[ascl:2002.008]
ExoSim: Simulator for predicting signal and noise in transit spectroscopy observations

ExoSim models host star and planet transit events, simulating the temporal change in stellar flux due to the light curve. It is wavelength-dependent, using an input planet spectrum to determine the light curve depth for any given wavelength and can capture temporal effects, such as correlated noise. ExoSim's star spot simulator produces simulated observations that include spot and facula contamination. The code is flexible and can be generically applied to different instruments that simulate specific time-dependent processes.

[ascl:2002.007]
ProSpect: Spectral generation package

ProSpect generates good quality SEDs that can be used to estimate the broad band photometric properties of galaxies that have known star formation and gas metallicity histories. It allows for complex star formation and metallicity histories to be specified, and can be used in a generative or fitting (Bayesian) mode. ProSpect provides a high level interface to the BC03 (low and high resolution) and EMILES libraries, as well as the Dale 2014 dust emission templates. Its source code is available for download, and it is also available as an interactive web tool.

[ascl:2002.006]
ScamPy: Sub-halo Clustering and Abundance Matching Python interface

ScamPy "paints" an observed population of cosmological objects on top of the DM-halo/subhalo hierarchy obtained from DM-only simulations. The method combines the Halo Occupation Distribution (HOD) method with sub-halo abundance matching (SHAM); the two processes together are dubbed Sub-halo clustering and abundance matching (SCAM). The procedure requires applying the two methods in sequence; by applying the HOD scheme, the host sub-haloes are selected, and the SHAM algorithm associates an observable property of choice to each sub-halo. The provided python interface allows users to load and populate DM halos and sub-halos obtained by FoF and SUBFIND algorithms applied to DM snapshots at any redshift. The software is highly-optimized and flexible.

[ascl:2002.005]
ODUSSEAS: Observing Dwarfs Using Stellar Spectroscopic Energy-Absorption Shapes

Antoniadis-Karnavas, A.; Sousa, S. G.; Delgado-Mena, E.; Santos, N. C.; Teixeira, G. D. C.; Neves, V.

ODUSSEAS (Observing Dwarfs Using Stellar Spectroscopic Energy-Absorption Shapes) uses machine learning to derive the Teff and [Fe/H] of M dwarf stars by using their optical spectra obtained by different spectrographs with different resolutions. The software uses the measurement of the pseudo equivalent widths for more than 4000 stellar absorption lines and the machine learning Python package scikit-learn (https://scikit-learn.org/stable/) to predict the stellar parameters.

[ascl:2002.004]
triceratops: Candidate exoplanet rating tool

triceratops (Tool for Rating Interesting Candidate Exoplanets and Reliability Analysis of Transits Originating from Proximate Stars) validates planet candidates from the Transiting Exoplanet Survey Satellite (TESS). The code calculates the probabilities of a wide range of transit-producing scenarios using the primary transit of the planet candidate and preexisting knowledge of its host and nearby stars. It then uses the known properties of these stars to calculate star-specific priors for each scenario with estimates of stellar multiplicity and planet occurrence rates.

[ascl:2002.003]
ORIGIN: detectiOn and extRactIon of Galaxy emIssion liNes

ORIGIN performs blind detection of faint emitters in MUSE datacubes. The algorithm is tuned to detect faint spatial-spectral emission signatures while allowing for a stable false detection rate over the data cube, and providing in the same time an automated and reliable estimation of the purity. ORIGIN implements a nuisance removal part based on a continuum subtraction combining a Discrete Cosine Transform and an iterative Principal Component Analysis and a detection part based on the local maxima of Generalized Likelihood Ratio test statistics obtained for a set of spatial-spectral profiles of emission line emitters. In addition, it performs a purity estimation in which the proportion of true emission lines is estimated from the data itself: the distribution of the local maxima in the noise only configuration is estimated from that of the local minima.

[ascl:2002.002]
RASCAS: Resonant line transfer in AMR simulations

Michel-Dansac, Leo; Blaizot, Jeremy; Garel, Thibault; Verhamme, Anne; Kimm, Taysun; Trebitsch, Maxime

The massively parallel code RASCAS (RAdiative SCattering in Astrophysical Simulations) performs radiative transfer on an adaptive mesh with an octree structure using the Monte Carlo technique. The code features full MPI parallelization, domain decomposition, adaptive load-balancing, and a standard peeling algorithm to construct mock observations. The radiative transport of resonant line photons through different mixes of species (e.g. HI, SiII, MgII, FeII), including their interaction with dust, is implemented in a modular fashion to allow new transitions to be easily added to the code. RASCAS may also be used to propagate photons at any wavelength (e.g. stellar continuum or fluorescent lines), and has been designed to be easily customizable and to process simulations of arbitrarily large sizes on large supercomputers.

[ascl:2002.001]
SDAR: Slow-Down Algorithmic Regularization code for solving few-body problems

SDAR (Slow-Down Algorithmic Regularization) simulates the long-term evolution of few-body systems such as binaries and triples. The algorithm used provides a few orders of magnitude faster performance than the classical N-body method. The secular evolution of hierarchical systems, *e.g.* Kozai-Lidov oscillation, can be well reproduced. The code is written in the C++ language and can be used either as a stand-alone tool or a library to be plugged in other N-body codes. The high precision of the floating point to 62 digits is also supported.

[submitted]
Determination of Length of (Earth) Day [LOD] in the past geologic epochs

The protocol describes the algorithm of arriving at LOD in a given past geological Epoch. First the lunar orbital radius of the given geologic epoch has to be determined. For this the velocity of recession of Moon for the accelerated phase has to be determined. The spatial integral of the reciprocal of Velocity of recession gives the the transit time of Moon from desired orbit to the present orbit.Through several iterations the transit time is made to converge on the geologic epoch. Once we determine the desired orbital radius it has to be substituted in the LOD expression to determine the LOD in the given geologic epoch.

[submitted]
MERA: Analysis Tool for Astrophysical Simulation Data in the Julia Language

MERA works with large 3D AMR/uniform-grid and N-body particle data sets from astrophysical simulations such as those produced by the hydrodynamic code RAMSES (ascl:1011.007) and is written entirely in the Julia language. The package provides essential functions for efficient and memory lightweight data loading and analysis. The core of MERA is a database framework.

[submitted]
pycf3 - Cosmicflows-3 Distance-Velocity Calculator client for Python

The project is a simple Python client for Cosmicflows-3 Distance-Velocity Calculator at distances less than 400 Mpc (http://edd.ifa.hawaii.edu/CF3calculator/)

Compute expectation distances or velocities based on smoothed velocity field from the Wiener filter model of https://ui.adsabs.harvard.edu/abs/2019MNRAS.488.5438G/abstract.

[submitted]
StarburstPy: Python Wrapper for Starburst99

StarburstPy is a python wrapper for Starburst99 (ascl:1104.003). The code contains methods for setting all inputs, running Starburst99, and reading output data into python dictionaries.

[ascl:2001.015]
gnm: The MCMC Jagger

gnm is an implementation of the affine-invariant sampler for Markov chain Monte Carlo (MCMC) that uses the Gauss-Newton-Metropolis (GNM) Algorithm. The GNM algorithm is specialized in sampling highly non-linear posterior probability distribution functions of the form exp(-||f(x)||^2/2). The code includes dynamic hyper-parameter optimization to increase performance of the sampling; other features include the Jacobian tester and an error bars creator.

[ascl:2001.014]
Peasoup: C++/CUDA GPU pulsar searching library

The NVIDIA GPU-based pipeline code peasoup provides a one-step pulsar search, including searching for pulsars with up to moderate accelerations, with only one command. Its features include dedispersion, dereddening in the Fourier domain, resampling, peak detection, and optional time series folding. peasoup's output is the candidate list.

[ascl:2001.013]
RPPPS: Re-analyzing Pipeline for Parkes Pulsar Survey

RPPPS (Re-analysing Pipeline for Parkes Pulsar Survey) uses Linux shell scripts, C language, and python code and two parallel strategies to reorganize the PRESTO (ascl:1107.017) pulsar search pipeline to run multiple processes in parallel, thus accelerating the search for pulsars. Though originally designed for reprocessing PMPS data, the code has also been successfully used with FAST (Five-hundred-meter Aperture Spherical radio Telescope) drift scan data. The pipeline is only CPU-based and can be easily and quickly deployed in computing nodes for testing purposes or data processes.

[ascl:2001.012]
MCMCI: Markov Chain Monte Carlo + Isochrones method for characterizing exoplanetary systems

MCMCI (Markov chain Monte Carlo + isochrones) characterizes a whole exoplanetary system directly by modeling the star and its planets simultaneously. The code, written in Fortran, uses light curves and basic stellar parameters with a transit analysis algorithm that interacts with stellar evolutionary models, thus using both model-dependent and empirical age indicators to characterize the system.

[ascl:2001.011]
ExoTETHyS: Exoplanetary transits and eclipsing binaries modeler

Morello, Giuseppe; Claret, Antonio; Martin-Lagarde, Marine; Cossou, Christophe; Tsiaras, Angelos; Lagage, Pierre-Olivier

ExoTETHyS models exoplanetary transits, eclipsing binaries, and related phenomena. The package calculates stellar limb-darkening coefficients down to <10 parts per million (ppm) and generates an exact transit light-curve based on the entire stellar intensity profile rather than limb-darkening coefficients.

[ascl:2001.010]
CosMOPED: Compressed Planck likelihood

CosMOPED (Cosmological MOPED) uses the MOPED (Multiple/Massively Optimised Parameter Estimation and Data compression) compression scheme to compress the Planck power spectrum. This convenient and lightweight compressed likelihood code is implemented in Python. To compute the likelihood for the LambdaCDM model using CosMOPED, one needs only six compression vectors, one for each parameter, and six numbers from compressing the Planck data using the six compression vectors. Using these, the likelihood of a theory power spectrum given the Planck data is the product of six one-dimensional Gaussians. Extended cosmological models require computing extra compression vectors.

[ascl:2001.009]
ORCS: Analysis engine for SITELLE spectral cubes

ORCS (Outils de Réduction de Cubes Spectraux) is an analysis engine for SITELLE spectral cubes. The software extracts integrated spectra, fits the sinc emission lines, and recalibrates data in wavelength, astrometry and flux. ORCS offers a choice between a Bayesian or a classical fitting algorithm , and also provides automatic source detection and radial velocity correction.

[ascl:2001.008]
DebrisDiskFM: Debris Disk Forward Modeling

DebrisDiskFM provides forward modeling for circumstellar debris disks in scattered light using the MCFOST disk modeling software to generate disk model images using given input parameters and emcee (ascl:1303.002) to obtain the posterior distributions for these parameters.

[ascl:2001.007]
BTS: Behind The Spectrum

Clarke, S. D.; Whitworth, A. P.; Spowage, R. L.; Duarte-Cabral, A.; Suri, S. T.; Jaffa, S. E.; Walch, S.; Clark, P. C.

Behind The Spectrum (BTS) is a fully-automated multiple-component fitter for optically-thin spectra. Written as a python module, the routine uses the first, second and third derivatives to determine thenumber of components in the spectrum. A least-squared fitting routine then determines the best fit with that number of components, checking for over-fitting and over-lapping velocity centroids.

[ascl:2001.006]
Protostellar Evolution: Stellar evolution simulator

Protostellar Evolution simulates the evolution of stellar stellar radius and luminosity from the bound core stage through to the core hydrogen ignition as a zero-age main-sequence (ZAMS) star and beyond. Written in Fortran 90, the code is implemented as a module of the FLASH astrophysical fluid dynamics code (ascl:1010.082).

[ascl:2001.005]
FAKEOBS: Model visibilities generator

The CASA (1107.013) task FAKEOBS generates model visibilities from already-existing measurement sets. This task can be used to substitute all the visibilities of the target with simulations computed from any model image. The measurement can either be with real or simulated data, the target can have been observed in mosaic mode, and there can be several sources (*e.g.*, bandpass calibrator, flux/phase calibrator, and target).

[ascl:2001.004]
FragMent: Fragmentation techniques for studying filaments

FragMent studies fragmentation in filaments by collating a number of different techniques, including nearest neighbour separations, minimum spanning tree, two-point correlation function, and Fourier power spectrum. It also performs model selection using a frequentist and Bayesian approach to find the best descriptor of a filament's fragmentation. While the code was designed to investigate filament fragmentation, the functions are general and may be used for any set of 2D points to study more general cases of fragmentation.

[ascl:2001.003]
sf3dmodels: Star-forming regions 3D modelling package

sf3dmodels models star-forming regions; it brings together analytical models in order to compute their physical properties in a 3-dimensional grid. The package can couple different models in a single grid to recreate complex star forming systems such as those being revealed by current instruments. The output data can be read with LIME (ascl:1107.012) or RADMC-3D (ascl:1108.016) to carry out radiative transfer calculations of the modeled region.

[ascl:2001.002]
TRANSPHERE: 1-D spherical continuum radiative transfer

TRANSPHERE is a simple dust continuum radiative transfer code for spherically symmetric circumstellar envelopes. It handles absorption and re-emission and computes the dust temperature self-consistently; it does not, however, deal with scattering. TRANSPHERE uses a variable eddington factor method for the radiative transfer. The RADMD code (ascl:1108.016) is more versatile, but for a spherically symmetric problem for which scattering is of much concern, it may be easier to use a simple code such as TRANSPHERE.

Please note that this code has not been updated since 2006.

[ascl:2001.001]
Min-CaLM: Mineral compositional analysis on debris disk spectra

Min-CaLM performs automated mineral compositional analysis on debris disk spectra. The user inputs the debris disk spectrum, and using Min-CaLM's built-in mineralogical library, Min-CaLM calculates the relative mineral abundances within the disk. To do this calculation, Min-CaLM converts the debris disk spectrum and the mineralogical library spectra into a system of linear equations, which it then solves using non-negative least square minimization. This code comes with a GitHub tutorial on how to use the Min-CaLM package.

[submitted]
amber_meta

amber_meta integrates a few routines to launch AMBER (the “Apertif Monitor for Bursts Encountered in Real-time”, https://github.com/AA-ALERT/AMBER) in a systematic manner. To avoid typing a string in the command line manually with all parameters required to launch AMBER, amber_meta generates the command from configuration files, and can directly launch AMBER instances.

[submitted]
Time-domain astronomy sandbox

Time-domain astronomy sandbox consists in a series of classes to simulate and process time-domain astronomy data products in Python. The code was originally developed to model Fast Radio Burst (FRB) and Radio Frequency Interference (RFI), and evaluate different RFI mitigation methods and their effect on FRB search.

[submitted]
JetSeT: numerical modeling and SED fitting tool for relativistic jets

JetSeT is an open source C/Python framework to reproduce radiative and accelerative processes acting in relativistic jets, allowing to fit the numerical models to observed data. The main features of this framework are:

- Handling observed data: re-binning, definition of data sets, bindings to astropy tables and quantities

definition of complex numerical radiative scenarios: Synchrotron Self-Compton (SSC), external Compton

(EC) and EC against the CMB

- Constraining of the model in the pre-fitting stage, based on accurate and already published

phenomenological trends. In particular, starting from phenomenological parameters, such as spectral indices,

peak fluxes and frequencies, and spectral curvatures, that the code evaluates automatically, the pre-fitting

algorithm is able to provide a good starting model, following the phenomenological trends that I have

implemented. fitting of multiwavelength SEDs using both frequentist approach (iminuit) and bayesian MCMC

sampling (emcee)

- Self-consistent temporal evolution of the plasma under the effect of radiative and accelerative processes,

both first order and second order (stochastic acceleration) processes.

[submitted]
SDSS Dual Active Nuclei Galaxy Detection Pipeline

Dual Active Nuclei Galaxies (DAGNs) are rare occurrences in the sky. Until now, most AGNs have been described to be found serendipitously, or by manual observation. In recent years, there has been an increasing interest in such dual AGNs and their astrophysical properties. Their study is important to the understanding of galaxy formation, star formation and these objects are the precursors to Gravitational Wave Sources.

Hence, we have devised a pipeline, that along with systematic data collection, can detect such dual AGN candidates. A novel algorithm 'Graph-Boosted Gradient Ascent' has been devised to detect whether an R-band image of a galaxy is a potential candidate for a DAGN or not. The pipeline can be cloned to a user's machine, and by joining the AstrIRG_DAGN group on SciServer, astronomers can collectively contribute to the mining of DAGNs.

[submitted]
K2CE: Kepler-K2 Cadence Events

Since early 2018, the Kepler/K2 project has been performing a uniform global reprocessing of data from K2 Campaigns 0 through 14. Subsequent K2 campaigns (C15-C19) are being processed using the same processing pipeline. One of the major benefits of the reprocessing effort is that, for the first time, short-cadence (1-min) light curves are produced in addition to the standard long-cadence (30-min) light curves. Users have been cautioned that the Kepler pipeline detrending module (PDC), developed for use on original Kepler data, has not been tailored for use on short-cadence K2 observations. Systematics due to events on fast timescales, such as thruster firings, are sometimes poorly corrected for many short-cadence targets. A Python data visualization and manipulation tool, called Kepler-K2 Cadence Events, has been developed that identifies and removes cadences associated with problematic thruster events, thus producing better light curves. Kepler-K2 Cadence Events can be used to visualize and manipulate light curve files and target pixel files from the Kepler, K2, and TESS missions. This software is available at the following NASA GitHub repository https://github.com/nasa/K2CE .

[ascl:1912.020]
MRExo: Non-parametric mass-radius relationship for exoplanets

MRExo performs non-parametric fitting and analysis of the mass-radius (M-R) relationship for exoplanets. Written in Python, it offers tools for fitting the M-R relationship to a given data set and also includes predicting (M->R, and R->M) and plotting functions.

[ascl:1912.019]
STACKER: Stack sources in interferometric data

STACKER stacks sources in interferometric data, *i.e.*, averaging emission from different sources. The library allows stacking to be done directly on visibility data as well as in the image domain. The code is in format of a CASA (ascl:1107.013) task and implements uv- and image-stacking algorithms; it also provides several useful tasks for stacking related data processing. It allows introduction and stacking of random sources to estimate bias and noise, and also allows removal of a model of bright sources from the data.

[ascl:1912.018]
Tangos: Framework and web interface for database-driven analysis of numerical structure formation simulations

Tangos builds databases (along the lines of Eagle or MultiDark) for cosmological and zoom simulations. Its

modular system generates and queries databases. It is designed to store and manage results from a user's own analysis code, provides web and python interfaces, and allows users to construct science-focused queries, including across entire merger trees, without requiring knowledge of SQL. Tangos manages the process of populating the database with science data, including auto-parallelizing the analysis. It can be customized to work with multiple python modules such as pynbody (ascl:1305.002) or yt (ascl:1011.022) to process raw simulation data; it defaults to using SQLite, but allows use of other databases as the underlying store through the use of SQLAlchemy.

[ascl:1912.017]
PTMCMCSampler: Parallel tempering MCMC sampler package written in Python

PTMCMCSampler performs MCMC sampling using advanced techniques. The code implements a variety of proposal schemes, including adaptive Metropolis, differential evolution, and parallel tempering, which can be used together in the same run.

[ascl:1912.016]
GWpy: Python package for studying data from gravitational-wave detectors

Macleod, Duncan; Urban, Alex L.; Coughlin, Scott; Massinger, Thomas; Pitkin, Matt; Altin, Paul; Areeda, Joseph; Quintero, Eric; Leinweber, Katrin

The Python package GWpy analyzes and characterizes gravitational wave data. It provides a user-friendly, intuitive interface to the common time-domain and frequency-domain data produced by the LIGO and Virgo observatories and their analyses. The core Python infrastructure is influenced by, and extends the functionality of, the Astropy (ascl:1304.002) package, and its methodology has been derived from, and augmented by, the LIGO Algorithm Library Suite (LALSuite), a large collection of primarily C99 routines for analysis and manipulation of data from gravitational-wave detectors. These packages use the SWIG program to produce Python wrappings for all C modules, allowing the GWpy package to leverage both the completeness, and the speed, of these libraries.

[ascl:1912.015]
ENTERPRISE: Enhanced Numerical Toolbox Enabling a Robust PulsaR Inference SuitE

ENTERPRISE (Enhanced Numerical Toolbox Enabling a Robust PulsaR Inference SuitE) is a pulsar-timing analysis code which performs noise analysis, gravitational-wave searches, and timing model analysis. It uses Tempo2 (ascl:1210.015) to find the maximum-likelihood fit for the timing parameters and the basis of the fit for the red noise parameters if they are significant.

[ascl:1912.014]
HARMPI: 3D massively parallel general relativictic MHD code

HARMPI is a parallel, 3D version of HARM (ascl:1209.005), which solves hyperbolic partial differential equations in conservative form using high-resolution shock-capturing techniques. The code is parallelized using MPI and is fully operational in 3D. HARMPI, like HARM, is capable of using non-uniform grids and solves the relativistic magnetohydrodynamic equations of motion on a stationary black hole spacetime in Kerr-Schild coordinates to evolve an accretion disk model.

[ascl:1912.013]
GriSPy: Fixed-radius nearest neighbors grid search in Python

Chalela, Martín; Sillero, Emanuel; Pereyra, Luis; Garcia, Mario A.; Cabral, Juan B.; Lares, Marcelo; Merchán, Manuel

GriSPy (Grid Search in Python) uses a regular grid search algorithm for quick fixed-radius nearest-neighbor lookup. It indexes a set of k-dimensional points in a regular grid providing a fast approach for nearest neighbors queries. Optional periodic boundary conditions can be provided for each axis individually. GriSPy implements three types of queries: *bubble*, *shell* and the *nth-nearest*, and offers three different metrics of interest in astronomy: the *Euclidean* and two distance functions in spherical coordinates of varying precision, *haversine* and *Vincenty*. It also provides a custom distance function. GriSPy is particularly useful for large datasets where a brute-force search is not practical.

[ascl:1912.012]
GAME: GAlaxy Machine learning for Emission lines

GAME infers different ISM physical properties by analyzing the emission line intensities in a galaxy spectrum. The code is trained with a large library of synthetic spectra spanning many different ISM phases, including HII (ionized) regions, PDRs, and neutral regions. GAME is based on a Supervised Machine Learning algorithm called AdaBoost with Decision Trees as base learner. Given a set of input lines in a spectrum, the code performs a training on the library and then evaluates the line intensities to give a determination of the physical properties. The errors on the input emission line intensities and the uncertainties on the physical properties determinations are also taken into account. GAME infers gas density, column density, far-ultraviolet (FUV, 6–13.6 eV) flux, ionization parameter, metallicity, escape fraction, and visual extinction. A web interface for using the code is available.

[ascl:1912.011]
QSOSIM: Simulated Quasar Spectrum Generator

QSOSIM realistically simulates high-resolution quasar spectra using a set of basic parameters (magnitude, redshift, and spectral index). The simulated spectra include physical effects seen in the real data: the power-law quasar continuum, the narrow and broad emission lines, absorption by neutral hydrogen (HI) in the Lyman alpha forest, and heavy element transitions along the line of sight. The code uses empirical HI column density, redshift, and b-parameter distributions to simulate absorption in the Lyman alpha forest. All absorbers with column densities larger than log [N(HI)/cm^{2}]>17 have heavy element absorption, for which the column densities are calculated using the plasma simulation code CLOUDY (ascl:9910.001) and the radiative transfer code CUBA. The code also simulates the clustering of the intergalactic medium along the line of sight, the proximity effect of the quasar, and the effect of the cosmic ultraviolet background. Each simulated spectrum is saved in a single FITS file in as a noiseless R=100000 spectrum, as well as a spectrum convolved with Sloan Digital Sky Survey resolution (R=10000) and realistic noise.

[ascl:1912.010]
AstroAccelerate: Accelerated software package for processing time-domain radio astronomy data

AstroAccelerate processes time-domain radio astronomy data. It offers a standalone code that can be used to process filterbank data and a library that performs GPU-accelerated single pulse processing (SPS), Fourier Domain Acceleration Searching (FDAS) and dedispersion in real-time on very large data-sets comparable to those that will be produced by next-generation radio telescopes such as the SKA. AstroAccelerate uses NVIDIAR GPUs, and is configurable, stable, and easily maintained.

[ascl:1912.009]
FORSTAND: Flexible ORbit Superposition Toolbox for ANalyzing Dynamical models

FORSTAND constructs dynamical models of galaxies using the Schwarzschild orbit-superposition method; the method is available as part of the AGAMA (ascl:1805.008) framework. The models created are constrained by line-of-sight kinematic observations and are applicable to galaxies of all morphological types, including disks and triaxial rotating bars.

[submitted]
Exo-MerCat: a merged exoplanet catalog with Virtual Observatory connection.

The heterogeneity of papers dealing with the discovery and characterization of exoplanets makes every attempt to maintain a uniform exoplanet catalog almost impossible. Four sources currently available online (NASA Exoplanet Archive, Exoplanet Orbit Database, Exoplanet Encyclopaedia, and Open Exoplanet Catalogue) are commonly used by the community, but they can hardly be compared, due to discrepancies in notations and selection criteria.

Exo-MerCat is a Python code that collects and selects the most precise measurement for all interesting planetary and orbital parameters contained in the four databases, accounting for the presence of multiple aliases for the same target. It can download information about the host star as well by the use of Virtual Observatory ConeSearch connections to the major archives such as SIMBAD and those available in VizieR. A Graphical User Interface is provided to filter data based on the user's constraints and generate automatic plots that are commonly used in the exoplanetary community.

With Exo-MerCat, we retrieved a unique catalog that merges information from the four main databases, standardizing the output and handling notation differences issues. Exo-MerCat can correct as many issues that prevent a direct correspondence between multiple items in the four databases as possible, with the available data. The catalog is available as a VO resource for everyone to use and it is periodically updated, according to the update rates of the source catalogs.

[submitted]
PyFOSC: a pipeline toolbox for BFOSC/YFOSC long-slit spectroscopy data reduction

PyFOSC is a pipeline toolbox for long-slit spectroscopy data reduction written in Python. It can be used for FOSC (Faint Object Spectrograph and Camera) data from Xinglong/Lijiang 2-meter telescopes in China. This pipeline privodes a neat way for data pre-processing, including updating missing header fileds for BFOSC data, reducing fits file extension for YFOSC data, etc. And it makes the data reduction procedure efficient by using previously identified lamp spectra as re-identification references during wavelength calibration, and applying multiprocessing in some modules. PyFOSC also enables customization for any other long-slit spectroscopy data.

[ascl:1912.008]
PopSyCLE: Population Synthesis for Compact object Lensing Events

PopSyCLE performs compact object population synthesis while taking photometric and astrometric microlensing effects into consideration. It uses Galaxia (ascl:1101.007) to produces a synthetic survey, injects compact objects into the resulting survey, and then produces a list of microlensing events, enabling the discovery of black holes with microlensing. It can be used to examine historical microlensing events from photometric surveys to statistically constrain the abundance of black holes in our galaxy, and to forward model microlensing survey results to constrain, for example, the properties of compact objects, Galactic structure, and the initial-final mass relation.

[ascl:1912.007]
anesthetic: Nested sampling visualization

anesthetic brings together tools for processing nested sampling chains, leveraging standard scientific python libraries. The code provides computation of Bayesian evidences, Kullback-Liebler divergences and Bayesian model dimensionalities, marginalized 1d and 2d plots, and dynamic replaying of nested sampling. anesthetic was designed primarily for use with nested sampling outputs, although it can be used for normal MCMC chains.

[ascl:1912.006]
HSIM: HARMONI simulation pipeline

Zieleniewski, S.; Thatte, N.; Kendrew, S.; Houghton, R. C. W.; Swinbank, A. M.; Tecza, M.; Clarke, F.; Fusco, T.

HSIM simulates observations with HARMONI on the Extremely Large Telescope. HSIM takes high spectral and spatial resolution input data cubes, encoding physical descriptions of astrophysical sources, and generates mock observed data cubes. The simulations incorporate detailed models of the sky, telescope, instrument, and detectors to produce realistic mock data. HSIM performs in-depth simulations for several key science cases as part of the design and development of the HARMONI integral field spectrograph, including the ELT AO performance, atmospheric effects and realistic detector statistics.

[ascl:1912.005]
Athena++: Radiation GR magnetohydrodynamics code

Athena++ is a complete re-write of the Athena astrophysical magnetohydrodynamics (MHD) code (ascl:1010.014) in C++. Compared to earlier versions, the Athena++ code has much more flexible coordinate and grid options and supports new physics. It also offers significantly improved performance and scalability, and improved source code clarity and modularity. Athena++ supports compressible hydrodynamics and MHD in 1D, 2D, and 3D, and special and general relativistic hydrodynamics and MHD. In addition, it supports Cartesian, cylindrical, or spherical polar coordinates; static or adaptive mesh refinement in any coordinate system; mixed parallelization with both OpenMP and MPI; and a task-based execution model for improved load balancing, scalability and modularity.

[ascl:1912.004]
DALiuGE: Data Activated Liu Graph Engine

Wu, Chen; Tobar, Rodrigo; Vinsen, Kevin; Wicenec, Andreas; Pallot, Dave; Lao, Baoqiang; Wang, Ruonan; An, Tao; Boulton, Mark; Cooper, Ian; Dodson, Richard.; Dolensky, Markus; Mei, Ying; Wang, Feng

DALiuGE provides a distributed data management platform and a scalable pipeline execution environment to support continuous, soft real-time, data-intensive processing for producing radio astronomy data products; it originated from a prototyping activity as part of the SKA SDP Consortium called Data Flow Management System (DFMS). Though the development of DALiuGE is largely based on radio astronomy processing requirements, it has adopted a generic, data-driven framework architecture potentially applicable to many other data-intensive applications.

[ascl:1912.003]
ASKAPsoft: ASKAP science data processor software

Guzman, Juan; Whiting, Matthew; Voronkov, Max; Mitchell, Daniel; Ord, Stephen; Collins, Daniel; Marquarding, Malte; Lahur, Paulus; Maher, Tony; Van Diepen, Ger; Bannister, Keith; Wu, Xinyu; Lenc, Emil; Khoo, Jonathan; Bastholm, Eric

ASKAPsoft provides data processing functionality for Australian Square Kilometre Array Pathfinder, including calibration, spectral line imaging, continuum imaging, source detection and generation of source catalogs, and transient detection. The MPI-based package is the primary software for storing and processing raw data, and initiating the archiving of resulting science data products into the data archive (CASDA). The processing pipelines within ASKAPsoft are largely written in C++ built on top of casacore (ascl:1912.002) and other third party libraries.

[ascl:1912.002]
casacore: Suite of C++ libraries for radio astronomy data processing

The casacore package contains the core libraries of the old AIPS++/CASA (ascl:1107.013) package. This split was made to get a better separation of core libraries and applications. CASA is now built on top of Casacore. The system consists of a set of layered libraries (packages) and includes a library (using Boost-Python) that converts the basic Casacore types (e.g., Array, Record) to and from Python.

Casacore includes the casa package for core functionality and data types like Array and Record; a scimath package for N-dim functions with auto-differentiation and linear or non-linear fitting; and a

tables package for the table data system supporting N-dim arrays with advanced querying. It also includes the measures package to manage values in astronomical reference frames using physical units (Quanta) and the MeasurementSets for storing data in the UV-domain, and also the images package for N-dim images in world coordinates with various analysis operations.

[ascl:1912.001]
Polyspectrum: Computing polyspectra using an FFT estimator

Polyspectrum computes the polyspectrum from 3D grids using a fast Fourier transformation (FFT) estimator. The code, written in C and MPI-parallelized, support the computation of power- and bispectra; it also supports higher-order polyspectra, but streamlining the input data is required.

[ascl:1911.024]
comb: Spectral line data reduction and analysis package

comb is a single-dish radio astronomy spectral line data reduction and analysis package developed at AT&T Bell labs and was used for data reduction for many single-dish telescopes, including Bell Labs 7-m, NRAO 12-m, DSN network, FCRAO 14-m, Arecibo, AST/RO, SEST, BIMA, and in 2011-2012, the Stratospheric Terahertz Observatory. A cookbook for the code is available.

[ascl:1911.023]
miluphcuda: Smooth particle hydrodynamics code

Schaefer, Christoph M.; Riecker, Sven; Wandel, Oliver; Maindl, Thomas I.; Scherrer, Samuel; Werner, Janka; Burger, Christoph; Morlock, Marius

miluphcuda is the CUDA port of the original miluph code; it runs on single Nvidia GPUs with compute capability 5.0 and higher and provides fast and efficient computation. The code can be used for hydrodynamical simulations and collision and impact physics, and features self-gravity via Barnes-Hut trees and porosity models such as P-alpha and epsilon-alpha. It can model solid bodies, including ductile and brittle materials, as well as non-viscous fluids, granular media, and porous continua.

[ascl:1911.022]
FFTLog-and-beyond: Generalized FFTLog algorithm

FFTLog-and-beyond takes the FFTLog algorithm for single-Bessel integrals and generalizes it for integrals containing a derivative of the Bessel function to solve the non-Limber integrals. The full non-Limber angular power spectrum integral is simplified by noting the small contribution from unequal-time nonlinear terms; this significantly reduces the computation and avoids the double-Bessel integral. The original FFTLog algorithm is also extended to compute integrals containing derivatives of Bessel functions, which can be used to efficiently compute angular power spectra including redshift-space distortions (RSD) and Doppler effects. C and Python versions of the code are available.

[ascl:1911.021]
TreeFrog: Construct halo merger trees and compare halo catalogs

TreeFrog reads in particle IDs information between various structure catalogs and cross matches catalogs, assuming that particle IDs are unique and constant across snapshots. Though it is built as a cross correlator (in that it can match particles across several different catalogs), its principle use is as halo merger tree builder. TreeFrog produces links between objects found at different snapshots (or catalogs) and uses several possible functions to evaluate the merit of a link between one object at a given snapshot (or in a given catalog) to another object in a previous snapshot (or different catalog). It can also produce a full graph. The code utilizes MPI and OpenMP. It is optimzed for reading VELOCIraptor (ascl:1911.020) output but can also read output from other structure finders such as AHF (ascl:1102.009).

[ascl:1911.020]
VELOCIraptor-STF: Six-dimensional Friends-of-Friends phase space halo finder

VELOCIraptor-STF, formerly STructure Finder (ascl:1306.009), is a 6-Dimensional Friends-of-Friends (6D-FoF) phase space halo finder and constructs halo catalogs. The code uses using MPI and OpenMP APIs and can be compiled as a library for on-the-fly halo finding within an N-body/hydrodynamnical code. There is an associated halo merger tree code TreeFrog (ascl:1911.021).

[ascl:1911.019]
OrbWeaver: Galaxy/(sub)halo orbital processing tool

OrbWeaver extracts orbits from halo catalogs, enabling large statistical studies of their orbital parameters. The code is run in two stages. For the first run, a configuration file is used to modify orbit host selection and the region around orbit host used for the superset of orbiting halos. Each orbit host has a orbit forest (containing halos that passed within the region of interest); the code generates a pre-processed catalog which contains a superset of orbiting halo for each identified orbit host. The second run uses the file list generated in the first stage for the creation of the orbit catalog, which is the final output.

[ascl:1911.018]
WhereWolf: Galaxy/(sub)Halo ghosting tool for N-body simulations

WhereWolf tracks (sub)haloes even if they have been lost by a halo finder in cosmological simulations and supplements halo catalogs such as VELOCIraptor (ascl:1911.020) with these recovered (sub)haloes. The code can improve measurements of the subhalo/halo mass function and present estimates of the distribution of radii at which subhaloes merge.

[ascl:1911.017]
HLattice: Scalar fields and gravity simulator for the early universe

HLattice simulates scalar fields and gravity in the early universe. The code allows the user to select between symplectic integrators, descretization schemes, and metrics such as Minkowski or FRW backgrounds and adaptice schemes in an "all-in-one" configuration file.

[ascl:1911.016]
CLUSTEREASY: Lattice simulator for evolving interacting scalar fields in an expanding universe on parallel computing clusters

CLUSTEREASY is a parallel programming extension of the simulation program LATTICEEASY (ascl:1911.015); running the program in parallel greatly extends the range of scales and times that can be simulated. The program is particularly useful for the study of reheating and thermalization after inflation.

[ascl:1911.015]
LATTICEEASY: Lattice simulator for evolving interacting scalar fields in an expanding universe

LATTICEEASY creates lattice simulations of the evolution of interacting scalar fields in an expanding universe. The program can do runs with different parameters and new models can be easily introduced for evaluation. Simulations can be done in one, two, or three dimensions by resetting a single variable. Mathematica notebooks for plotting the output and a range of models are also available for download; a parallel processing version of LATTICEEASY called CLUSTEREASY (ascl:1911.016) is also available.

[ascl:1911.014]
MORDI: Massively-Overlapped Ring-Diagram Inversion

MORDI (Massively-Overlapped Ring-Diagram Inversion) performs three-dimensional ring-diagram inversions. The code reads in frequency shift measurements and their associated sensitivity kernels and outputs two-dimensional slices of the subsurface flow field at a constant depth and (optionally) the associated averaging kernels. It relies on both distributed-memory (MPI) and shared-memory (OpenMP) parallelism to scale efficiently up to a few thousand processors, but can also run reasonably well on small machines (1-4 cpus). The actions of the code are modified by command-line parameters, which enable a significant amount of flexibility when setting up an inversion.

[ascl:1911.013]
ATLAS: Turning Dopplergram images into frequency shift measurements

ATLAS performs the tracking, projecting, power-spectrum-making, and ring-fitting needed to turn a set of Dopplergram images into a set of frequency shift measurements. This code is essentially a combination of three codes, FRACK (FORTRAN Tracking), PSPEC (Power SPECtrum), and MRF (Multi-Ridge Fitting), included in the ATLAS package. ATLAS reads in a list of longitude/latitude coordinates corresponding to the desired tile centers and a set of full-disk Dopplergram images and outputs frequency shift measurements from each wave mode of each tile. The code relies on both distributed-memory (MPI) and shared-memory (OpenMP) parallelism to scale up to around 1000 processes. Due to the immense volume of data produced by the tracking and projecting steps, the intermediate data products (tiles, power spectra) are never written out.

[ascl:1911.012]
Zeltron: Explicit 3D relativistic electromagnetic Particle-In-Cell code

Zeltron is an explicit 3D relativistic electromagnetic Particle-In-Cell code suited for modeling particle acceleration in astrophysical plasmas. The code is efficiently parallelized with the Message Passing Interface, and can be run on a laptop computer or on multiple cores on current supercomputers. Zeltron takes into account the effect of the radiation reaction force on the motion of the particles; it assigns variable weights to the macro-particles to model particle density gradients, and does not strictly conserve the total energy. The code uses linear interpolation to deposit the charges and currents generated by each particle at the nodes of the computational grid, and computes the charge and current densities for Maxwell's equations. Zeltron contains a large set of analysis tools, including plasma density, particle spectrum, optically thin synchrotron and inverse Compton spectra, angular distributions, and stress-energy tensor.

[ascl:1911.011]
IDG: Image Domain Gridding

IDG (Image Domain Gridding) is an imager that makes w-term corrections and a-term corrections computationally very cheap. It works with WSClean (ascl:1408.023) and supports the same cleaning and data selections options that WSClean offers in normal mode (such as cotton-schwab, multi-frequency multi-scale cleaning, and auto-masking). IDG also allows gridding with a time-variable beam including the LOFAR, AARTFAAC and MWA beam and can perform full beam or differential correction. The code requires measurement sets with four polarizations (*e.g.* XX/XY/YX/YY), can apply a spatially varying time-variable TEC term that can additionally be different for different antennas and output channels, and performs extremely well on GPUs.

[ascl:1911.010]
Fruitbat: Fast radio burst redshift estimation

Fruitbat estimates the redshift of Fast Radio Bursts (FRB) from their dispersion measure. The code combines various dispersion measure (DM) and redshift relations with the YMW16 galactic dispersion measure model into a single easy to use API.

[ascl:1911.009]
frbpoppy: Fast radio burst population synthesis in Python

frbpoppy conducts fast radio burst population synthesis and continues the work of PSRPOP (ascl:1107.019) and PsrPopPy (ascl:1501.006) in the realm of FRBs. The code replicates observed FRB detection rates and FRB distributions in three steps. It first simulates a cosmic population of one-off FRBs and allows the user to select options such as models for source number density, cosmology, DM host/IGM/Milky Way, luminosity functions, and emission bands as well as maximum redshift and size of the FRB population. The code then generates a survey by adopting a beam pattern using various survey parameters, among them telescope gain, sampling time, receiver temperature, central frequency, channel bandwidth, number of polarizations, and survey region limits. Finally, frbpoppy convolves the generated intrinsic population with the generated survey to simulate an observed FRB population.

[ascl:1911.008]
HeatingRate: Radioactive heating rate and macronova (kilonova) light curve

HeatingRate calculates the nuclear heating rates [erg/s/g] of beta-decay, alpha-decay, and spontaneous fission of r-process nuclei, taking into account for thermalization of gamma-rays and charged decay products in r-process ejecta. It uses the half-lives and injection energy spectra from an evaluated nuclear data library (ENDF/B-VII.1). Each heating rate is computed for given abundances, ejecta mass, velocity, and density profile. HeatingRate also computes the bolometric light curve and the evolution of the effective temperature for given abundances, ejecta mass, velocity, and density profile assuming opacities independent of the wavelength.

