO.
AMADA allows an iterative exploration and information retrieval of high-dimensional data sets. This is done by performing a hierarchical clustering analysis for different choices of correlation matrices and by doing a principal components analysis in the original data. Additionally, AMADA provides a set of modern visualization data-mining diagnostics. The user can switch between them using the different tabs.
Written in Python, dust calculates X-ray dust scattering and extinction in the intergalactic and local interstellar media.
HELIOS-K is an opacity calculator for exoplanetary atmospheres. It takes a line list as an input and computes the line shapes of an arbitrary number of spectral lines (~millions to billions). HELIOS-K is capable of computing 100,000 spectral lines in 1 second; it is written in CUDA and is optimized for graphics processing units (GPUs).
TAME measures the equivalent width (EWs) in high-resolution spectra. Written by IDL, TAME provides the EWs of spectral lines by profile fitting in an automatic or interactive mode and is reliable for measuring EWs in a spectrum with a spectral resolution of R ≳ 20000. It offers an interactive mode for more flexible measurement of the EW and a fully automatic mode that can simultaneously measure the EWs for a large set of lines.
Galax2d computes the 2D stationary solution of the isothermal Euler equations of gas dynamics in a rotating galaxy with a weak bar. The gravitational potential represents a weak bar and controls the flow. A damped Newton method solves the second-order upwind discretization of the equations for a steady-state solution, using a consistent linearization and a direct solver. The code can be applied as a tool for generating flow models if used on not too fine meshes, up to 256 by 256 cells for half a disk in polar coordinates.
K2flix makes it easy to inspect the CCD pixel data obtained by NASA's Kepler space telescope. The two-wheeled extended Kepler mission, K2, is affected by new sources of systematics, including pointing jitter and foreground asteroids, that are easier to spot by eye than by algorithm. The code takes Kepler's Target Pixel Files (TPF) as input and turns them into contrast-stretched animated gifs or MPEG-4 movies. K2flix can be used both as a command-line tool or using its Python API.
ROBOSPECT, written in C, automatically measures and deblends line equivalent widths for absorption and emission spectra. ROBOSPECT should not be used for stars with spectra in which there is no discernible continuum over large wavelength regions, nor for the most carbon-enhanced stars for which spectral synthesis would be favored. Although ROBOSPECT was designed for metal-poor stars, it is capable of fitting absorption and emission features in a variety of astronomical sources.
AstroLines adjusts spectral line parameters (gf and damping constant) starting from an initial line list. Written in IDL and tailored to the APO Galactic Evolution Experiment (APOGEE), it runs a slightly modified version of MOOG (ascl:1202.009) to compare synthetic spectra with FTS spectra of the Sun and Arcturus.
MaLTPyNT (Matteo's Libraries and Tools in Python for NuSTAR Timing) provides a quick-look timing analysis of NuSTAR data, properly treating orbital gaps and exploiting the presence of two independent detectors by using the cospectrum as a proxy for the power density spectrum. The output of the analysis is a cospectrum, or a power density spectrum, that can be fitted with XSPEC (ascl:9910.005) or ISIS (ascl:1302.002). The software also calculates time lags. Though written for NuSTAR data, MaLTPyNT can also perform standard spectral analysis on X-ray data from other satellite such as XMM-Newton and RXTE.
ketu, written in Python, searches K2 light curves for evidence of exoplanets; the code simultaneously fits for systematic effects caused by small (few-pixel) drifts in the telescope pointing and other spacecraft issues and the transit signals of interest. Though more computationally expensive than standard search algorithms, it can be efficiently implemented and used to discover transit signals.
XPCell simulates convective plasma cells. The program is implemented in two versions, one using GNUPLOT and the second OpenGL. XPCell offers a GUI to introduce the parameter required by the program.
XFGL visualizes gravitational lenses. It has an XFORM GUI and is completely interactive with the mouse. It uses OpenGL for the simulations.
AMIsurvey is a fully automated calibration and imaging pipeline for data from the AMI-LA radio observatory; it has two key dependencies. The first is drive-ami, included in this entry. Drive-ami is a Python interface to the specialized AMI-REDUCE calibration pipeline, which applies path delay corrections, automatic flags for interference, pointing errors, shadowing and hardware faults, applies phase and amplitude calibrations, Fourier transforms the data into the frequency domain, and writes out the resulting data in uvFITS format. The second is chimenea, which implements an automated imaging algorithm to convert the calibrated uvFITS into science-ready image maps. AMIsurvey links the calibration and imaging stages implemented within these packages together, configures the chimenea algorithm with parameters appropriate to data from AMI-LA, and provides a command-line interface.
libnova is a general purpose, double precision, celestial mechanics, astrometry and astrodynamics library. Among many other calculations, it can calculate aberration, apparent position, proper motion, planetary positions, orbit velocities and lengths, angular separation of bodies, and hyperbolic motion of bodies.
Camelus provides a prediction on weak lensing peak counts from input cosmological parameters. Written in C, it samples halos from a mass function and assigns a profile, carries out ray-tracing simulations, and then counts peaks from ray-tracing maps. The creation of the ray-tracing simulations requires less computing time than N-body runs and the results is in good agreement with full N-body simulations.
Magnetron, written in Python, decomposes magnetar bursts into a superposition of small spike-like features with a simple functional form, where the number of model components is itself part of the inference problem. Markov Chain Monte Carlo (MCMC) sampling and reversible jumps between models with different numbers of parameters are used to characterize the posterior distributions of the model parameters and the number of components per burst.
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