[ascl:1911.007]
planetplanet: General photodynamical code for exoplanet light curves

planetplanet models exoplanet transits, secondary eclipses, phase curves, and exomoons, as well as eclipsing binaries, circumbinary planets, and more. The code was originally developed to model planet-planet occultation (PPO) light curves for the TRAPPIST-1 system, but it is generally applicable to any exoplanet system. During a PPO, a planet occults (transits) the disk of another planet in the same planetary system, blocking its thermal (and reflected) light, which can be measured photometrically by a distant observer. planetplanet is coded in C and wrapped in a user-friendly Python interface.

[ascl:1911.006]
ATHOS: A Tool for HOmogenizing Stellar parameters

ATHOS provides on-the-fly stellar parameter determination of FGK stars based on flux ratios from optical spectra. Once configured properly, it will measure flux ratios in the input spectra and deduce the stellar parameters effective temperature, iron abundance (a.k.a [Fe/H]), and surface gravity by employing pre-defined analytical relations. ATHOS can be configured to run in parallel in an arbitrary number of threads, thus enabling the fast and efficient analysis of huge datasets.

[ascl:1911.005]
MARTINI: Mock spatially resolved spectral line observations of simulated galaxies

MARTINI (Mock APERTIF-like Radio Telescope Interferometry of the Neutal ISM) creates synthetic resolved HI line observations (data cubes) of smoothed-particle hydrodynamics simulations of galaxies. The various aspects of the mock-observing process are divided logically into sub-modules handling the data cube, source, beam, noise, spectral model and SPH kernel. MARTINI is object-oriented: each sub-module provides a class (or classes) which can be configured as desired. For most sub-modules, base classes are provided to allow for straightforward customization. Instances of each sub-module class are then given as parameters to the Martini class. A mock observation is then constructed by calling a handful of functions to execute the desired steps in the mock-observing process.

[ascl:1911.004]
PypeIt: Python spectroscopic data reduction pipeline

Prochaska, J. Xavier; Hennawi, Joseph; Cooke, Ryan; Westfall, Kyle; Wang, Feige; Farina, Emanuele Paolo; Hsyu, Tiffany; Wasserman, Asher; Villaume, Alexa; Young, David; Simha, Sunil; Wilde, Matt; Tejos, Nicolas; Isbell, Jacob; Betts, Edward; Holden, Brad

PypeIt reduces data from echelle and low-resolution spectrometers; the code can be run in several modes of reduction that demark the level of sophistication (e.g. quick and dirty vs. MonteCarlo) and also the amount of output written to disk. It also generates numerous data products, including 1D and 2D spectra; calibration images, fits, and meta files; and quality assurance figures.

[ascl:1911.003]
OpenSPH: Astrophysical SPH and N-body simulations and interactive visualization tools

OpenSPH runs hydrodynamical and N-body simulations and was written for asteroid collisions and subsequent gravitational evolution. The code offers SPH and N-body solvers with several different equations of state and material rheologies. It is written in C++14 with a modular object-oriented design, focused on extensibility and maintainability, and it can be used either as a library or as a standalone graphical program that allows to set up the problem in a convenient graphical node editor. The graphical program further allows real-time visualization of the simulation, diagnostics and tools for analysis of the results.

[ascl:1911.002]
uvplot: Interferometric visibilities plotter

uvplot makes nice plots of deprojected interferometric visibilities (often called uvplots). It implements plotting functionality, handles MS tables with spectral windows with different number of channels, and can import visibilities from ASCII to MS Table. It also allows export of specific channels. uvplot can be installed inside the NRAO CASA package (ascl:1107.013).

[ascl:1911.001]
PLAN: A Clump-finder for Planetesimal Formation Simulations

PLAN (PLanetesimal ANalyzer) identifies and characterizes planetesimals produced in numerical simulations of the Streaming Instability that includes particle self-gravity with code Athena (ascl:1010.014). PLAN works with the 3D particle output of Athena and finds gravitationally bound clumps robustly and efficiently. PLAN — written in C++ with OpenMP/MPI — is massively parallelized, memory-efficient, and scalable to analyze billions of particles and multiple snapshots simultaneously. The approach of PLAN is based on the dark matter halo finder HOP (ascl:1102.019), but with many customizations for planetesimal formation. PLAN can be easily adapted to analyze other object formation simulations that use Lagrangian particles (e.g., Athena++ simulations). PLAN is also equipped with a toolkit to analyze the grid-based hydro data (VTK dumps of primitive variables) from Athena, which requires the Boost MultiDimensional Array Library.

[submitted]
Network Flux Transport Demonstration

We have developed a method to efficiently simulate the dynamics of the magnetic flux in the solar network. We call this method Network Flux Transport (NFT). Implemented using a Spherical Centroidal Voronoi Tessellation (SCVT) based network model, magnetic flux is advected by photospheric plasma velocity fields according to the geometry of the SCVT model. We test NFT by simulating the magnetism of the Solar poles. The poles of the sun above 55 deg latitude are free from flux emergence from active regions or ephemeral regions. As such, they are ideal targets for a simplified simulation that relies on the strengths of the NFT model. This simulation method reproduces the magnetic and spatial distributions for the solar poles over two full solar cycles.

[ascl:1910.022]
qnm: Kerr quasinormal modes, separation constants, and spherical-spheroidal mixing coefficients calculator

qnm computes the Kerr quasinormal mode frequencies, angular separation constants, and spherical-spheroidal mixing coefficients. The qnm package includes a Leaver solver with the Cook-Zalutskiy spectral approach to the angular sector, and a caching mechanism to avoid repeating calculations. A large cache of low ℓ, m, n modes is available for download and can be installed with a single function call and interpolated to provide good initial guess for root-polishing at new values of spin.

[ascl:1910.021]
AOtools: Adaptive optics modeling and analysis toolkit

The AOtools package offers generic adaptive optics processing tools in addition to astronomy-specific methods; among these are analyzing data in the pupil plane, images and point spread functions in the focal plane, wavefront sensors, modeling of atmospheric turbulence, physical optical propagation of wavefronts, and conversion functions to convert stellar brightness into photon flux for a given waveband. The software also calculates integrated atmospheric parameters, such as coherence time and isoplanatic angle from atmospheric turbulence and wind speed profile.

[ascl:1910.020]
OCD: O'Connell Effect Detector using push-pull learning

OCD (O'Connell Effect Detector) detects eclipsing binaries that demonstrate the O'Connell Effect. This time-domain signature extraction methodology uses a supporting supervised pattern detection algorithm. The methodology maps stellar variable observations (time-domain data) to a new representation known as Distribution Fields (DF), the properties of which enable efficient handling of issues such as irregular sampling and multiple values per time instance. Using this representation, the code applies a metric learning technique directly on the DF space capable of specifically identifying the stars of interest; the metric is tuned on a set of labeled eclipsing binary data from the Kepler survey, targeting particular systems exhibiting the O’Connell Effect. This code is useful for large-scale data volumes such as that expected from next generation telescopes such as LSST.

[ascl:1910.019]
Cobaya: Bayesian analysis in cosmology

Cobaya (Code for BAYesian Analysis) provides a framework for sampling and statistical modeling and enables exploration of an arbitrary prior or posterior using a range of Monte Carlo samplers, including the advanced MCMC sampler from CosmoMC (ascl:1106.025) and the advanced nested sampler PolyChord (ascl:1502.011). The results of the sampling can be analyzed with GetDist (ascl:1910.018). It supports MPI parallelization and is highly extensible, allowing the user to define priors and likelihoods and create new parameters as functions of other parameters.

It includes interfaces to the cosmological theory codes CAMB (ascl:1102.026) and CLASS (ascl:1106.020) and likelihoods of cosmological experiments, such as Planck, Bicep-Keck, and SDSS. Automatic installers are included for those external modules; Cobaya can also be used as a wrapper for cosmological models and likelihoods, and integrated it in other samplers and pipelines. The interfaces to most cosmological likelihoods are agnostic as to which theory code is used to compute the observables, which facilitates comparison between those codes. Those interfaces are also parameter-agnostic, allowing use of modified versions of theory codes and likelihoods without additional editing of Cobaya’s source.

[ascl:1910.018]
GetDist: Monte Carlo sample analyzer

GetDist analyzes Monte Carlo samples, including correlated samples from Markov Chain Monte Carlo (MCMC). It offers a point and click GUI for selecting chain files, viewing plots, marginalized constraints, and LaTeX tables, and includes a plotting library for making custom publication-ready 1D, 2D, 3D-scatter, triangle and other plots. Its convergence diagnostics include correlation length and diagonalized Gelman-Rubin statistics, and the optimized kernel density estimation provides an automated optimal bandwidth choice for 1D and 2D densities with boundary and bias correction. It is available as a standalong package and with CosmoMC (ascl:1106.025).

[ascl:1910.017]
ChainConsumer: Corner plots, LaTeX tables and plotting walks

ChainConsumer consumes the chains output from Monte Carlo processes such as MCMC to produce plots of the posterior surface inferred from the chain distributions, to plot the chains as walks to check for mixing and convergence, and to output parameter summaries in the form of LaTeX tables. It handles multiple models (chains), allowing for model comparison using AIC, BIC or DIC metrics.

[ascl:1910.016]
MiSTree: Construct and analyze Minimum Spanning Tree graphs

MiSTree quickly constructs minimum spanning tree graphs for various coordinate systems, including Celestial coordinates, by using a k-nearest neighbor graph (k NN, rather than a matrix of pairwise distances) which is then fed to Kruskal's algorithm to create the graph. MiSTree bins the MST statistics into histograms and plots the distributions; enabling the inclusion of high-order statistics information from the cosmic web to provide additional information that improves cosmological parameter constraints. Though MiSTree was designed for use in cosmology, it can be used in any field requiring extracting non-Gaussian information from point distributions.

[ascl:1910.015]
MarsLux: Illumination Mars maps generator

MarsLux generates illumination maps of Mars from Digital Terrain Model (DTM), permitting users to investigate in detail the illumination conditions on Mars based on its topography and the relative position of the Sun. MarsLux consists of two Python codes, SolaPar and MarsLux. SolaPar calculates the matrix with solar parameters for one date or a range between the two. The Marslux code generates the illumination maps using the same DTM and the files generated by SolaPar. The resulting illumination maps show areas that are fully illuminated, areas in total shadow, and areas with partial shade, and can be used for geomorphological studies to examine gullies, thermal weathering, or mass wasting processes as well as for producing energy budget maps for future exploration missions.

[ascl:1910.014]
ANNz2: Estimating photometric redshift and probability density functions using machine learning methods

ANNz2, a newer implementation of ANNz (ascl:1209.009), utilizes multiple machine learning methods such as artificial neural networks, boosted decision/regression trees and k-nearest neighbors to measure photo-zs based on limited spectral data. The code dynamically optimizes the performance of the photo-z estimation and properly derives the associated uncertainties. In addition to single-value solutions, ANNz2 also generates full probability density functions (PDFs) in two different ways. In addition, estimators are incorporated to mitigate possible problems of spectroscopic training samples which are not representative or are incomplete. ANNz2 is also adapted to provide optimized solutions to general classification problems, such as star/galaxy separation.

[ascl:1910.013]
E0102-VR: Virtual Reality application to visualize the optical ejecta in SNR 1E 0102.2-7219

E0102-VR facilitates the characterization of the 3D structure of the oxygen-rich optical ejecta in the young supernova remnant 1E 0102.2-7219 in the Small Magellanic Cloud. This room-scale Virtual Reality application written for the HTC Vive contributes to the exploration of the scientific potential of this technology for the field of observational astrophysics.

[ascl:1910.012]
AOTOOLS: Reduce IR images from Adaptive Optics

AOTOOLS reduces IR images from adaptive optics. It uses effective dithering, either sky subtraction or dark-subtration, and flat-fielding techniques to determine the effect of the instrument on an image of an object. It also performs bad pixel masking, degrades an AO on-axis PSF due to effects of anisoplanicity, and corrects an AO on-axis PSF due to effects of seeing.

[ascl:1910.011]
LEO-Py: Likelihood Estimation of Observational data with Python

LEO-Py uses a novel technique to compute the likelihood function for data sets with uncertain, missing, censored, and correlated values. It uses Gaussian copulas to decouple the correlation structure of variables and their marginal distributions to compute likelihood functions, thus mitigating inconsistent parameter estimates and accounting for non-normal distributions in variables of interest or their errors.

[ascl:1910.010]
PEXO: Precise EXOplanetology

Feng, Fabo; Lisogorskyi, Maksym; Jones, Hugh R. A.; Kopeikin, Sergei M.; Butler, R. Paul; Anglada-Escude, Guillem; Boss, Alan P.

PEXO provides a global modeling framework for ns timing, μas astrometry, and μm/s radial velocities. It can account for binary motion and stellar reflex motions induced by planetary companions and also treat various relativistic effects both in the Solar System and in the target system (Roemer, Shapiro, and Einstein delays). PEXO is able to model timing to a precision of 1 ns, astrometry to a precision of 1 μas, and radial velocity to a precision of 1 μm/s.

[ascl:1910.009]
orbitize: Orbit-fitting for directly imaged objects

Blunt, Sarah; Wang, Jason; Angelo, Isabel; Ngo, Henry; Cody, Devin; De Rosa, Robert J.; Graham, James; Hirsch, Lea; Nagpal, Vighnesh; Nielsen, Eric L.; Pearce, Logan; Rice, Malena; Tejada, Roberto

orbitize fits the orbits of directly-imaged objects by packaging the Orbits for the Impatient (OFTI) algorithm and a parallel-tempered Markov Chain Monte Carlo (MCMC) algorithm into a consistent API. It accepts observations in three measurement formats, which can be mixed in the same input file, generates orbits, and plots the computed orbital parameters. orbitize offers numerous ways to visualize the data, including histograms, corner plots, and orbit plots. Generated orbits can be saved in HDF5 format for future use and analysis.

[ascl:1910.008]
ECLIPS3D: Linear wave and circulation calculations

ECLIPS3D (Eigenvectors, Circulation, and Linear Instabilities for Planetary Science in 3 Dimensions) calculates a posteriori energy equations for the study of linear processes in planetary atmospheres with an arbitrary steady state, and provides both increased robustness and physical meaning to the obtained eigenmodes. It was developed originally for planetary atmospheres and includes python scripts for data analysis. ECLIPS3D can be used to study the initial spin up of superrotation of GCM simulations of hot Jupiters in addition to being applied to other problems.

[ascl:1910.007]
TLS: Transit Least Squares

TLS is an optimized transit-fitting algorithm to search for periodic transits of small planets. In contrast to BLS: Box Least Squares (ascl:1607.008), which searches for rectangular signals in stellar light curves, TLS searches for transit-like features with stellar limb-darkening and including the effects of planetary ingress and egress. TLS also analyses the entire, unbinned data of the phase-folded light curve. TLS yields a ~10% higher detection efficiency (and similar false alarm rates) compared to BLS though has a higher computational load. This load is partly compensated for by applying an optimized period sampling and transit duration sampling constrained to the physically plausible range.

[ascl:1910.006]
EMERGE: Empirical ModEl for the foRmation of GalaxiEs

Emerge (Empirical ModEl for the foRmation of GalaxiEs) populates dark matter halo merger trees with galaxies using simple empirical relations between galaxy and halo properties. For each model represented by a set of parameters, it computes a mock universe, which it then compares to observed statistical data to obtain a likelihood. Parameter space can be explored with several advanced stochastic algorithms such as MCMC to find the models that are in agreement with the observations.

[ascl:1910.005]
exoplanet: Probabilistic modeling of transit or radial velocity observations of exoplanets

exoplanet is a toolkit for probabilistic modeling of transit and/or radial velocity observations of exoplanets and other astronomical time series using PyMC3 (ascl:1610.016), a flexible and high-performance model building language and inference engine. exoplanet extends PyMC3's language to support many of the custom functions and distributions required when fitting exoplanet datasets. These features include a fast and robust solver for Kepler's equation; scalable Gaussian processes using celerite (ascl:1709.008); and fast and accurate limb darkened light curves using the code starry (ascl:1810.005). It also offers common reparameterizations for limb darkening parameters, and planet radius and impact parameters.

[ascl:1910.004]
DM_phase: Algorithm for correcting dispersion of radio signals

DM_phase maximizes the coherent power of a radio signal instead of its intensity to calculate the best dispersion measure (DM) for a burst such as those emitted by pulsars and fast radio bursts (FRBs). It is robust to complex burst structures and interference, thus mitigating the limitations of traditional methods that search for the best DM value of a source by maximizing the signal-to-noise ratio (S/N) of the detected signal.

[ascl:1910.003]
a3cosmos-gas-evolution: Galaxy cold molecular gas evolution functions

a3cosmos-gas-evolution calculates galaxies' cold molecular gas properties using gas scaling functions derived from the A3COSMOS project. By known galaxies' redshifts or cosmic age, stellar masses, and star formation enhancement to galaxies' star-forming main sequence (Delta MS), the gas scaling functions predict their stellar mass ratio (gas fraction) and gas depletion time.

[ascl:1910.002]
PreProFit: Pressure Profile Fitter for galaxy clusters in Python

PreProFit fits the pressure profile of galaxy clusters using Markov chain Monte Carlo (MCMC). The software can analyze data from different sources and offers flexible parametrization for the pressure profile. PreProFit accounts for Abel integral, beam smearing, and transfer function filtering when fitting data and returns χ2, model parameters and uncertainties in addition to marginal and joint probability contours, diagnostic plots, and surface brightness radial profiles. The code can be used for analytic approximations for the beam and transfer functions for feasibility studies.

[ascl:1910.001]
PINK: Parallelized rotation and flipping INvariant Kohonen maps

Morphological classification is one of the most demanding challenges in astronomy. With the advent of all-sky surveys, an enormous amount of imaging data is publicly available, and are typically analyzed by experts or encouraged amateur volunteers. For upcoming surveys with billions of objects, however, such an approach is not feasible anymore. PINK (Parallelized rotation and flipping INvariant Kohonen maps) is a simple yet effective variant of a rotation-invariant self-organizing map that is suitable for many analysis tasks in astronomy. The code reduces the computational complexity via modern GPUs and applies the resulting framework to galaxy data for morphological analysis.

[submitted]
Magnetizer: computing magnetic fields of evolving galaxies

Computes time and radial dependent magnetic fields for a sample of galaxies in the output of a semi-analytic model of galaxy formation. The magnetic field is obtained by numerically solving the galactic dynamo equations throughout history of each galaxy. Stokes parameters and Faraday rotation measure can also be computed along a random line-of-sight for each galaxy.

[submitted]
HaloAnalysis: read and analyze halo catalogs and merger trees

HaloAnalysis reads and analyzes halo/galaxy catalogs, generated from Rockstar (ascl:1210.008) or AHF (ascl:1102.009), and merger trees generated from Consistent Trees (ascl:1210.011). Written in Python, it offers the following functionality: reads halo/galaxy/tree catalogs from multiple file formats; assigns baryonic particles and galaxy properties to dark-matter halos; combines and re-generates halo/galaxy/tree files in hdf5 format; analyzes properties of halos/galaxies; selects halos to generate zoom-in initial conditions. Includes a Jupyter notebook tutorial.

[submitted]
GizmoAnalysis: read and analyze Gizmo simulations

GizmoAnalysis reads and analyzes N-body simulations run with the Gizmo code (ascl:1410.003). Written in Python, we developed it primarily to analyze FIRE simulations, though it is useable with any Gizmo snapshot files. It offers the following functionality: reads snapshot files and converts particle data to physical units; provides a flexible dictionary class to store particle data and compute derived quantities on the fly; plots images and properties of particles; generates region files for input to MUSIC (ascl:1311.011) to generate cosmological zoom-in initial conditions; computes rates of supernovae and stellar winds, including their nucleosynthetic yields, as used in FIRE simulations. Includes a Jupyter notebook tutorial.

[ascl:1909.014]
fgivenx: Functional posterior plotter

fgivenx plots a predictive posterior of a function, dependent on sampled parameters, for a Bayesian posterior Post(theta|D,M) described by a set of posterior samples {theta_i}~Post. If there is a function parameterized by theta y=f(x;theta), this script produces a contour plot of the conditional posterior P(y|x,D,M) in the (x,y) plane.

[ascl:1909.013]
EPOS: Exoplanet Population Observation Simulator

EPOS (Exoplanet Population Observation Simulator) simulates observations of exoplanet populations. It provides an interface between planet formation simulations and exoplanet surveys such as Kepler. EPOS can also be used to estimate planet occurrence rates and the orbital architectures of planetary systems.

[ascl:1909.012]
HISS: HI spectra stacker

Healy, J.; Blyth, S. -L.; Elson, E.; van Driel, W.; Butcher, Z.; Schneider, S.; Lehnert, M. D.; Minchin, R.

HISS stacks HI (emission and absorption) spectra in a consistent and reliable manner to enable statistical analysis of average HI properties. It provides plots of the stacked spectrum and reference spectrum with any fitted function, of the stacked noise response, and of the distribution of the integrated fluxes when calculating the uncertainties. It also produces a table containing the integrated flux calculated from the fitted functions and the stacked spectrum, among other output files.

[ascl:1909.011]
WVTICs: SPH initial conditions using Weighted Voronoi Tesselations

Arth, Alexander; Donnert, Julius; Steinwandel, Ulrich; Böss, Ludwig; Halbesma, Timo; Pütz, Martin; Hubber, David; Dolag, Klaus

WVTICs generates glass-like initial conditions for Smoothed Particle Hydrodynamics. Relaxation of the particle distribution is done using an algorithm based on Weighted Voronoi Tesselations; additional particle reshuffling can be enabled to improve over- and undersampled maxima/minima. The WBTICs package includes a full suite of analytical test problems.

[ascl:1909.010]
AREPO: Cosmological magnetohydrodynamical moving-mesh simulation code

AREPO is a massively parallel gravity and magnetohydrodynamics code for astrophysics, designed for problems of large dynamic range. It employs a finite-volume approach to discretize the equations of hydrodynamics on a moving Voronoi mesh, and a tree-particle-mesh method for gravitational interactions. AREPO is originally optimized for cosmological simulations of structure formation, but has also been used in many other applications in astrophysics.

[ascl:1909.009]
CLOVER: Convolutional neural network spectra identifier and kinematics predictor

CLOVER (Convnet Line-fitting Of Velocities in Emission-line Regions) is a convolutional neural network (ConvNet) trained to identify spectra with two velocity components along the line of sight and predict their kinematics. It works with Gaussian emission lines (e.g., CO) and lines with hyperfine structure (e.g., NH3). CLOVER has two prediction steps, classification and parameter prediction. For the first step, CLOVER segments the pixels in an input data cube into one of three classes: noise (i.e., no emission), one-component (emission line with single velocity component), and two-component (emission line with two velocity components). For the pixels identified as two-components in the first step, a second regression ConvNet is used to predict centroid velocity, velocity dispersion, and peak intensity for each velocity component.

[ascl:1909.008]
RascalC: Fast code for galaxy covariance matrix estimation

RascalC quickly estimates covariance matrices from two- or three-point galaxy correlation functions. Given an input set of random particle locations and a two-point correlation function (or input set of galaxy positions), RascalC produces an estimate of the associated covariance for a given binning strategy, with non-Gaussianities approximated by a ‘shot-noise-rescaling’ parameter. For the 2PCF, the rescaling parameter can be calibrated by dividing the particles into jackknife regions and comparing sample to theoretical jackknife covariance. RascalC can also be used to compute Legendre-binned covariances and cross-covariances between different two-point correlation functions.

[ascl:1909.007]
EBHLIGHT: General relativistic radiation magnetohydrodynamics with Monte Carlo transport

EBHLIGHT solves the equations of general relativistic radiation magnetohydrodynamics in stationary spacetimes. Fluid integration is performed with the second order shock-capturing scheme HARM (ascl:1209.005) and frequency-dependent radiation transport is performed with the second order Monte Carlo code grmonty (ascl:1306.002). Fluid and radiation exchange four-momentum in an explicit first-order operator-split fashion.

[ascl:1909.006]
ChempyMulti: Multi-star Bayesian inference with Chempy

ChempyMulti is an update to Chempy (ascl:1702.011) and provides yield table scoring and multi-star Bayesian inference. This replaces the ChempyScoring package in Chempy. Chempy is a flexible one-zone open-box chemical evolution model, incorporating abundance fitting and stellar feedback calculations. It includes routines for parameter optimization for simulations and observational data and yield table scoring.

[ascl:1909.005]
HADES: Hexadecapolar Analysis for Dust Estimation in Simulations (of CMB B-mode thermal dust emission)

HADES analyzse dust levels in simulated CMB galactic dust maps with realistic experimental noise and lensing configurations. It allows detection of dust via its anisotropy properties in CMB B-modes. It also includes techniques for computing null-tests and a rudimentary technique for dedusting.

[ascl:1909.004]
TPI: Test Particle Integrator

TPI computes the gravitational dynamics of particles orbiting a supermassive black hole (SBH). A distinction is made to two types of particles: test particles and field particles. Field particles are assumed to move in quasi-static Keplerian orbits around the SBH that precess due to the enclosed mass (Newtonian 'mass precession') and relativistic effects. Otherwise, field-particle-field-particle interactions are neglected. Test particles are integrated in the time-dependent potential of the field particles and the SBH. Relativistic effects are included in the equations of motion (including the effects of SBH spin), and test-particle-test-particle interactions are neglected.

[ascl:1909.003]
SecularMultiple: Hierarchical multiple system secular evolution model

SecularMultiple computes the secular (orbit-averaged) gravitational dynamics of hierarchical multiple systems composed of nested binary orbits (simplex-type systems) with any configuration and any number of bodies. A particle can represent a binary or a body. The structure of the system is determined by linking to other particles with the attributes child1 and child2, and tidal interactions and relativistic corrections are included in an ad hoc fashion. SecularMultiple also includes routines for external perturbations such as flybys and supernovae.

[ascl:1909.002]
MultiColorFits: Colorize and combine multiple fits images for visually aesthetic scientific plots

MultiColorFits is a tool to colorize and combine multiple fits images for making visually aesthetic scientific plots. The standard method to make color composites by combining fits images programmatically in python is to assign three images as separate red, green, and blue channels. This can produce unsatisfactory results for a variety of reasons, such as when less than three images are available, or additional images are desired to be shown. MultiColorFits breaks these limitations by allowing users to apply any color to a given image, not just red, green, or blue. Composites can then be created from an arbitrary number of images. Controls are included for stretching brightness scales with common functions.

[ascl:1909.001]
Auto-multithresh: Automated masking for clean

Auto-multithresh implements an automated masking algorithm for clean. It operates on the residual image within the minor cycle of clean to identify and mask regions of significant emission. It then cascades these significant regions down to lower signal to noise. It includes features to pad the mask to avoid sharp edges and to remove small regions that are unlikely to be significant emission. The algorithm described by this code was incorporated into the tclean task within CASA as auto-multithresh.

[submitted]
CR-SISTEM: Symplectic integrator for lunar core-mantle and orbital dynamics

This integrator is based on the algorithm of Touma and Wisdom (2001, http://ui.adsabs.harvard.edu/abs/2001AJ....122.1030T). The triaxial Moon has a triaxial liquid core, and is perturbed by the Sun and Earth's oblateness. Orbits of the Moon and Earth are fully integrated, and other planets (or additional point-mass satellites) may be included in the integration. Lunar and solar tides on Earth, eccentricity and obliquity tides on the Moon, and lunar core-mantle friction and all included. The tides on Earth and the Moon are treated in the same way Cuk et al (2016, http://ui.adsabs.harvard.edu/abs/2016Natur.539..402C) and many details of their closely-related code can be found in the online supplement of that paper. In the posted version, the lunar core-mantle friction torque is directly proportional to the core-mantle differential rotation, with a fixed damping timescale of 10,000 present-day sidereal months (120 yrs, after Pavlov et al. (2016, https://ui.adsabs.harvard.edu/abs/2016CeMDA.126...61P).

[ascl:1908.025]
FastCSWT: Fast directional Continuous Spherical Wavelet Transform

FastCSWT performs a directional continuous wavelet transform on the sphere. The transform is based on the construction of the continuous spherical wavelet transform (CSWT) developed by Antoine and Vandergheynst (1999). A fast implementation of the CSWT (based on the fast spherical convolution developed by Wandelt and Gorski 2001) is also provided.

[ascl:1908.024]
PYSAT: Python Satellite Data Analysis Toolkit

The Python Satellite Data Analysis Toolkit (pysat) provides a simple and flexible interface for downloading, loading, cleaning, managing, processing, and analyzing space science data. The toolkit supports in situ satellite observations and many different types of ground- and space-based measurements. Its analysis routines are independent of instrument and data source.

[ascl:1908.023]
FIRST Classifier: Automated compact and extended radio sources classifier

FIRST Classifier is an on-line system for automated classification of compact and extended radio sources. It is developed based on a trained Deep Convolutional Neural Network Model to automate the morphological classification of compact and extended radio sources observed in the FIRST radio survey. FIRST Classifier is able to predict the morphological class for a single source or for a list of sources as Compact or Extended (FRI, FRII and BENT).

[ascl:1908.022]
YMW16: Electron-density model

YMW16 models the distribution of free electrons in the Galaxy, the Magellanic Clouds and the inter-galactic medium and can be used to estimate distances for real or simulated pulsars and fast radio bursts (FRBs) based on their position and dispersion measure. The Galactic model is based on 189 pulsars that have independently determined distances as well as dispersion measures, whereas simpler models are used for the electron density in the MC and the IGM.

[ascl:1908.021]
bias_emulator: Halo bias emulator

bias_emulator models the clustering of halos on large scales. It incorporates the cosmological dependence of the bias beyond the mapping of halo mass to peak height. Precise measurements of the halo bias in the simulations are interpolated across cosmological parameter space to obtain the halo bias at any point in parameter space within the simulation cloud. A tool to produce realizations of correlated noise for propagating the modeling uncertainty into error budgets that use the emulator is also provided.

[ascl:1908.020]
QLF: Luminosity function analysis code

QLF derives full posterior distributions for and analyzes luminosity functions models; it also models hydrogen and helium reionization. Used with the included homogenized data, the derived luminosity functions can be easily compared with theoretical models or future data sets.

[ascl:1908.019]
MAESTROeX: Low Mach number stellar hydrodynamics code

MAESTROeX solves the equations of low Mach number hydrodynamics for stratified atmospheres or stars with a general equation of state. It includes reactions and thermal diffusion and can be used on anything from a single core to 100,000s of processor cores with MPI + OpenMP. MAESTROeX maintains the accuracy of its predecessor MAESTRO (ascl:1010.044) while taking advantage of a simplified temporal integration scheme and leveraging the AMReX software framework for block-structured adaptive mesh refinement (AMR) applications.

[ascl:1908.018]
EBAI: Eclipsing Binaries with Artificial Intelligence

Prša, A.; Guinan, E. F.; Devinney, E. J.; DeGeorge, M.; Bradstreet, D. H.; Giammarco, J. M.; Alcock, C. R.; Engle, S. G.

Eclipsing Binaries via Artificial Intelligence (EBAI) automates the process of solving light curves of eclipsing binary stars. EBAI is based on the back-propagating neural network paradigm and is highly flexible in construction of neural networks. EBAI comes in two flavors, serial (ebai) and multi-processor (ebai.mpi), and can be run in training, continued training, and recognition mode.

[ascl:1908.017]
JPLephem: Jet Propulsion Lab ephemerides package

JPLephem loads and uses standard Jet Propulsion Laboratory (JPL) ephemerides for predicting the position and velocity of a planet or other Solar System body. It is one of the foundations of the Skyfield (ascl:1907.024) astronomy library for Python, and can also be used as a standalone package to generate raw vectors.

[ascl:1908.016]
DustCharge: Charge distribution for a dust grain

Ibáñez-Mejía, Juan C.; Walch, Stefanie; Ivlev, Alexei V.; Clarke, Seamus; Caselli, Paola; Joshi, Prabesh R.

DustCharge calculates the equilibrium charge distribution for a dust grain of a given size and composition, depending on the local interstellar medium conditions, such as density, temperature, ionization fraction, local radiation field strength, and cosmic ray ionization fraction.

[ascl:1908.015]
Analysator: Quantitative analysis of Vlasiator files

Hannuksela, Otto Akseli; Battarbee, Markus; Pfau-Kempf, Yann; von Alfthan, Sebastian; Jarvinen, Riku; Ganse, Urs; Suni, Jonas

Analysator analyzes vlsv files produced by Vlasiator (ascl:1908.014). The code facilitates studies of particle paths, pitch angle distributions, velocity distributions, and more. It can read and write VLSV files and do calculations with the data, plot the real space from VLSV files with Mayavi (ascl:1205.008), and plot the velocity space (both blocks and iso surface) from VLSV files. It can also take cut-throughs, pitch angle distributions, gyrophase angle, and 3d slices, plot variables with sub plots in a clean format, and fit 1D polynomials to data.

[ascl:1908.014]
Vlasiator: Hybrid-Vlasov simulation code

von Alfthan, Sebastian; Pfau-Kempf, Yann; Sandroos, Arto; Hannuksela, Otto Akseli; Ganse, Urs; Battarbee, Markus; Pokhotelov, Dimitry

Vlasiator is a 6-dimensional Vlasov theory-based simulation. It simulates the entire near-Earth space at a global scale using the kinetic hybrid-Vlasov approach, to study fundamental plasma processes (reconnection, particle acceleration, shocks), and to gain a deeper understanding of space weather.

[ascl:1908.013]
BEAST: Bayesian Extinction And Stellar Tool

Gordon, Karl D.; Fouesneau, Morgan; Arab, Heddy; Tchernyshyov, Kirill; Weisz, Daniel R.; Dalcanton, Julianne J.; Williams, Benjamin F.; Bell, Eric F.; Bianchi, Luciana; Boyer, Martha; Choi, Yumi; Dolphin, Andrew; Girardi, Léo; Hogg, David W.; Kalirai, Jason S.; Kapala, Maria; Lewis, Alexia R.; Rix, Hans-Walter; Sandstrom, Karin; Skillman, Evan D.

BEAST (Bayesian Extinction and Stellar Tool) fits the ultraviolet to near-infrared photometric SEDs of stars to extract stellar and dust extinction parameters. The stellar parameters are age (t), mass (M), metallicity (M), and distance (d). The dust extinction parameters are dust column (Av), average grain size (Rv), and mixing between type A and B extinction curves (fA).

[ascl:1908.012]
oscode: Oscillatory ordinary differential equation solver

oscode solves oscillatory ordinary differential equations efficiently. It is designed to deal with equations of the form *x*¨(*t*)+2γ(*t*)*x*˙(*t*)+ω2(*t*)*x*(*t*)=0, where γ(*t*) and ω(*t*) can be given as explicit functions or sequence containers (Eigen::Vectors, arrays, std::vectors, lists) in C++ or as numpy.arrays in Python. oscode makes use of an analytic approximation of *x(t)* embedded in a stepping procedure to skip over long regions of oscillations, giving a reduction in computing time. The approximation is valid when the frequency changes slowly relative to the timescales of integration, it is therefore worth applying when this condition holds for at least some part of the integration range.

[ascl:1908.011]
NuRadioMC: Monte Carlo simulation package for radio neutrino detectors

Glaser, Christian; García-Fernández, Daniel; Nelles, Anna; Alvarez-Muñiz, Jaime; Barwick, Steven W.; Besson, Dave Z.; Clark, Brian A.; Connolly, Amy; Deaconu, Cosmin; de Vries, Krijn; Hanson, Jordan C.; Hokanson-Fasig, Ben; Lahmann, R.; Latif, Uzair; Kleinfelder, Stuart A.; Persichilli, Christopher; Pan, Yue; Pfender, Carl; Plaisier, Ilse; Seckel, Dave Torres, Jorge; Toscano, Simona; van Eijndhoven, Nick; Vieregg, Abigail; Welling, Christoph; Winchen, Tobias; Wissel, Stephanie A.

NuRadioMC simulates ultra-high energy neutrino detectors that rely on the radio detection method, which exploits the radio emission generated in the electromagnetic component of a particle shower following a neutrino interaction. The code simulates the neutrino interaction in a medium, subsequent Askaryan radio emission, propagation of the radio signal to the detector and the detector response. NuRadioMC is a Monte Carlo framework that combines flexibility in detector design with user-friendliness. It includes an event generator, improved modeling of the radio emission, a revisited approach to signal propagation, and increased flexibility and precision in the detector simulation.

[ascl:1908.010]
SNAPDRAGONS: Stellar Numbers And Parameters Determined Routinely And Generated Observing N-body Systems

Hunt, Jason A. S.; Kawata, Daisuke; Grand, Robert J. J.; Minchev, Ivan; Pasetto, Stefano; Cropper, Mark

SNAPDRAGONS (Stellar Numbers And Parameters Determined Routinely And Generated Observing N-body Systems) is a simplified version of the population synthesis code Galaxia (ascl:1101.007), using a different process to generate the stellar catalog. It splits each N-body particle from the galaxy simulation into an appropriate number of stellar particles to create a mock catalog of observable stars from the N-body model. SNAPDRAGON uses the same isochrones and extinction map as Galaxia.

[ascl:1908.009]
PyRADS: Python RADiation model for planetary atmosphereS

The 1D radiation code PyRADS provides line-by-line spectral resolution. For Earth-like atmospheres, PyRADS currently uses HITRAN 2016 line lists and the MTCKD continuum model. A version for shortwave radiation (scattering) is also available.

[ascl:1908.008]
TRISTAN-MP: TRIdimensional STANford - Massively Parallel code

TRISTAN-MP is a fully relativistic Particle-In-Cell (PIC) code for plasma physics computations and self-consistently solves the full set of Maxwell’s equations, along with the relativistic equations of motion for the charged particles. Fields are discretized on a finite 3D or 2D mesh, the computational grid; the code then uses time-centered and space-centered finite difference schemes to advance the equations in time via the Lorentz force equation, and to calculate spatial derivatives, so that the algorithm is second order accurate in space and time. The charges and currents derived from the particles' velocities and positions are then used as source terms to re-calculate the electromagnetic fields. TRISTAN-MP is based on the original TRISTAN code by O. Buneman (1999).

[ascl:1908.007]
MosfireDRP: MOSFIRE Data Reduction Pipeline

MosfireDRP reduces data from the MOSFIRE spectrograph of the Keck Observatory; it produces flat-fielded, wavelength calibrated, rectified, and stacked 2D spectrograms for each slit on a given mask in nearly real time. Background subtraction is performed in two states: a simple pairwise subtraction of interleaved stacks, and then fitting a 2D b-spline model to the background residuals.

[ascl:1908.006]
GBKFIT: Galaxy kinematic modeling

GBKFIT performs galaxy kinematic modeling. It can be used to extract morphological and kinematical properties of galaxies by fitting models to spatially resolved kinematic data. The software can also take beam smearing into account by using the knowledge of the line and point spread functions. GBKFIT can take advantage of many-core and massively parallel architectures such as multi-core CPUs and Graphics Processing Units (GPUs), making it suitable for modeling large-scale surveys of thousands of galaxies within a very seasonable time frame. GBKFIT features an extensible object-oriented architecture that supports arbitrary models and optimization techniques in the form of modules; users can write custom modules without modifying GBKFIT’s source code. The software is written in C++ and conforms to the latest ISO standards.

[ascl:1908.005]
dips: Detrending periodic signals in timeseries

dips detrends timeseries of strictly periodic signals. It does not assume any functional form for the signal or the background or the noise; it disentangles the strictly periodic component from everything else. It has been used for detrending Kepler, K2 and TESS timeseries of periodic variable stars, eclipsing binary stars, and exoplanets.

[ascl:1908.004]
Gramsci: GRAph Made Statistics for Cosmological Information

Gramsci (GRAph Made Statistics for Cosmological Information) computes the general N-point spatial correlation functions of any discrete point set embedded within an Euclidean space of ℝ^n. It uses kd-trees and graph databases to count all possible N-tuples in binned configurations within a given length scale, e.g. all pairs of points or all triplets of points with side lengths. Gramsci can run in serial, OpenMP, MPI and hybrid parallel schemes. It is useful for performing domain decomposition of input catalogs, especially if the catalogs are large or the Rmax value is too large.

[ascl:1908.003]
ActSNClass: Active learning for supernova photometric classification

ActSNClass uses a parametric feature extraction method, Random Forest classifier and two learning strategies (uncertainty sampling and random sampling) to performs active learning for supernova photometric classification.

[ascl:1908.002]
Molsoft: Molonglo Telescope Observing Software

Molsoft operates, monitors and schedules observations, both through predetermined schedule files and fully dynamically, at the refurbished Molonglo Observatory Synthesis Radio Telescope (MOST). It was developed as part of the UTMOST upgrade of the facility. The software runs a large-scale pulsar timing program; the autonomous observing system and the dynamic scheduler have increased the observing efficiency by a factor of 2-3 in comparison with static scheduling.

[ascl:1908.001]
QAC: Quick Array Combinations front end to CASA

QAC (Quick Array Combinations) is a front end to CASA (ascl:1107.013) and calls tools and tasks to help in combining data from a single dish and interferometer. QAC hides some of the complexity of writing CASA scripts and provide a simple interface to array combination tools and tasks in CASA. This project was conceived alongside the TP2VIS (ascl:1904.021) project, where it was used to provide an easier way to call CASA and perform regression tests.

[ascl:1907.032]
Astro-SCRAPPY: Speedy Cosmic Ray Annihilation Package in Python

Astro-SCRAPPY detects cosmic rays in images (numpy arrays), based on Pieter van Dokkum's L.A.Cosmic algorithm and originally adapted from cosmics.py written by Malte Tewes. This implementation is optimized for speed, resulting in slight difference from the original code, such as automatic recognition of saturated stars (rather than treating such stars as large cosmic rays, and use of a separable median filter instead of the true median filter. Astro-SCRAPPY is an AstroPy (ascl:1304.002) affiliated package.

[ascl:1907.031]
MGB: Interactive spectral classification code

MGB (Marxist Ghost Buster) attacks spectral classification by using an interactive comparison with spectral libraries. It allows the user to move along the two traditional dimensions of spectral classification (spectral subtype and luminosity classification) plus the two additional ones of rotation index and spectral peculiarities. Double-lined spectroscopic binaries can also be fitted using a combination of two standards. The code includes OB2500 v2.0, a standard grid of blue-violet *R* ~ 2500 spectra of O stars from the Galactic O-Star Spectroscopic Survey, but other grids can be added to MGB.

[ascl:1907.030]
Wōtan: Stellar detrending methods

Wōtan provides free and open source algorithms to remove trends from time-series data automatically as an aid to to search efficiently for transits in stellar light curves from surveys. The toolkit helps determine empirically the best tool for a given job, serving as a one-stop solution for various smoothing tasks.

[ascl:1907.029]
XDF-GAN: Mock astronomical survey generator

XDF-GAN generates mock galaxy surveys with a Spatial Generative Adversarial Network (SGAN)-like architecture. Mock galaxy surveys are generated from data that is preprocessed as little as possible (preprocessing is only a 99.99th percentile clipping). The outputs can also be tessellated together to create a very large survey, limited in size only by the RAM of the generation machine.

[ascl:1907.028]
ROHSA: Separation of diffuse sources in hyper-spectral data

ROHSA (Regularized Optimization for Hyper-Spectral Analysis) reveals the statistical properties of interstellar gas through atomic and molecular lines. It uses a Gaussian decomposition algorithm based on a multi-resolution process from coarse to fine grid to decompose any kind of hyper-spectral observations into a sum of coherent Gaussian. Optimization is performed on the whole data cube at once to obtain a solution with spatially smooth parameters.

[ascl:1907.027]
intensitypower: Spectrum multipoles modeler

intensitypower measures and models the auto- and cross-power spectrum multipoles of galaxy catalogs and radio intensity maps presented in spherical coordinates. It can also convert the multipoles to power spectrum wedges P(k,mu) and 2D power spectra P(k_perp,k_par). The code assumes the galaxy catalog is a set of discrete points and the radio intensity map is a pixelized continuous field which includes angular pixelization using healpix, binning in redshift channels, smoothing by a Gaussian telescope beam, and the addition of a Gaussian noise in each cell. The galaxy catalog and radio intensity map are transferred onto an FFT grid, and power spectrum multipoles are measured including curved-sky effects. Both maps include redshift-space distortions.

[ascl:1907.026]
MCRGNet: Morphological Classification of Radio Galaxy Network

MCRGNet (Morphological Classification of Radio Galaxy Network) classifies radio galaxies of different morphologies. It is based on the Convolutional Neural Network (CNN), which is trained and applied under a three-step framework: 1.) pretraining the network unsupervisedly with unlabeled samples, 2.) fine-tuning the pretrained network parameters supervisedly with labeled samples, and 3.) classifying a new radio galaxy by the trained network. The code uses a dichotomous tree classifier composed of cascaded CNN based subclassifiers.

[ascl:1907.025]
GIST: Galaxy IFU Spectroscopy Tool

Bittner, A.; Falcón-Barroso, J.; Nedelchev, B.; Dorta, A.; Gadotti, D. A.; Sarzi, M.; Molaeinezhad, A.; Iodice, E.; Rosado-Belza, D.; de Lorenzo-Cáceres, A.; Fragkoudi, F.; Galán-de Anta, P. M.; Husemann, B.; Méndez-Abreu, J.; Neumann, J.; Pinna, F.; Querejeta, M.; Sánchez-Blázquez, P.; Seidel, M. K.

GIST (Galaxy IFU Spectroscopy Tool) provides a convenient all-in-one framework for the scientific analysis of fully reduced, (integral-field) spectroscopic data, conducting all the steps from the preparation of input data to the scientific analysis and to the production of publication-quality plots. In its basic set-up, the GIST pipeline extracts stellar kinematics, performs an emission-line analysis, and derives stellar population properties from full spectral fitting and via the measurement of absorption line-strength indices by exploiting pPXF (ascl:1210.002)and GandALF routines. The pipeline is not specific to any instrument or analysis technique, and includes a dedicated visualization routine with a sophisticated graphical user interface for fully interactive plotting of all measurements, spectra, fits, and residuals, as well as star formation histories and the weight distribution of the models.

[ascl:1907.024]
Skyfield: High precision research-grade positions for planets and Earth satellites generator

Skyfield computes positions for the stars, planets, and satellites in orbit around the Earth. Its results should agree with the positions generated by the United States Naval Observatory and their Astronomical Almanac to within 0.0005 arcseconds (which equals half a “mas” or milliarcsecond). It computes geocentric coordinates or topocentric coordinates specific to your location on the Earth’s surface. Skyfield accepts AstroPy (ascl:1304.002) time objects as input and can return results in native AstroPy units but is not dependend on AstroPy nor its compiled libraries.

[ascl:1907.023]
REVOLVER: REal-space VOid Locations from suVEy Reconstruction

REVOLVER reconstructs real space positions from redshift-space tracer data by subtracting RSD through FFT-based reconstruction (optional) and applies void-finding algorithms to create a catalogue of voids in these tracers. The tracers are normally galaxies from a redshift survey but could also be halos or dark matter particles from a simulation box. Two void-finding routines are provided. The first is based on ZOBOV (ascl:1304.005) and uses Voronoi tessellation of the tracer field to estimate the local density, followed by a watershed void-finding step. The second is a voxel-based method, which uses a particle-mesh interpolation to estimate the tracer density, and then uses a similar watershed algorithm. Input data files can be in FITS format, or ASCII- or NPY-formatted data arrays.

[ascl:1907.022]
CMDPT: Color Magnitude Diagrams Plot Tool

CMD Plot Tool calculates and plots Color Magnitude Diagrams (CMDs) from astronomical photometric data, *e.g.* of a star cluster observed in two filter bandpasses. It handles multiple file formats (plain text, DAOPHOT .mag files, ACS Survey of Galactic Globular Clusters .zpt files) to generate professional and customized plots without a steep learning curve. It works “out of the box” and does not require any installation of development environments, additional libraries, or resetting of system paths. The tool is available as a single application/executable file with the source code. Sample data is also bundled for demonstration. CMD Plot Tool can also convert DAOPHOT magnitude files to CSV format.

[ascl:1907.021]
PRISM: Probabilistic Regression Instrument for Simulating Models

PRISM analyzes scientific models using the Bayes linear approach, the emulation technique, and history matching to construct an approximation ('emulator') of any given model. The software facilitates and enhances existing MCMC methods by restricting plausible regions and exploring parameter space efficiently and can be used as a standalone alternative to MCMC for model analysis, providing insight into the behavior of complex scientific models. PRISM stores results in HDF5-files and can be executed in serial or MPI on any number of processes. It accepts any type of model and comparison data and can reduce relevant parameter space by factors over 100,000 using only a few thousand model evaluations.

[ascl:1907.020]
GaussPy+: Gaussian decomposition package for emission line spectra

Riener, Manuel; Kainulainen, Jouni; Henshaw, Jonathan D.; Orkisz, Jan H.; Murray, Claire E.; Beuther, Henrik

GaussPy+ is a fully automated Gaussian decomposition package for emission line spectra. It is based on GaussPy (ascl:1907.019) and offers several improvements, including automating preparatory steps and providing an accurate noise estimation, improving the fitting routine, and providing a routine to refit spectra based on neighboring fit solutions. GaussPy+ handles complex emission and low to moderate signal-to-noise values.

[ascl:1907.019]
GaussPy: Python implementation of the Autonomous Gaussian Decomposition algorithm

GaussPy implements the Autonomous Gaussian Decomposition (AGD) algorithm, which uses computer vision and machine learning techniques to provide optimized initial guesses for the parameters of a multi-component Gaussian model automatically and efficiently. The speed and adaptability of AGD allow it to interpret large volumes of spectral data efficiently. Although it was initially designed for applications in radio astrophysics, AGD can be used to search for one-dimensional Gaussian (or any other single-peaked spectral profile)-shaped components in any data set. To determine how many Gaussian functions to include in a model and what their parameters are, AGD uses a technique called derivative spectroscopy. The derivatives of a spectrum can efficiently identify shapes within that spectrum corresponding to the underlying model, including gradients, curvature and edges.

[ascl:1907.018]
StePar: Inferring stellar atmospheric parameters using the EW method

StePar computes the stellar atmospheric parameters T_{eff}, log g, [Fe/H], and ξ of FGK-type stars using the Equivalent Width (*EW*) method. The code implements a grid of MARCS model atmospheres and uses the MOOG radiative transfer code (ascl:1202.009) and TAME (ascl:1503.003). StePar uses a Downhill Simplex minimization algorithm, running it twice for any given star, to compute the stellar atmospheric parameters.

[ascl:1907.017]
ZChecker: Zwicky Transient Facility moving target checker for short object lists

Kelley, Michael S.P.; Bodewits, Dennis; Ye, Qaunzhi; Laher, Russ R.; Masci, Frank J.; Monkewitz, Serge; Riddle, Reed; Rusholme, Ben; Shupe, David L; Soumagnac, Maayane T.

ZChecker finds, measures, and visualizes known comets in the Zwicky Transient Facility time-domain survey. Images of targets are identified using on-line ephemeris generation and survey metadata. The photometry of the targets are measured and the images are processed with temporal filtering to highlight morphological variations in time.

[ascl:1907.016]
astrodendro: Astronomical data dendrogram creator

Astrodendro, written in Python, creates dendrograms for exploring and displaying hierarchical structures in observed or simulated astronomical data. It handles noisy data by allowing specification of the minimum height of a structure and the minimum number of pixels needed for an independent structure. Astrodendro allows interactive viewing of computed dendrograms and can also produce publication-quality plots with the non-interactive plotting interface.

[ascl:1907.015]
TurbuStat: Turbulence statistics in spectral-line data cubes

Koch, Eric W.; Rosolowsky, Erik W.; Boyden, Ryan D.; Burkhart, Blakesley; Ginsburg, Adam; Loeppky, Jason L.; Offner, Stella S. R.

TurbuStat implements a variety of turbulence-based statistics described in the astronomical literature and defines distance metrics for each statistic to quantitatively compare spectral-line data cubes, as well as column density, integrated intensity, or other moment maps. The software can simulate observations of fractional Brownian Motion fields, including 2-D images and optically thin H I data cubes. TurbuStat also offers multicore fast-Fourier-transform support and provides a segmented linear model for fitting lines with a break point.

[ascl:1907.014]
sbpy: Small-body planetary astronomy

Mommert, Michael; Kelley, Michael S. P.; de Val-Borro, Miguel; Li, Jian-Yang; Guzman, Giannina; Sipőcz, Brigitta; Ďurech, Josef; Granvik, Mikael; Grundy, Will; Moskovitz, Nick; Penttilä, Antti; Samarasinha, Nalin

sbpy, an Astropy affiliated package, supplements functionality provided by Astropy (ascl:1304.002) with functions and methods that are frequently used for planetary astronomy with a clear focus on asteroids and comets. It offers access tools for various databases for orbital and physical data, spectroscopy analysis tools and models, photometry models for resolved and unresolved observations, ephemerides services, and other tools useful for small-body planetary astronomy.

[ascl:1907.013]
RVSpecFit: Radial velocity and stellar atmospheric parameter fitting

RVSpecFit determines radial velocities and stellar atmospheric parameters from spectra by direct pixel fitting by interpolated stellar templates. The code doesn't require spectrum normalization and can deal with non-flux calibrated spectra. RVSpecFit is able to fit multiple spectra simultaneously.

[ascl:1907.012]
molly: 1D astronomical spectra analyzer

molly analyzes 1D astronomical spectra. Its prime purpose is for handling large numbers of similar spectra (*e.g.,* time series spectroscopy), but it contains many of the standard operations used for normal spectrum analysis as well. It overlaps with the various similar programs such as dipso (ascl:1405.016) and has strengths (particularly for time series spectra) and weaknesses compared to them.

[ascl:1907.011]
beamconv: Cosmic microwave background detector data simulator

beamconv simulates the scanning of the CMB sky while incorporating realistic beams and scan strategies. It uses (spin-)spherical harmonic representations of the (polarized) beam response and sky to generate simulated CMB detector signal timelines. Beams can be arbitrarily shaped. Pointing timelines can be read in or calculated on the fly; optionally, the results can be binned on the sphere.

[ascl:1907.010]
OMNICAL: Redundant calibration code for low frequency radio interferometers

OMNICAL calibrates antennas in the redundant subset of the array. The code consists of two algorithms, a logarithmic method (logcal) and a linearized method (lincal). OMNICAL makes visibilities from physically redundant baselines agree with each other and also explicitly minimizes the variance within redundant visibilities.

[ascl:1907.009]
Plonk: Smoothed particle hydrodynamics data analysis and visualization

Plonk analyzes and visualizes smoothed particle hydrodynamics simulation data. It is built on the scientific Python ecosystem, including NumPy, Matplotlib, Cython, h5py, SymPy, and pandas. Plock's visualization module uses Splash (ascl:1103.004) to produce images using smoothed particle hydrodynamics interpolation. The code is modular and extendible, and can be scripted or used interactively.

[submitted]
Accretion Disk Radial Structure Models

A collection of radial structure models of various accretion disk solutions. Each model implements a common interface that gives the radial dependence of selected geometrical, physical and thermodynamic quantities of the accretion flow.

[ascl:1907.008]
Dewarp: Distortion removal and on-sky orientation solution for LBTI detectors

Dewarp constructs pipelines to remove distortion from a detector and find the orientation with true North. It was originally written for the LBTI LMIRcam detector, but is generalizable to any project with reference sources and/or an astrometric field paired with a machine-readable file of astrometric target locations.

[ascl:1907.007]
SPAM: Hu-Sawicki f(R) gravity imprints search

SPAM searches for imprints of Hu-Sawicki f(R) gravity on the rotation curves of the SPARC (Spitzer Photometry and Accurate Rotation Curves) sample using the MCMC sampler emcee (ascl:1303.002). The code provides attributes for inspecting the MCMC chains and translating names of parameters to indices. The SPAM package also contains plotting scripts.

[ascl:1907.006]
POCS: PANOPTES Observatory Control System

PANOPTES (Panoptic Astronomical Networked Observatories for a Public Transiting Exoplanets Survey) is a citizen science project for low cost, robotic detection of transiting exoplanets. POCS (PANOPTES Observatory Control System) is the main software driver for the PANOPTES telescope system, responsible for high-level control of the unit. POCS defines an Observatory class that automatically controls a commercially available equatorial mount, including image analysis and corresponding mount adjustment to obtain a percent-level photometric precision.

[ascl:1907.005]
SARA-PPD: Preconditioned primal-dual algorithm for radio-interferometric imaging

SARA-PPD is a proof of concept MATLAB implementation of an acceleration strategy for a recently proposed primal-dual distributed algorithm. The algorithm optimizes resolution by accounting for the correct noise statistics, leverages natural weighting in the definition of the minimization problem for image reconstruction, and optimizes sensitivity by enabling accelerated convergence through a preconditioning strategy incorporating sampling density information. This algorithm offers efficient processing of large-scale data sets that will be acquired by next generation radio-interferometers such as the Square Kilometer Array.

[ascl:1907.004]
pyGTC: Parameter covariance plots

pyGTC creates giant triangle confusogram (GTC) plots. Triangle plots display the results of a Monte-Carlo Markov Chain (MCMC) sampling or similar analysis. The recovered parameter constraints are displayed on a grid in which the diagonal shows the one-dimensional posteriors (and, optionally, priors) and the lower-left triangle shows the pairwise projections. Such plots are useful for seeing the parameter covariances along with the priors when fitting a model to data.

[ascl:1907.003]
pyuvdata: Pythonic interface to interferometric data sets

pyuvdata defines a pythonic interface to interferometric data sets; it supports the development of and interchange of data between calibration and foreground subtraction pipelines. It can read and write MIRIAD (ascl:1106.007), uvfits, and uvh5 files and reads CASA (ascl:1107.013) measurement sets and FHD (Fast Holographic Deconvolution) visibility save files. Particular focus has been paid to supporting drift and phased array modes.

[ascl:1907.002]
healvis: Radio interferometric visibility simulator based on HEALpix maps

Healvis simulates radio interferometric visibility off of HEALPix shells. It generates a flat-spectrum and a GSM model and computes visibilities, and can simulates visibilities given an Observation Parameter YAML file. Healvis can perform partial frequency simulations in serial to minimize instantaneous memory loads.

[ascl:1907.001]
schwimmbad: Parallel processing pools interface

schwimmbad provides a uniform interface to parallel processing pools and enables switching easily between local development (e.g., serial processing or with multiprocessing) and deployment on a cluster or supercomputer (via, e.g., MPI or JobLib). The utilities provided by schwimmbad require that tasks or data be “chunked” and that code can be “mapped” onto the chunked tasks.

[ascl:1906.022]
pyLIMA: Microlensing modeling package

pyLIMA (python Lightcurve Identification and Microlensing Analysis) fits microlensing lightcurves and derives the physical quantities of lens systems. The package provides microlensing modeling, and the magnification estimation for high cadence lightcurves has been optimized. pyLIMA is designed to make microlensing modeling and event simulation widely available to the community.

[ascl:1906.021]
centerRadon: Center determination code in stellar images

centerRadon finds the center of stars based on Radon Transform to sub-pixel precision. For a coronagraphic image of a star, it starts from a given location, then for each sub-pixel position, it interpolates the image and sums the pixels along different angles, creating a cost function. The center of the star is expected to correspond with where the cost function maximizes. The default values are set for the STIS coronagraphic images of the Hubble Space Telescope by summing over the diagonals (i.e., 45° and 135°), but it can be generally applied to other high-contrast imaging instruments with or without Adaptive Optics systems such as HST-NICMOS, P1640, or GPI.

[ascl:1906.020]
LIZARD: Particle initial conditions for cosmological simulations

LIZARD (Lagrangian Initialization of Zeldovich Amplitudes for Resimulations of Displacements) creates particle initial conditions for cosmological simulations using the Zel'dovich approximation for the matter and velocity power spectrum.

[ascl:1906.019]
PlasmaPy: Core Python package for plasma physics

PlasmaPy Community; Murphy, Nicholas A.; Stańczak, Dominik; Kozlowski, Pawel M.; Langendorf, Samuel J.; Leonard, Andrew J.; Beckers, Jasper P.; Haggerty, Colby C.; Mumford, Stuart J.; Malhotra, Ritiek; Bessi, Ludovico; Carroll, Sean; Choubey, Apoorv; Díaz Pérez, Roberto; Einhorn, Leah; Fan, Thomas; Goudeau, Graham; Guidoni, Silvina; Hillairet, Julien; How, Poh Zi; Huang, Yi-Min; Humphrey, Nabil; Isupova, Maria; Kulshrestha, Siddharth; Kuszaj, Piotr; Munn, Joshua; Parashar, Tulasi; Patel, Neil; Raj, Raajit; Sherpa, Dawa Nurbu; Stansby, David; Tavant, Antoine; Xu, Sixue

PlasmaPy provides core functionality and a common framework for data visualization and analysis for plasma physics. It has modules for basic plasma physics calculations, running desktop-scale simulations to test preliminary ideas such as one-dimensional MHD/PIC or test particles, or comparing data from two different sources, such as simulations and spacecraft.

[ascl:1906.018]
MEGAlib: Medium Energy Gamma-ray Astronomy library

The Medium Energy Gamma-ray Astronomy library (MEGAlib) simulates, calibrates, and analyzes data of hard X-ray and gamma-ray detectors, with a specialization on Compton telescopes. The library comprises all necessary data analysis steps for these telescopes, from simulation/measurements via calibration, event reconstruction to image reconstruction.

MEGAlib contains a geometry and detector description tool for the detailed modeling of different detector types and characteristics, and provides an easy to use simulation program based on Geant4 (ascl:1010.079). For different Compton telescope detector types (electron tracking, multiple Compton or time of flight based), specialized Compton event reconstruction algorithms are implemented in different approaches (Chi-square and Bayesian). The high level data analysis tools calculate response matrices, perform image deconvolution (specialized in list-mode-likelihood-based Compton image reconstruction), determine detector resolutions and sensitivities, retrieve spectra, and determine polarization modulations.

[ascl:1906.017]
mcfit: Multiplicatively Convolutional Fast Integral Transforms

mcfit computes integral transforms, inverse transforms without analytic inversion, and integral kernels as derivatives. It can also transform input array along any axis, output the matrix form, an is easily extensible for other kernels.

[ascl:1906.016]
PandExo: Instrument simulations for exoplanet observation planning

Batalha, Natasha E.; Mandell, Avi; Pontoppidan, Klaus; Stevenson, Kevin B.; Lewis, Nikole K.; Kalirai, Jason; Earl, Nick; Greene, Thomas; Albert, Loïc; Nielsen, Louise D.

PandExo generates instrument simulations of JWST’s NIRSpec, NIRCam, NIRISS and NIRCam and HST WFC3 for planning exoplanet observations. It uses throughput calculations from STScI’s Exposure Time Calculator, Pandeia, and offers both an online tool and a python package.

[ascl:1906.015]
OIT: Nonconvex optimization approach to optical-interferometric imaging

In the context of optical interferometry, only undersampled power spectrum and bispectrum data are accessible, creating an ill-posed inverse problem for image recovery. Recently, a tri-linear model was proposed for monochromatic imaging, leading to an alternated minimization problem; in that work, only a positivity constraint was considered, and the problem was solved by an approximated Gauss–Seidel method.

The Optical-Interferometry-Trilinear code improves the approach on three fundamental aspects. First, the estimated image is defined as a solution of a regularized minimization problem, promoting sparsity in a fixed dictionary using either an l1 or a (re)weighted-l1 regularization term. Second, the resultant non-convex minimization problem is solved using a block-coordinate forward–backward algorithm. This algorithm is able to deal both with smooth and non-smooth functions, and benefits from convergence guarantees even in a non-convex context. Finally, the model and algorithm are generalized to the hyperspectral case, promoting a joint sparsity prior through an l2,1 regularization term.

[ascl:1906.014]
GPUVMEM: Maximum Entropy Method (MEM) GPU algorithm for radio astronomical image synthesis

Cárcamo, Miguel; Muñoz, Nicolás; Rannou, Fernando; Román, Pablo; Casassus, Simón; Osses, Axel; Moral, Victor

The maximum entropy method (MEM) is a well known deconvolution technique in radio-interferometry. This method solves a non-linear optimization problem with an entropy regularization term. Other heuristics such as CLEAN are faster but highly user dependent. Nevertheless, MEM has the following advantages: it is unsupervised, it has a statistical basis, it has a better resolution and better image quality under certain conditions. GPUVMEM presents a high performance GPU version of non-gridding MEM.

[ascl:1906.013]
MORPHEUS: A 3D Eulerian Godunov MPI-OpenMP hydrodynamics code with multiple grid geometries

MORPHEUS (Manchester Omni-geometRical Program for Hydrodynamical EUlerian Simulations) is a 3D hydrodynamical code used to simulate astrophysical fluid flows. It has three different grid geometries (cartesian, spherical, and cylindrical) and uses a second-order Godunov method to solve the equations of hydrodynamics. Physical modules also include radiative cooling and gravity, and a hybrid MPI-OpenMP parallelization allows computations to be run on large-scale architectures. MORPHEUS is written in Fortran90 and does not require any libraries (apart from MPI) to run.

[ascl:1906.012]
Morpheus: Library to generate morphological semantic segmentation maps of astronomical images

Morpheus generates pixel level morphological classifications of astronomical sources by leveraging advances in deep learning to perform source detection, source segmentation, and morphological classification pixel-by-pixel via a semantic segmentation algorithm adopted from the field of computer vision. By utilizing morphological information about the flux of real astronomical sources during object detection, Morpheus shows resiliency to false positive identifications of sources.

[ascl:1906.011]
Lizard: An extensible Cyclomatic Complexity Analyzer

Lizard is an extensible Cyclomatic Complexity Analyzer for imperative programming languages including C/C++/C#, Python, Java, and Javascript. It counts the nloc (lines of code without comments) and CCN (cyclomatic complexity number), and takes a token count of functions and a parameter count of functions. It also does copy-paste detection (code clone detection/code duplicate detection) and many other forms of static code analysis. Lizard is often used in software-related research and calculates how complex the code looks rather than how complex the code really is; thought it's often very hard to get all the included folders and files right when they are complicated, that accuracy is not needed to determine cyclomatic complexity, which can be useful for measuring the maintainability of a software package.

[ascl:1906.010]
PyA: Python astronomy-related packages

Czesla, Stefan; Schröter, Sebastian; Schneider, Christian P.; Huber, Klaus F.; Pfeifer, Fabian; Andreasen, Daniel T.; Zechmeister, Mathias

The PyA (PyAstronomy) suite of astronomy-related packages includes a convenient fitting package that provides support for minimization and MCMC sampling, a set of astrophysical models (*e.g.*, transit light-curve modeling), and algorithms for timing analysis such as the Lomb-Scargle and the Generalized Lomb-Scargle periodograms.

[ascl:1906.009]
PyMORESANE: Python MOdel REconstruction by Synthesis-ANalysis Estimators

PyMORESANE is a Python and pyCUDA-accelerated implementation of the MORESANE deconvolution algorithm, a sparse deconvolution algorithm for radio interferometric imaging. It can restore diffuse astronomical sources which are faint in brightness, complex in morphology and possibly buried in the dirty beam’s side lobes of bright radio sources in the field.

[ascl:1906.008]
T-RECS: Tiered Radio Extragalactic Continuum Simulation

Bonaldi, Anna; Bonato, Matteo; Galluzzi, Vincenzo; Harrison, Ian; Massardi, Marcella; Kay, Scott; De Zotti, Gianfranco; Brown, Michael L.

T-RECS produces radio sources catalogs with user-defined frequencies, area and depth. It models two main populations of radio galaxies, Active Galactic Nuclei (AGNs) and Star-Forming Galaxies (SFGs), and corresponding sub-populations. T-RECS is not computationally demanding and can be run multiple times, using the same catalog inputs, to project the simulated sky onto different fields.

[ascl:1906.007]
limb-darkening: Limb-darkening coefficients generator

Limb-darkening generates limb-darkening coefficients from ATLAS and PHOENIX model atmospheres using arbitrary response functions. The code uses PyFITS (ascl:1207.009) and has several other dependencies, and produces a folder of results with descriptions of the columns contained in each file.

[ascl:1906.006]
turboSETI: Python-based SETI search algorithm

TurboSETI analyzes filterbank data (frequency vs. time) for narrow band drifting signals; its main purpose is to search for signals of extraterrestrial origin. TurboSETI can search the data for hundreds of drift rates (in Hz/sec) and handles either .fil or .h5 file formats. It has several dependencies, including Blimpy (ascl:1906.002) and Astropy (ascl:1304.002).

[ascl:1906.005]
Kalman: Forecasts and interpolations for ALMA calibrator variability

Kalman models an inhomogeneous time series of measurements at different frequencies as noisy sampling from a finite mixture of Gaussian Ornstein-Uhlenbeck processes to try to reproduce the variability of the fluxes and of the spectral indices of the quasars used as calibrators in the Atacama Large Millimeter/Sub-millimeter Array (ALMA), assuming sensible parameters are provided to the model (obtained, for example, from maximum likelihood estimation). One routine in the Kalman Perl module calculates best forecast estimations based on a state space representation of the stochastic model using Kalman recursions, and another routine calculates the smoothed estimation (or interpolations) of the measurements and of the state space also using Kalman recursions. The code does not include optimization routines to calculate best fit parameters for the stochastic processes.

[ascl:1906.004]
The Exo-Striker: Transit and radial velocity interactive fitting tool for orbital analysis and N-body simulations

The Exo-Striker analyzes exoplanet orbitals, performs N-body simulations, and models the RV stellar reflex motion caused by dynamically interacting planets in multi-planetary systems. It offers a broad range of tools for detailed analysis of transit and Doppler data, including power spectrum analysis for Doppler and transit data; Keplerian and dynamical modeling of multi-planet systems; MCMC and nested sampling; Gaussian Processes modeling; and a long-term stability check of multi-planet systems. The Exo-Striker can also analyze Mean Motion Resonance (MMR) analysis, create fast fully interactive plots, and export ready-to-use LaTeX tables with best-fit parameters, errors, and statistics. It combines Fortran efficiency and Python flexibility and is cross-platform compatible (MAC OS, Linux, Windows). The tool relies on a number of open-source packages, including RVmod engine, emcee (ascl:1303.002), batman (ascl:1510.002), celerite (ascl:1709.008), and dynesty (ascl:1809.013).

[ascl:1906.003]
FREDDA: A fast, real-time engine for de-dispersing amplitudes

FREDDA detects Fast Radio Bursts (FRBs) in power data. It is optimized for use at ASKAP, namely GHz frequencies with 10s of beams, 100s of channels and millisecond integration times. The code is written in CUDA for NVIDIA Graphics Processing Units.

[ascl:1906.002]
Blimpy: Breakthrough Listen I/O Methods for Python

Blimpy (Breakthrough Listen I/O Methods for Python) provides utilities for viewing and interacting with the data formats used within the Breakthrough Listen program, including Sigproc filterbank (.fil) and HDF5 (.h5) files that contain dynamic spectra (aka 'waterfalls'), and guppi raw (.raw) files that contain voltage-level data. Blimpy can also extract, calibrate, and visualize data and a suite of command-line utilities are also available.

[ascl:1906.001]
Astroalign: Asterism-matching alignment of astronomical images

Astroalign tries to register (align) two stellar astronomical images, especially when there is no WCS information available. It does so by finding similar 3-point asterisms (triangles) in both images and deducing the affine transformation between them. Generic registration routines try to match feature points, using corner detection routines to make the point correspondence. These generally fail for stellar astronomical images since stars have very little stable structure so are, in general, indistinguishable from each other. Asterism matching is more robust and closer to the human way of matching stellar images. Astroalign can match images of very different field of view, point-spread function, seeing and atmospheric conditions. It may require special care or may not work on images of extended objects with few point-like sources or in crowded fields.

[submitted]
Sacc: Save All Correlations and Covariances

Zuntz, J.; Slosar, A.; Alonso, D.; Becker, M.; Broussard, A.; McClintock, T.; Nicola, A.; Miyatake, H.; Sanchez, J.; Neveu, J.

SACC (Save All Correlations and Covariances) is a format and reference library for general storage

of summary statistic measurements for the Dark Energy Science Collaboration (DESC) within and from the Large Synoptic Survey Telescope (LSST) project's Dark Energy Science Collaboration.

[submitted]
HaloAnalysis

HaloAnalysis reads and analyzes halo/galaxy catalogs, generated from Rockstar (ascl:1210.008) or AHF (ascl:1102.009), and merger trees generated from Consistent Trees (ascl:1210.011). Written in Python 3, it offers the following functionality: reads halo/galaxy/tree catalogs from multiple file formats; assigns baryonic particles and properties to dark-matter halos; combines and re-generates halo/galaxy/tree files in hdf5 format; analyzes properties of halos/galaxies; selects halos to generate zoom-in initial conditions. Includes a Jupyter notebook tutorial.

[submitted]
GizmoAnalysis: read and analyze Gizmo simulations

GizmoAnalysis reads and analyzes N-body simulations run with the Gizmo code (ascl:1410.003). Written in Python 3, we developed it primarily to analyze FIRE simulations, though it is useable with any Gizmo snapshot files. It offers the following functionality: reads snapshot files and converts particle data to physical units; provides a flexible dictionary class to store particle data and compute derived quantities on the fly; plots images and properties of particles; generates region files for input to MUSIC (ascl:1311.011) to generate cosmological zoom-in initial conditions; computes rates of supernovae and stellar winds, including their nucleosynthetic yields, as used in FIRE simulations. Includes a Jupyter notebook tutorial.

[ascl:1905.027]
PyPDR: Python Photo Dissociation Regions

PyPDR calculates the chemistry, thermal balance and molecular excitation of a slab of gas under FUV irradiation in a self-consistent way. The effect of FUV irradiation on the chemistry is that molecules get photodissociated and the gas is heated up to several 1000 K, mostly by the photoelectric effect on small dust grains or UV pumping of H2 followed by collision de-excitation. The gas is cooled by molecular and atomic lines, thus indirectly the chemical composition also affects the thermal structure through the abundance of molecules and atoms. To find a self-consistent solution between heating and cooling, the code iteratively calculates the chemistry, thermal-balance and molecular/atomic excitation.

[ascl:1905.026]
SEDPY: Modules for storing and operating on astronomical source spectral energy distribution

SEDPY performs a variety of tasks for astronomical spectral energy distributions. It can generate synthetic photometry through any filter, provides detailed modeling of extinction curves, and offers basic aperture photometry algorithms. SEDPY can also store and interpolate model SEDs, convolve absolute or apparent fluxes, and calculate rest-frame magnitudes.

[ascl:1905.025]
Prospector: Stellar population inference from spectra and SEDs

Prospector conducts principled inference of stellar population properties from photometric and/or spectroscopic data. The code combine photometric and spectroscopic data rigorously using a flexible spectroscopic calibration model and infer high-dimensional stellar population properties using parameteric SFHs (with ensemble MCMC sampling). Prospector also constrains the linear combination of stellar population components that are present in a galaxy (e.g. non-parametric SFHs) using spectra and/or photometry, and fits individual stellar spectra using large interpolated grids.

[ascl:1905.024]
SICON: Stokes Inversion based on COnvolutional Neural networks

SICON (Stokes Inversion based on COnvolutional Neural networks) provides a three-dimensional cube of thermodynamical and magnetic properties from the interpretation of two-dimensional maps of Stokes profiles by use of a convolutional neural network. In addition to being much faster than parallelized inversion codes, SICON, when trained on synthetic Stokes profiles from two numerical simulations of different structures of the solar atmosphere, also provided a three-dimensional view of the physical properties of the region of interest in geometrical height, and pressure and Wilson depression properties that are decontaminated from the blurring effect of instrumental point spread functions.

[ascl:1905.023]
CASI-2D: Convolutional Approach to Shell Identification - 2D

CASI-2D (Convolutional Approach to Shell Identification) identifies stellar feedback signatures using data from magneto-hydrodynamic simulations of turbulent molecular clouds with embedded stellar sources and deep learning techniques. Specifically, a deep neural network is applied to dense regression and segmentation on simulated density and synthetic 12 CO observations to identify shells, sometimes referred to as "bubbles," and other structures of interest in molecular cloud data.

[ascl:1905.022]
ClusterPyXT: Galaxy cluster pipeline for X-ray temperature maps

ClusterPyXT (Cluster Pypeline for X-ray Temperature maps) creates X-ray temperature maps, pressure maps, surface brightness maps, and density maps from X-ray observations of galaxy clusters to show turbulence, shock fronts, nonthermal phenomena, and the overall dynamics of cluster mergers. It requires CIAO (ascl:1311.006) and CALDB. The code analyzes archival data and provides capability for integrating additional observations into the analysis. The ClusterPyXT code is general enough to analyze data from other sources, such as galaxies, active galactic nuclei, and supernovae, though minor modifications may be necessary.

[ascl:1905.021]
ODEPACK: Ordinary differential equation solver library

ODEPACK solves for the initial value problem for ordinary differential equation systems. It consists of nine solvers, a basic solver called LSODE and eight variants of it: LSODES, LSODA, LSODAR, LSODPK, LSODKR, LSODI, LSOIBT, and LSODIS. The collection is suitable for both stiff and nonstiff systems. It includes solvers for systems given in explicit form, dy/dt = f(t,y), and also solvers for systems given in linearly implicit form, A(t,y) dy/dt = g(t,y). The ODEPACK solvers are written in standard Fortran and there are separate double and single precision versions. Each solver consists of a main driver subroutine having the same name as the solver and some number of subordinate routines. For each solver, there is also a demonstration program, which solves one or two simple problems in a somewhat self-checking manner.

[ascl:1905.020]
NAPLES: Numerical Analysis of PLanetary EncounterS

NAPLES (Numerical Analysis of PLanetary EncounterS) performs batch propagations of close encounters in the three-body problem and computes the numerical error with respect to reference trajectories computed in quadruple precision. It uses the LSODAR integrator from ODEPACK (ascl:1905.021) and the equations of motion correspond to several regularized formulations.

[ascl:1905.019]
PICASO: Planetary Intensity Code for Atmospheric Scattering Observations

PICASO (Planetary Intensity Code for Atmospheric Scattering Observations), written in Python, computes the reflected light of exoplanets at any phase geometry using direct and diffuse scattering phase functions and Raman scattering spectral features.

[ascl:1905.018]
THALASSA: Orbit propagator for near-Earth and cislunar space

THALASSA (Tool for High-Accuracy, Long-term Analyses for SSA) propagates orbits for bodies in the Earth-Moon-Sun system. Written in Fortran, it integrates either Newtonian equations in Cartesian coordinates or regularized equations of motion with the LSODAR (Livermore Solver for Ordinary Differential equations with Automatic Root-finding). THALASSA is a command-line tool; the repository also includes some Python3 scripts to perform batch propagations.

[ascl:1905.017]
LensQuEst: CMB Lensing QUadratic Estimator

LensQuEst forecasts the signal-to-noise of CMB lensing estimators (standard, shear-only, magnification-only), generates mock maps, lenses them, and applies various lensing estimators to them. It can manipulate flat sky maps in various ways, including FFT, filtering, power spectrum, generating Gaussian random field, and applying lensing to a map, and evaluate these estimators on flat sky maps.

[ascl:1905.016]
LensCNN: Gravitational lens detector

The LensCNN (Convolutional Neural Network) identifies images containing gravitational lensing systems after being trained and tested on simulated images, recovering most systems that are identifiable by eye.

[ascl:1905.015]
rPICARD: Radboud PIpeline for the Calibration of high Angular Resolution Data

rPICARD (Radboud PIpeline for the Calibration of high Angular Resolution Data) reduces data from different VLBI arrays, including high-frequency and low-sensitivity arrays, and supports continuum, polarization, and phase-referencing observations. Built on the CASA (ascl:1107.013) framework, it uses CASA for CLEAN imaging and self-calibration, and can be run non-interactively after only a few non-default input parameters are set. rPICARD delivers high-quality calibrated data and large bandwidth data can be processed within reasonable computing times.

[ascl:1905.014]
Bandmerge: Merge data from different wavebands

Bandmerge takes in ASCII tables of positions and fluxes of detected astronomical sources in 2-7 different wavebands, and write out a single table of the merged data. The tool was designed to work with source lists generated by the Spitzer Science Center's MOPEX software, although it can be "fooled" into running on other data as well.

[ascl:1905.013]
SPARK: K-band Multi Object Spectrograph data reduction

SPARK (Software Package for Astronomical Reduction with KMOS) reduces data from the K-band Multi Object Spectrograph (KMOS) for the VLT. In many cases, science data can be processed using a single recipe; alternately, all functions this recipe provides can be performed using other recipes provided as tools. Among the functions the recipes provide are sky subtraction, cube reconstruction with the application of flexure corrections, dividing out the telluric spectrum, applying an illumination correction, aligning the cubes, and then combinging them. The result is a set of files which contain the combined datacube and associated noise cube for each of the 24 integral field unit (IFUs). The pipeline includes simple error propagation.

[ascl:1905.012]
Fitsverify: FITS file format-verification tool

Fitsverify rigorously checks whether a FITS (Flexible Image Transport System) data file conforms to the requirements defined in Version 3.0 of the FITS Standard document; it is a standalone version of the ftverify and fverify tasks that are distributed as part of the ftools (ascl:9912.002) software package. The source code must be compiled and linked with the CFITSIO (ascl:1010.001) library. An interactive web is also available that can verify the format of any FITS data file on a local computer or on the Web.

[ascl:1905.011]
Fermitools: Fermi Science Tools

Fermi Science Tools is a suite of tools for the analysis of both the Large-Area Telescope (LAT) and the Gamma-ray Burst Monitor (GBM) data, including point source analysis for generating maps, spectra, and light curves, pulsar timing analysis, and source identification.

[ascl:1905.010]
FastPM: Scaling N-body Particle Mesh solver

FastPM solves the gravity Possion equation with a boosted particle mesh. Arbitrary time steps can be used. The code is intended to study the formation of large scale structure and supports plain PM and Comoving-Lagranian (COLA) solvers. A broadband correction enforces the linear theory model growth factor at large scale. FastPM scales extremely well to hundred thousand MPI ranks, which is possible through the use of the PFFT Fourier Transform library. The size of mesh in FastPM can vary with time, allowing one to use coarse force mesh at high redshift with increase temporal resolution for accurate large scale modes. The code supports a variety of Greens function and differentiation kernels, though for most practical simulations the choice of kernels does not make a difference. A parameter file interpreter is provided to validate and execute the configuration files without running the simulation, allowing creative usages of the configuration files.

[ascl:1905.009]
HAOS-DIPER: HAO Spectral Diagnostic Package For Emitted Radiation

HAOS-DIPER works with and manipulates data for neutral atoms and atomic ions to understand radiation emitted by some space plasmas, notably the solar atmosphere and stellar atmospheres. HAOS-DIPER works with quantum numbers for atomic levels, enabling it to perform tasks otherwise difficult or very tedious, including a variety of data checks, calculations based upon the atomic numbers, and searching and manipulating data based upon these quantum numbers. HAOS-DIPER handles conditions from LTE to coronal-like conditions, in a manner controlled by one system variable !REGIME, and has some capability for estimating data for which no accurate parameters are available and for accounting for the effects of missing atomic levels.

[ascl:1905.008]
Q3C: A PostgreSQL package for spatial queries and cross-matches of large astronomical catalogs

Q3C (Quad Tree Cube) enables fast cone, ellipse and polygonal searches and cross-matches between large astronomical catalogs inside a PostgreSQL database. The package supports searches even if objects have proper motions.

[ascl:1905.007]
Astrocut: Tools for creating cutouts of TESS images

The Transiting Exoplanet Survey Satellite (TESS) produces Full Frame Images (FFIs) at a half hour cadence and keeps the same pointing for ~27 days at a time. Astrocut performs the same cutout across all FFIs that share a common pointing to create a time series of images on a small portion of the sky.

The Astrocut package has two parts: the CubeFactory and the CutoutFactory. The CubeFactory class creates a large image cube from a list of FFI files, which allows the cutout operation to be performed efficiently. The CutoutFactory class performs the actual cutout and builds a target pixel file (TPF) that is compatible with TESS pipeline TPFs. Because this software operates on TESS mission-produced FFIs, the resulting TPFs are not background-subtracted. In addition to the Astrocut software itself, the Mikulski Archive for Space Telescopes (MAST) provides a cutout service, TESScut, which runs Astrocut on MAST servers, and allows users to simply request cutouts through a web form or direct HTTP API query.

[submitted]
MiraPy: Python package for Deep Learning in Astronomy

MiraPy is a Python package for problem-solving in astronomy using Deep Learning for astrophysicist, researchers and students. Current applications of MiraPy are X-Ray Binary classification, ATLAS variable star feature classification, OGLE variable star light-curve classification, HTRU1 dataset classification and Astronomical image reconstruction using encoder-decoder network. It also contains modules for loading various datasets, curve-fitting, visualization and other utilities. It is built using Keras for developing ML models to run on CPU and GPU seamlessly.

[ascl:1905.006]
beamModelTester: Model evaluation for fixed antenna phased array radio telescopes

beamModelTester enables evaluation of models of the variation in sensitivity and apparent polarization of fixed antenna phased array radio telescopes. The sensitivity of such instruments varies with respect to the orientation of the source to the antenna, resulting in variation in sensitivity over altitude and azimuth that is not consistent with respect to frequency due to other geometric effects. In addition, the different relative orientation of orthogonal pairs of linear antennae produces a difference in sensitivity between the antennae, leading to an artificial apparent polarization. Comparing the model with observations made using the given telescope makes it possible evaluate the model's performance; the results of this evaluation can provide a figure of merit for the model and guide improvements to it. This system also enables plotting of results from a single station observation on a variety of parameters.

[ascl:1905.005]
MMIRS-DRP: MMIRS Data Reduction Pipeline

The MMIRS data reduction pipeline provides complete and flexible data reduction for long-slit and multi-slit spectroscopic observations collected using the MMT and Magellan Infrared Spectrograph (MMIRS). Written in IDL, it offers sky subtraction, correction for telluric absorpition, and is fast enough to permit real-time data reduction for quality control.

[ascl:1905.004]
Binospec: Data reduction pipeline for the Binospec imaging spectrograph

Kansky, Jan; Chilingarian, Igor; Fabricant, Daniel; Matthews, Anne; Moran, Sean; Paegert, Martin; Duane Gibson, J.; Porter, Dallan; Roll, John

Binospec reduces data for the Binospec imaging spectrograph. The software is also used for observation planning and instrument control, and is automated to decrease the number of tasks the user has to perform. Binospec uses a database-driven approach for instrument configuration and sequencing of observations to maximize efficiency, and a web-based interface is available for defining observations, monitoring status, and retrieving data products.

[ascl:1905.003]
evolstate: Assign simple evolutionary states to stars

evolstate assigns crude evolutionary states (main-sequence, subgiant, red giant) to stars given an input temperature and radius/surface gravity, based on physically motivated boundaries from solar metallicity interior models.

[ascl:1905.002]
Py4CAtS: PYthon for Computational ATmospheric Spectroscopy

Py4CAtS (PYthon scripts for Computational ATmospheric Spectroscopy) implements the individual steps of an infrared or microwave radiative transfer computation in separate scripts (and corresponding functions) to extract lines of relevant molecules in the spectral range of interest, compute line-by-line cross sections for given pressure(s) and temperature(s), combine cross sections to absorption coefficients and optical depths, and integrate along the line-of-sight to transmission and radiance/intensity. The code is a Python re-implementation of the Fortran code GARLIC (Generic Atmospheric Radiation Line-by-line Code) and uses the Numeric/Scientific Python modules for computationally-intensive highly optimized array-processing. Py4CAtS can be used in the console/terminal, inside the (I)Python interpreter, and in Jupyter notebooks.

[ascl:1905.001]
Grizli: Grism redshift and line analysis software

Grizli produces quantitative and comprehensive modeling and fitting of slitless spectroscopic observations, which typically involve overlapping spectra of hundreds or thousands of objects in exposures taken with one or more separate grisms and at multiple dispersion position angles. This type of analysis provides complete and uniform characterization of the spectral properties (e.g., continuum shape, redshifts, line fluxes) of all objects in a given exposure taken in the slitless spectroscopic mode.

[ascl:1904.030]
nudec_BSM: Neutrino Decoupling Beyond the Standard Model

nudec_BSM uses a simplified approach to solve for the neutrino decoupling, allowing one to capture the time dependence of the process while accounting for all possible interactions that can alter it.

[ascl:1904.029]
JVarStar: Variable Star Analysis Library

JVarStar (Java Variable Star Analysis) performs pattern classification by analyzing variable star data. This all-in-one library package includes machine learning techniques, fundamental mathematical methods, and digital signal processing functions that can be externally referenced (i.e., from Python), or can be used for further Java development. This library has dependencies on several open source packages that, along with the developed functionality, provides a developer with an easily accessible library from which to construct stable variable star analysis and classification code.

[ascl:1904.028]
covdisc: Disconnected covariance of 2-point functions in large-scale structure of the Universe

covdisc computes the disconnected part of the covariance matrix of 2-point functions in large-scale structure studies, accounting for the survey window effect. This method works for both power spectrum and correlation function, and applies to the covariances for various probes including the multi- poles and the wedges of 3D clustering, the angular and the projected statistics of clustering and lensing, as well as their cross covariances.

[ascl:1904.027]
nbodykit: Massively parallel, large-scale structure toolkit

nbodykit provides algorithms for analyzing cosmological datasets from N-body simulations and large-scale structure surveys, and takes advantage of the abundance and availability of large-scale computing resources. The package provides a unified treatment of simulation and observational datasets by insulating algorithms from data containers, and reduces wall-clock time by scaling to thousands of cores. All algorithms are parallel and run with Message Passing Interface (MPI); the code is designed to be deployed on large super-computing facilities. nbodykit offers an interactive user interface that performs as well in a Jupyter notebook as on super-computing machines.

[ascl:1904.026]
pyRSD: Accurate predictions for the clustering of galaxies in redshift-space in Python

pyRSD computes the theoretical predictions of the redshift-space power spectrum of galaxies. It also includes functionality for fitting data measurements and finding the optimal model parameters, using both MCMC and nonlinear optimization techniques.

[ascl:1904.025]
Properimage: Image coaddition and subtraction

Properimage processes astronomical image; it is specially written for coaddition and image subtraction. It performs the statistical proper-coadd of several images using a spatially variant PSF estimation, and also difference image analysis by several strategies developed by others. Most of the code is based on a class called SingleImage, which provides methods and properties for image processing such as PSF determination.

[ascl:1904.024]
OoT: Out-of-Transit Light Curve Generator

OoT (Out-of-Transit) calculates the light curves and radial velocity signals due to a planet orbiting a star. It explicitly models the effects of tides, orbital motion. relativistic beaming, and reflection of the stars light by the planet. The code can also be used to model secondary eclipses.

[ascl:1904.023]
digest2: NEO binary classifier

Keys, Sonia; Vereš, Peter; Payne, Matthew J.; Holman, Matthew J.; Jedicke, Robert; Williams, Gareth V.; Spahr, Tim; Asher, David J.; Hergenrother, Carl

digest2 classifies Near-Earth Object (NEO) candidates by providing a score, *D _{2}*, that represents a pseudo-probability that a tracklet belongs to a given solar system orbit type. The code accurately and precisely distinguishes NEOs from non-NEOs, thus helping to identify those to be prioritized for follow-up observation. This fast, short-arc orbit classifier for small solar system bodies code is built upon the Pangloss code developed by Robert McNaught and further developed by Carl Hergenrother and Tim Spahr and Robert Jedicke's 223.f code.

[ascl:1904.022]
eleanor: Extracted and systematics-corrected light curves for TESS-observed stars

Feinstein, Adina D.; Montet, Benjamin T.; Foreman-Mackey, Daniel; Bedell, Megan E.; Saunders, Nicholas; Bean, Jacob L.; Christiansen, Jessie L.; Hedges, Christina; Luger, Rodrigo; Scolnic, Daniel; Cardoso, Jose Vinicius de Miranda

eleanor extracts target pixel files from TESS Full Frame Images and produces systematics-corrected light curves for any star observed by the TESS mission. eleanor takes a TIC ID, a Gaia source ID, or (RA, Dec) coordinates of a star observed by TESS and returns, as a single object, a light curve and accompanying target pixel data. The process can be customized, allowing, for example, examination of intermediate data products and changing the aperture used for light curve extraction. eleanor also offers tools that make it easier to work with stars observed in multiple TESS sectors.

[ascl:1904.021]
TP2VIS: Total Power Map to Visibilities

TP2VIS creates visibilities from a single dish cube; the TP visibilities can be combined with the interferometric visibilities in a joint deconvolution using, for example, CASA's tclean() method. TP2VIS requires CASA 5.4 (ascl:1107.013) or above.

[ascl:1904.020]
SARAH: SUSY and non-SUSY model builder and analyzer

SARAH builds and analyzes SUSY and non-SUSY models. It calculates all vertices, mass matrices, tadpoles equations, one-loop corrections for tadpoles and self-energies, and two-loop RGEs for a given model. SARAH writes model files for a variety of other software packages for dark matter studies, includes many SUSY and non-SUSY models, and makes implementing new models efficient and straightforward. Written in Mathematica, SARAH can also use output from Vevacious (ascl:1904.019) to check for the global minimum for a given model and parameter point.

[ascl:1904.019]
Vevacious: Global minima of one-loop effective potentials generator

Vevacious takes a generic expression for a one-loop effective potential energy function and finds all the tree-level extrema, which are then used as the starting points for gradient-based minimization of the one-loop effective potential. The tunneling time from a given input vacuum to the deepest minimum, if different from the input vacuum, can be calculated. The parameter points are given as files in the SLHA format (though is not restricted to supersymmetric models), and new model files can be easily generated automatically by the Mathematica package SARAH (ascl:1904.020).

[ascl:1904.018]
Specstack: A simple spectral stacking tool

Specstack creates stacked spectra using a simple algorithm with sigma-clipping to combine the spectra of galaxies in the rest-frame into a single averaged spectrum. Though written originally for galaxy spectra, it also works for other types of objects. It is written in Python and is started from the command-line.

[ascl:1904.017]
dfitspy: A dfits/fitsort implementation in Python

dfitspy searches and displays metadata contained in FITS files. Written in Python, it displays the results of a metadata search and is able to grep certain values of keywords inside large samples of files in the terminal. dfitspy can be used directly with the command line interface and can also be imported as a python module into other python code or the python interpreter.

[ascl:1904.016]
simuTrans: Gravity-darkened exoplanet transit simulator

simuTrans models transit light curves affected by gravity-darkened stars. The code defines a star on a grid by modeling the brightness of each point as blackbody emission, then sets a series of parameters and uses emcee (ascl:1303.002) to explore the posterior probability distribution for the remaining fitted parameters and determine their best-fit values.

[ascl:1904.015]
SBGAT: Small Bodies Geophysical Analysis Tool

SBGAT (Small Body Geophysical Analysis Tool) generates simulated data originating from small bodies shape models, combined with advanced shape-modification properties. It uses polyhedral shape models from which can be computed mass properties such as volume, center of mass, and inertia, synthetic observations such as lightcurves and radar, and which can be used within dynamical models, such as spherical harmonics and polyhedron gravity modeling. SBGAT can generate spherical harmonics expansions from constant-density polyhedra (and export them to JSON) and evaluate the spherical harmonics expansions. It can also generate YORP coefficients, multi-threaded Polyhedron Gravity Model gravity and potential evaluations, and synthetic light-curve and radar observations for single/primary asteroids.

SBGAT has two distinct packages: a dynamic library SBGAT Core that contains the data structure and algorithm backbone of SBGAT, and SBGAT Gui, which wraps the former inside a VTK, Qt user interface to facilitate user/data interaction. SBGAT Core can be used without the SBGAT Gui wrapper.

[ascl:1904.014]
rate: Reliable Analytic Thermochemical Equilibrium

rate computes thermochemical-equilibrium abundances for a H-C-N-O system with known pressure, temperature, and elemental abundances. The output abundances are H2O, CH4, CO, CO2, NH3, C2H2, C2H4, HCN, and N2, H2, H, and He.

[ascl:1904.013]
EightBitTransit: Calculate light curves from pixel grids

EightBitTransit calculates the light curve of any pixelated image transiting a star and inverts a light curve to recover the "shadow image" that produced it.

[ascl:1904.012]
CausticFrog: 1D Lagrangian Simulation Package

CausticFrog models the reaction of a system of orbiting particles to instantaneous mass loss. It applies to any spherically symmetric potential, and follows the radial evolution of shells of mass. CausticFrog tracks the inner and outer edge of each shell, whose radius evolves as a test particle. The amount of mass in each shell is fixed but multiple shells can overlap leading to higher densities.

[ascl:1904.011]
FortesFit: Flexible spectral energy distribution modelling with a Bayesian backbone

FortesFit efficiently explores and discriminates between various spectral energy distributions (SED) models of astronomical sources. The Python package adds Bayesian inference to a framework that is designed for the easy incorporation and relative assessment of SED models, various fitting engines, and a powerful treatment of priors, especially those that may arise from non-traditional wave-bands such as the X-ray or radio emission, or from spectroscopic measurements. It has been designed with particular emphasis for its scalability to large datasets and surveys.

[ascl:1904.010]
CLEAR: CANDELS Ly-alpha Emission at Reionization processing pipeline and library

Simons, Raymond; Estrada-Carpenter, Vicente; Gosmeyer, Catherine; Papovich, Casey; Momcheva, Ivelina

The CLEAR pipeline and library performs various tasks for the CANDELS Ly-alpha Emission at Reionization (CLEAR) experiment of deep Hubble grism observations of high-z galaxies. It interlaces images, models contamination of overlapping grism spectra, extracts source spectra, stacks the extracted source spectra, and estimates fits for sources redshifts and emission lines.

[ascl:1904.009]
deproject: Deprojection of two-dimensional annular X-ray spectra

Deproject extends Sherpa (ascl:1107.005) to facilitate deprojection of two-dimensional annular X-ray spectra to recover the three-dimensional source properties. For typical thermal models, this includes the radial temperature and density profiles. This basic method is used for X-ray cluster analysis and is the basis for the XSPEC (ascl:9910.005) model project. The deproject module is written in Python and is straightforward to use and understand. The basic physical assumption of deproject is that the extended source emissivity is constant and optically thin within spherical shells whose radii correspond to the annuli used to extract the specta. Given this assumption, one constructs a model for each annular spectrum that is a linear volume-weighted combination of shell models.

[ascl:1904.008]
repack: Repack and compress line-transition data

repack re-packs and compresses line-transition data for radiative-transfer calculations. It identifies the strong lines that dominate the spectrum from the large-majority of weaker lines, returning a binary line-by-line (LBL) file with the strong lines info (wavenumber, Elow, gf, and isotope ID), and an ASCII file with the combined contribution of the weaker lines compressed into a continuum extinction coefficient (in cm-1 amagat-1) as function of wavenumber and temperature.

[ascl:1904.007]
AutoBayes: Automatic design of customized analysis algorithms and programs

AutoBayes automatically generates customized algorithms from compact, declarative specifications in the data analysis domain, taking a statistical model as input and creating documented and optimized C/C++ code. The synthesis process uses Bayesian networks to enable problem decompositions and guide the algorithm derivation. Program schemas encapsulate advanced algorithms and data structures, and a symbolic-algebraic system finds closed-form solutions for problems and emerging subproblems. AutoBayes has been used to analyze planetary nebulae images taken by the Hubble Space Telescope, and can be applied to other scientific data analysis tasks.

[ascl:1904.006]
CDAWeb: Coordinated Data Analysis Web

CDAWeb (Coordinated Data Analysis Workshop Web) enables viewing essentially any data produced in Common Data Format/CDF with the ISTP/IACG Guidelines and supports interactive plotting of variables from multiple instruments on multiple investigations simultaneously on arbitrary, user-defined time-scales. It also supports data retrieval in both CDF or ASCII format. NASA's GSFC Space Physics Data Facility maintains a publicly available database that includes approximately 600 data variables from Geotail, Wind, Interball, Polar, SOHO, ancilliary spacecraft and ground-based investigations. CDAWeb includes high resolution digital data products that support event correlative science. The system combines the client-server user interface technology of the Web with a powerful set of customized routines based in the COTS Interactive Data Language (IDL) package to leverage the data format standards.

[ascl:1904.005]
SMILI: Sparse Modeling Imaging Library for Interferometry

Akiyama, Kazunori; Tazaki, Fumie; Moriyama, Kotaro; Cho, Ilje; Ikeda, Shiro; Sasada, Mahito; Okino, Hiroki; Honma, Mareki

SMILI uses sparse sampling techniques and other regularization methods for interferometric imaging. The python-interfaced library is mainly designed for very long baseline interferometry, and has been under the active development primarily for the Event Horizon Telescope (EHT).

[ascl:1904.004]
ehtim: Imaging, analysis, and simulation software for radio interferometry

Chael, Andrew A.; Bouman, Katherine L.; Johnson, Michael D.; Narayan, Ramesh; Doeleman, Sheperd S.; Wardle, John F. C.; Blackburn, Lindy L.; Akiyama, Kazunori; Wielgus, Maciek; Chan, Chi-kwan; Farah, Joseph R.; Palumbo, Daniel; Pesce, Dominic

ehtim (eht-imaging) simulates and manipulates VLBI data and produces images with regularized maximum likelihood methods. The package contains several primary classes for loading, simulating, and manipulating VLBI data. The main classes are the Image, Array, Obsdata, Imager, and Caltable classes, which provide tools for loading images and data, producing simulated data from realistic u-v tracks, calibrating, inspecting, and plotting data, and producing images from data sets in various polarizations using various data terms and regularizers.

[submitted]
SimCADO - An observations simulator for infrared telescopes and instruments

SimCADO is a python package which allows the user to simulate observations with any NIR/Vis imaging system. The package was originally designed to simulate images for the European extremely large telescope (ELT) and MICADO, however with the proper input it is capable of simulating observations from many different Telescope + Instrument configurations.

The documentation can be found here: https://simcado.readthedocs.io/en/latest/

[ascl:1904.003]
CGS: Collisionless Galactic Simulator

CGS (Collisionless Galactic Simulator) uses Fourier techniques to solve the Possion equation ∇^{2}Φ = 4πGρ, relating the mean potential Φ of a system to the mass density ρ. The angular dependence of the force is treated exactly in terms of the single-particle Legendre polynomials, which preserves accuracy and avoids systematic errors. The density is assigned to a radial grid by means of a cloud-in-cell scheme with a linear kernel, *i.e.*, a particle contributes to the density of the two closest cells with a weight depending linearly on the distance from the center of the cell considered. The same kernel is then used to assign the force from the grid to the particle. The time step is chosen adaptively in such a way that particles are not allowed to cross more than one radial cell during one step. CGS is based on van Albada's code (1982) and is distributed in the NEMO (ascl:1010.051) Stellar Dynamics Toolbox.

[ascl:1904.002]
GALAXY: N-body simulation software for isolated, collisionless stellar systems

GALAXY evolves (almost) isolated, collisionless stellar systems, both disk-like and ellipsoidal. In addition to the N-body code galaxy, which offers eleven different methods to compute the gravitational accelerations, the package also includes sophisticated set-up and analysis software. While not as versatile as tree codes, for certain restricted applications the particle-mesh methods in GALAXY are 50 to 200 times faster than a widely-used tree code. After reading in data providing the initial positions, velocities, and (optionally) masses of the particles, GALAXY compute the gravitational accelerations acting on each particle and integrates forward the velocities and positions of the particles for a short time step, repeating these two steps as desired. Intermediate results can be saved, as can the final moment in a state from which the integration could be resumed. Particles can have individual masses and their motion can be integrated using a range of time steps for greater efficiency; message-passing-interface (MPI) calls are available to enable GALAXY's use on parallel machines with high efficiency.

[ascl:1904.001]
sxrbg: ROSAT X-Ray Background Tool

The ROSAT X-Ray Background Tool (sxrbg) calculates the average X-ray background count rate and statistical uncertainty in each of the six standard bands of the ROSAT All-Sky Survey (RASS) diffuse background maps (R1, R2, R4, R5, R6, R7) for a specified astronomical position and a search region consisting of either a circle with a specified radius or an annulus with specified inner and outer radii centered on the position. The values returned by the tool are in units of 10^-6 counts/second/arcminute^2. sxrbg can also create a count-rate-based spectrum file which can be used with XSpec (ascl:9910.005) to calculate fluxes and offers support for counts statistics (cstat), an alternative method for generating a background spectrum. HEASoft (ascl:1408.004) is a prerequisite for building. The code is in the public domain.

[ascl:1903.017]
HelioPy: Heliospheric and planetary physics library

HelioPy provides a set of tools to download and read in data, and carry out other common data processing tasks for heliospheric and planetary physics. It handles a wide variety of solar and satellite data and builds upon the SpiceyPy package (ascl:1903.016) to provide an accessible interface for performing orbital calculations. It has also implemented a framework to perform transformations between some common coordinate systems.

[ascl:1903.016]
SpiceyPy: Python wrapper for the NAIF C SPICE Toolkit

Annex, Andrew; Carcich, Brian; Murakami, Shin-ya; Kulumani, Shankar; de Val-Borro, Miguel; Stefko, Marcel; Diaz del Rio, Jorge; Seignovert, B.

SpiceyPy is a Python wrapper for the NAIF C SPICE Toolkit (ascl:1903.015). It is compatible with Python 2 and 3, and was written using ctypes.

[ascl:1903.015]
SPICE: Observation Geometry System for Space Science Missions

The SPICE (Spacecraft Planet Instrument C-matrix [“Camera matrix”] Events) toolkit offers a set of building blocks for constructing tools supporting multi-mission, international space exploration programs and research in planetary science, heliophysics, Earth science, and for observations from terrestrial observatories. It computes many kinds of observation geometry parameters, including the ephemerides, orientations, sizes, and shapes of planets, satellites, comets and asteroids. It can also compute the orientation of a spacecraft, its various moving structures, and an instrument's field-of-view location on a planet's surface or atmosphere. It can determine when a specified geometric event occurs, such as when an object is in shadow or is in transit across another object. The SPICE toolkit is available in FORTRAN 77, ANSI C, IDL, and MATLAB.

[ascl:1903.014]
PLATON: PLanetary Atmospheric Transmission for Observer Noobs

PLATON (PLanetary Atmospheric Transmission for Observer Noobs) calculates transmission spectra for exoplanets and retrieves atmospheric characteristics based on observed spectra; it is based on ExoTransmit (ascl:1611.005). PLATON supports the most common atmospheric parameters, such as temperature, metallicity, C/O ratio, cloud-top pressure, and scattering slope. It also has less commonly included features, such as a Mie scattering cloud model and unocculted starspot corrections.

[ascl:1903.013]
NFWdist: Density, distribution function, quantile function and random generation for the 3D NFW profile

Available in R and Python, the simple analytic scheme NFWdist performs highly efficient and exact sampling of the Navarro, Frenk & White (NFW) profile as a true probability distribution function, with the only variable being the concentration.

[ascl:1903.012]
DAVE: Discovery And Vetting of K2 Exoplanets

Mullally, Fergal; Coughlin, Jeffrey; Mullally, Susan; Barclay, Thomas; Barentsen, Geert; Burke, Christopher J.; Colón, Knicole D.; Quintana, Elisa V.

DAVE implements a pipeline to find and vet planets planets using data from NASA's K2 mission. The pipeline contains several modules tailored to particular aspects of the vetting procedures, using photocenter analysis to rule out background eclipsing binaries and flux time-series analysis to rule out odd–even differences, secondary eclipses, low-S/N events, variability other than a transit, and size of the transiting object.

[ascl:1903.011]
AsPy: Aspherical fluctuations on the spherical collapse background

AsPy computes the determinants of aspherical fluctuations on the spherical collapse background. Written in Python, this procedure includes analytic factorization and cancellation of the so-called `IR-divergences'—spurious enhanced contributions that appear in the dipole sector and are associated with large bulk flows.

[ascl:1903.010]
GalIMF: Galaxy-wide Initial Mass Function

GalIMF (Galaxy-wide Initial Mass Function) computes the galaxy-wide initial stellar mass function by integrating over a whole galaxy, parameterized by star formation rate and metallicity. The generated stellar mass distribution depends on the galaxy-wide star formation rate (SFR, which is related to the total mass of a galalxy) and the galaxy-wide metallicity. The code can generate a galaxy-wide IMF (IGIMF) and can also generate all the stellar masses within a galaxy with optimal sampling (OSGIMF). To compute the IGIMF or the OSGIMF, the GalIMF module contains all local IMF properties (e.g. the dependence of the stellar IMF on the metallicity, on the density of the star-cluster forming molecular cloud cores), and this software module can, therefore, be also used to obtain only the stellar IMF with various prescriptions, or to investigate other features of the stellar population such as what is the most massive star that can be formed in a star cluster.

[ascl:1903.009]
PRF: Probabilistic Random Forest

PRF (Probabilistic Random Forest) is a machine learning algorithm for noisy datasets. The PRF is a modification of the long-established Random Forest (RF) algorithm, and takes into account uncertainties in the measurements (i.e., features) as well as in the assigned classes (i.e., labels). To do so, the Probabilistic Random Forest (PRF) algorithm treats the features and labels as probability distribution functions, rather than as deterministic quantities.

[ascl:1903.008]
NIFTy5: Numerical Information Field Theory v5

Arras, Philipp; Baltac, Mihai; Ensslin, Torsten A.; Frank, Philipp; Hutschenreuter, Sebastian; Knollmueller, Jakob; Leike, Reimar; Newrzella, Max-Niklas; Platz, Lukas; Reinecke, Martin; Stadler, Julia

NIFTy (Numerical Information Field Theory) facilitates the construction of Bayesian field reconstruction algorithms for fields being defined over multidimensional domains. A NIFTy algorithm can be developed for 1D field inference and then be used in 2D or 3D, on the sphere, or on product spaces thereof. NIFTy5 is a complete redesign of the previous framework (ascl:1302.013), and requires only the specification of a probabilistic generative model for all involved fields and the data in order to be able to recover the former from the latter. This is achieved via Metric Gaussian Variational Inference, which also provides posterior samples for all unknown quantities jointly.

[ascl:1903.007]
ICSF: Intensity Conserving Spectral Fitting

ICSF (Intensity Conserving Spectral Fitting) "corrects" (x,y) data in which the ordinate represents the average of a quantity over a finite interval in the abscissa. A typical example is spectral data, where the average intensity over a wavelength bin (the measured quantity) is assigned to the center of the bin. If the profile is curved, the average will be different from the discrete value at the bin center location. ICSF, written in IDL and available separately and as part of SolarSoft (ascl:1208.013), corrects the intensity using an iterative procedure and cubic spline. The corrected intensity equals the "true" intensity at bin center, rather than the average over the bin. Unlike other methods that are restricted to a single fitting function, typically a spline, ICSF can be used with any function, such as a cubic spline or a Gaussian, with slight changes to the code.

[ascl:1903.006]
SimSpin: Kinematic analysis of galaxy simulations

The R-package SimSpin measures the kinematics of a galaxy simulation as if it had been observed using an IFU. The functions included in the package can produce a kinematic data cube and measure the "observables" from this data cube, specifically the observable spin parameter λr. This package, once installed, is fully documented and tested.

[ascl:1903.005]
Galmag: Computation of realistic galactic magnetic fields

Galmag computes galactic magnetic fields based on mean field dynamo theory. Written in Python, Galmag allows quick exploration of solutions to the mean field dynamo equation based on galaxy parameters specified by the user, such as the scale height profile and the galaxy rotation curves. The magnetic fields are solenoidal by construction and can be helical.

[ascl:1903.004]
brutifus: Python module to post-process datacubes from integral field spectrographs

brutifus aids in post-processing datacubes from integral field spectrographs. The set of Python routines in the package handle generic tasks, such as the registration of a datacube WCS solution with the Gaia catalogue, the correction of Galactic reddening, or the subtraction of the nebular/stellar continuum on a spaxel-per-spaxel basis, with as little user interactions as possible. brutifus is modular, in that the order in which the post-processing routines are run is entirely customizable.

[ascl:1903.003]
allesfitter: Flexible star and exoplanet inference from photometry and radial velocity

allesfitter provides flexible and robust inference of stars and exoplanets given photometric and radial velocity (RV) data. The software offers a rich selection of orbital and transit models, accommodating multiple exoplanets, multi-star systems, star spots, stellar flares, and various noise models. It features both parameter estimation and model selection. A graphical user interface is used to specify input parameters, and to easily run a nested sampling or Markov Chain Monte Carlo (MCMC) fit, producing publication-ready tables, LaTex code, and plots. allesfitter provides an inference framework that unites the versatile packages ellc (ascl:1603.016), aflare (flare model; Davenport et al. 2014), dynesty (ascl:1809.013), emcee (ascl:1303.002) and celerite (ascl:1709.008).

[ascl:1903.002]
SIXTE: Simulation of X-ray Telescopes

SIXTE simulates X-Ray telescope observation; the software performs instrument performance analyses and produces simulated event files for mission and analysis studies. SIXTE strives to find a compromise between exactness of the simulation and speed. Using calibration files such as the PSF, RMF and ARF makes efficient simulations possible at comparably high speed, even though they include nonlinear effects such as pileup. Setups for some current and future missions, such as XMM-Newton and Athena, are included in the package; others can be added by the user with relatively little effort through specifying the main instrument characteristics in a flexible, human-readable XML-based format. Properties of X-ray sources to be simulated are described in a detector-independent format, i.e., the same input can be used for simulating observations with all available instruments, and the same input can also be used for simulations with the SIMX simulator. The input files are easily generated from standard data such as XSPEC (ascl:9910.005) spectral models or FITS images with tools provided with the SIXTE distribution. The input data scale well from single point sources up to very complicated setups.

[ascl:1902.012]
Specutils: Spectroscopic analysis and reduction

Specutils provides a basic interface for the loading, manipulation, and common forms of analysis of spectroscopic data. Its generic data containers and accompanying modules can be used to build a particular scientific workflow or higher-level analysis tool. It is an AstroPy (ascl:1304.002) affiliated package, and SpecViz (ascl:1902.011), which is built on top of Specutils, provides a visual, interactive interface to its analysis capabilities.

[ascl:1902.011]
SpecViz: 1D Spectral Visualization Tool

SpecViz interactively visualizes and analyzes 1D astronomical spectra. It reads data from FITS and ASCII tables and allows spectra to be easily plotted and examined. It supports instrument-specific data quality handling, flexible spectral units conversions, custom plotting attributes, plot annotations, tiled plots, among other features. SpecViz includes a measurement tool for spectral lines for performing and recording measurements and a model fitting capability for creating simple (e.g., single Gaussian) or multi-component models (e.g., multiple Gaussians for emission and absorption lines in addition to regions of flat continua). SpecViz is built on top of the Specutils (ascl:1902.012) Astropy-affiliated python library, providing a visual, interactive interface to the analysis capabilities in that library.

[ascl:1902.010]
dyPolyChord: Super fast dynamic nested sampling with PolyChord

dyPolyChord implements dynamic nested sampling using the efficient PolyChord (ascl:1502.011) sampler to provide state-of-the-art nested sampling performance. Any likelihoods and priors which work with PolyChord can be used (Python, C++ or Fortran), and the output files produced are in the PolyChord format.

[ascl:1902.009]
ExPRES: Exoplanetary and Planetary Radio Emissions Simulator

ExPRES (Exoplanetary and Planetary Radio Emission Simulator) reproduces the occurrence of CMI-generated radio emissions from planetary magnetospheres, exoplanets or star-planet interacting systems in time-frequency plane, with special attention given to computation of the radio emission beaming at and near its source. Physical information drawn from such radio observations may include the location and dynamics of the radio sources, the type of current system leading to electron acceleration and their energy and, for exoplanetary systems, the magnetic field strength, the orbital period of the emitting body and the rotation period, tilt and offset of the planetary magnetic field. Most of these parameters can be remotely measured only via radio observations. ExPRES code provides the proper framework of analysis and interpretation for past (Cassini, Voyager, Galileo), current (Juno, ground-based radio telescopes) and future (BepiColombo, Juice) observations of planetary radio emissions, as well as for future detection of radio emissions from exoplanetary systems.

[ascl:1902.008]
Radynversion: Solar atmospheric properties during a solar flare

Radynversion infers solar atmospheric properties during a solar flare. The code is based on an Invertible Neural Network (INN) that is trained to learn an approximate bijective mapping between the atmospheric properties of electron density, temperature, and bulk velocity (all as a function of altitude), and the observed Hα and Ca II λ8542 line profiles. As information is lost in the forward process of radiation transfer, this information is injected back into the model during the inverse process by means of a latent space; the training allows this latent space to be filled using an n-dimensional unit Gaussian distribution, where n is the dimensionality of the latent space. The code is based on a model trained by simulations made by RADYN, a 1D non-equilibrium radiation hydrodynamic model with good optically thick radiation treatment that does not consider magnetic effects.

[submitted]
BELLAMY: A cross-matching package for the cynical astronomer

BELLAMY is a cross-matching algorithm designed primarily for radio images, that aims to match all sources in the supplied target catalogue to sources in a reference catalogue by calculating the probability of a match. BELLAMY utilises not only the position of a source on the sky, but also the flux data to calculate this probability, determining the most probable match in the reference catalog to the target source. Additionally, BELLAMY attempts to undo any spatial distortion that may be affecting the target catalogue, by creating a model of the offsets of matched sources which is then applied to unmatched sources. This combines to produce an iterative cross-matching algorithm that provides the user with an obvious measure of how confident they should be with the results of a cross-match.

[ascl:1902.007]
PINT: High-precision pulsar timing analysis package

Luo, Jing; Ransom, Scott; Demorest, Paul; van Haasteren, Rutger; Ray, Paul; Stovall, Kevin; Bachetti, Matteo; Archibald, Anne; Kerr, Matthew; Colen, Jonathan; Jenet, Fredrick

PINT (PINT Is Not Tempo3) analyzes high-precision pulsar timing data, enabling interactive data analysis and providing an extensible and flexible development platform for timing applications. PINT utilizes well-debugged public Python packages and modern software development practices (e.g., the NumPy and Astropy libraries, version control and development with git and GitHub, and various types of testing) for increased development efficiency and enhanced stability. PINT has been developed and implemented completely independently from traditional pulsar timing software such as TEMPO (ascl:1509.002) and Tempo2 (ascl:1210.015) and is a robust tool for cross-checking timing analyses and simulating data.

[ascl:1902.006]
RPFITS: Routines for reading and writing RPFITS files

Norris, Ray; Calabretta, Mark; Wieringa, Mark; Hunt, A.J.; May, H.; Killeen, N.; Sault, R.; Wilson, Warwick; Kesteven, Michael

The RPFITS data file format records synthesis visibility data obtained from the Australia Telescope Compact Array (ATCA) at Narrabri, NSW. It is also used for single-dish spectral line data obtained from Parkes and Mopra, including Parkes multibeam data. RPFITS superficially resembles random group FITS, but differs in important respects, making it incompatible with standard FITS software such as FITSIO (ascl:1010.001) and FTOOLS (ascl:9912.002) and, in particular, it precludes the use of fv (ascl:1205.005). The RPFITS Fortran library contains routines for reading and writing RPFITS files. A header file, RPFITS.h, is provided to facilitate usage by C and C++ applications. Also included is rpfhdr, a utility for viewing RPFITS headers (it also works for standard FITS), and rpfex for extracting selected scans from an RPFITS file.

[ascl:1902.005]
LiveData: Data reduction pipeline

LiveData is a multibeam single-dish data reduction system for bandpass calibration and gridding. It is used for processing Parkes multibeam and Mopra data.

[ascl:1902.004]
GraviDy: Gravitational Dynamics

GraviDy performs N-body 3D visualizations; it is a GPU, direct-summation N-body integrator based on the Hermite scheme and includes relativistic corrections for sources of gravitational radiation. The software is modular, allowing users to readily introduce new physics, and exploits available computational resources. The software can be used in parallel on multiple CPUs and GPUs, with a considerable speed-up benefit. The single-GPU version is between one and two orders of magnitude faster than the single-CPU version.

[ascl:1902.003]
PyMF: Matched filtering techniques for astronomical images

PyMF performs spatial filtering (matched filter, matched multifilter, constrained matched filter and constrained matched mutifilter) image processing that provides optimal reduction of the contamination introduced by sources that can be approximated by templates. These techniques use the flat-sky approximation.

[ascl:1902.002]
LPNN: Limited Post-Newtonian N-body code for collisionless self-gravitating systems

The Limited Post-Newtonian N-body code (LPNN) simulates post-Newtonian interactions between a massive object and many low-mass objects. The interaction between one massive object and low-mass objects is calculated by post-Newtonian approximation, and the interaction between low-mass objects is calculated by Newtonian gravity. This code is based on the sticky9 code, and can be accelerated with the use of GPU in a CUDA (version 4.2 or earlier) environment.

[ascl:1902.001]
SNTD: Supernova Time Delays

Supernova Time Delays (SNTD) simulates and measures time delay of multiply-imaged supernovae, and offers an improved characterization of the uncertainty caused by microlensing. Lensing time delays can be determined by fitting the multiple light curves of these objects; measuring these delays provide precise tests of lens models or constraints on the Hubble constant and other cosmological parameters that are independent of the local distance ladder. Fitting the effects of microlensing without an accurate prior often leads to biases in the time delay measurement and over-fitting to the data; this can be mitigated by using a Gaussian Process Regression (GPR) technique to determine the uncertainty due to microlensing. SNTD can produce accurate simulations for wide-field time domain surveys such as LSST and WFIRST.

[ascl:1901.012]
stellarWakes: Dark matter subhalo searches using stellar kinematic data

stellarWakes uses stellar kinematic data to search for dark matter (DM) subhalos through their gravitational perturbations to the stellar phase-space distribution.

[ascl:1901.011]
Bilby: Bayesian inference library

Ashton, Gregory; Hübner, Moritz; Lasky, Paul D.; Talbot, Colm; Ackley, Kendall; Biscoveanu, Sylvia; Chu, Qi; Divarkala, Atul; Easter, Paul J.; Goncharov, Boris; Hernandez Vivanco, Francisco; Harms, Jan; Lower, Marcus E.; Meadors, Grant D.; Melchor, Denyz; Payne, Ethan; Pitkin, Matthew D.; Powell, Jade,; Sarin, Nikhil; Smith, Rory J. E.; Thrane, Eric

Bilby provides a user-friendly interface to perform parameter estimation. It is primarily designed and built for inference of compact binary coalescence events in interferometric data, such as analysis of compact binary mergers and other types of signal model including supernovae and the remnants of binary neutron star mergers, but it can also be used for more general problems. The software is flexible, allowing the user to change the signal model, implement new likelihood functions, and add new detectors. Bilby can also be used to do population studies using hierarchical Bayesian modelling.

[ascl:1901.010]
eddy: Extracting Disk DYnamics

The Python suite eddy recovers precise rotation profiles of protoplanetary disks from Doppler shifted line emission, providing an easy way to fit first moment maps and the inference of a rotation velocity from an annulus of spectra.

[ascl:1901.009]
bettermoments: Line-of-sight velocity calculation

bettermoments measures precise line-of-sight velocities from Doppler shifted lines to determine small scale deviations indicative of, for example, embedded planets.

[ascl:1901.008]
SEDobs: Observational spectral energy distribution simulation

SEDobs uses state-of-the-art theoretical galaxy SEDs (spectral energy distributions) to create simulated observations of distant galaxies. It used BC03 and M05 theoretical models and allows the user to configure the simulated observation that are needed. For a given simulated galaxy, the user is able to simulate multi-spectral and multi-photometric observations.

[ascl:1901.007]
Photon: Python tool for data plotting

Photon makes simple 1D plots in python. It uses mainly matplotlib and PyQt5 and has been build to be fully customizable, allowing the user to change the fontstyle, fontsize, fontcolors, linewidth of the axes, thickness, and other parameters, and see the changes directly in the plot. Once a customization is created, it can be saved in a configuration file and reloaded for future use, allowing reuse of the customization for other plots. The main tool is a graphical user interface and it is started using a command line interface.

[ascl:1901.006]
ssos: Solar system objects detection pipeline

The ssos pipeline detects and identifies known and unknown Solar System Objects (SSOs) in astronomical images. ssos requires at least 3 images with overlapping field-of-views in the sky taken within a reasonable amount of time (*e.g.*, 2 hours, 1 night). SSOs are detected mainly by judging the apparent motion of all sources in the images. The pipeline serves as a wrapper for the SExtractor (ascl:1010.064) and SCAMP (ascl:1010.063) software suites and allows different source extraction strategies to be chosen. All sources in the images are subject to a highly configurable filter pipeline. ssos is a versatile, light-weight, and easy-to-use software for surveys or PI-observation campaigns lacking a dedicated SSO detection pipeline.

[ascl:1901.005]
Galaxia_wrap: Galaxia wrapper for generating mock stellar surveys

Galaxia_wrap is a python wrap around the popular Galaxia tool (ascl:1101.007) for generating mock stellar surveys, such as a magnitude limited survey, using a built-in Galaxy model or directly from n-body data. It also offers n-body functionality and has been used to infer the age distribution of a specific stellar tracer population.

[ascl:1901.004]
unwise_psf: PSF models for unWISE coadds

The unwise_psf Python module renders point spread function (PSF) models appropriate for use in modeling of unWISE coadd images. unwise_psf translates highly detailed single-exposure WISE PSF models in detector coordinates to the corresponding pixelized PSF models in coadd space, accounting for subtleties including the WISE scan direction and its considerable variation near the ecliptic poles. Applications of the unwise_psf module include performing forced photometry on unWISE coadds, constructing WISE-selected source catalogs based on unWISE coadds and masking unWISE coadd regions contaminated by bright stars.

[ascl:1901.003]
CCL: Core Cosmology Library

Chisari, Nora Elisa; Alonso, David; Krause, Elisabeth; Leonard, C. Daniellle; Bull, Philip; Neveu, Jérémy; Villarreal, Antonio; Singh, Sukhdeep; McClintock, Thomas; Ellison, John; Du, Zilong; Zuntz, Joe; Mead, Alexander; Joudaki, Shahab; Lorenz, Christiane S.; Troester, Tilman; Sanchez, Javier; Lanusse, Francois; Ishak, Mustapha; Hlozek, Renée; Blazek, Jonathan; Campagne, Jean-Eric; Almoubayyed, Husni; Eifler, Tim; Kirby, Matthew; Kirkby, David; Plaszczynski, Stéphane; Slosar, Anze; Vrastil, Michal; Wagoner, Erika L.

The Core Cosmology Library (CCL) computes basic cosmological observables and provides predictions for many cosmological quantities, including distances, angular power spectra, correlation functions, halo bias and the halo mass function through state-of-the-art modeling prescriptions. Fiducial specifications for the expected galaxy distributions for the Large Synoptic Survey Telescope (LSST) are also included, together with the capability of computing redshift distributions for a user-defined photometric redshift model. Predictions for correlation functions of galaxy clustering, galaxy-galaxy lensing and cosmic shear are within a fraction of the expected statistical uncertainty of the observables for the models and in the range of scales of interest to LSST. CCL is written in C and has a python interface.

[ascl:1901.002]
OCFit: Python package for fitting of O-C diagrams

OCFit fits and analyzes O-C diagrams using Genetic Algorithms and Markov chain Monte Carlo methods. The MC method is used to determine a very good estimation of errors of the parameters. Unlike some other fitting routines, OCFit does not need any initial values of fitted parameters. An intuitive graphic user interface is provided for ease of fitting, and nine common models of periodic O-C changes are included.

[ascl:1901.001]
cFE: Core Flight Executive

The Core Flight Executive is a portable, platform-independent embedded system framework that is the basis for flight software for satellite data systems and instruments; cFE can be used on other embedded systems as well. The Core Flight Executive is written in C and depends on the software library Operating System Abstraction Layer (OSAL), which is available at https://sourceforge.net/projects/osal/.

[ascl:1812.018]
OctApps: Octave functions for continuous gravitational-wave data analysis

Wette, Karl; Prix, Reinhard; Keitel, David; Pitkin, Matthew; Dreissigacker, Christoph; Whelan, John T.; Leaci, Paola

The OctApps library provides various functions, written in Octave, for performing searches for the weak signatures of continuous gravitational waves from rapidly-rotating neutron stars amidst the instrumental noise of the LIGO and Virgo detectors.

[ascl:1812.017]
psrqpy: Python module to query the ATNF Pulsar Catalogue

psrqpy directly queries the Australia Telescope National Facility (ATNF) Pulsar Catalogue by downloading and parsing the full catalog database, which is cached and can be reused. The module assists astronomers who want access to the latest pulsar information via a script rather than through the standard web interface.

[ascl:1812.016]
Juliet: Transiting and non-transiting exoplanetary systems modelling tool

Juliet essentially serves as a wrapper of other tools, including Batman (ascl:1510.002), George (ascl:1511.015), Dynesty (ascl:1809.013) and AstroPy (ascl:1304.002), to analyze and model transits, radial-velocities, or both from multiple instruments at the same time. Using nested sampling algorithms, it performs a thorough sampling of the parameter space and a model comparison via Bayesian evidences. Juliet also fits transiting and non-transiting multi-planetary systems, and Gaussian Processes (GPs) which might share hyperparameters between the photometry and radial-velocities simultaneously (e.g., stellar rotation periods).

[ascl:1812.015]
AUTOSPEC: Automated Spectral Extraction Software for integral field unit data cubes

AUTOSPEC provides fast, automated extraction of high quality 1D spectra from astronomical datacubes with minimal user effort. AutoSpec takes an integral field unit (IFU) datacube and a simple parameter file in order to extract a 1D spectra for each object in a supplied catalogue. A custom designed cross-correlation algorithm improves signal to noise as well as isolates sources from neighboring contaminants.

[ascl:1812.014]
GENGA: Gravitational ENcounters with Gpu Acceleration

GENGA (Gravitational ENcounters with Gpu Acceleration) integrates planet and planetesimal dynamics in the late stage of planet formation and stability analyses of planetary systems. It uses mixed variable integration when the motion is a perturbed Kepler orbit and combines this with a direct N-body Bulirsch-Stoer method during close encounters. It supports three simulation modes: 1.) integration of up to 2048 massive bodies; 2.) integration with up to a million test particles; and 3.) parallel integration of a large number of individual planetary systems.

[ascl:1812.013]
Lightkurve: Kepler and TESS time series analysis in Python

Lightkurve Collaboration; Cardoso, José Vinícius de Miranda; Hedges, Christina; Gully-Santiago, Michael; Saunders, Nicholas; Cody, Ann Marie; Barclay, Thomas; Hall, Oliver; Sagear, Sheila; Turtelboom, Emma; Zhang, Johnny; Tzanidakis, Andy; Mighell, Ken; Coughlin, Jeff; Bell, Keaton; Berta-Thompson, Zach; Williams, Peter; Dotson, Jessie; Barentsen, Geert

Lightkurve analyzes astronomical flux time series data, in particular the pixels and light curves obtained by NASA’s Kepler, K2, and TESS exoplanet missions. This community-developed Python package is designed to be user friendly to lower the barrier for students, astronomers, and citizen scientists interested in analyzing data from these missions. Lightkurve provides easy tools to download, inspect, and analyze time series data and its documentation is supported by a large syllabus of tutorials.

[ascl:1812.012]
distlink: Minimum orbital intersection distance (MOID) computation library

distlink computes the minimum orbital intersection distance (MOID), or global minimum of the distance between the points lying on two Keplerian ellipses by finding all stationary points of the distance function, based on solving an algebraic polynomial equation of 16th degree. The program tracks numerical errors and carefully treats nearly degenerate cases, including practical cases with almost circular and almost coplanar orbits. Benchmarks confirm its high numeric reliability and accuracy, and even with its error-controlling overheads, this algorithm is a fast MOID computation method that may be useful in processing large catalogs. Written in C++, the library also includes auxiliary functions.

[ascl:1812.011]
GRAND-HOD: GeneRalized ANd Differentiable Halo Occupation Distribution

GRAND-HOD (GeneRalized ANd Differentiable Halo Occupation Distribution) takes a generalized Halo Occupation Distribution (HOD) prescription as input and outputs the corresponding mock galaxy catalogs in binary files. The code is differentiable and incorporates various generalizations to the standard HOD. It is written for the Abacus simulations, but the main functionalities can be easily adapted for other halo catalogs with the appropriate properties.

[ascl:1812.010]
PynPoint 0.6.0: Pipeline for processing and analysis of high-contrast imaging data

PynPoint processes and analyzes high-contrast imaging data of exoplanets and circumstellar disks. The generic, end-to-end pipeline's modular architecture separates the core functionalities and the pipeline modules. These modules have specific tasks such as background subtraction, frame selection, centering, PSF subtraction with principal component analysis, estimation of detection limits, and photometric and astrometric analysis. All modules store their results in a central database. Management of the available hardware by the backend of the pipeline is in particular an advantage for data sets containing thousands of images, as is common in the mid-infrared wavelength regime. This version of PynPoint is a significant rewrite of the earlier PynPoint package (ascl:1501.001).

[ascl:1812.009]
galclassify: Stellar classifications using a galactic population synthesis model

The stellar classification code galclassify is a stand-alone version of Galaxia (ascl:1101.007). It classifies and generates a synthetic population for each star using input containing observables in a fixed format rather than using a precomputed population over a large field. It is suitable for individual stellar classifications, but slow if you want to classify large samples of stars.

[ascl:1812.008]
easyaccess: SQL command line interpreter for astronomical surveys

easyaccess facilitates access to astronomical catalogs stored in SQL Databases. It is an enhanced command line interpreter and provides a custom interface with custom commands and was specifically designed to access data from the Dark Energy Survey Oracle database, including autocompletion of tables, columns, users and commands, simple ways to upload and download tables using csv, fits and HDF5 formats, iterators, search and description of tables among others. It can easily be extended to other surveys or SQL databases. The package is written in Python and supports customized addition of commands and functionalities.

[ascl:1812.007]
ExoGAN: Exoplanets Generative Adversarial Network

ExoGAN (Exoplanets Generative Adversarial Network) analyzes exoplanetary atmospheres using an unsupervised deep-learning algorithm that recognizes molecular features, atmospheric trace-gas abundances, and planetary parameters. After training, ExoGAN can be applied to a large number of instruments and planetary types and can be used either as a final atmospheric analysis or to provide prior constraints to subsequent retrieval.

[ascl:1812.006]
Fermipy: Fermi-LAT data analysis package

Wood, M.; Caputo, R.; Charles, E.; Di Mauro, M.; Magill, J.; Perkins, J. S.; Fermi-LAT Collaboration

Fermipy facilitates analysis of data from the Large Area Telescope (LAT) with the Fermi Science Tools. It is built on the pyLikelihood interface of the Fermi Science Tools and provides a set of high-level tools for performing common analysis tasks, including data and model preparation with the gt-tools, extracting a spectral energy distribution (SED) of a source, and generating TS and residual maps for a region of interest. Fermipy also finds new source candidates and can localize a source or fit its spatial extension. The package uses a configuration-file driven workflow in which the analysis parameters (data selection, IRFs, and ROI model) are defined in a YAML configuration file. Analysis is executed through a python script that calls the methods of GTAnalysis to perform different analysis operations.

[ascl:1812.005]
SPAMCART: Smoothed PArticle Monte CArlo Radiative Transfer

SPAMCART generates synthetic spectral energy distributions and intensity maps from smoothed particle hydrodynamics simulation snapshots. It follows discrete luminosity packets as they propagate through a density field, and computes the radiative equilibrium temperature of the ambient dust from their trajectories. The sources can be extended and/or embedded, and discrete and/or diffuse. The density is not mapped on to a grid, and therefore the calculation is performed at exactly the same resolution as the hydrodynamics. The code strictly adheres to Kirchhoff's law of radiation. The algorithm is based on the Lucy Monte Carlo radiative transfer method and is fairly simple to implement, as it uses data structures that are already constructed for other purposes in modern particle codes

[ascl:1812.004]
aesop: ARC Echelle Spectroscopic Observation Pipeline

aesop (ARC Echelle Spectroscopic Observation Pipeline) analyzes echelle spectra for observations made by the Astrophysics Research Consortium (ARC) Echelle Spectrograph on the ARC 3.5 m Telescope at Apache Point Observatory. It is a high resolution spectroscopy software toolkit that picks up where the traditional IRAF reduction scripts leave off, and offers blaze function normalization by polynomial fits to observations of early-type stars, a robust least-squares normalization method, and radial velocity measurements (or offset removals) via cross-correlation with model spectra, including barycentric radial velocity calculations. It also concatenates multiple echelle orders into a simple 1D spectrum and provides approximate flux calibration.

[ascl:1812.003]
PFANT: Stellar spectral synthesis code

PFANT computes a synthetic spectrum assuming local thermodynamic equilibrium from a given stellar model atmosphere and lists of atomic and molecular lines; it provides large wavelength coverage and line lists from ultraviolet through the visible and near-infrared. PFANT has been optimized for speed, offers error reporting, and command-line configuration options.

[ascl:1812.002]
GLADIS: GLobal Accretion Disk Instability Simulation

GLADIS (GLobal Accretion Disk Instability Simulation) computes the time-dependent evolution of a black hole accretion disk, in one-dimensional, axisymmetric, vertically integrated scheme. The code solves two partial-differential equations of hydrodynamics for surface density and temperature evolution, *i.e.*, given by viscous diffusion and energy conservation. Accretion disks can be subject to radiation-pressure instability if the stress tensor is proportional to the total (gas plus radiation) pressure. In the gas-pressure dominated case there is no instability. An intermediate case is provided in the code by the square root of the gas and total pressures. GLADIS is parallelized with MPI, and sample .ini and run command files are provided with the code.

[ascl:1812.001]
WISP: Wenger Interferometry Software Package

WISP (Wenger Interferometry Software Package) is a radio interferometry calibration, reduction, imaging, and analysis package. WISP is a collection of Python code implemented through CASA (ascl:1107.013). Its generic and modular framework is designed to handle any continuum or spectral line radio interferometry data.

[submitted]
taktent: A Python framework for agent-based simulations of SETI observations

This Python package allows the user to setup and run an agent-based simulation of a SETI survey. The package allows the creation of a population of observing and transmitting civilisations. Each transmitter and observer conducts their activities according to an input strategy. The success of observers and transmitters can then be recorded, and multiple simulations can be run for Monte Carlo Realisation.

This package is therefore a flexible framework in which to simulate and test different SETI strategies, both as an Observer and as a Transmitter. It is primarily designed with radio SETI in mind, but is sufficiently flexible to simulate all forms of electromagnetic SETI, and potentially neutrino and gravitational wave SETI.

[submitted]
cuvarbase: fast period finding utilities for GPU's (Python)

cuvarbase provides a Python (2.7+) library for performing period finding (Lomb-Scargle, Phase Dispersion Minimization, Conditional Entropy, Box-least squares) on astronomical time-series datasets. Speedups over CPU implementations depend on the algorithm, dataset, and GPU capabilities but are typically ~1-2 orders of magnitude and are especially high for BLS and Lomb-Scargle. Unit tested and available via pip or from source at GitHub.

[ascl:1811.020]
PulsarHunter: Searching for and confirming pulsars

Pulsarhunter searches for and confirms pulsars; it provides a set of time domain optimization tools for processing timeseries data produced by SIGPROC (ascl:1107.016). The software can natively write candidate lists for JReaper (included in the package), removing the need to manually import candidates into JReaper; JReaper also reads the PulsarHunter candidate file format.

[ascl:1811.019]
PENTACLE: Large-scale particle simulations code for planet formation

PENTACLE calculates gravitational interactions between particles within a cut-off radius and a Barnes-Hut tree method for gravity from particles beyond. It uses FDPS (ascl:1604.011) to parallelize a Barnes-Hut tree algorithm for a memory-distributed supercomputer. The software can handle 1-10 million particles in a high-resolution N-body simulation on CPU clusters for collisional dynamics, including physical collisions in a planetesimal disc.

[ascl:1811.018]
gdr2_completeness: GaiaDR2 data retrieval and manipulation

gdr2_completeness queries Gaia DR2 TAP services and divides the queries into sub-queries chunked into arbitrary healpix bins. Downloaded data are formatted into arrays. Internal completeness is calculated by dividing the total starcount and starcounts with an applied cut (*e.g.*, radial velocity measurement and good parallax). Independent determination of the external GDR2 completeness per healpix (level 6) and G magnitude bin (3 coarse bins: 8-12,12-15,15-18) is inferred from a crossmatch with 2MASS data. The overall completeness of a specific GDR2 sample can be approximated by multiplying the internal with the external completeness map, which is useful when data are compared to models thereof. Jupyter notebooks showcasing both utilities enable the user to easily construct the overall completeness for arbitrary samples of the GDR2 catalogue.

[ascl:1811.017]
Vplanet: Virtual planet simulator

Barnes, Rory; Deitrick, Russell; Luger, Rodrigo; Driscoll, Peter; Fleming, David; Quinn, Thomas; Smotherman, Hayden; Garcia, Rodolfo; McDonald, Diego; Wilhelm, Caitlyn; Guyer, Benjamin

Vplanet simulates planetary system evolution with a focus on habitability. Physical models, typically consisting of ordinary differential equations for stellar, orbital, tidal, rotational, atmospheric, internal, magnetic, climate, and galactic evolution, are coupled together to simulate evolution for the age of a system.

[ascl:1811.016]
VoigtFit: Absorption line fitting for Voigt profiles

VoigtFit fits Voigt profiles to absorption lines. It fits multiple components for various atomic lines simultaneously, allowing parameters to be tied and fixed, and can automatically fit a polynomial continuum model together with the line profiles. A physical model can be used to constrain thermal and turbulent broadening of absorption lines as well as implementing molecular excitation models. The code uses a χ2 minimization approach to find the best solution and offers interactive features such as manual continuum placement locally around each line, manual masking of undesired fitting regions, and interactive definition of velocity components for various elements, improving the ease of estimating initial guesses.

[ascl:1811.015]
radon: Streak detection using the Fast Radon Transform

radon performs a Fast Radon Transform (FRT) on image data for streak detection. The software finds short streaks and multiple streaks, convolves the images with a given PSF, and tracks the best S/N results and find a automatic threshold. It also calculates the streak parameters in the input image and the streak parameters in the input image. radon has a simulator that can make multiple streaks of different intensities and coordinates, and can simulate random streaks with parameters chosen uniformly in a user-defined range.

[ascl:1811.014]
pygad: Analyzing Gadget Simulations with Python

pygad provides a framework for dealing with Gadget snapshots. The code reads any of the many different Gadget (ascl:0003.001) formats, allows easy masking snapshots to particles of interest, decorates the data blocks with units, allows to add automatically updating derived blocks, and provides several binning and plotting routines, among other tasks, to provide convenient, intuitive handling of the Gadget data without the need to worry about technical details. pygad provides access to single stellar population (SSP) models, has an interface to Rockstar (ascl:1210.008) output files, provides its own friends-of-friends (FoF) finder, calculates spherical overdensities, and has a sub-module to generate mock absorption lines.

[ascl:1811.013]
DiskSim: Modeling Accretion Disk Dynamics with SPH

DiskSim is a source-code distribution of the SPH accretion disk modeling code previously released in a Windows executable form as FITDisk (ascl:1305.011). The code released now is the full research code in Fortran and can be modified as needed by the user.

[ascl:1811.012]
muLAn: gravitational MICROlensing Analysis Software

muLAn analyzes and fits light curves of gravitational microlensing events. The code includes all classical microlensing models (for example, single and binary microlenses, ground- and space-based parallax effects, orbital motion, finite-source effects, and limb-darkening); these can be combined into several time intervals of the analyzed light curve. Minimization methods include an Affine-Invariant Ensemble Sampler to generate a multivariate proposal function while running several Markov Chain Monte Carlo (MCMC) chains, for the set of parameters which is chosen to be fit; non-fitting parameters can be either kept fixed or set on a grid defined by the user. Furthermore, the software offers a model-free option to align all data sets together and allow inspection the light curve before any modeling work. It also comes with many useful routines (export publication-quality figures, data formatting and cleaning) and state-of-the-art statistical tools.

Modeling results can be interpreted using an interactive html page which contains all information about the light curve model, caustics, source trajectory, best-fit parameters and chi-square. Parameters uncertainties and statistical properties (such as multi-modal features of the posterior density) can be assessed from correlation plots. The code is modular, allowing the addition of other computation or minimization routines by directly adding their Python files without modifying the main code. The software has been designed to be easy to use even for the newcomer in microlensing, with external, synthetic and self-explanatory setup files containing all important commands and option settings. The user may choose to launch the code through command line instructions, or to import muLAn within another Python project like any standard Python package.

[ascl:1811.011]
SIM5: Library for ray-tracing and radiation transport in general relativity

The SIM5 library contains routines for relativistic raytracing and radiation transfer in GR. Written C with a Python interface, it has a special focus on raytracing from accretion disks, tori, hot spots or any other 3D configuration of matter in Kerr geometry, but it can be used with any other metric as well. It handles both optically thick and thin sources as well as transport of polarization of the radiation and calculates the propagation of light rays from the source to an observer through a curved spacetime. It supports parallelization and runs on GPUs.

[ascl:1811.010]
MillCgs: Searching for Compact Groups in the Millennium Simulation

MillCgs clusters galaxies from the semi-analytic models run on top of the Millennium Simulation to identify Compact Groups. MillCgs uses a machine learning clustering algorithm to find the groups and then runs analytics to filter out the groups that do not fit the user specified criteria. The package downloads the data, processes it, and then creates graphs of the data.

[ascl:1811.009]
RLOS: Time-resolved imaging of model astrophysical jets

RLOS (Relativistic Line Of Sight) uses hydrocode output data, such as that from PLUTO (ascl:1010.045), to create synthetic images depicting what a model relativistic astrophysical jet looks like to a stationary observer. The approximate time-delayed imaging algorithm used is implemented within existing line-of-sight code. The software has the potential to study a variety of dynamical astrophysical phenomena in collaboration with other imaging and simulation tools.

[ascl:1811.008]
Pylians: Python libraries for the analysis of numerical simulations

Pylians facilitates the analysis of numerical simulations (both N-body and hydro). This set of libraries, written in python, cython and C, compute power spectra, bispectra, and correlation functions, identifies voids, and populates halos with galaxies using an HOD. Pylians can also apply HI+H2 corrections to the output of hydrodynamic simulations, makes 21cm maps, computes DLAs column density distribution functions, and plots density fields.

[ascl:1811.007]
Flame: Near-infrared and optical spectroscopy data reduction pipeline

Flame reduces near-infrared and optical multi-object spectroscopic data. Although the pipeline was created for the LUCI instrument at the Large Binocular Telescope, Flame, written in IDL, is modular and can be adapted to work with data from other instruments. The software uses 2D transformations, thus using one interpolation step to wavelength calibrate and rectify the data. The γ(x, y) transformation also includes the spatial misalignment between frames, which can be measured from a reference star observed simultaneously with the science targets; sky subtraction can be performed via nodding and/or modelling of the sky spectrum.

[ascl:1811.006]
QuickSip: Project survey image properties onto the sky into Healpix maps

QuickSip quickly projects Survey Image Properties (e.g. seeing, sky noise, airmass) into Healpix sky maps with flexible weighting schemes. It was initially designed to produce observing condition "systematics" maps for the Dark Energy Survey (DES), but will work with any multi-epoch survey and images with valid WCS. QuickSip can reproduce the Mangle (ascl:1202.005) magnitude limit maps at sub-percent accuracy but doesn't support additional masks (stars, trails, etc), in which case Mangle should be used. Thus, QuickSip can be seen as a simplified Mangle to project image properties into Healpix maps in a fast and more flexible manner.

[ascl:1811.005]
Shark: Flexible semi-analytic galaxy formation model

Lagos, Claudia del P.; Tobar, Rodrigo J.; Robotham, Aaron S. G.; Obreschkow, Danail; Mitchell, Peter D.; Power, Chris; Elahi, Pascal J.

Shark is a flexible semi-analytic galaxy formation model for easy exploration of different physical processes. Shark has been implemented with several models for gas cooling, active galactic nuclei, stellar and photo-ionization feedback, and star formation (SF). The software can determine the stellar mass function and stellar–halo mass relation at z=0–4; cosmic evolution of the star formation rate density, stellar mass, atomic and molecular hydrogen; local gas scaling relations; and structural galaxy properties. It performs particularly well for the mass–size relation for discs/bulges, the gas–stellar mass and stellar mass–metallicity relations. Shark is written in C++11 and has been parallelized with OpenMP.

[ascl:1811.004]
SEP: Source Extraction and Photometry

SEP (Source Extraction and Photometry) makes the core algorithms of Source Extractor (ascl:1010.064) available as a library of standalone functions and classes. These operate directly on in-memory arrays (no FITS files or configuration files). The code is derived from the Source Extractor code base (written in C) and aims to produce results compatible with Source Extractor whenever possible. SEP consists of a C library with no dependencies outside the standard library and a Python module that wraps the C library in a Pythonic API. The Python wrapper operates on NumPy arrays with NumPy as its only dependency. It is generated using Cython.

From Source Extractor, SEP includes background estimation, image segmentation (including on-the-fly filtering and source deblending), aperture photometry in circular and elliptical apertures, and source measurements such as Kron radius, "windowed" position fitting, and half-light radius. It also adds the following features that are not available in Source Extractor: optimized matched filter for variable noise in source extraction; circular annulus and elliptical annulus aperture photometry functions; local background subtraction in shape consistent with aperture in aperture photometry functions; exact pixel overlap mode in all aperture photometry functions; and masking of elliptical regions on images.

[ascl:1811.003]
binaryBHexp: On-the-fly visualizations of precessing binary black holes

binaryBHexp (binary black hole explorer) uses surrogate models of numerical simulations to generate on-the-fly interactive visualizations of precessing binary black holes. These visualizations can be generated in a few seconds and at any point in the 7-dimensional parameter space of the underlying surrogate models. These visualizations provide a valuable means to understand and gain insights about binary black hole systems and gravitational physics such as those detected by the LIGO gravitational wave detector.

[ascl:1811.002]
DRAGONS: Gemini Observatory data reduction platform

DRAGONS (Data Reduction for Astronomy from Gemini Observatory North and South) is Gemini's Python-based data reduction platform. DRAGONS offers an automation system that allows for hands-off pipeline reduction of Gemini data, or of any other astronomical data once configured. The platform also allows researchers to control input parameters and in some cases will offer to interactively optimize some data reduction steps, e.g. change the order of fit and visualize the new solution.

[ascl:1811.001]
synphot: Synthetic photometry using Astropy

Synphot simulates photometric data and spectra, observed or otherwise. It can incorporate the user's filters, spectra, and data, and use of a pre-defined standard star (Vega), bandpass, or extinction law. synphot can also construct complicated composite spectra using different models, simulate observations, and compute photometric properties such as count rate, effective wavelength, and effective stimulus. It can manipulate a spectrum by, for example, applying redshift, or normalize it to a given flux value in a given bandpass. Synphot can also sample a spectrum at given wavelengths, plot a quick-view of a spectrum, and perform repetitive operations such as simulating the observations of multiple type of sources through multiple bandpasses. Synphot understands Astropy (ascl:1304.002) models and units and is an Astropy affiliated package.

[submitted]
stginga: Ginga for STScI

stginga customizes Ginga to aid data analysis for the data supported by STScI (e.g., HST or JWST). For instance, it provides plugins and configuration files that understand HST and JWST data products.

[submitted]
stsynphot: synphot for HST and JWST

An extension to synphot (ascl:1811.001), stsynphot implements synthetic photometry package for HST and JWST support. The software constructs spectra from various grids of model atmosphere spectra, parameterized spectrum models, and atlases of stellar spectrophotometry. It also simulates observations specific to HST and JWST, computes photometric calibration parameters for any supported instrument mode, and plots instrument-specific sensitivity curves and calibration target spectra.

[ascl:1810.021]
Firefly: Interactive exploration of particle-based data

Firefly provides interactive exploration of particle-based data in the browser. The user can filter, display vector fields, and toggle the visibility of their customizable datasets all on-the-fly. Different Firefly visualizations, complete with preconfigured data and camera view-settings, can be shared by URL. As Firefly is written in WebGL, it can be hosted online, though Firefly can also be used locally, without an internet connection. Firefly was developed with simulations of galaxy formation in mind but is flexible enough to display any particle-based data. Other features include a stereoscopic 3D picture mode and mobile compatibility.

[ascl:1810.020]
DDS: Debris Disk Radiative Transfer Simulator

DDS simulates scattered light and thermal reemission in arbitrary optically dust distributions with spherical, homogeneous grains where the dust parameters (optical properties, sublimation temperature, grain size) and SED of the illuminating/ heating radiative source can be arbitrarily defined. The code is optimized for studying circumstellar debris disks where large grains (*i.e.*, with large size parameters) are expected to determine the far-infrared through millimeter dust reemission spectral energy distribution. The approach to calculate dust temperatures and dust reemission spectra is only valid in the optically thin regime. The validity of this constraint is verified for each model during the runtime of the code. The relative abundances of different grains can be arbitrarily chosen, but must be constant outside the dust sublimation region., *i.e.*, the shape of the (arbitrary) radial dust density distribution outside the dust sublimation region is the same for all grain sizes and chemistries.

[ascl:1810.019]
MIEX: Mie scattering code for large grains

Miex calculates Mie scattering coefficients and efficiency factors for broad grain size distributions and a very wide wavelength range (λ ≈ 10-10-10-2m) of the interacting radiation and incorporates standard solutions of the scattering amplitude functions. The code handles arbitrary size parameters, and single scattering by particle ensembles is calculated by proper averaging of the respective parameters.

[ascl:1810.018]
APPLawD: Accurate Potentials in Power Law Disks

APPLawD (Accurate Disk Potentials for Power Law Surface densities) determines the gravitational potential in the equatorial plane of a flat axially symmetric disk (inside and outside) with finite size and power law surface density profile. Potential values are computed on the basis of the density splitting method, where the residual Poisson kernel is expanded over the modulus of the complete elliptic integral of the first kind. In contrast with classical multipole expansions of potential theory, the residual series converges linearly inside sources, leading to very accurate potential values for low order truncations of the series. The code is easy to use, works under variable precision, and is written in Fortran 90 with no external dependencies.

[ascl:1810.017]
SOPHISM: Software Instrument Simulator

Blanco Rodríguez, J.; del Toro Iniesta, J. C.; Orozco Suárez, D.; Martínez Pillet, V.; Bonet, J. A.; Feller, A.; Hirzberger, J.; Lagg, A.; Piqueras, J.; Gasent Blesa, J. L.

SOPHISM models astronomical instrumentation from the entrance of the telescope to data acquisition at the detector, along with software blocks dealing with, for example, demodulation, inversion, and compression. The code performs most analyses done with light in astronomy, such as differential photometry, spectroscopy, and polarimetry. The simulator offers flexibility and implementation of new effects and subsystems, making it user-adaptable for a wide variety of instruments. SOPHISM can be used for all stages of instrument definition, design, operation, and lifetime tracking evaluation.

[ascl:1810.016]
XCLASS: eXtended CASA Line Analysis Software Suite

XCLASS (eXtended CASA Line Analysis Software Suite) extends CASA (ascl:1107.013) with new functions for modeling interferometric and single dish data. It provides a tool for calculating synthetic spectra by solving the radiative transfer equation for an isothermal object in one dimension, taking into account the finite source size and dust attenuation. It also includes an interface for MAGIX (ascl:1303.009) to find the parameter set that most closely reproduces the data.

[ascl:1810.015]
cuFFS: CUDA-accelerated Fast Faraday Synthesis

cuFFS (CUDA-accelerated Fast Faraday Synthesis) performs Faraday rotation measure synthesis; it is particularly well-suited for performing RM synthesis on large datasets. Compared to a fast single-threaded and vectorized CPU implementation, depending on the structure and format of the data cubes, cuFFs achieves an increase in speed of up to two orders of magnitude. The code assumes that the pixels values are IEEE single precision floating points (BITPIX=-32), and the input cubes must have 3 axes (2 spatial dimensions and 1 frequency axis) with frequency axis as NAXIS1. A package is included to reformat data with individual stokes Q and U channel maps to the required format. The code supports both the HDFITS format and the standard FITS format, and is written in C with GPU-acceleration achieved using Nvidia's CUDA parallel computing platform.

[ascl:1810.014]
STiC: Stockholm inversion code

STiC is a MPI-parallel non-LTE inversion code for observed full-Stokes observations. The code processes lines from multiple atoms in non-LTE, including partial redistribution effects of scattered photons in angle and frequency of scattered photons (PRD), and can be used with model atmospheres that have a complex depth stratification without introducing artifacts.

[ascl:1810.013]
catsHTM: Catalog cross-matching tool

The catsHTM package quickly accesses and cross-matches large astronomical catalogs that have been reformatted into the HDF5-based file format. It performs efficient cone searches at resolutions from a few arc-seconds to degrees within a few milliseconds time, cross-match numerous catalogs, and can do general searches.

[ascl:1810.012]
GiRaFFE: General relativistic force-free electrodynamics code

GiRaFFE leverages the Einstein Toolkit's (ascl:1102.014) highly-scalable infrastructure to create large-scale simulations of magnetized plasmas in strong, dynamical spacetimes on adaptive-mesh refinement (AMR) grids. It is based on IllinoisGRMHD, a user-friendly, open-source, dynamical-spacetime GRMHD code, and is highly scalable, to tens of thousands of cores.

[ascl:1810.011]
Eclairs: Efficient Codes for the LArge scales of the unIveRSe

Eclairs calculates matter power spectrum based on standard perturbation theory and regularized pertubation theory. The codes are written in C++ with a python wrapper which is designed to be easily combined with MCMC samplers.

[ascl:1810.010]
ODTBX: Orbit Determination Toolbox

ODTBX (Orbit Determination Toolbox) provides orbit determination analysis, advanced mission simulation, and analysis for concept exploration, proposal, early design phase, and/or rapid design center environments. The core ODTBX functionality is realized through a set of estimation commands that incorporate Monte Carlo data simulation, linear covariance analysis, and measurement processing at a generic level; its functions and utilities are combined in a flexible architecture to allow modular development of navigation algorithms and simulations. ODTBX is written in Matlab and Java.

[ascl:1810.009]
PyUltraLight: Pseudo-spectral Python code to compute ultralight dark matter dynamics

PyUltraLight computes non-relativistic ultralight dark matter dynamics in a static spacetime background. It uses pseudo-spectral methods to compute the evolution of a complex scalar field governed by the Schrödinger-Poisson system of coupled differential equations. Computations are performed on a fixed-grid with periodic boundary conditions, allowing for a decomposition of the field in momentum space by way of the discrete Fourier transform. The field is then evolved through a symmetrized split-step Fourier algorithm, in which nonlinear operators are applied in real space, while spatial derivatives are computed in Fourier space. Fourier transforms within PyUltraLight are handled using the pyFFTW pythonic wrapper around FFTW (ascl:1201.015).

[ascl:1810.008]
pycraf: Spectrum-management compatibility

The pycraf Python package provides functions and procedures for spectrum-management compatibility studies, such as calculating the interference levels at a radio telescope produced from a radio broadcasting tower. It includes an implementation of ITU-R Recommendation P.452-16 for calculating path attenuation for the distance between an interferer and the victim service. It supports NASA's Shuttle Radar Topography Mission (SRTM) data for height-profile generation, includes a full implementation of ITU-R Rec. P.676-10, which provides two atmospheric models to calculate the attenuation for paths through Earth's atmosphere, and provides various antenna patterns necessary for compatibility studies (e.g., RAS, IMT, fixed-service links). The package can also convert power flux densities, field strengths, transmitted and received powers at certain distances and frequencies into each other.

[ascl:1810.007]
ARTES: 3D Monte Carlo scattering radiative transfer in planetary atmospheres

The 3D Monte Carlo radiative transfer code ARTES calculates reflected light and thermal radiation in a spherical grid with a parameterized distribution of gas, clouds, hazes, and circumplanetary material. Designed specifically for (polarized) scattered light simulations of planetary atmospheres, it can compute both reflected stellar light and thermal emission from the planet for an arbitrary atmospheric structure and distribution of opacity sources. Multiple scattering, absorption, and polarization are fully treated and the output includes an image, spectrum, or phase curve. Several tools are included to create opacities and scattering matrices for molecules and clouds.

[ascl:1810.006]
Echelle++: Generic spectrum simulator

Echelle++ simulates realistic raw spectra based on the Zemax model of any spectrograph, with a particular emphasis on cross-dispersed Echelle spectrographs. The code generates realistic spectra of astronomical and calibration sources, with accurate representation of optical aberrations, the shape of the point spread function, detector characteristics, and photon noise. It produces high-fidelity spectra fast, an important feature when testing data reduction pipelines with a large set of different input spectra, when making critical choices about order spacing in the design phase of the instrument, or while aligning the spectrograph during construction. Echelle++ also works with low resolution, low signal to noise, multi-object, IFU, or long slit spectra, for simulating a wide array of spectrographs.

[ascl:1810.005]
STARRY: Analytic computation of occultation light curves

Luger, Rodrigo; Agol, Eric; Foreman-Mackey, Daniel; Fleming, David P.; Lustig-Yaeger, Jacob; Deitrick, Russell

STARRY computes light curves for various applications in astronomy: transits and secondary eclipses of exoplanets, light curves of eclipsing binaries, rotational phase curves of exoplanets, light curves of planet-planet and planet-moon occultations, and more. By modeling celestial body surface maps as sums of spherical harmonics, STARRY does all this analytically and is therefore fast, stable, and differentiable. Coded in C++ but wrapped in Python, STARRY is easy to install and use.

[ascl:1810.004]
VaeX: Visualization and eXploration of Out-of-Core DataFrames

VaeX (Visualization and eXploration) interactively visualizes and explores big tabular datasets. It can calculate statistics such as mean, sum, count, and standard deviation on an N-dimensional grid up to a billion (10^{9}) objects/rows per second. Visualization is done using histograms, density plots, and 3d volume rendering, allowing interactive exploration of big data. VaeX uses memory mapping, zero memory copy policy and lazy computations for best performance, and integrates well with the Jupyter/IPython notebook/lab ecosystem.

[ascl:1810.003]
JETGET: Hydrodynamic jet simulation visualization and analysis

JETGET accesses, visualizes, and analyses (magnetized-)fluid dynamics data stored in Hierarchical Data Format (HDF) and ASCII files. Although JETGET has been optimized to handle data output from jet simulations using the Zeus code (ascl:1306.014) from NCSA, it is also capable of analyzing other data output from simulations using other codes. JETGET can select variables from the data files, render both two- and three-dimensional graphics and analyze and plot important physical quantities. Graphics can be saved in encapsulated Postscript, JPEG, VRML, or saved into an MPEG for later visualization and/or presentations. The strength of JETGET in extracting the physics underlying such phenomena is demonstrated as well as its capabilities in visualizing the 3-dimensional features of the simulated magneto-hydrodynamic jets. The JETGET tool is written in Interactive Data Language (IDL) and uses a graphical user interface to manipulate the data. The tool was developed on a LINUX platform and can be run on any platform that supports IDL.

[ascl:1810.002]
Barcode: Bayesian reconstruction of cosmic density fields

Barcode (BAyesian Reconstruction of COsmic DEnsity fields) samples the primordial density fields compatible with a set of dark matter density tracers after cosmic evolution observed in redshift space. It uses a redshift space model based on the analytic solution of coherent flows within a Hamiltonian Monte Carlo posterior sampling of the primordial density field; this method is applicable to analytically derivable structure formation models, such as the Zel'dovich approximation, but also higher order schemes such as augmented Lagrangian perturbation theory or even particle mesh models. The algorithm is well-suited for analysis of the dark matter cosmic web implied by the observed spatial distribution of galaxy clusters, such as obtained from X-ray, SZ or weak lensing surveys, as well as that of the intergalactic medium sampled by the Lyman alpha forest. In these cases, virialized motions are negligible and the tracers cannot be modeled as point-like objects. Barcode can be used in all of these contexts as a baryon acoustic oscillation reconstruction algorithm.

[ascl:1810.001]
galfast: Milky Way mock catalog generator

galfast generates catalogs for arbitrary, user-supplied Milky Way models, including empirically derived ones. The built-in model set is based on fits to SDSS stellar observations over 8000 deg^{2} of the sky and includes a three-dimensional dust distribution map. Because of the capability to use empirically derived models, galfast typically produces closer matches to the actual observed counts and color-magnitude diagrams. In particular, galfast-generated catalogs are used to derive the stellar component of “Universe Model” catalogs used by the LSST Project. A key distinguishing characteristic of galfast is its speed. Galfast uses the GPU (with kernels written in NVIDIA C/C++ for CUDA) to offload compute intensive model sampling computations to the GPU, enabling the generation of realistic catalogs to full LSST depth in hours (instead of days or weeks), making it possible to study proposed science cases with high precision.

[ascl:1809.016]
RequiSim: Variance weighted overlap calculator

RequiSim computes the Variance Weighted Overlap, which is a measure of the bias on the lensing signal from power spectrum modelling bias for any non-linear model. It assumes that the bias on the power spectrum is Gaussian with a covariance described by a user-provided knowledge matrix that describes the covariance in the bias on the power spectrum. The data from the Euclid wide-field survey are included.

[ascl:1809.015]
MrMoose: Multi-Resolution Multi-Object/Origin Spectral Energy distribution fitting procedure

MrMoose (Multi-Resolution Multi-Object/Origin Spectral Energy) fits user-defined models onto a set of multi-wavelength data using a Bayesian framework. The code can handle blended sources, large variation in resolution, and even upper limits consistently. It also generates a series of outputs allowing for an quick interpretation of the results. The code uses emcee (ascl:1303.002), and saves the emcee sampler object, thus allowing users to transfer the output to a personal graphical interface.

[ascl:1809.014]
stepped_luneburg: Stacked-based ray tracing code to model a stepped Luneburg lens

stepped_luneburg investigates the scattered light properties of a Luneburg lens approximated as a series of concentric shells with discrete refractive indices. The optical Luneburg lens has promising applications for low-cost, continuous all-sky monitoring to obtain transit light curves of bright, nearby stars. This code implements a stack-based algorithm that tracks all reflected and refracted rays generated at each optical interface of the lens as described by Snell's law. The Luneburg lens model parameters, such as number of lens layers, the power-law that describes the refractive indices, the number of incident rays, and the initial direction of the incident wavefront can be altered to optimize lens performance. The stepped_luneburg module can be imported within the Python environment or used with scripting, and it is accompanied by two other modules, enc_int and int_map, that help the user to determine the resolving power of the lens and the strength of scattered light haloes for the purpose of quality assessment.

[ascl:1809.013]
dynesty: Dynamic Nested Sampling package

dynesty is a Dynamic Nested Sampling package for estimating Bayesian posteriors and evidences. dynesty samples from a given distribution when provided with a loglikelihood function, a prior_transform function (that transforms samples from the unit cube to the target prior), and the dimensionality of the parameter space.

[ascl:1809.012]
nestcheck: Nested sampling calculations analysis

Nestcheck analyzes nested sampling runs and estimates numerical uncertainties on calculations using them. The package can load results from a number of nested sampling software packages, including MultiNest (ascl:1109.006), PolyChord (ascl:1502.011), dynesty (ascl:1809.013) and perfectns (ascl:1809.005), and offers the flexibility to add input functions for other nested sampling software packages. Nestcheck utilities include error analysis, diagnostic tests, and plots for nested sampling calculations.

[ascl:1809.011]
qp: Quantile parametrization for probability distribution functions

qp manipulates parametrizations of 1-dimensional probability distribution functions, as suitable for photo-z PDF compression. The code helps determine a parameterization for storing a catalog of photo-z PDFs that balances the available storage resources against the accuracy of the photo-z PDFs and science products reconstructed from the stored parameters.

[ascl:1809.010]
Isca: Idealized global circulation modeling

Vallis, Geoffrey K.; Colyer, Greg; Geen, Ruth; Gerber, Edwin; Jucker, Martin; Maher, Penelope; Paterson, Alexander; Pietschnig, Marianne; Penn, James; Thomson, Stephen I.

Isca provides a framework for the idealized modeling of the global circulation of planetary atmospheres at varying levels of complexity and realism. Though Isca is an outgrowth of models designed for Earth's atmosphere, it may readily be extended into other planetary regimes. Various forcing and radiation options are available. At the simple end of the spectrum a Held-Suarez case is available. An idealized grey radiation scheme, a grey scheme with moisture feedback, a two-band scheme and a multi-band scheme are also available, all with simple moist effects and astronomically-based solar forcing. At the complex end of the spectrum the framework provides a direct connection to comprehensive atmospheric general circulation models.

[ascl:1809.009]
NEBULA: Radiative transfer code of ionized nebulae at radio wavelengths

NEBULA performs the radiative transfer of the 3He+ hyperfine transition, radio recombination lines (RRLs), and free-free continuum emission through a model nebula. The model nebula is composed of only H and He within a three-dimension Cartesian grid with arbitrary density, temperature, and ionization structure. The 3He+ line is assumed to be in local thermodynamic equilibrium (LTE), but non-LTE effects and pressure broadening from electron impacts can be included for the RRLs. All spectra are broadened by thermal and microturbulent motions.

[ascl:1809.008]
PyQSOFit: Python code to fit the spectrum of quasars

The Python QSO fitting code (PyQSOFit) measures spectral properties of quasars. Based on Shen's IDL version, this code decomposes different components in the quasar spectrum, e.g., host galaxy, power-law continuum, Fe II component, and emission lines. In addition, it can run Monto Carlo iterations using flux randomization to estimate the uncertainties.

[ascl:1809.007]
surfinBH: Surrogate final black hole properties for mergers of binary black holes

surfinBH predicts the final mass, spin and recoil velocity of the remnant of a binary black hole merger. Trained directly against numerical relativity simulations, these models are extremely accurate, reproducing the results of the simulations at the same level of accuracy as the simulations themselves. Fits such as these play a crucial role in waveform modeling and tests of general relativity with gravitational waves, performed by LIGO.

[ascl:1809.006]
spops: Spinning black-hole binary population synthesis

Gerosa, Davide; Berti, Emanuele; O'Shaughnessy, Richard; Belczynski, Krzysztof; Kesden, Michael; Wysocki, Daniel; Gladysz, Wojciech

spops is a database of populations synthesis simulations of spinning black-hole binary systems, together with a python module to query it. Data are obtained with the startrack and precession [ascl:1611.004] numerical codes to consistently evolve binary stars from formation to gravitational-wave detection. spops allows quick exploration of the interplay between stellar physics and black-hole spin dynamics.

[ascl:1809.005]
perfectns: "Perfect" dynamic and standard nested sampling for spherically symmetric likelihoods and priors

perfectns performs dynamic nested sampling and standard nested sampling for spherically symmetric likelihoods and priors, and analyses the samples produced. The spherical symmetry allows the nested sampling algorithm to be followed “perfectly” - *i.e.* without implementation-specific errors correlations between samples. It is intended for use in research into the statistical properties of nested sampling, and to provide a benchmark for testing the performance of nested sampling software packages used for practical problems - which rely on numerical techniques to produce approximately uncorrelated samples.

[ascl:1809.004]
VBBINARYLENSING: Microlensing light-curve computation

Bozza, Valerio; Bachelet, Etienne; Bartolić, Fran; Heintz, Tyler M.; Hoag, Ava R.; Hundertmark, Markus

VBBinaryLensing forward models gravitational microlensing events using the advanced contour integration method; it supports single and binary lenses. The lens map is inverted on a collection of points on the source boundary to obtain a corresponding collection of points on the boundaries of the images from which the area of the images can be recovered by use of Green’s theorem. The code takes advantage of a number of techniques to make contour integration much more efficient, including using a parabolic correction to increase the accuracy of the summation, introducing an error estimate on each arc of the boundary to enable defining an optimal sampling, and allowing the inclusion of limb darkening. The code is written as a C++ library and wrapped as a Python package, and can be called from either C++ or Python.

[ascl:1809.003]
PASTA: Python Astronomical Stacking Tool Array

PASTA performs median stacking of astronomical sources. Written in Python, it can filter sources, provide stack statistics, generate Karma annotations, format source lists, and read information from stacked Flexible Image Transport System (FITS) images. PASTA was originally written to examine polarization stack properties and includes a Monte Carlo modeler for obtaining true polarized intensity from the observed polarization of a stack. PASTA is also useful as a generic stacking tool, even if polarization properties are not being examined.

[ascl:1809.002]
PCCDPACK: Polarimetry with CCD

PCCDPACK analyzes polarimetry data. The set of routines is written in CL-IRAF (including compiled Fortran codes) and analyzes dozens of point objects simultaneously on the same CCD image. A subpackage, specpol, is included to analyze spectropolarimetry data.

[ascl:1809.001]
LEMON: Differential photometry pipeline

LEMON is a differential-photometry pipeline, written in Python, that determines the changes in the brightness of astronomical objects over time and compiles their measurements into light curves. This code makes it possible to completely reduce thousands of FITS images of time series in a matter of only a few hours, requiring minimal user interaction.

[ascl:1808.011]
Robbie: Radio transients and variables detection workflow

Robbie automates cataloging sources, finding variables, and identifying transients in the image domain. It works in a batch processing paradigm with a modular design so components can be swapped out or upgraded to adapt to different input data while retaining a consistent and coherent methodological approach. Robbie is based on commonly used and open software, including AegeanTools (ascl:1212.009) and STILS/TOPCAT (ascl:1101.010).

[ascl:1808.010]
hi_class: Horndeski in the Cosmic Linear Anisotropy Solving System

hi_class implements Horndeski's theory of gravity in the modern Cosmic Linear Anisotropy Solving System (ascl:1106.020). It can be used to compute any cosmological observable at the level of background or linear perturbations, such as cosmological distances, cosmic microwave background, matter power and number count spectra (including relativistic effects). hi_class can be readily interfaced with Monte Python (ascl:1307.002) to test Gravity and Dark Energy models.

[ascl:1808.009]
py-sdm: Support Distribution Machines

py-sdm (Support Distribution Machines) is a Python implementation of nonparametric nearest-neighbor-based estimators for divergences between distributions for machine learning on sets of data rather than individual data points. It treats points of sets of data as samples from some unknown probability distribution and then statistically estimates the distance between those distributions, such as the KL divergence, the closely related Rényi divergence, L2 distance, or other similar distances.

[ascl:1808.008]
PyMieDap: Python Mie Doubling Adding Program

PyMieDAP (Python Mie Doubling Adding Program) makes light scattering computations with Mie scattering and radiative transfer computations with full orders of scattering and taking into account the polarization of the light scattered. Full planet modeling at any phase angle is possible. With the included subpackage exopy, it is also possible to simulate systems with a star, a planet and a possible moon.

[ascl:1808.007]
2DSF: Vectorized Structure Function Algorithm

The vectorized physical domain structure function (SF) algorithm calculates the velocity anisotropy within two-dimensional molecular line emission observations. The vectorized approach is significantly faster than brute force iterative algorithms and is very efficient for even relatively large images. Furthermore, unlike frequency domain algorithms which require the input data to be fully integrable, this algorithm, implemented in Python, has no such requirements, making it a robust tool for observations with irregularities such as asymmetric boundaries and missing data.

[ascl:1808.006]
Fips: An OpenGL based FITS viewer

FIPS is a cross-platform FITS viewer with a responsive user interface. Unlike other FITS viewers, FIPS uses GPU hardware via OpenGL to provide functionality such as zooming, panning and level adjustments. OpenGL 2.1 and later is supported. FIPS supports all 2D image formats except floating point formats on OpenGL 2.1. FITS image extension has basic limited support.

[ascl:1808.005]
hfof: Friends-of-Friends via spatial hashing

hfof is a 3-d friends-of-friends (FoF) cluster finder with Python bindings based on a fast spatial hashing algorithm that identifies connected sets of points where the point-wise connections are determined by a fixed spatial distance. This technique sorts particles into fine cells sufficiently compact to guarantee their cohabitants are linked, and uses locality sensitive hashing to search for neighboring (blocks of) cells. Tests on N-body simulations of up to a billion particles exhibit speed increases of factors up to 20x compared with FOF via trees, and is consistently complete in less than the time of a k-d tree construction, giving it an intrinsic advantage over tree-based methods.

[ascl:1808.004]
ImPlaneIA: Image Plane Approach to Interferometric Analysis

Aperture masking interferometric data analysis involves measuring phases and amplitudes of fringes formed by interference between holes in the pupil mask. These fringe observables can be measured by computing an analytic model of the point spread function and fitting the relevant set of spatial frequencies directly in the image plane, without recourse to numerical Fourier transforms. The ImPlaneIA pipeline converts aperture masking images to fringe observables by fitting fringes in the image plane, calibrates data from a target of interest with one or more point source calibrators, and contains some basic model-fitting routines. The pipeline can accept different mask geometries, instruments, and observing modes.

[ascl:1808.003]
CPF: Corral Pipeline Framework

Cabral, Juan; Sanchez, Bruno; Beroiz, Martin; Dominguez, Mariano; Lares, Marcelo; Gurovich, Sebastian; Granitto, Pablo

Corral generates astronomical pipelines. Data processing pipelines represent an important slice of the astronomical software library that include chains of processes that transform raw data into valuable information via data reduction and analysis. Written in Python, Corral features a Model-View-Controller design pattern on top of an SQL Relational Database capable of handling custom data models, processing stages, and communication alerts. It also provides automatic quality and structural metrics based on unit testing. The Model-View-Controller provides concept separation between the user logic and the data models, delivering at the same time multi-processing and distributed computing capabilities.

[ascl:1808.002]
rsigma: Resonant disturbance

rsigma calculates the resonant disturbing function, R(sigma), for a massless particle in an arbitrary orbit perturbed by a planet in circular orbit. This function defines the strength of the resonance (its semi-amplitude) and the location of the stable equilibrium points (the minima). It depends on the variable sigma called critical angle and on the particle's orbital elements a, e, i and the argument of the perihelion. R(sigma) is numerically calculated and the code is valid for arbitrary eccentricities and inclinations, including retrograde orbits.

[ascl:1808.001]
Barycorrpy: Barycentric velocity calculation and leap second management

barycorrpy (BCPy) is a Python implementation of Wright and Eastman's 2014 code (ascl:1807.017) that calculates precise barycentric corrections well below the 1 cm/s level. This level of precision is required in the search for 1 Earth mass planets in the Habitable Zones of Sun-like stars by the Radial Velocity (RV) method, where the maximum semi-amplitude is about 9 cm/s. BCPy was developed for the pipeline for the next generation Doppler Spectrometers - Habitable-zone Planet Finder (HPF) and NEID. An automated leap second management routine improves upon the one available in Astropy. It checks for and downloads a new leap second file before converting from the UT time scale to TDB. The code also includes a converter for JDUTC to BJDTDB.

[submitted]
3D texturized model of MARS (MOLA) regions

The Matlab Tool generates a 3D model (WRL, texturized in height false color map) of a defined region of the Mars surface. It defines the region of interest of the Mars surface (by Lat Long), a resolution of the MOLA DTMs to be considered (with a minimum px onground of 468 m), a scale factor to be multiplied to the height of the surface to improve features visibility for bumping or shadowing effect.

[ascl:1807.033]
LSC: Supervised classification of time-series variable stars

LSC (LINEAR Supervised Classification) trains a number of classifiers, including random forest and K-nearest neighbor, to classify variable stars and compares the results to determine which classifier is most successful. Written in R, the package includes anomaly detection code for testing the application of the selected classifier to new data, thus enabling the creation of highly reliable data sets of classified variable stars.

[ascl:1807.032]
SSMM: Slotted Symbolic Markov Modeling for classifying variable star signatures

SSMM (Slotted Symbolic Markov Modeling) reduces time-domain stellar variable observations to classify stellar variables. The method can be applied to both folded and unfolded data, and does not require time-warping for waveform alignment. Written in Matlab, the performance of the supervised classification code is quantifiable and consistent, and the rate at which new data is processed is dependent only on the computational processing power available.

[ascl:1807.031]
xGDS: Exploration Ground Data Systems

xGDS (Exploration Ground Data Systems) synthesizes real world data (from sensors, robots, ROVs, mobile devices, etc) and human observations into rich, digital maps and displays for analysis, decision making, and collaboration. xGDS processes and maps data (including video) in real-time during operations and uses it to support live role-based geolocated note taking. Notes can be used to search for and display important data. The software enables real-time analysis of data, permitting one to make inferences and plan new data collection operations while still in the field.

[ascl:1807.030]
ASP: Ames Stereo Pipeline

ASP (Ames Stereo Pipeline) provides fully automated geodesy and stereogrammetry tools for processing stereo imagery captured from satellites (around Earth and other planets), robotic rovers, aerial cameras, and historical imagery, with and without accurate camera pose information. It produces cartographic products, including digital elevation models (DEMs), ortho-projected imagery, 3D models, and bundle-adjusted networks of cameras. ASP's data products are suitable for science analysis, mission planning, and public outreach.

[ascl:1807.029]
EVEREST: Tools for de-trending stellar photometry

Luger, Rodrigo; Agol, Eric; Kruse, Ethan; Barnes, Rory; Becker, Andrew; Foreman-Mackey, Daniel; Deming, Drake

EVEREST (EPIC Variability Extraction and Removal for Exoplanet Science Targets) removes instrumental noise from light curves with pixel level decorrelation and Gaussian processes. The code, written in Python, generates the EVEREST catalog and offers tools for accessing and interacting with the de-trended light curves. EVEREST exploits correlations across the pixels on the CCD to remove systematics introduced by the spacecraft’s pointing error. For K2, it yields light curves with precision comparable to that of the original Kepler mission. Interaction with the EVEREST catalog catalog is available via the command line and through the Python interface. Though written for K2, EVEREST can be applied to additional surveys, such as the TESS mission, to correct for instrumental systematics and enable the detection of low signal-to-noise transiting exoplanets.

[ascl:1807.028]
ktransit: Exoplanet transit modeling tool in python

The routines in ktransit create and fit a transiting planet model. The underlying model is a Fortran implementation of the Mandel & Agol (2002) limb darkened transit model. The code calculates a full orbital model and eccentricity can be allowed to vary; radial velocity data can also be calculated via the model and included in the fit.

[ascl:1807.027]
kplr: Tools for working with Kepler data using Python

kplr provides a lightweight Pythonic interface to the catalog of planet candidates (Kepler Objects of Interest [KOIs]) in the NASA Exoplanet Archive and the data stored in the Barbara A. Mikulski Archive for Space Telescopes (MAST). kplr automatically supports loading Kepler data using pyfits (ascl:1207.009) and supports two types of data: light curves and target pixel files.

[ascl:1807.026]
SENR: Simple, Efficient Numerical Relativity

SENR (Simple, Efficient Numerical Relativity) provides the algorithmic framework that combines the C codes generated by NRPy+ (ascl:1807.025) into a functioning numerical relativity code. It is part of the numerical relativity code package SENR/NRPy+. The package extends previous implementations of the BSSN reference-metric formulation to a much broader class of curvilinear coordinate systems, making it suitable for modeling physical configurations with approximate or exact symmetries, such as modeling black hole dynamics.

[ascl:1807.025]
NRPy+: Code generator for Numerical Relativity

NRPy+ (Python-based Code generation for Numerical Relativity and Beyond) generates highly-optimized C code from complex tensorial expressions input in Einstein-like notation. NRPy+ uses SymPy as its computer algebra system backend. It is part of the NRPy+/SENR numerical relativity code package for solving Einstein's equations of general relativity to model compact objects at about 1/100 the cost in memory of more traditional, AMR-based numerical relativity codes, thus allowing desktop computers to be used for gravitational wave astrophysics.

[ascl:1807.024]
TBI: Three-Body Integration

Three-Body Integration performs numerical n-body simulations for mapping conditions for close approaches for the relevant parameter space of configurations and mass values of two white dwarfs and a third star. Low tertiary masses of 0.1M⊙ can be studied, and the collision probability can be estimated with good confidence for the case of nearly equal mass white dwarfs.

[ascl:1807.023]
DAMOCLES: Monte Carlo line radiative transfer code

The Monte Carlo code DAMOCLES models the effects of dust, composed of any combination of species and grain size distributions, on optical and NIR emission lines emitted from the expanding ejecta of a late-time (> 1 yr) supernova. The emissivity and dust distributions follow smooth radial power-law distributions; any arbitrary distribution can be specified by providing the appropriate grid. DAMOCLES treats a variety of clumping structures as specified by a clumped dust mass fraction, volume filling factor, clump size and clump power-law distribution, and the emissivity distribution may also initially be clumped. The code has a large number of variable parameters ranging from 5 dimensions in the simplest models to > 20 in the most complex cases.

[ascl:1807.022]
PUMA: Low-frequency radio catalog cross-matching

PUMA (Positional Update and Matching Algorithm) cross-matches low-frequency radio catalogs using a Bayesian positional probability with spectral matching criteria. The code reliably finds the correct spectral indices of sources and recovers ionospheric offsets. PUMA can be used to facilitate all-sky cross-matches with further constraints applied for other science goals.

[ascl:1807.021]
POWER: Python Open-source Waveform ExtractoR

POWER (Python Open-source Waveform ExtractoR) monitors the status and progress of numerical relativity simulations and post-processes the data products of these simulations to compute the gravitational wave strain at future null infinity.

[ascl:1807.020]
wdmerger: Simulate white dwarf mergers with CASTRO

wdmerger simulates binary white dwarf mergers (and related events) in CASTRO (ascl:1105.010) and provides useful information on the viability of mergers of white dwarfs as a progenitor for Type Ia supernovae.

[ascl:1807.019]
GLS: Generalized Lomb-Scargle periodogram

The Lomb-Scargle periodogram is a common tool in the frequency analysis of unequally spaced data equivalent to least-squares fitting of sine waves. GLS is a solution for the generalization to a full sine wave fit, including an offset and weights (χ2 fitting). Compared to the Lomb-Scargle periodogram, GLS is superior as it provides more accurate frequencies, is less susceptible to aliasing, and gives a much better determination of the spectral intensity.

[ascl:1807.018]
BARYCORR: Python interface for barycentric RV correction

BARYCORR is a Python interface for ZBARYCORR (ascl:1807.017); it requires the measured redshift and returns the corrected barycentric velocity and time correction.

[ascl:1807.017]
ZBARYCORR: Barycentric redshift calculator

ZBARYCORR determines the barycentric redshift (*z _{B}*) for a given star. It calculates the positions and velocities of solar system objects, applies the rotation, precession, nutation, and polar motion of the Earth, applies the stellar motion using the Markwardt library (ascl:1807.016), Shapiro delay, and light-travel term, and finally calculates the quantity

[ascl:1807.016]
MIDLL: Markwardt IDL Library

The Markwardt IDL Library contains routines for curve fitting and function minimization, including MPFIT (ascl:1208.019), statistical tests, and non-linear optimization (TNMIN); graphics programs including plotting three-dimensional data as a cube and fixed- or variable-width histograms; adaptive numerical integration (Quadpack), Chebyshev approximation and interpolation, and other mathematical tools; many ephemeris and timing routines; and array and set operations, such as computing the fast product of a large array, efficiently inserting or deleting elements in an array, and performing set operations on numbers and strings; and many other useful and varied routines.

[ascl:1807.015]
CAESAR: Compact And Extended Source Automated Recognition

CAESAR extracts and parameterizes both compact and extended sources from astronomical radio interferometric maps. The processing pipeline is a series of stages that can run on multiple cores and processors. After local background and rms map computation, compact sources are extracted with flood-fill and blob finder algorithms, processed (selection + deblending), and fitted using a 2D gaussian mixture model. Extended source search is based on a pre-filtering stage, allowing image denoising, compact source removal and enhancement of diffuse emission, followed by a final segmentation. Different algorithms are available for image filtering and segmentation. The outputs delivered to the user include source fitted and shape parameters, regions and contours. Written in C++, CAESAR is designed to handle the large-scale surveys planned with the Square Kilometer Array (SKA) and its precursors.

[ascl:1807.014]
SPEGID: Single-Pulse Event Group IDentification

SPEGID (Single-Pulse Event Group IDentification) identifies astrophysical pulse candidates as trial single-pulse event groups (SPEGs) by first applying Density Based Spatial Clustering of Applications with Noise (DBSCAN) on trial single-pulse events and then merging the clusters that fall within the expected DM (Dispersion Measure) and time span of astrophysical pulses. SPEGID also calculates the peak score for each SPEG in the S/N versus DM space to identify the expected peak-like shape in the signal-to-noise (S/N) ratio versus DM curve of astrophysical pulses. Additionally, SPEGID groups SPEGs that appear at a consistent DM and therefore are likely emitted from the same source. After running SPEGID, periocity.py can be used to find (or verify) the underlying periodicity among a group of SPEGs (i.e., astrophysical pulse candidates).

[ascl:1807.013]
CLASSgal: Relativistic cosmological large scale structure code

CLASSgal computes large scale structure observables; it includes all relativistic corrections and computes both the power spectrum *C _{l}*(

[ascl:1807.012]
AngPow: Fast computation of accurate tomographic power spectra

AngPow computes the auto (z1 = z2) and cross (z1 ≠ z2) angular power spectra between redshift bins (i.e. Cℓ(z1,z2)). The developed algorithm is based on developments on the Chebyshev polynomial basis and on the Clenshaw-Curtis quadrature method. AngPow is flexible and can handle any user-defined power spectra, transfer functions, bias functions, and redshift selection windows. The code is fast enough to be embedded inside programs exploring large cosmological parameter spaces through the Cℓ(z1,z2) comparison with data.

[ascl:1807.011]
nfield: Stochastic tool for QFT on inflationary backgrounds

nfield uses a stochastic formalism to compute the IR correlation functions of quantum fields during cosmic inflation in n-field dimensions. This is a necessary 1-loop resummation of the correlation functions to render them finite. The code supports the implementation of n-numbers of coupled test fields (energetically sub-dominant) as well as non-test fields.

[ascl:1807.010]
THOR: Global Circulation Model for planetary atmospheres

THOR solves the three-dimensional nonhydrostatic Euler equations. The code implements an icosahedral grid for the poles where converging meridians lead to increasingly smaller time steps; irregularities in the grid are smoothed using spring dynamics. THOR is designed to run on graphics processing units (GPUs) and is part of the open-source Exoclimes Simulation Platform.

[ascl:1807.009]
HELIOS: Radiative transfer code for exoplanetary atmospheres

Malik, Matej; Grosheintz, Luc; Mendonça, João M.; Grimm, Simon L.; Lavie, Baptiste; Kitzmann, Daniel; Tsai, Shang-Min; Burrows, Adam; Kreidberg, Laura; Bedell, Megan; Bean, Jacob L.; Stevenson, Kevin B.; Heng, Kevin

HELIOS, a radiative transfer code, is constructed for studying exoplanetary atmospheres. The model atmospheres of HELIOS are one-dimensional and plane-parallel, and the equation of radiative transfer is solved in the two-stream approximation with non-isotropic scattering. Though HELIOS can be used alone, the opacity calculator HELIOS-K (ascl:1503.004) can be used with it to provide the molecular opacities.

[ascl:1807.008]
HII-CHI-mistry_UV: Oxygen abundance and ionizionation parameters for ultraviolet emission lines

HII-CHI-mistry_UV derives oxygen and carbon abundances using the ultraviolet (UV) lines emitted by the gas phase ionized by massive stars. The code first fixes C/O using ratios of appropriate emission lines and, in a second step, calculates O/H and the ionization parameter from carbon lines in the UV. An optical version of this Python code, HII-CHI-mistry (ascl:1807.007), is also available.

[ascl:1807.007]
HII-CHI-mistry: Oxygen abundance and ionizionation parameters for optical emission lines

HII-CHI-mistry calculates the oxygen abundance for gaseous nebulae ionized by massive stars using optical collisionally excited emission lines. This code takes the extinction-corrected emission line fluxes and, based on a *Χ*^{2} minimization on a photoionization models grid, determines chemical-abundances (O/H, N/O) and ionization parameters. An ultraviolet version of this Python code, HII-CHI-mistry-UV (ascl:1807.008), is also available.

[ascl:1807.006]
pyqz: Emission line code

pyqz computes the values of log(Q) [the ionization parameter] and 12+log(O/H) [the oxygen abundance, either total or in the gas phase] for a given set of strong emission lines fluxes from HII regions. The log(Q) and 12+log(O/H) values are interpolated from a finite set of diagnostic line ratio grids computed with the MAPPINGS V code (ascl:1807.005). The grids used by pyqz are chosen to be flat, without wraps, to decouple the influence of log(Q) and 12+log(O/H) on the emission line ratios.

[ascl:1807.005]
MAPPINGS V: Astrophysical plasma modeling code

MAPPINGS V is a update of the MAPPINGS code (ascl:1306.008) and provides new cooling function computations for optically thin plasmas based on the greatly expanded atomic data of the CHIANTI 8 database. The number of cooling and recombination lines has been expanded from ~2000 to over 80,000, and temperature-dependent spline-based collisional data have been adopted for the majority of transitions. The expanded atomic data set provides improved modeling of both thermally ionized and photoionized plasmas; the code is now capable of predicting detailed X-ray spectra of nonequilibrium plasmas over the full nonrelativistic temperature range, increasing its utility in cosmological simulations, in modeling cooling flows, and in generating accurate models for the X-ray emission from shocks in supernova remnants.

[ascl:1807.004]
ARKCoS: Radial kernel convolution on the sphere

ARKCoS (Accelerated radial kernel convolution on the sphere) efficiently convolves pixelated maps on the sphere with radially symmetric kernels with compact support. It performs the convolution along isolatitude rings in Fourier space and integrates in longitudinal direction in pixel space. The computational costs scale linearly with the kernel support, making the method most beneficial for convolution with compact kernels. Typical applications include CMB beam smoothing, symmetric wavelet analyses, and point-source filtering operations. The software is written in C++/CUDA and provides two independent code paths to do the necessary computation either on conventional hardware (CPUs), or on graphics processing units (GPUs).

[ascl:1807.003]
PyAutoLens: Strong lens modeling

PyAutoLens models and analyzes galaxy-scale strong gravitational lenses. This automated module suite simultaneously models the lens galaxy's light and mass while reconstructing the extended source galaxy on an adaptive pixel-grid. Source-plane discretization is amorphous, adapting its clustering and regularization to the intrinsic properties of the lensed source. The lens's light is fitted using a superposition of Sersic functions, allowing PyAutoLens to cleanly deblend its light from the source. Bayesian model comparison is used to automatically chose the complexity of the light and mass models. PyAutoLens provides accurate light, mass, and source profiles inferred for data sets representative of both existing Hubble imaging and future Euclid wide-field observations.

[ascl:1807.002]
Warpfield: Winds And Radiation Pressure: Feedback Induced Expansion, colLapse and Dissolution

Warpfield (Winds And Radiation Pressure: Feedback Induced Expansion, colLapse and Dissolution) calculates shell dynamics and shell structure simultaneously for isolated massive clouds (≥10^{5} M_{☉}). This semi-analytic 1D feedback model scans a large range of physical parameters (gas density, star formation efficiency, and metallicity) to estimate escape fractions of ionizing radiation f_{esc, I}, the minimum star formation efficiency ∊_{min} required to drive an outflow, and recollapse time-scales for clouds that are not destroyed by feedback.

[ascl:1807.001]
POLARIS: POLArized RadIation Simulator

POLARIS (POLArized RadIation Simulator) simulates the intensity and polarization of light emerging from analytical astrophysical models as well as complex magneto-hydrodynamic simulations on various grids. This 3D Monte-Carlo continuum radiative transfer code is written in C++ and is capable of performing dust heating, dust grain alignment, line radiative transfer, and synchrotron simulations to calculate synthetic intensity and polarization maps. The code makes use of a full set of physical quantities (density, temperature, velocity, magnetic field distribution, and dust grain properties as well as different sources of radiation) as input.

[ascl:1806.032]
pwv_kpno: Modeling atmospheric absorption

pwv_kpno provides models for the atmospheric transmission due to precipitable water vapor (PWV) at user specified sites. Atmospheric transmission in the optical and near-infrared is highly dependent on the PWV column density along the line of sight. The pwv_kpno package uses published SuomiNet data in conjunction with MODTRAN models to determine the modeled, time-dependent atmospheric transmission between 3,000 and 12,000 Å. By default, models are provided for Kitt Peak National Observatory (KPNO). Additional locations can be added by the user for any of the hundreds of SuomiNet locations worldwide.

[ascl:1806.031]
ASPIC: Accurate Slow-roll Predictions for Inflationary Cosmology

Aspic, written in modern Fortran, computes various observable quantities used in cosmology from definite single field inflationary models. It provides an efficient, extendable, and accurate way of comparing theoretical inflationary predictions with cosmological data and supports many (~70) models of inflation. The Hubble flow functions, observable quantities up to second order in the slow-roll approximation, are in direct correspondence with the spectral index, the tensor-to-scalar ratio and the running of the primordial power spectrum. The ASPIC library also provides the field potential, its first and second derivatives, the energy density at the end of inflation, the energy density at the end of reheating, and the field value (or e-fold value) at which the pivot scale crossed the Hubble radius during inflation. All these quantities are computed in a way which is consistent with the existence of a reheating phase.

[ascl:1806.030]
foxi: Forecast Observations and their eXpected Information

Using information theory and Bayesian inference, the foxi Python package computes a suite of expected utilities given futuristic observations in a flexible and user-friendly way. foxi requires a set of n-dim prior samples for each model and one set of n-dim samples from the current data, and can calculate the expected ln-Bayes factor between models, decisiveness between models and its maximum-likelihood averaged equivalent, the decisivity, and the expected Kullback-Leibler divergence (i.e., the expected information gain of the futuristic dataset). The package offers flexible inputs and is designed for all-in-one script calculation or an initial cluster run then local machine post-processing, which should make large jobs quite manageable subject to resources and includes features such as LaTeX tables and plot-making for post-data analysis visuals and convenience of presentation.

[ascl:1806.029]
EXO-NAILER: EXOplanet traNsits and rAdIal veLocity fittER

EXO-NAILER (EXOplanet traNsits and rAdIal veLocity fittER) efficiently fits exoplanet transit lightcurves, radial velocities (RVs) or both. The code handles data taken with different instruments. For RVs, a different center-of-mass velocity can be fitted for each instrument to account for offsets between them; if jitter is included, a different jitter term can also fitted for each instrument. For transits, a different photometric jitter can be fitted to each instrument as can different limb-darkening coefficients and different transit depths. In addition to general options that need to be set, EXO-NAILER also requires that photometry and radial velocity options be defined for each instrument.

[ascl:1806.028]
PyMUSE: VLT/MUSE data analyzer

PyMUSE analyzes VLT/MUSE datacubes. The package is optimized to extract 1-D spectra of arbitrary spatial regions within the cube and also for producing images using photometric filters and customized masks. It is intended to provide the user the tools required for a complete analysis of a MUSE data set.

[ascl:1806.027]
fcmaker: Creating ESO-compliant finding charts for Observing Blocks on p2

fcmaker creates astronomical finding charts for Observing Blocks (OBs) on the p2 web server from the European Southern Observatory (ESO). It automates the creation of ESO-compliant finding charts for Service Mode and/or Visitor Mode OBs at the Very Large Telescope (VLT). The design of the fcmaker finding charts, based on an intimate knowledge of VLT observing procedures, is fine-tuned to best support night time operations. As an automated tool, fcmaker also allows observers to independently check visually, for the first time, the observing sequence coded inside an OB. This includes, for example, the signs of telescope and position angle offsets.

[ascl:1806.026]
BWED: Brane-world extra dimensions

Braneworld-extra-dimensions places constraints on the size of the AdS5 radius of curvature within the Randall-Sundrum brane-world model in light of the near-simultaneous detection of the gravitational wave event GW170817 and its optical counterpart, the short γ-ray burst event GRB170817A. The code requires a (supplied) patch to the Montepython cosmological MCMC sampler (ascl:1805.027) to sample the posterior distribution of the 4-dimensional parameter space in VBV17 and obtain constraints on the parameters.

[ascl:1806.025]
BRATS: Broadband Radio Astronomy ToolS

BRATS (Broadband Radio Astronomy ToolS) provides tools for the spectral analysis of broad-bandwidth radio data and legacy support for narrowband telescopes. It can fit models of spectral ageing on small spatial scales, offers automatic selection of regions based on user parameters (e.g. signal to noise), and automatic determination of the best-fitting injection index. It includes statistical testing, including Chi-squared, error maps, confidence levels and binning of model fits, and can map spectral index as a function of position. It also provides the ability to reconstruct sources at any frequency for a given model and parameter set, subtract any two FITS images and output residual maps, easily combine and scale FITS images in the image plane, and resize radio maps.

[ascl:1806.024]
RMextract: Ionospheric Faraday Rotation calculator

RMextract calculates Ionospheric Faraday Rotation for a given epoch, location and line of sight. This Python code extracts TEC, vTEC, Earthmagnetic field and Rotation Measures from GPS and WMM data for radio interferometry observations.

[ascl:1806.023]
Spheral++: Coupled hydrodynamical and gravitational numerical simulations

Spheral++ provides a steerable parallel environment for performing coupled hydrodynamical and gravitational numerical simulations. Hydrodynamics and gravity are modeled using particle-based methods (SPH and N-Body). It uses an Adaptive Smoothed Particle Hydrodynamics (ASPH) algorithm, provides a total energy conserving compatible hydro mode, and performs fluid and solid material modeling and damage and fracture modeling in solids.

[ascl:1806.022]
Keras: The Python Deep Learning library

Keras is a high-level neural networks API written in Python and capable of running on top of TensorFlow, CNTK, or Theano. It focuses on enabling fast experimentation.

[ascl:1806.021]
LASR: Linear Algorithm for Significance Reduction

LASR removes stellar variability in the light curves of δ-Scuti and similar stars. It subtracts oscillations from a time series by minimizing their statistical significance in frequency space.

[ascl:1806.020]
exoinformatics: Compute the entropy of a planetary system's size-ordering

exoinformatics computes the entropy of a planetary system's size ordering using three different entropy methods: tally-scores, integral path, and change points.

[ascl:1806.019]
SYGMA: Modeling stellar yields for galactic modeling

SYGMA (Stellar Yields for Galactic Modeling Applications) follows the ejecta of simple stellar populations as a function of time to model the enrichment and feedback from simple stellar populations. It is the basic building block of the galaxy code One-zone Model for the Evolution of GAlaxies (OMEGA, ascl:1806.018) and is part of the NuGrid Python Chemical Evolution Environment (NuPyCEE, ascl:1610.015). Stellar yields of AGB and massive stars are calculated with the same nuclear physics and are provided by the NuGrid collaboration.

[ascl:1806.018]
OMEGA: One-zone Model for the Evolution of GAlaxies

OMEGA (One-zone Model for the Evolution of GAlaxies) calculates the global chemical evolution trends of galaxies. From an input star formation history, it uses SYGMA to create as a function of time multiple simple stellar populations with different masses, ages, and initial compositions. OMEGA offers several prescriptions for modeling the star formation efficiency and the evolution of galactic inflows and outflows. OMEGA is part of the NuGrid (ascl:1610.015) chemical evolution package.

[ascl:1806.017]
RadFil: Radial density profile builder for interstellar filaments

RadFil is a radial density profile building and fitting tool for interstellar filaments. The software uses an image array and (in most cases) a boolean mask array that delineates the boundary of the filament to build and fit a radial density profile for the filaments.

[ascl:1806.016]
DirectDM-py: Dark matter direct detection

DirectDM, written in Python, takes the Wilson coefficients of relativistic operators that couple DM to the SM quarks, leptons, and gauge bosons and matches them onto a non-relativistic Galilean invariant EFT in order to calculate the direct detection scattering rates. A Mathematica implementation of DirectDM is also available (ascl:1806.015).

[ascl:1806.015]
DirectDM-mma: Dark matter direct detection

The Mathematica code DirectDM takes the Wilson coefficients of relativistic operators that couple DM to the SM quarks, leptons, and gauge bosons and matches them onto a non-relativistic Galilean invariant EFT in order to calculate the direct detection scattering rates. A Python implementation of DirectDM is also available (ascl:1806.016).

[ascl:1806.014]
pile-up: Monte Carlo simulations of star-disk torques on hot Jupiters

The pile-up gnuplot script generates a Monte Carlo simulation with a selectable number of randomized drawings (1000 by default, ~1min on a modern laptop). For each realization, the script calculates the torque acting on a hot Jupiter around a young, solar-type star as a function of the star-planet distance. The total torque on the planet is composed of the disk torque in the type II migration regime (that is, the planet is assumed to have opened up a gap in the disk) and of the stellar tidal torque. The model has four free parameters, which are drawn from a normal or lognormal distribution: (1) the disk's gas surface density at 1 astronomical unit, (2) the magnitude of tidal dissipation within the star, (3) the disk's alpha viscosity parameter, and (4) and the mean molecular weight of the gas in the disk midplane. For each realization, the total torque is screened for a distance at which it becomes zero. If present, then this distance would represent a tidal migration barrier to the planet. In other words, the planet would stop migrating. This location is added to a histogram on top of the main torque-over-distance panel and the realization is counted as one case that contributes to the overall survival rate of hot Jupiters. Finally, the script generates an output file (PDF by default) and prints the hot Jupiter survival rate for the assumed parameterization of the star-planet-disk system.

[ascl:1806.013]
SpS: Single-pulse Searcher

The presence of human-made interference mimicking the behavior of celestial radio pulses is a major challenge when searching for radio pulses emitted on millisecond timescales by celestial radio sources such as pulsars and fast radio bursts due to the highly imbalanced samples. Single-pulse Searcher (SpS) reduces the presence of radio interference when processing standard output from radio single-pulse searches to produce diagnostic plots useful for selecting good candidates. The modular software allows modifications for specific search characteristics. LOTAAS Single-pulse Searcher (L-SpS) is an implementation of different features of the software (such as a machine-learning approach) developed for a particular study: the LOFAR Tied-Array All-Sky Survey (LOTAAS).

[ascl:1806.012]
WDEC: White Dwarf Evolution Code

WDEC (White Dwarf Evolution Code), written in Fortran, offers a fast and fairly easy way to produce models of white dwarfs. The code evolves hot (~100,000 K) input models down to a chosen effective temperature by relaxing the models to be solutions of the equations of stellar structure. The code can also be used to obtain g-mode oscillation modes for the models.

[ascl:1806.011]
P2DFFT: Parallelized technique for measuring galactic spiral arm pitch angles

P2DFFT is a parallelized version of 2DFFT (ascl:1608.015). It isolates and measures the spiral arm pitch angle of galaxies. The code allows direct input of FITS images, offers the option to output inverse Fourier transform FITS images, and generates idealized logarithmic spiral test images of a specified size that have 1 to 6 arms with pitch angles of -75 degrees to 75 degrees. Further, it can output Fourier amplitude versus inner radius and pitch angle versus inner radius for each Fourier component (m = 0 to m = 6), and calculates the Fourier amplitude weighted mean pitch angle across m = 1 to m = 6 versus inner radius.

[ascl:1806.010]
SpaghettiLens: Web-based gravitational lens modeling tool

SpaghettiLens allows citizen scientists to model gravitational lenses collaboratively; the software should also be easily adaptable to any other, reasonably similar problem. It lets volunteers execute a computer intensive task that cannot be easily executed client side and relies on citizen scientists collaborating. SpaghettiLens makes survey data available to citizen scientists, manages the model configurations generated by the volunteers, stores the resulting model configuration, and delivers the actual model. A model can be shared and discussed with other volunteers and revised, and new child models can be created, resulting in a branching version tree of models that explore different possibilities. Scientists can choose a collection of models; discussion among volunteers and scientists prune the tree to determine which models will receive further analysis.

[ascl:1806.009]
GLASS: Parallel, free-form gravitational lens modeling tool and framework

GLASS models strong gravitational lenses. It produces an ensemble of possible models that fit the observed input data and conform to certain constraints specified by the user. GLASS makes heavy use of the numerical routines provided by the numpy and scipy packages as well as the linear programming package GLPK. This latter package, and its Python interface, is provided with GLASS and installs automatically in the GLASS build directory.

[ascl:1806.008]
gsf: galactic structure finder

Obreja, Aura; Macciò, Andrea V.; Moster, Benjamin; Dutton, Aaron A.; Buck, Tobias; Stinson, Gregory S.; Wang, Liang

gsf applies Gaussian Mixture Models in the stellar kinematic space of normalized angular momentum and binding energy on NIHAO high resolution galaxies to separate the stars into multiple components. The gsf analysis package assumes that the simulation snapshot has been pre-processed with a halo finder. It is based on pynbody (ascl:1305.002) and the scikit-learnpython package for Machine Learning; after loading, orienting, and transforming a simulation snapshot to physical units, it runs the clustering algorithm and performs the direct N-body gravity force using all the particles in the given halo.

[ascl:1806.007]
PyAMOR: AMmOnia data Reduction

PyAMOR models spectra of low level ammonia transitions (between (J,K)=(1,1) and (5,5)) and derives parameters such as intrinsic linewidth, optical depth, and rotation temperature. For low S/N or low spectral resolution data, the code uses cross-correlation between a model and a regridded spectrum (e.g. 10 times smaller channel width) to find the velocity, then fixes it and runs the minimization process. For high S/N data, PyAMOR runs with the velocity as a free parameter.

[ascl:1806.006]
QE: Quantum opEn-Source Package for Research in Electronic Structure, Simulation, and Optimization

Giannozzi, P.; Andreussi, O.; Baroni, S.; Bonini, Nicola; Brumme, T.; Bunau, O.; Buongiorno Nardelli, M.; Calandra, M.; Car, R.; Cavazzoni, C.; Ceresoli, D.; Chiarotti, Guido L.; Cococcioni, M.; Colonna, N.; Carnimeo, I.; Dabo, Ismaila; Dal Corso, A.; de Gironcoli, S.; Delugas, P.; DiStasio, R. A., Jr.; Fabris, Stefano; Ferretti, A.; Floris, A.; Fratesi, G.; Fugallo, G.; Gebauer, R.; Gerstmann, U.; Giustino, F.; Gorni, T.; Gougoussis, Christos; Jia, J.; Kawamura, M.; Ko, H.-Y.; Kokalj, A.; Küçükbenli, E.; Lazzeri, M.; Marsili, M.; Martin-Samos, Layla; Marzari, N.; Mauri, F.; Mazzarello, Riccardo; Nguyen, N. L.; Nguyen, H.-V.; Otero-de-la-Roza, A.; Paolini, Stefano; Pasquarello, Alfredo; Paulatto, L.; Poncé, S.; Rocca, D.; Sabatini, R.; Santra, B.; Sbraccia, Scandolo, Sandro; Carlo; Schlipf, M.; Sclauzero, Gabriele; Seitsonen, A. P.; Smogunov, A.; Timrov, I.; Thonhauser, T.; Umari, P.; Vast, N.; Wentzcovitch, Renata M.; Wu, X.

Quantum ESPRESSO (opEn-Source Package for Research in Electronic Structure, Simulation, and Optimization) is an integrated suite of codes for electronic-structure calculations and materials modeling at the nanoscale. It is based on density-functional theory, plane waves, and pseudopotentials. QE performs ground-state calculations such as self-consistent total energies, forces, stresses and Kohn-Sham orbitals, Car-Parrinello and Born-Oppenheimer molecular dynamics, and quantum transport such as ballistic transport, coherent transport from maximally localized Wannier functions, and Kubo-Greenwood electrical conductivity. It can also determine spectroscopic properties and examine time-dependent density functional perturbations and electronic excitations, and has a wide range of other functions.

[ascl:1806.005]
Indri: Pulsar population synthesis toolset

Indri models the population of single (not in binary or hierarchical systems) neutron stars. Given a starting distribution of parameters (birth place, velocity, magnetic field, and period), the code moves a set of stars through the time (by evolving spin period and magnetic field) and the space (by propagating through the Galactic potential). Upon completion of the evolution, a set of observables is computed (radio flux, position, dispersion measure) and compared with a radio survey such as the Parkes Multibeam Survey. The models' parameters are optimised by using the Markov Chain Monte Carlo technique.

[ascl:1806.004]
WiseView: Visualizing motion and variability of faint WISE sources

WiseView renders image blinks of Wide-field Infrared Survey Explorer (WISE) coadds spanning a multi-year time baseline in a browser. The software allows for easy visual identification of motion and variability for sources far beyond the single-frame detection limit, a key threshold not surmounted by many studies. WiseView transparently gathers small image cutouts drawn from many terabytes of unWISE coadds, facilitating access to this large and unique dataset. Users need only input the coordinates of interest and can interactively tune parameters including the image stretch, colormap and blink rate. WiseView was developed in the context of the Backyard Worlds: Planet 9 citizen science project, and has enabled hundreds of brown dwarf candidate discoveries by citizen scientists and professional astronomers.

[ascl:1806.003]
pyZELDA: Python code for Zernike wavefront sensors

pyZELDA analyzes data from Zernike wavefront sensors dedicated to high-contrast imaging applications. This modular software was originally designed to analyze data from the ZELDA wavefront sensor prototype installed in VLT/SPHERE; simple configuration files allow it to be extended to support several other instruments and testbeds. pyZELDA also includes simple simulation tools to measure the theoretical sensitivity of a sensor and to compare it to other sensors.

[ascl:1806.002]
BHDD: Primordial black hole binaries code

BHDD (BlackHolesDarkDress) simulates primordial black hole (PBH) binaries that are clothed in dark matter (DM) halos. The software uses N-body simulations and analytical estimates to follow the evolution of PBH binaries formed in the early Universe.

[ascl:1806.001]
feets: feATURE eXTRACTOR FOR tIME sERIES

feets characterizes and analyzes light-curves from astronomical photometric databases for modelling, classification, data cleaning, outlier detection and data analysis. It uses machine learning algorithms to determine the numerical descriptors that characterize and distinguish the different variability classes of light-curves; these range from basic statistical measures such as the mean or standard deviation to complex time-series characteristics such as the autocorrelation function. The library is not restricted to the astronomical field and could also be applied to any kind of time series. This project is a derivative work of FATS (ascl:1711.017).

[ascl:1805.032]
PyCCF: Python Cross Correlation Function for reverberation mapping studies

PyCCF emulates a Fortran program written by B. Peterson for use with reverberation mapping. The code cross correlates two light curves that are unevenly sampled using linear interpolation and measures the peak and centroid of the cross-correlation function. In addition, it is possible to run Monto Carlo iterations using flux randomization and random subset selection (RSS) to produce cross-correlation centroid distributions to estimate the uncertainties in the cross correlation results.

[ascl:1805.031]
CubiCal: Suite for fast radio interferometric calibration

CubiCal implements several accelerated gain solvers which exploit complex optimization for fast radio interferometric gain calibration. The code can be used for both direction-independent and direction-dependent self-calibration. CubiCal is implemented in Python and Cython, and multiprocessing is fully supported.

[ascl:1805.030]
PyCBC: Gravitational-wave data analysis toolkit

PyCBC analyzes data from gravitational-wave laser interferometer detectors, finds signals, and studies their parameters. It contains algorithms that can detect coalescing compact binaries and measure the astrophysical parameters of detected sources. PyCBC was used in the first direct detection of gravitational waves by LIGO and is used in the ongoing analysis of LIGO and Virgo data.

[ascl:1805.029]
DeepMoon: Convolutional neural network trainer to identify moon craters

DeepMoon trains a convolutional neural net using data derived from a global digital elevation map (DEM) and catalog of craters to recognize craters on the Moon. The TensorFlow-based pipeline code is divided into three parts. The first generates a set images of the Moon randomly cropped from the DEM, with corresponding crater positions and radii. The second trains a convnet using this data, and the third validates the convnet's predictions.

[ascl:1805.028]
SP_Ace: Stellar Parameters And Chemical abundances Estimator

SP_Ace (Stellar Parameters And Chemical abundances Estimator) estimates the stellar parameters Teff, log g, [M/H], and elemental abundances. It employs 1D stellar atmosphere models in Local Thermodynamic Equilibrium (LTE). The code is highly automated and suitable for analyzing the spectra of large spectroscopic surveys with low or medium spectral resolution (R = 2000-20 000). A web service for calculating these values with the software is also available.

[ascl:1805.027]
MontePython 3: Parameter inference code for cosmology

MontePython 3 provides numerous ways to explore parameter space using Monte Carlo Markov Chain (MCMC) sampling, including Metropolis-Hastings, Nested Sampling, Cosmo Hammer, and a Fisher sampling method. This improved version of the Monte Python (ascl:1307.002) parameter inference code for cosmology offers new ingredients that improve the performance of Metropolis-Hastings sampling, speeding up convergence and offering significant time improvement in difficult runs. Additional likelihoods and plotting options are available, as are post-processing algorithms such as Importance Sampling and Adding Derived Parameter.

[ascl:1805.026]
PySE: Python Source Extractor for radio astronomical images

Spreeuw, Hanno; Swinbank, John; Molenaar, Gijs; Staley, Tim; Rol, Evert; Sanders, John; Scheers, Bart; Kuiack, Mark

PySE finds and measures sources in radio telescope images. It is run with several options, such as the detection threshold (a multiple of the local noise), grid size, and the forced clean beam fit, followed by a list of input image files in standard FITS or CASA format. From these, PySe provides a list of found sources; information such as the calculated background image, source list in different formats (e.g. text, region files importable in DS9), and other data may be saved. PySe can be integrated into a pipeline; it was originally written as part of the LOFAR Transient Detection Pipeline (TraP, ascl:1412.011).

[ascl:1805.025]
GLACiAR: GaLAxy survey Completeness AlgoRithm

GLACiAR (GaLAxy survey Completeness AlgoRithm) estimates the completeness and selection functions in galaxy surveys. Tailored for multiband imaging surveys aimed at searching for high-redshift galaxies through the Lyman Break technique, the code can nevertheless be applied broadly. GLACiAR generates artificial galaxies that follow Sérsic profiles with different indexes and with customizable size, redshift and spectral energy distribution properties, adds them to input images, and measures the recovery rate.

[ascl:1805.024]
ASTROPOP: ASTROnomical Polarimetry and Photometry pipeline

AstroPoP reduces almost any CCD photometry and image polarimetry data. For photometry reduction, the code performs source finding, aperture and PSF photometry, astrometry calibration using different automated and non-automated methods and automated source identification and magnitude calibration based on online and local catalogs. For polarimetry, the code resolves linear and circular Stokes parameters produced by image beam splitter or polarizer polarimeters. In addition to the modular functions, ready-to-use pipelines based in configuration files and header keys are also provided with the code. AstroPOP was initially developed to reduce the IAGPOL polarimeter data installed at Observatório Pico dos Dias (Brazil).

[ascl:1805.023]
PROM7: 1D modeler of solar filaments or prominences

PROM7 is an update of PROM4 (ascl:1306.004) and computes simple models of solar prominences and filaments using Partial Radiative Distribution (PRD). The models consist of plane-parallel slabs standing vertically above the solar surface. Each model is defined by 5 parameters: temperature, density, geometrical thickness, microturbulent velocity and height above the solar surface. It solves the equations of radiative transfer, statistical equilibrium, ionization and pressure equilibria, and computes electron and hydrogen level population and hydrogen line profiles. Moreover, the code treats calcium atom which is reduced to 3 ionization states (Ca I, Ca II, CA III). Ca II ion has 5 levels which are useful for computing 2 resonance lines (H and K) and infrared triplet (to 8500 A).

[ascl:1805.022]
BCcodes: Bolometric Corrections and Synthetic Stellar Photometry

BCcodes computes bolometric corrections and synthetic colors in up to 5 filters for input values of the stellar parameters Teff, log(g), [Fe/H], E(B-V) and [alpha/Fe].

[ascl:1805.021]
PampelMuse: Crowded-field 3D spectroscopy

PampelMuse analyzes integral-field spectroscopic observations of crowded stellar fields and provides several subroutines to perform the individual steps of the data analysis. All analysis steps assume that the IFS data has been properly reduced and that all the instrumental artifacts have been removed. PampelMuse is designed to correctly handle IFS data regardless of which instrument was used to observe the data. In addition to the actual data, the software also requires an estimate of the variances for the analysis; optionally, it can use a bad pixel mask. The analysis relies on the presence of a reference catalogue, containing coordinates and magnitudes of the stars in and around the observed field.

[ascl:1805.020]
SWIFT: SPH With Inter-dependent Fine-grained Tasking

SWIFT runs cosmological simulations on peta-scale machines for solving gravity and SPH. It uses the Fast Multipole Method (FMM) to calculate gravitational forces between nearby particles, combining these with long-range forces provided by a mesh that captures both the periodic nature of the calculation and the expansion of the simulated universe. SWIFT currently uses a single fixed but time-variable softening length for all the particles. Many useful external potentials are also available, such as galaxy haloes or stratified boxes that are used in idealised problems. SWIFT implements a standard LCDM cosmology background expansion and solves the equations in a comoving frame; equations of state of dark-energy evolve with scale-factor. The structure of the code allows implementation for modified-gravity solvers or self-interacting dark matter schemes to be implemented. Many hydrodynamics schemes are implemented in SWIFT and the software allows users to add their own.

[ascl:1805.019]
HENDRICS: High ENergy Data Reduction Interface from the Command Shell

HENDRICS, a rewrite and update to MaLTPyNT (ascl:1502.021), contains command-line scripts based on Stingray (ascl:1608.001) to perform a quick-look (spectral-)timing analysis of X-ray data, treating the gaps in the data due, e.g., to occultation from the Earth or passages through the SAA, properly. Despite its original main focus on NuSTAR, HENDRICS can perform standard aperiodic timing analysis on X-ray data from, in principle, any other satellite, and its features include power density and cross spectra, time lags, pulsar searches with the Epoch folding and the Z_n^2 statistics, color-color and color-intensity diagrams. The periodograms produced by HENDRICS (such as a power density spectrum or a cospectrum) can be saved in a format compatible with XSPEC (ascl:9910.005) or ISIS (ascl:1302.002)

[ascl:1805.018]
CUBE: Information-optimized parallel cosmological N-body simulation code

CUBE, written in Coarray Fortran, is a particle-mesh based parallel cosmological N-body simulation code. The memory usage of CUBE can approach as low as 6 bytes per particle. Particle pairwise (PP) force, cosmological neutrinos, spherical overdensity (SO) halofinder are included.

[ascl:1805.017]
SNSEDextend: SuperNova Spectral Energy Distributions extrapolation toolkit

Pierel, Justin D. R.; Rodney, Steven A.; Avelino, Arturo; Bianco, Federica; Foley, Ryan J.; Friedman, Andrew; Hicken, Malcolm; Hounsell, Rebekah; Jha, Saurabh W.; Kessler, Richard; Kirshner, Robert; Mandel, Kaisey; Narayan, Gautham; Filippenko, Alexei V.; Scolnic, Daniel; Strolger, Louis-Gregory

SNSEDextend extrapolates core-collapse and Type Ia Spectral Energy Distributions (SEDs) into the UV and IR for use in simulations and photometric classifications. The user provides a library of existing SED templates (such as those in the authors' SN SED Repository) along with new photometric constraints in the UV and/or NIR wavelength ranges. The software then extends the existing template SEDs so their colors match the input data at all phases. SNSEDextend can also extend the SALT2 spectral time-series model for Type Ia SN for a "first-order" extrapolation of the SALT2 model components, suitable for use in survey simulations and photometric classification tools; as the code does not do a rigorous re-training of the SALT2 model, the results should not be relied on for precision applications such as light curve fitting for cosmology.

[ascl:1805.016]
xspec_emcee: XSPEC-friendly interface for the emcee package

XSPEC_EMCEE is an XSPEC-friendly interface for emcee (ascl:1303.002). It carries out MCMC analyses of X-ray spectra in the X-ray spectral fitting program XSPEC (ascl:9910.005). It can run multiple xspec processes simultaneously, speeding up the analysis, and can switch to parameterizing norm

parameters in log space.

[ascl:1805.015]
BinMag: Widget for comparing stellar observed with theoretical spectra

BinMag examines theoretical stellar spectra computed with Synth/SynthMag/Synmast/Synth3/SME spectrum synthesis codes and compare them to observations. An IDL widget program, BinMag applies radial velocity shift and broadening to the theoretical spectra to account for the effects of stellar rotation, radial-tangential macroturbulence, and instrumental smearing. The code can also simulate spectra of spectroscopic binary stars by appropriate coaddition of two synthetic spectra. Additionally, BinMag can be used to measure equivalent width, fit line profile shapes with analytical functions, and to automatically determine radial velocity and broadening parameters. BinMag interfaces with the Synth3 (ascl:1212.010) and SME (ascl:1202.013) codes, allowing the user to determine chemical abundances and stellar atmospheric parameters from the observed spectra.

[ascl:1805.014]
OSS: OSSOS Survey Simulator

Comparing properties of discovered trans-Neptunian Objects (TNOs) with dynamical models is impossible due to the observational biases that exist in surveys. The OSSOS Survey Simulator takes an intrinsic orbital model (from, for example, the output of a dynamical Kuiper belt emplacement simulation) and applies the survey biases, so the biased simulated objects can be directly compared with real discoveries.

[ascl:1805.012]
Arcmancer: Geodesics and polarized radiative transfer library

Arcmancer computes geodesics and performs polarized radiative transfer in user-specified spacetimes. The library supports Riemannian and semi-Riemannian spaces of any dimension and metric; it also supports multiple simultaneous coordinate charts, embedded geometric shapes, local coordinate systems, and automatic parallel propagation. Arcmancer can be used to solve various problems in numerical geometry, such as solving the curve equation of motion using adaptive integration with configurable tolerances and differential equations along precomputed curves. It also provides support for curves with an arbitrary acceleration term and generic tools for generating ray initial conditions and performing parallel computation over the image, among other tools.

[ascl:1805.011]
PoMiN: A Post-Minkowskian N-Body Solver

PoMiN is a lightweight N-body code based on the Post-Minkowskian N-body Hamiltonian of Ledvinka, Schafer, and Bicak, which includes General Relativistic effects up to first order in Newton's constant G, and all orders in the speed of light c. PoMiN is a single file written in C and uses a fourth-order Runge-Kutta integration scheme. PoMiN has also been written to handle an arbitrary number of particles (both massive and massless) with a computational complexity that scales as O(N^2).

[ascl:1805.010]
StarSmasher: Smoothed Particle Hydrodynamics code for smashing stars and planets

Smoothed Particle Hydrodynamics (SPH) is a Lagrangian particle method that approximates a continuous fluid as discrete nodes, each carrying various parameters such as mass, position, velocity, pressure, and temperature. In an SPH simulation the resolution scales with the particle density; StarSmasher is able to handle both equal-mass and equal number-density particle models. StarSmasher solves for hydro forces by calculating the pressure for each particle as a function of the particle's properties - density, internal energy, and internal properties (e.g. temperature and mean molecular weight). The code implements variational equations of motion and libraries to calculate the gravitational forces between particles using direct summation on NVIDIA graphics cards. Using a direct summation instead of a tree-based algorithm for gravity increases the accuracy of the gravity calculations at the cost of speed. The code uses a cubic spline for the smoothing kernel and an artificial viscosity prescription coupled with a Balsara Switch to prevent unphysical interparticle penetration. The code also implements an artificial relaxation force to the equations of motion to add a drag term to the calculated accelerations during relaxation integrations. Initially called StarCrash, StarSmasher was developed originally by Rasio.

[ascl:1805.009]
STARBLADE: STar and Artefact Removal with a Bayesian Lightweight Algorithm from Diffuse Emission

STARBLADE (STar and Artefact Removal with a Bayesian Lightweight Algorithm from Diffuse Emission) separates superimposed point-like sources from a diffuse background by imposing physically motivated models as prior knowledge. The algorithm can also be used on noisy and convolved data, though performing a proper reconstruction including a deconvolution prior to the application of the algorithm is advised; the algorithm could also be used within a denoising imaging method. STARBLADE learns the correlation structure of the diffuse emission and takes it into account to determine the occurrence and strength of a superimposed point source.

[ascl:1805.008]
AGAMA: Action-based galaxy modeling framework

The AGAMA library is a collection of tools for constructing and analyzing models of galaxies. It computes gravitational potential and forces, performs orbit integration and analysis, and can convert between position/velocity and action/angle coordinates. It offers a framework for finding best-fit parameters of a model from data and self-consistent multi-component galaxy models, and contains useful auxiliary utilities such as various mathematical routines. The core of the library is written in C++, and there are Python and Fortran interfaces. AGAMA may be used as a plugin for the stellar-dynamical software packages galpy (ascl:1411.008), AMUSE (ascl:1107.007), and NEMO (ascl:1010.051).

[ascl:1805.007]
exocartographer: Constraining surface maps orbital parameters of exoplanets

exocartographer solves the exo-cartography inverse problem. This flexible forward-modeling framework, written in Python, retrieves the albedo map and spin geometry of a planet based on time-resolved photometry; it uses a Markov chain Monte Carlo method to extract albedo maps and planet spin and their uncertainties. Gaussian Processes use the data to fit for the characteristic length scale of the map and enforce smooth maps.

[ascl:1805.006]
StePS: Stereographically Projected Cosmological Simulations

StePS (Stereographically Projected Cosmological Simulations) compactifies the infinite spatial extent of the Universe into a finite sphere with isotropic boundary conditions to simulate the evolution of the large-scale structure. This eliminates the need for periodic boundary conditions, which are a numerical convenience unsupported by observation and which modifies the law of force on large scales in an unrealistic fashion. StePS uses stereographic projection for space compactification and naive O(N2) force calculation; this arrives at a correlation function of the same quality more quickly than standard (tree or P3M) algorithms with similar spatial and mass resolution. The N2 force calculation is easy to adapt to modern graphics cards, hence StePS can function as a high-speed prediction tool for modern large-scale surveys.

[ascl:1805.005]
3DCORE: Forward modeling of solar storm magnetic flux ropes for space weather prediction

Möstl, C.; Amerstorfer, T.; Palmerio, E.; Isavnin, A.; Farrugia, C. J.; Lowder, C.; Winslow, R. M.; Donnerer, J. M.; Kilpua, E. K. J.; Boakes, P. D.

3DCORE forward models solar storm magnetic flux ropes called 3-Dimensional Coronal Rope Ejection (3DCORE). The code is able to produce synthetic in situ observations of the magnetic cores of solar coronal mass ejections sweeping over planets and spacecraft. Near Earth, these data are taken currently by the Wind, ACE and DSCOVR spacecraft. Other suitable spacecraft making these kind of observations carrying magnetometers in the solar wind were MESSENGER, Venus Express, MAVEN, and even Helios.

[ascl:1805.004]
EARL: Exoplanet Analytic Reflected Lightcurves package

EARL (Exoplanet Analytic Reflected Lightcurves) computes the analytic form of a reflected lightcurve, given a spherical harmonic decomposition of the planet albedo map and the viewing and orbital geometries. The EARL Mathematica notebook allows rapid computation of reflected lightcurves, thus making lightcurve numerical experiments accessible.

[ascl:1805.003]
lcps: Light curve pre-selection

lcps searches for transit-like features (i.e., dips) in photometric data. Its main purpose is to restrict large sets of light curves to a number of files that show interesting behavior, such as drops in flux. While lcps is adaptable to any format of time series, its I/O module is designed specifically for photometry of the Kepler spacecraft. It extracts the pre-conditioned PDCSAP data from light curves files created by the standard Kepler pipeline. It can also handle csv-formatted ascii files. lcps uses a sliding window technique to compare a section of flux time series with its surroundings. A dip is detected if the flux within the window is lower than a threshold fraction of the surrounding fluxes.

[ascl:1805.002]
dftools: Distribution function fitting

dftools, written in R, finds the most likely P parameters of a D-dimensional distribution function (DF) generating N objects, where each object is specified by D observables with measurement uncertainties. For instance, if the objects are galaxies, it can fit a mass function (D=1), a mass-size distribution (D=2) or the mass-spin-morphology distribution (D=3). Unlike most common fitting approaches, this method accurately accounts for measurement in uncertainties and complex selection functions.

[ascl:1805.001]
powerbox: Arbitrarily structured, arbitrary-dimension boxes and log-normal mocks

powerbox creates density grids (or boxes) with an arbitrary two-point distribution (i.e. power spectrum). The software works in any number of dimensions, creates Gaussian or Log-Normal fields, and measures power spectra of output fields to ensure consistency. The primary motivation for creating the code was the simple creation of log-normal mock galaxy distributions, but the methodology can be used for other applications.

[submitted]
pydftools: Distribution function fitting in Python

pydftools is a pure-python port of the dftools R package (ascl:1805.002), which finds the most likely P parameters of a D-dimensional distribution function (DF) generating N objects, where each object is specified by D observables with measurement uncertainties. For instance, if the objects are galaxies, it can fit a MF (P=1), a mass-size distribution (P=2) or the mass-spin-morphology distribution (P=3). Unlike most common fitting approaches, this method accurately accounts for measurement in uncertainties and complex selection functions. Though this package imitates the dftools package quite closely while being as Pythonic as possible, it has not implemented 2D+ nor non-parametric.

[ascl:1804.026]
KSTAT: KD-tree Statistics Package

KSTAT calculates the 2 and 3-point correlation functions in discreet point data. These include the two-point correlation function in 2 and 3-dimensions, the anisotripic 2PCF decomposed in either sigma-pi or Kazin's dist. mu projection. The 3-point correlation function can also work in anisotropic coordinates. The code is based on kd-tree structures and is parallelized using a mixture of MPI and OpenMP.

[ascl:1804.025]
FastChem: An ultra-fast equilibrium chemistry

FastChem is an equilibrium chemistry code that calculates the chemical composition of the gas phase for given temperatures and pressures. Written in C++, it is based on a semi-analytic approach, and is optimized for extremely fast and accurate calculations.

[ascl:1804.024]
LFlGRB: Luminosity function of long gamma-ray bursts

LFlGRB models the luminosity function (LF) of long Gamma Ray Bursts (lGRBs) by using a sample of Swift and Fermi lGRBs to re-derive the parameters of the Yonetoku correlation and self-consistently estimate pseudo-redshifts of all the bursts with unknown redshifts. The GRB formation rate is modeled as the product of the cosmic star formation rate and a GRB formation efficiency for a given stellar mass.

[ascl:1804.023]
LFsGRB: Binary neutron star merger rate via the luminosity function of short gamma-ray bursts

LFsGRB models the luminosity function (LF) of short Gamma Ray Bursts (sGRBs) by using the available catalog data of all short GRBs (sGRBs) detected till 2017 October, estimating the luminosities via pseudo-redshifts obtained from the Yonetoku correlation, and then assuming a standard delay distribution between the cosmic star formation rate and the production rate of their progenitors. The data are fit well both by exponential cutoff powerlaw and broken powerlaw models. Using the derived parameters of these models along with conservative values in the jet opening angles seen from afterglow observations, the true rate of short GRBs is derived. Assuming a short GRB is produced from each binary neutron star merger (BNSM), the rate of gravitational wave (GW) detections from these mergers are derived for the past, present and future configurations of the GW detector networks.

[ascl:1804.022]
UniDAM: Unified tool to estimate Distances, Ages, and Masses

UniDAM obtains a homogenized set of stellar parameters from spectrophotometric data of different surveys. Parallax and extinction data can be incorporated into the isochrone fitting method used in UniDAM to reduce distance and age estimate uncertainties for TGAS stars for distances up to 1 kpc and decrease distance Gaia end-of-mission parallax uncertainties by about a factor of 20 and age uncertainties by a factor of two for stars up to 10 kpc away from the Sun.

[ascl:1804.021]
allantools: Allan deviation calculation

allantools calculates Allan deviation and related time & frequency statistics. The library is written in Python and has a GPL v3+ license. It takes input data that is either evenly spaced observations of either fractional frequency, or phase in seconds. Deviations are calculated for given tau values in seconds. Several noise generators for creating synthetic datasets are also included.

[ascl:1804.020]
Agatha: Disentangling period signals from correlated noise in a periodogram framework

Agatha is a framework of periodograms to disentangle periodic signals from correlated noise and to solve the two-dimensional model selection problem: signal dimension and noise model dimension. These periodograms are calculated by applying likelihood maximization and marginalization and combined in a self-consistent way. Agatha can be used to select the optimal noise model and to test the consistency of signals in time and can be applied to time series analyses in other astronomical and scientific disciplines. An interactive web implementation of the software is also available at http://agatha.herts.ac.uk/.

[ascl:1804.019]
ViSBARD: Visual System for Browsing, Analysis and Retrieval of Data

Roberts, D. Aaron; Boller, Ryan; Rezapkin, V.; Coleman, J.; McGuire, R.; Goldstein, M.; Kalb, V.; Kulkarni, R.; Luckyanova, M.; Byrnes, J.; Kerbel, U.; Candey, R.; Holmes, C.; Chimiak, R.; Harris, B.

ViSBARD interactively visualizes and analyzes space physics data. It provides an interactive integrated 3-D and 2-D environment to determine correlations between measurements across many spacecraft. It supports a variety of spacecraft data products and MHD models and is easily extensible to others. ViSBARD provides a way of visualizing multiple vector and scalar quantities as measured by many spacecraft at once. The data are displayed three-dimesionally along the orbits which may be displayed either as connected lines or as points. The data display allows the rapid determination of vector configurations, correlations between many measurements at multiple points, and global relationships. With the addition of magnetohydrodynamic (MHD) model data, this environment can also be used to validate simulation results with observed data, use simulated data to provide a global context for sparse observed data, and apply feature detection techniques to the simulated data.

[ascl:1804.018]
3DView: Space physics data visualizer

Génot, V.; Beigbeder, L.; Popescu, D.; Dufourg, N.; Gangloff, M.; Bouchemit, M.; Caussarieu, S.; Toniutti, J.-P.; Durand, J.; Modolo, R.; André, N.; Cecconi, B.; Jacquey, C.; Pitout, F.; Rouillard, A.; Pinto, R.; Erard, S.; Jourdane, N.; Leclercq, L.; Hess, S.; Khodachenko, M.; Al-Ubaidi, T.; Scherf, M.; Budnik, E.

3DView creates visualizations of space physics data in their original 3D context. Time series, vectors, dynamic spectra, celestial body maps, magnetic field or flow lines, and 2D cuts in simulation cubes are among the variety of data representation enabled by 3DView. It offers direct connections to several large databases and uses VO standards; it also allows the user to upload data. 3DView's versatility covers a wide range of space physics contexts.

[ascl:1804.017]
APPHi: Automated Photometry Pipeline for High Cadence Large Volume Data

Sánchez, E.; Castro, J.; Silva, J.; Hernández, J.; Reyes, M.; Hernández, B.; Alvarez, F.; García, T.

APPHi (Automated Photometry Pipeline) carries out aperture and differential photometry of TAOS-II project data. It is computationally efficient and can be used also with other astronomical wide-field image data. APPHi works with large volumes of data and handles both FITS and HDF5 formats. Due the large number of stars that the software has to handle in an enormous number of frames, it is optimized to automatically find the best value for parameters to carry out the photometry, such as mask size for aperture, size of window for extraction of a single star, and the number of counts for the threshold for detecting a faint star. Although intended to work with TAOS-II data, APPHi can analyze any set of astronomical images and is a robust and versatile tool to performing stellar aperture and differential photometry.

[ascl:1804.016]
surrkick: Black-hole kicks from numerical-relativity surrogate models

surrkick quickly and reliably extract recoils imparted to generic, precessing, black hole binaries. It uses a numerical-relativity surrogate model to obtain the gravitational waveform given a set of binary parameters, and from this waveform directly integrates the gravitational-wave linear momentum flux. This entirely bypasses the need of fitting formulae which are typically used to model black-hole recoils in astrophysical contexts.

[ascl:1804.015]
NR-code: Nonlinear reconstruction code

NR-code applies nonlinear reconstruction to the dark matter density field in redshift space and solves for the nonlinear mapping from the initial Lagrangian positions to the final redshift space positions; this reverses the large-scale bulk flows and improves the precision measurement of the baryon acoustic oscillations (BAO) scale.

[ascl:1804.014]
IMNN: Information Maximizing Neural Networks

This software trains artificial neural networks to find non-linear functionals of data that maximize Fisher information: information maximizing neural networks (IMNNs). As compressing large data sets vastly simplifies both frequentist and Bayesian inference, important information may be inadvertently missed. Likelihood-free inference based on automatically derived IMNN summaries produces summaries that are good approximations to sufficient statistics. IMNNs are robustly capable of automatically finding optimal, non-linear summaries of the data even in cases where linear compression fails: inferring the variance of Gaussian signal in the presence of noise, inferring cosmological parameters from mock simulations of the Lyman-α forest in quasar spectra, and inferring frequency-domain parameters from LISA-like detections of gravitational waveforms. In this final case, the IMNN summary outperforms linear data compression by avoiding the introduction of spurious likelihood maxima.

[ascl:1804.013]
CAT-PUMA: CME Arrival Time Prediction Using Machine learning Algorithms

CAT-PUMA (CME Arrival Time Prediction Using Machine learning Algorithms) quickly and accurately predicts the arrival of Coronal Mass Ejections (CMEs) of CME arrival time. The software was trained via detailed analysis of CME features and solar wind parameters using 182 previously observed geo-effective partial-/full-halo CMEs and uses algorithms of the Support Vector Machine (SVM) to make its predictions, which can be made within minutes of providing the necessary input parameters of a CME.

[ascl:1804.012]
Lenstronomy: Multi-purpose gravitational lens modeling software package

Lenstronomy is a multi-purpose open-source gravitational lens modeling python package. Lenstronomy reconstructs the lens mass and surface brightness distributions of strong lensing systems using forward modelling and supports a wide range of analytic lens and light models in arbitrary combination. The software is also able to reconstruct complex extended sources as well as point sources. Lenstronomy is flexible and numerically accurate, with a clear user interface that could be deployed across different platforms. Lenstronomy has been used to derive constraints on dark matter properties in strong lenses, measure the expansion history of the universe with time-delay cosmography, measure cosmic shear with Einstein rings, and decompose quasar and host galaxy light.

[ascl:1804.011]
DESCQA: Synthetic Sky Catalog Validation Framework

Mao, Yao-Yuan; Uram, Thomas D.; Zhou, Rongpu; Kovacs, Eve; Ricker, Paul M.; Kalmbach, J. Bryce; Padilla, Nelson; Lanusse, François; Zu, Ying; Tenneti, Ananth; Vikraman, Vinu; DeRose, Joseph

The DESCQA framework provides rigorous validation protocols for assessing the quality of high-quality simulated sky catalogs in a straightforward and comprehensive way. DESCQA enables the inspection, validation, and comparison of an inhomogeneous set of synthetic catalogs via the provision of a common interface within an automated framework. An interactive web interface is also available at portal.nersc.gov/project/lsst/descqa.

[ascl:1804.010]
SMERFS: Stochastic Markov Evaluation of Random Fields on the Sphere

SMERFS (Stochastic Markov Evaluation of Random Fields on the Sphere) creates large realizations of random fields on the sphere. It uses a fast algorithm based on Markov properties and fast Fourier Transforms in 1d that generates samples on an n *X* n grid in O(*n*^{2} log *n*) and efficiently derives the necessary conditional covariance matrices.

[ascl:1804.009]
orbit-estimation: Fast orbital parameters estimator

orbit-estimation tests and evaluates the Stäckel approximation method for estimating orbit parameters in galactic potentials. It relies on the approximation of the Galactic potential as a Stäckel potential, in a prolate confocal coordinate system, under which the vertical and horizontal motions decouple. By solving the Hamilton Jacobi equations at the turning points of the horizontal and vertical motions, it is possible to determine the spatial boundary of the orbit, and hence calculate the desired orbit parameters.

[ascl:1804.008]
EGG: Empirical Galaxy Generator

Schreiber, C.; Elbaz, D.; Pannella, M.; Merlin, E.; Castellano, M.; Fontana, A.; Bourne, N.; Boutsia, K.; Cullen, F.; Dunlop, J.; Ferguson, H. C.; Michałowski, M. J.; Okumura, K.; Santini, P.; Shu, X. W.; Wang, T.; White, C.

The Empirical Galaxy Generator (EGG) generates fake galaxy catalogs and images with realistic positions, morphologies and fluxes from the far-ultraviolet to the far-infrared. The catalogs are generated by egg-gencat and stored in binary FITS tables (column oriented). Another program, egg-2skymaker, is used to convert the generated catalog into ASCII tables suitable for ingestion by SkyMaker (ascl:1010.066) to produce realistic high resolution images (e.g., Hubble-like), while egg-gennoise and egg-genmap can be used to generate the low resolution images (e.g., Herschel-like). These tools can be used to test source extraction codes, or to evaluate the reliability of any map-based science (stacking, dropout identification, etc.).

[ascl:1804.007]
chroma: Chromatic effects for LSST weak lensing

Chroma investigates biases originating from two chromatic effects in the atmosphere: differential chromatic refraction (DCR), and wavelength dependence of seeing. These biases arise when using the point spread function (PSF) measured with stars to estimate the shapes of galaxies with different spectral energy distributions (SEDs) than the stars.

[ascl:1804.006]
ProFound: Source Extraction and Application to Modern Survey Data

ProFound detects sources in noisy images, generates segmentation maps identifying the pixels belonging to each source, and measures statistics like flux, size, and ellipticity. These inputs are key requirements of ProFit (ascl:1612.004), our galaxy profiling package; these two packages used in unison semi-automatically profile large samples of galaxies. The key novel feature introduced in ProFound is that all photometry is executed on dilated segmentation maps that fully contain the identifiable flux, rather than using more traditional circular or ellipse-based photometry. Also, to be less sensitive to pathological segmentation issues, the de-blending is made across saddle points in flux. ProFound offers good initial parameter estimation for ProFit, and also segmentation maps that follow the sometimes complex geometry of resolved sources, whilst capturing nearly all of the flux. A number of bulge-disc decomposition projects are already making use of the ProFound and ProFit pipeline.

[ascl:1804.005]
DaCHS: Data Center Helper Suite

DaCHS, the Data Center Helper Suite, is an integrated package for publishing astronomical data sets to the Virtual Observatory. Network-facing, it speaks the major VO protocols (SCS, SIAP, SSAP, TAP, Datalink, etc). Operator-facing, many input formats, including FITS/WCS, ASCII files, and VOTable, can be processed to publication-ready data. DaCHS puts particular emphasis on integrated metadata handling, which facilitates a tight integration with the VO's Registry

[ascl:1804.004]
AstroCV: Astronomy computer vision library

AstroCV processes and analyzes big astronomical datasets, and is intended to provide a community repository of high performance Python and C++ algorithms used for image processing and computer vision. The library offers methods for object recognition, segmentation and classification, with emphasis in the automatic detection and classification of galaxies.

[ascl:1804.003]
DPPP: Default Pre-Processing Pipeline

DPPP (Default Pre-Processing Pipeline, also referred to as NDPPP) reads and writes radio-interferometric data in the form of Measurement Sets, mainly those that are created by the LOFAR telescope. It goes through visibilities in time order and contains standard operations like averaging, phase-shifting and flagging bad stations. Between the steps in a pipeline, the data is not written to disk, making this tool suitable for operations where I/O dominates. More advanced procedures such as gain calibration are also included. Other computing steps can be provided by loading a shared library; currently supported external steps are the AOFlagger (ascl:1010.017) and a bridge that enables loading python steps.

[ascl:1804.002]
ipole: Semianalytic scheme for relativistic polarized radiative transport

ipole is a ray-tracing code for covariant, polarized radiative transport particularly useful for modeling Event Horizon Telescope sources, though may also be used for other relativistic transport problems. The code extends the ibothros scheme for covariant, unpolarized transport using two representations of the polarized radiation field: in the coordinate frame, it parallel transports the coherency tensor, and in the frame of the plasma, it evolves the Stokes parameters under emission, absorption, and Faraday conversion. The transport step is as spacetime- and coordinate- independent as possible; the emission, absorption, and Faraday conversion step is implemented using an analytic solution to the polarized transport equation with constant coefficients. As a result, ipole is stable, efficient, and produces a physically reasonable solution even for a step with high optical depth and Faraday depth.

[ascl:1804.001]
ASERA: A Spectrum Eye Recognition Assistant

ASERA, ASpectrum Eye Recognition Assistant, aids in quasar spectral recognition and redshift measurement and can also be used to recognize various types of spectra of stars, galaxies and AGNs (Active Galactic Nucleus). This interactive software allows users to visualize observed spectra, superimpose template spectra from the Sloan Digital Sky Survey (SDSS), and interactively access related spectral line information. ASERA is an efficient and user-friendly semi-automated toolkit for the accurate classification of spectra observed by LAMOST (the Large Sky Area Multi-object Fiber Spectroscopic Telescope) and is available as a standalone Java application and as a Java applet. The software offers several functions, including wavelength and flux scale settings, zoom in and out, redshift estimation, and spectral line identification.

[ascl:1803.015]
RAPTOR: Imaging code for relativistic plasmas in strong gravity

Bronzwaer, Thomas; Davelaar, Jordy; Younsi, Ziri; Mościbrodzka, Monika; Falcke, Heino; Kramer, Michael; Rezzolla, Luciano

RAPTOR produces accurate images, animations, and spectra of relativistic plasmas in strong gravity by numerically integrating the equations of motion of light rays and performing time-dependent radiative transfer calculations along the rays. The code is compatible with any analytical or numerical spacetime, is hardware-agnostic and may be compiled and run on both GPUs and CPUs. RAPTOR is useful for studying accretion models of supermassive black holes, performing time-dependent radiative transfer through general relativistic magneto-hydrodynamical (GRMHD) simulations and investigating the expected observational differences between the so-called fastlight and slow-light paradigms.

[ascl:1803.014]
ExoCross: Spectra from molecular line lists

ExoCross generates spectra and thermodynamic properties from molecular line lists in ExoMol, HITRAN, or several other formats. The code is parallelized and also shows a high degree of vectorization; it works with line profiles such as Doppler, Lorentzian and Voigt and supports several broadening schemes. ExoCross is also capable of working with the recently proposed method of super-lines. It supports calculations of lifetimes, cooling functions, specific heats and other properties. ExoCross converts between different formats, such as HITRAN, ExoMol and Phoenix, and simulates non-LTE spectra using a simple two-temperature approach. Different electronic, vibronic or vibrational bands can be simulated separately using an efficient filtering scheme based on the quantum numbers.

[ascl:1803.013]
optBINS: Optimal Binning for histograms

optBINS (optimal binning) determines the optimal number of bins in a uniform bin-width histogram by deriving the posterior probability for the number of bins in a piecewise-constant density model after assigning a multinomial likelihood and a non-informative prior. The maximum of the posterior probability occurs at a point where the prior probability and the the joint likelihood are balanced. The interplay between these opposing factors effectively implements Occam's razor by selecting the most simple model that best describes the data.

[ascl:1803.012]
LWPC: Long Wavelength Propagation Capability

Long Wavelength Propagation Capability (LWPC), written as a collection of separate programs that perform unique actions, generates geographical maps of signal availability for coverage analysis. The program makes it easy to set up these displays by automating most of the required steps. The user specifies the transmitter location and frequency, the orientation of the transmitting and receiving antennae, and the boundaries of the operating area. The program automatically selects paths along geographic bearing angles to ensure that the operating area is fully covered. The diurnal conditions and other relevant geophysical parameters are then determined along each path. After the mode parameters along each path are determined, the signal strength along each path is computed. The signal strength along the paths is then interpolated onto a grid overlying the operating area. The final grid of signal strength values is used to display the signal-strength in a geographic display. The LWPC uses character strings to control programs and to specify options. The control strings have the same meaning and use among all the programs.

[ascl:1803.011]
ExtLaw_H18: Extinction law code

Hosek, Matthew W., Jr.; Lu, Jessica R.; Anderson, Jay; Do, Tuan; Schlafly, Edward F.; Ghez, Andrea M.; Clarkson, William I.; Morris, Mark R.; Albers, Saundra M.

ExtLaw_H18 generates the extinction law between 0.8 - 2.2 microns. The law is derived using the Westerlund 1 (Wd1) main sequence (A_Ks ~ 0.6 mag) and Arches cluster field Red Clump at the Galactic Center (A_Ks ~ 2.7 mag). To derive the law a Wd1 cluster age of 5 Myr is assumed, though changing the cluster age between 4 Myr -- 7 Myr has no effect on the law. This extinction law can be applied to highly reddened stellar populations that have similar foreground material as Wd1 and the Arches RC, namely dust from the spiral arms of the Milky Way in the Galactic Plane.

[ascl:1803.010]
3D-PDR: Three-dimensional photodissociation region code

3D-PDR is a three-dimensional photodissociation region code written in Fortran. It uses the Sundials package (written in C) to solve the set of ordinary differential equations and it is the successor of the one-dimensional PDR code UCL_PDR (ascl:1303.004). Using the HEALpix ray-tracing scheme (ascl:1107.018), 3D-PDR solves a three-dimensional escape probability routine and evaluates the attenuation of the far-ultraviolet radiation in the PDR and the propagation of FIR/submm emission lines out of the PDR. The code is parallelized (OpenMP) and can be applied to 1D and 3D problems.

[ascl:1803.009]
SETI-EC: SETI Encryption Code

The SETI Encryption code, written in Python, creates a message for use in testing the decryptability of a simulated incoming interstellar message. The code uses images in a portable bit map (PBM) format, then writes the corresponding bits into the message, and finally returns both a PBM image and a text (TXT) file of the entire message. The natural constants (c, G, h) and the wavelength of the message are defined in the first few lines of the code, followed by the reading of the input files and their conversion into 757 strings of 359 bits to give one page. Each header of a page, i.e. the little-endian binary code translation of the tempo-spatial yardstick, is calculated and written on-the-fly for each page.

[ascl:1803.008]
FAST: Fitting and Assessment of Synthetic Templates

Kriek, Mariska; van Dokkum, Pieter G.; Labbé, Ivo; Franx, Marijn; Illingworth, Garth D.; Marchesini, Danilo; Quadri, Ryan F.; Aird, James; Coil, Alison L.; Georgakakis, Antonis

FAST (Fitting and Assessment of Synthetic Templates) fits stellar population synthesis templates to broadband photometry and/or spectra. FAST is compatible with the photometric redshift code EAzY (ascl:1010.052) when fitting broadband photometry; it uses the photometric redshifts derived by EAzY, and the input files (for examply, photometric catalog and master filter file) are the same. FAST fits spectra in combination with broadband photometric data points or simultaneously fits two components, allowing for an AGN contribution in addition to the host galaxy light. Depending on the input parameters, FAST outputs the best-fit redshift, age, dust content, star formation timescale, metallicity, stellar mass, star formation rate (SFR), and their confidence intervals. Though some of FAST's functions overlap with those of HYPERZ (ascl:1108.010), it differs by fitting fluxes instead of magnitudes, allows the user to completely define the grid of input stellar population parameters and easily input photometric redshifts and their confidence intervals, and calculates calibrated confidence intervals for all parameters. Note that FAST is not a photometric redshift code, though it can be used as one.

[ascl:1803.007]
IMAGINE: Interstellar MAGnetic field INference Engine

IMAGINE (Interstellar MAGnetic field INference Engine) performs inference on generic parametric models of the Galaxy. The modular open source framework uses highly optimized tools and technology such as the MultiNest sampler (ascl:1109.006) and the information field theory framework NIFTy (ascl:1302.013) to create an instance of the Milky Way based on a set of parameters for physical observables, using Bayesian statistics to judge the mismatch between measured data and model prediction. The flexibility of the IMAGINE framework allows for simple refitting for newly available data sets and makes state-of-the-art Bayesian methods easily accessible particularly for random components of the Galactic magnetic field.

[ascl:1803.006]
MulensModel: Microlensing light curves modeling

MulensModel calculates light curves of microlensing events. Both single and binary lens events are modeled and various higher-order effects can be included: extended source (with limb-darkening), annual microlensing parallax, and satellite microlensing parallax. The code is object-oriented and written in Python3, and requires AstroPy (ascl:1304.002).

[ascl:1803.005]
Kadenza: Kepler/K2 Raw Cadence Data Reader

Kadenza enables time-critical data analyses to be carried out using NASA's Kepler Space Telescope. It enables users to convert Kepler's raw data files into user-friendly Target Pixel Files upon downlink from the spacecraft. The primary motivation for this tool is to enable the microlensing, supernova, and exoplanet communities to create quicklook lightcurves for transient events which require rapid follow-up.

[ascl:1803.004]
nanopipe: Calibration and data reduction pipeline for pulsar timing

nanopipe is a data reduction pipeline for calibration, RFI removal, and pulse time-of-arrival measurement from radio pulsar data. It was developed primarily for use by the NANOGrav project. nanopipe is written in Python, and depends on the PSRCHIVE (ascl:1105.014) library.

[ascl:1803.003]
scarlet: Source separation in multi-band images by Constrained Matrix Factorization

Melchior, Peter; Moolekamp, Fred; Jerdee, Maximilian; Armstrong, Robert; Sun, Ai-Lei; Bosch, James; Lupton, Robert

SCARLET performs source separation (aka "deblending") on multi-band images. It is geared towards optical astronomy, where scenes are composed of stars and galaxies, but it is straightforward to apply it to other imaging data. Separation is achieved through a constrained matrix factorization, which models each source with a Spectral Energy Distribution (SED) and a non-parametric morphology, or multiple such components per source. The code performs forced photometry (with PSF matching if needed) using an optimal weight function given by the signal-to-noise weighted morphology across bands. The approach works well if the sources in the scene have different colors and can be further strengthened by imposing various additional constraints/priors on each source. Because of its generic utility, this package provides a stand-alone implementation that contains the core components of the source separation algorithm. However, the development of this package is part of the LSST Science Pipeline; the meas_deblender package contains a wrapper to implement the algorithms here for the LSST stack.

[ascl:1803.002]
CIFOG: Cosmological Ionization Fields frOm Galaxies

CIFOG is a versatile MPI-parallelised semi-numerical tool to perform simulations of the Epoch of Reionization. From a set of evolving cosmological gas density and ionizing emissivity fields, it computes the time and spatially dependent ionization of neutral hydrogen (HI), neutral (HeI) and singly ionized helium (HeII) in the intergalactic medium (IGM). The code accounts for HII, HeII, HeIII recombinations, and provides different descriptions for the photoionization rate that are used to calculate the residual HI fraction in ionized regions. This tool has been designed to be coupled to semi-analytic galaxy formation models or hydrodynamical simulations. The modular fashion of the code allows the user to easily introduce new descriptions for recombinations and the photoionization rate.

[ascl:1803.001]
DaMaSCUS-CRUST: Dark Matter Simulation Code for Underground Scatterings - Crust Edition

DaMaSCUS-CRUST determines the critical cross-section for strongly interacting DM for various direct detection experiments systematically and precisely using Monte Carlo simulations of DM trajectories inside the Earth's crust, atmosphere, or any kind of shielding. Above a critical dark matter-nucleus scattering cross section, any terrestrial direct detection experiment loses sensitivity to dark matter, since the Earth crust, atmosphere, and potential shielding layers start to block off the dark matter particles. This critical cross section is commonly determined by describing the average energy loss of the dark matter particles analytically. However, this treatment overestimates the stopping power of the Earth crust; therefore, the obtained bounds should be considered as conservative. DaMaSCUS-CRUST is a modified version of DaMaSCUS (ascl:1706.003) that accounts for shielding effects and returns a precise exclusion band.

[ascl:1802.016]
eqpair: Electron energy distribution calculator

eqpair computes the electron energy distribution resulting from a balance between heating and direct acceleration of particles, and cooling processes. Electron-positron pair balance, bremstrahlung, and Compton cooling, including external soft photon input, are among the processes considered, and the final electron distribution can be hybrid, thermal, or non-thermal.

[ascl:1802.015]
mrpy: Renormalized generalized gamma distribution for HMF and galaxy ensemble properties comparisons

mrpy calculates the MRP parameterization of the Halo Mass Function. It calculates basic statistics of the truncated generalized gamma distribution (TGGD) with the TGGD class, including mean, mode, variance, skewness, pdf, and cdf. It generates MRP quantities with the MRP class, such as differential number counts and cumulative number counts, and offers various methods for generating normalizations. It can generate the MRP-based halo mass function as a function of physical parameters via the mrp_b13 function, and fit MRP parameters to data in the form of arbitrary curves and in the form of a sample of variates with the SimFit class. mrpy also calculates analytic hessians and jacobians at any point, and allows the user to alternate parameterizations of the same form via the reparameterize module.

[ascl:1802.014]
collapse: Spherical-collapse model code

collapse calculates the spherical−collapse for standard cosmological models as well as for dark energy models when the dark energy can be taken to be spatially homogeneous. The calculation is valid on sub−horizon scales and takes a top−hat perturbation to exist in an otherwise featureless cosmos and follows its evolution into the non−linear regime where it reaches a maximum size and then recollapses. collapse provides the user with the linear−collapse threshold (delta_c) and the virial overdensity (Delta_v) for the collapsed halo over a range of cosmic scale factors.

[ascl:1802.013]
BHMcalc: Binary Habitability Mechanism Calculator

BHMcalc provides renditions of the instantaneous circumbinary habital zone (CHZ) and also calculates BHM properties of the system including those related to the rotational evolution of the stellar components and the combined XUV and SW fluxes as measured at different distances from the binary. Moreover, it provides numerical results that can be further manipulated and used to calculate other properties.

[ascl:1802.012]
PyOSE: Orbital sampling effect (OSE) simulator

PyOSE is a fully numerical orbital sampling effect (OSE) simulator that can model arbitrary inclinations of the transiting moon orbit. It can be used to search for exomoons in long-term stellar light curves such as those by Kepler and the upcoming PLATO mission.

[ascl:1802.011]
runDM: Running couplings of Dark Matter to the Standard Model

runDM calculates the running of the couplings of Dark Matter (DM) to the Standard Model (SM) in simplified models with vector mediators. By specifying the mass of the mediator and the couplings of the mediator to SM fields at high energy, the code can calculate the couplings at low energy, taking into account the mixing of all dimension-6 operators. runDM can also extract the operator coefficients relevant for direct detection, namely low energy couplings to up, down and strange quarks and to protons and neutrons.

[ascl:1802.010]
Glimpse: Sparsity based weak lensing mass-mapping tool

Glimpse, also known as Glimpse2D, is a weak lensing mass-mapping tool that relies on a robust sparsity-based regularization scheme to recover high resolution convergence from either gravitational shear alone or from a combination of shear and flexion. Including flexion allows the supplementation of the shear on small scales in order to increase the sensitivity to substructures and the overall resolution of the convergence map. To preserve all available small scale information, Glimpse avoids any binning of the irregularly sampled input shear and flexion fields and treats the mass-mapping problem as a general ill-posed inverse problem, regularized using a multi-scale wavelet sparsity prior. The resulting algorithm incorporates redshift, reduced shear, and reduced flexion measurements for individual galaxies and is made highly efficient by the use of fast Fourier estimators.

[ascl:1802.009]
astroplan: Observation planning package for astronomers

Morris, Brett M.; Tollerud, Erik; Sipocz, Brigitta; Deil, Christoph; Douglas, Stephanie T.; Berlanga Medina, Jazmin; Vyhmeister, Karl; Price-Whelan, Adrian M.; Jeschke, Eric

astroplan is a flexible toolbox for observation planning and scheduling. It is powered by Astropy (ascl:1304.002); it works for Python beginners and new observers, and is powerful enough for observatories preparing nightly and long-term schedules as well. It calculates rise/set/meridian transit times, alt/az positions for targets at observatories anywhere on Earth, and offers built-in plotting convenience functions for standard observation planning plots (airmass, parallactic angle, sky maps). It can also determine the observability of sets of targets given an arbitrary set of constraints (i.e., altitude, airmass, moon separation/illumination, etc.).

[ascl:1802.008]
AntiparticleDM: Discriminating between Majorana and Dirac Dark Matter

AntiparticleDM calculates the prospects of future direct detection experiments to discriminate between Majorana and Dirac Dark Matter (*i.e.*, to determine whether Dark Matter is its own antiparticle). Direct detection event rates and mock data generation are dealt with by a variation of the WIMpy code.

[ascl:1802.007]
HiGal_SED_Fitter: SED fitting tools for Herschel Hi-Gal data

HiGal SED Fitter fits modified blackbody SEDs to Herschel data, specifically targeted at Herschel Hi-Gal data.

[ascl:1802.006]
VISIBLE: VISIbility Based Line Extraction

Loomis, Ryan A.; Oberg, Karin I.; Andrews, Sean M.; Walsh, Catherine; Czekala, Ian; Huang, Jane; Rosenfeld, Katherine A.

VISIBLE applies approximated matched filters to interferometric data, allowing line detection directly in visibility space. The filter can be created from a FITS image or RADMC3D output image, and the weak line data can be a CASA MS or uvfits file. The filter response spectrum can be output either to a .npy file or returned back to the user for scripting.

[ascl:1802.005]
Verne: Earth-stopping effect for heavy dark matter

Verne calculates the Earth-stopping effect for super-heavy Dark Matter (DM). The code allows you to calculate the speed distribution (and DM signal rate) at an arbitrary detector location on the Earth. The calculation takes into account the full anisotropic DM velocity distribution and the full velocity dependence of the DM-nucleus cross section. Results can be obtained for any DM mass and cross section, though the results are most reliable for very heavy DM particles.

[submitted]
Opik Collision Probability

The Opik method gives the mean probability of collision of a small body with a given planet. It is a statistical value valid for an orbit with given (a,e,i) and undefined argument of perihelion. In some cases, the planet can eject the small body from the solar system; in these cases, the program estimates the mean time for the ejection. The Opik method does not take into account other perturbers than the planet considered, so it only provides an idea of the timescales involved.

[ascl:1802.004]
ARTIP: Automated Radio Telescope Image Processing Pipeline

Sharma, Ravi; Gyanchandani, Dolly; Kulkarni, Sarang; Gupta, Neeraj; Pathak, Vineet; Pande, Arti; Joshi, Unmesh

The Automated Radio Telescope Image Processing Pipeline (ARTIP) automates the entire process of flagging, calibrating, and imaging for radio-interferometric data. ARTIP starts with raw data, i.e. a measurement set and goes through multiple stages, such as flux calibration, bandpass calibration, phase calibration, and imaging to generate continuum and spectral line images. Each stage can also be run independently. The pipeline provides continuous feedback to the user through various messages, charts and logs. It is written using standard python libraries and the CASA package. The pipeline can deal with datasets with multiple spectral windows and also multiple target sources which may have arbitrary combinations of flux/bandpass/phase calibrators.

[ascl:1802.003]
CMacIonize: Monte Carlo photoionisation and moving-mesh radiation hydrodynamics

CMacIonize simulates the self-consistent evolution of HII regions surrounding young O and B stars, or other sources of ionizing radiation. The code combines a Monte Carlo photoionization algorithm that uses a complex mix of hydrogen, helium and several coolants in order to self-consistently solve for the ionization and temperature balance at any given time, with a standard first order hydrodynamics scheme. The code can be run as a post-processing tool to get the line emission from an existing simulation snapshot, but can also be used to run full radiation hydrodynamical simulations. Both the radiation transfer and the hydrodynamics are implemented in a general way that is independent of the grid structure that is used to discretize the system, allowing it to be run both as a standard fixed grid code and also as a moving-mesh code.

[ascl:1802.002]
venice: Mask utility

venice reads a mask file (DS9 or fits type) and a catalogue of objects (ascii or fits type) to create a pixelized mask, find objects inside/outside a mask, or generate a random catalogue of objects inside/outside a mask. The program reads the mask file and checks if a point, giving its coordinates, is inside or outside the mask, *i.e.* inside or outside at least one polygon of the mask.

[ascl:1802.001]
FAC: Flexible Atomic Code

FAC calculates various atomic radiative and collisional processes, including radiative transition rates, collisional excitation and ionization by electron impact, energy levels, photoionization, and autoionization, and their inverse processes radiative recombination and dielectronic capture. The package also includes a collisional radiative model to construct synthetic spectra for plasmas under different physical conditions.

[ascl:1801.012]
RadVel: General toolkit for modeling Radial Velocities

RadVel models Keplerian orbits in radial velocity (RV) time series. The code is written in Python with a fast Kepler's equation solver written in C. It provides a framework for fitting RVs using maximum a posteriori optimization and computing robust confidence intervals by sampling the posterior probability density via Markov Chain Monte Carlo (MCMC). RadVel can perform Bayesian model comparison and produces publication quality plots and LaTeX tables.

[ascl:1801.011]
GABE: Grid And Bubble Evolver

GABE (Grid And Bubble Evolver) evolves scalar fields (as well as other purposes) on an expanding background for non-canonical and non-linear classical field theory. GABE is based on the Runge-Kutta method.

[ascl:1801.010]
DICE/ColDICE: 6D collisionless phase space hydrodynamics using a lagrangian tesselation

DICE is a C++ template library designed to solve collisionless fluid dynamics in 6D phase space using massively parallel supercomputers via an hybrid OpenMP/MPI parallelization. ColDICE, based on DICE, implements a cosmological and physical VLASOV-POISSON solver for cold systems such as dark matter (CDM) dynamics.

[ascl:1801.009]
Gnuastro: GNU Astronomy Utilities

Gnuastro (GNU Astronomy Utilities) manipulates and analyzes astronomical data. It is an official GNU package of a large collection of programs and C/C++ library functions. Command-line programs perform arithmetic operations on images, convert FITS images to common types like JPG or PDF, convolve an image with a given kernel or matching of kernels, perform cosmological calculations, crop parts of large images (possibly in multiple files), manipulate FITS extensions and keywords, and perform statistical operations. In addition, it contains programs to make catalogs from detection maps, add noise, make mock profiles with a variety of radial functions using monte-carlo integration for their centers, match catalogs, and detect objects in an image among many other operations. The command-line programs share the same basic command-line user interface for the comfort of both the users and developers. Gnuastro is written to comply fully with the GNU coding standards and integrates well with all Unix-like operating systems. This enables astronomers to expect a fully familiar experience in the source code, building, installing and command-line user interaction that they have seen in all the other GNU software that they use. Gnuastro's extensive library is included for users who want to build their own unique programs.

[ascl:1801.008]
BOND: Bayesian Oxygen and Nitrogen abundance Determinations

BOND determines oxygen and nitrogen abundances in giant H II regions by comparison with a large grid of photoionization models. The grid spans a wide range in O/H, N/O and ionization parameter U, and covers different starburst ages and nebular geometries. Unlike other statistical methods, BOND relies on the [Ar III]/[Ne III] emission line ratio to break the oxygen abundance bimodality. By doing so, it can measure oxygen and nitrogen abundances without assuming any a priori relation between N/O and O/H. BOND takes into account changes in the hardness of the ionizing radiation field, which can come about due to the ageing of H II regions or the stochastically sampling of the IMF. The emission line ratio He I/Hβ, in addition to commonly used strong lines, constrains the hardness of the ionizing radiation field. BOND relies on the emission line ratios [O III]/Hβ, [O II]/Hβ and [N II]/Hβ, [Ar III]/Hβ, [Ne III]/Hβ, He I/Hβ as its input parameters, while its output values are the measurements and uncertainties for O/H and N/O.

[ascl:1801.007]
cambmag: Magnetic Fields in CAMB

cambmag is a modification to CAMB (ascl:1102.026) that calculates the compensated magnetic mode in the scalar, vector and tensor case. Previously CAMB included code only for the vectors. It also corrects for tight-coupling issues and adds in the ability to include massive neutrinos when calculating vector modes.

[ascl:1801.006]
DecouplingModes: Passive modes amplitudes

DecouplingModes calculates the amplitude of the passive modes, which requires solving the Einstein equations on superhorizon scales sourced by the anisotropic stress from the magnetic fields (prior to neutrino decoupling), and the magnetic and neutrino stress (after decoupling). The code is available as a Mathematica notebook.

[ascl:1801.005]
InitialConditions: Initial series solutions for perturbations in our Universe

InitialConditions finds the initial series solutions for perturbations in our Universe. This includes all scalar (1 adiabatic, 4 isocurvature and 2 magnetic modes), vector (1 vorticity mode, 1 magnetic mode), and tensor (1 gravitational wave mode and 1 magnetic mode) perturbations including terms up to second order in the neutrino mass. It can handle the standard species (cdm, baryons, photons), and two neutrino mass eigenstates (1 light, 1 heavy).

[ascl:1801.004]
hh0: Hierarchical Hubble Constant Inference

hh0 is a Bayesian hierarchical model (BHM) that describes the full distance ladder, from nearby geometric-distance anchors through Cepheids to SNe in the Hubble flow. It does not rely on any of the underlying distributions being Gaussian, allowing outliers to be modeled and obviating the need for any arbitrary data cuts.

[ascl:1801.003]
Stan: Statistical inference

Stan facilitates statistical inference at the frontiers of applied statistics and provides both a modeling language for specifying complex statistical models and a library of statistical algorithms for computing inferences with those models. These components are exposed through interfaces in environments such as R, Python, and the command line.

[ascl:1801.002]
iWander: Dynamics of interstellar wanderers

iWander assesses the origin of interstellar small bodies such as asteroids and comets. It includes a series of databases and tools that can be used in general for studying the dynamics of an interstellar vagabond object (small−body, interstellar spaceship and even stars).

[ascl:1801.001]
BANYAN_Sigma: Bayesian classifier for members of young stellar associations

Gagné, Jonathan; Mamajek, Eric E.; Malo, Lison; Riedel, Adric; Rodriguez, David; Lafrenière, David; Faherty, Jacqueline K.; Roy-Loubier, Olivier; Pueyo, Laurent; Robin, Annie C.; Doyon, René

BANYAN_Sigma calculates the membership probability that a given astrophysical object belongs to one of the currently known 27 young associations within 150 pc of the Sun, using Bayesian inference. This tool uses the sky position and proper motion measurements of an object, with optional radial velocity (RV) and distance (D) measurements, to derive a Bayesian membership probability. By default, the priors are adjusted such that a probability threshold of 90% will recover 50%, 68%, 82% or 90% of true association members depending on what observables are input (only sky position and proper motion, with RV, with D, with both RV and D, respectively). The algorithm is implemented in a Python package, in IDL, and is also implemented as an interactive web page.

[submitted]
A Neural Network for the Identification of Dangerous Planetesimals (Including scripts for data generation)

Two neural networks were designed to identify hazardous planetesimals that were trained on object trajectories calculated in a cloud computing environment. The first neural network was fully-connected and was trained on the orbital elements (OEs) of real/simulated planetesimals, while the second was a 1-dimensional convolutional neural network that was trained on the position Cartesian coordinates of real/simulated planetesimals. Ultimately, the network trained on OEs had a better performance by identifying one-third of known potentially hazardous objects including the 3 asteroids with the highest chance of impact with Earth (2009 FD, 1999 RQ36, 1950 DA) as established by NASA's Monte Carlo based Sentry system.

[submitted]
loci: Smooth Cubic Multivariate Local Interpolations

loci is a shared library for interpolations in up to 4 dimensions. It is written in C and can be used with C/C++, Python and others. In order to calculate the coefficients of the cubic polynom, only local values are used: The data itself and all combinations of first-order derivatives, i.e. in 2D f_x, f_y and f_xy. This is in contrast to splines, where the coefficients are not calculated using derivatives, but non-local data, which can lead to over-smoothing the result.

[ascl:1712.016]
LgrbWorldModel: Long-duration Gamma-Ray Burst World Model

LgrbWorldModel is written in Fortran 90 and attempts to model the population distribution of the Long-duration class of Gamma-Ray Bursts (LGRBs) as detected by the NASA's now-defunct Burst And Transient Source Experiment (BATSE) onboard the Compton Gamma Ray Observatory (CGRO). It is assumed that the population distribution of LGRBs is well fit by a multivariate log-normal distribution. The best-fit parameters of the distribution are then found by maximizing the likelihood of the observed data by BATSE detectors via a native built-in Adaptive Metropolis-Hastings Markov-Chain Monte Carlo (AMH-MCMC) Sampler.

[ascl:1712.015]
SgrbWorldModel: Short-duration Gamma-Ray Burst World Model

SgrbWorldModel, written in Fortran 90, presents an attempt at modeling the population distribution of the Short-duration class of Gamma-Ray Bursts (SGRBs) as detected by the NASA's now-defunct Burst And Transient Source Experiment (BATSE) onboard the Compton Gamma Ray Observatory (CGRO). It is assumed that the population distribution of SGRBs is well fit by a multivariate log-normal distribution, whose differential cosmological rate of occurrence follows the Star-Formation-Rate (SFR) convolved with a log-normal binary-merger delay-time distribution. The best-fit parameters of the model are then found by maximizing the likelihood of the observed data by the BATSE detectors via a native built-in Adaptive Metropolis-Hastings Markov-Chain Monte Carlo (AMH-MCMC)Sampler that is part of the code. A model for the detection algorithm of the BATSE detectors is also provided.

[ascl:1712.014]
QATS: Quasiperiodic Automated Transit Search

QATS detects transiting extrasolar planets in time-series photometry. It relaxes the usual assumption of strictly periodic transits by permitting a variable, but bounded, interval between successive transits.

[ascl:1712.013]
photodynam: Photodynamical code for fitting the light curves of multiple body systems

Photodynam facilitates so-called "photometric-dynamical" modeling. This model is quite simple and this is reflected in the code base. A N-body code provides coordinates and the photometric code produces light curves based on coordinates.

[ascl:1712.012]
MadDM: Computation of dark matter relic abundance

MadDM computes dark matter relic abundance and dark matter nucleus scattering rates in a generic model. The code is based on the existing MadGraph 5 architecture and as such is easily integrable into any MadGraph collider study. A simple Python interface offers a level of user-friendliness characteristic of MadGraph 5 without sacrificing functionality. MadDM is able to calculate the dark matter relic abundance in models which include a multi-component dark sector, resonance annihilation channels and co-annihilations. The direct detection module of MadDM calculates spin independent / spin dependent dark matter-nucleon cross sections and differential recoil rates as a function of recoil energy, angle and time. The code provides a simplified simulation of detector effects for a wide range of target materials and volumes.

[ascl:1712.011]
FBEYE: Analyzing Kepler light curves and validating flares

FBEYE, the "Flares By-Eye" detection suite, is written in IDL and analyzes Kepler light curves and validates flares. It works on any 3-column light curve that contains time, flux, and error. The success of flare identification is highly dependent on the smoothing routine, which may not be suitable for all sources.

[ascl:1712.010]
Flux Tube: Solar model

Flux Tube is a nonlinear, two-dimensional, numerical simulation of magneto-acoustic wave propagation in the photosphere and chromosphere of small-scale flux tubes with internal structure. Waves with realistic periods of three to five minutes are studied, after horizontal and vertical oscillatory perturbations are applied to the equilibrium model. Spurious reflections of shock waves from the upper boundary are minimized by a special boundary condition.

[ascl:1712.009]
RODRIGUES: RATT Online Deconvolved Radio Image Generation Using Esoteric Software

RODRIGUES (RATT Online Deconvolved Radio Image Generation Using Esoteric Software) is a web-based radio telescope simulation and reduction tool. From a technical perspective it is a web based parameterized docker container scheduler with a result set viewer.

[ascl:1712.008]
CosApps: Simulate gravitational lensing through ray tracing and shear calculation

Cosmology Applications (CosApps) provides tools to simulate gravitational lensing using two different techniques, ray tracing and shear calculation. The tool ray_trace_ellipse calculates deflection angles on a grid for light passing a deflecting mass distribution. Using MPI, ray_trace_ellipse may calculate deflection in parallel across network connected computers, such as cluster. The program physcalc calculates the gravitational lensing shear using the relationship of convergence and shear, described by a set of coupled partial differential equations.

[ascl:1712.007]
SFoF: Friends-of-friends galaxy cluster detection algorithm

SFoF is a friends-of-friends galaxy cluster detection algorithm that operates in either spectroscopic or photometric redshift space. The linking parameters, both transverse and along the line-of-sight, change as a function of redshift to account for selection effects.

[ascl:1712.006]
Nyx: Adaptive mesh, massively-parallel, cosmological simulation code

Nyx code solves equations of compressible hydrodynamics on an adaptive grid hierarchy coupled with an N-body treatment of dark matter. The gas dynamics in Nyx use a finite volume methodology on an adaptive set of 3-D Eulerian grids; dark matter is represented as discrete particles moving under the influence of gravity. Particles are evolved via a particle-mesh method, using Cloud-in-Cell deposition/interpolation scheme. Both baryonic and dark matter contribute to the gravitational field. In addition, Nyx includes physics for accurately modeling the intergalactic medium; in optically thin limits and assuming ionization equilibrium, the code calculates heating and cooling processes of the primordial-composition gas in an ionizing ultraviolet background radiation field.

[ascl:1712.005]
draco: Analysis and simulation of drift scan radio data

draco analyzes transit radio data with the m-mode formalism. It is telescope agnostic, and is used as part of the analysis and simulation pipeline for the CHIME (Canadian Hydrogen Intensity Mapping Experiment) telescope. It can simulate time stream data from maps of the sky (using the m-mode formalism) and add gain fluctuations and correctly correlated instrumental noise (i.e. Wishart distributed). Further, it can perform various cuts on the data and make maps of the sky from data using the m-mode formalism.

[ascl:1712.004]
Bitshuffle: Filter for improving compression of typed binary data

Bitshuffle rearranges typed, binary data for improving compression; the algorithm is implemented in a python/C package within the Numpy framework. The library can be used alongside HDF5 to compress and decompress datasets and is integrated through the dynamically loaded filters framework. Algorithmically, Bitshuffle is closely related to HDF5's Shuffle filter except it operates at the bit level instead of the byte level. Arranging a typed data array in to a matrix with the elements as the rows and the bits within the elements as the columns, Bitshuffle "transposes" the matrix, such that all the least-significant-bits are in a row, etc. This transposition is performed within blocks of data roughly 8kB long; this does not in itself compress data, but rearranges it for more efficient compression. A compression library is necessary to perform the actual compression. This scheme has been used for compression of radio data in high performance computing.

[ascl:1712.003]
Py-SPHViewer: Cosmological simulations using Smoothed Particle Hydrodynamics

Py-SPHViewer visualizes and explores N-body + Hydrodynamics simulations. The code interpolates the underlying density field (or any other property) traced by a set of particles, using the Smoothed Particle Hydrodynamics (SPH) interpolation scheme, thus producing not only beautiful but also useful scientific images. Py-SPHViewer enables the user to explore simulated volumes using different projections. Py-SPHViewer also provides a natural way to visualize (in a self-consistent fashion) gas dynamical simulations, which use the same technique to compute the interactions between particles.

[ascl:1712.002]
MPI_XSTAR: MPI-based parallelization of XSTAR program

MPI_XSTAR parallelizes execution of multiple XSTAR runs using Message Passing Interface (MPI). XSTAR (ascl:9910.008), part of the HEASARC's HEAsoft (ascl:1408.004) package, calculates the physical conditions and emission spectra of ionized gases. MPI_XSTAR invokes XSTINITABLE from HEASoft to generate a job list of XSTAR commands for given physical parameters. The job list is used to make directories in ascending order, where each individual XSTAR is spawned on each processor and outputs are saved. HEASoft's XSTAR2TABLE program is invoked upon the contents of each directory in order to produce table model FITS files for spectroscopy analysis tools.

[ascl:1712.001]
KDUtils: Kinematic Distance Utilities

The Kinematic Distance utilities (KDUtils) calculate kinematic distances and kinematic distance uncertainties. The package includes methods to calculate "traditional" kinematic distances as well as a Monte Carlo method to calculate kinematic distances and uncertainties.

[ascl:1711.024]
NOD3: Single dish reduction software

NOD3 processes and analyzes maps from single-dish observations affected by scanning effects from clouds, receiver instabilities, or radio-frequency interference. Its “basket-weaving” tool combines orthogonally scanned maps into a final map that is almost free of scanning effects. A restoration tool for dual-beam observations reduces the noise by a factor of about two compared to the NOD2 version. Combining single-dish with interferometer data in the map plane ensures the full recovery of the total flux density.

[ascl:1711.023]
HBT+: Subhalo finder and merger tree builder

HBT+ is a hybrid subhalo finder and merger tree builder for cosmological simulations. It comes as an MPI edition that can be run on distributed clusters or shared memory machines and is MPI/OpenMP parallelized, and also as an OpenMP edition that can be run on shared memory machines and is only OpenMP parallelized. This version is more memory efficient than the MPI branch on shared memory machines, and is more suitable for analyzing zoomed-in simulations that are difficult to balance on distributed clusters. Both editions support hydro simulations with gas/stars.

[ascl:1711.022]
HBT: Hierarchical Bound-Tracing

HBT is a Hierarchical Bound-Tracing subhalo finder and merger tree builder, for numerical simulations in cosmology. It tracks haloes from birth and continues to track them after mergers, finding self-bound structures as subhaloes and recording their merger histories as merger trees.

[ascl:1711.021]
Bifrost: Stream processing framework for high-throughput applications

Bifrost is a stream processing framework that eases the development of high-throughput processing CPU/GPU pipelines. It is designed for digital signal processing (DSP) applications within radio astronomy. Bifrost uses a flexible ring buffer implementation that allows different signal processing blocks to be connected to form a pipeline. Each block may be assigned to a CPU core, and the ring buffers are used to transport data to and from blocks. Processing blocks may be run on either the CPU or GPU, and the ring buffer will take care of memory copies between the CPU and GPU spaces.

[ascl:1711.020]
MARXS: Multi-Architecture Raytrace Xray mission Simulator

MARXS (Multi-Architecture-Raytrace-Xraymission-Simulator) simulates X-ray observatories. Primarily designed to simulate X-ray instruments on astronomical X-ray satellites and sounding rocket payloads, it can also be used to ray-trace experiments in the laboratory. MARXS performs polarization Monte-Carlo ray-trace simulations from a source (astronomical or lab) through a collection of optical elements such as mirrors, baffles, and gratings to a detector.

[ascl:1711.019]
SPIDERMAN: Fast code to simulate secondary transits and phase curves

SPIDERMAN calculates exoplanet phase curves and secondary eclipses with arbitrary surface brightness distributions in two dimensions. The code uses a geometrical algorithm to solve exactly the area of sections of the disc of the planet that are occulted by the star. Approximately 1000 models can be generated per second in typical use, which makes making Markov Chain Monte Carlo analyses practicable. The code is modular and allows comparison of the effect of multiple different brightness distributions for a dataset.

[ascl:1711.018]
LExTeS: Link Extraction and Testing Suite

LExTeS (Link Extraction and Testing Suite) extracts hyperlinks from PDF documents, tests the extracted links to see which are broken, and tabulates the results. Though written to support a particular set of PDF documents, the dataset and scripts can be edited for use on other documents.

[ascl:1711.017]
FATS: Feature Analysis for Time Series

Nun, Isadora; Protopapas, Pavlos; Sim, Brandon; Zhu, Ming; Dave, Rahul; Castro, Nicolas; Pichara, Karim

FATS facilitates and standardizes feature extraction for time series data; it quickly and efficiently calculates a compilation of many existing light curve features. Users can characterize or analyze an astronomical photometric database, though this library is not necessarily restricted to the astronomical domain and can also be applied to any kind of time series data.

[ascl:1711.016]
Thindisk: Protoplanetary disk model

Thindisk computes the line emission from a geometrically thin protoplanetary disk. It creates a datacube in FITS format that can be processed with a data reduction package (such as GILDAS, ascl:1305.010) to produce synthetic images and visibilities. These synthetic data can be compared with observations to determine the properties (e.g. central mass or inclination) of an observed disk. The disk is assumed to be in Keplerian rotation at a radius lower than the centrifugal radius (which can be set to a large value, for a purely Keplerian disk), and in infall with rotation beyond the centrifugal radius.

[ascl:1711.015]
rac-2d: Thermo-chemical for modeling water vapor formation in protoplanetary disks

rec-2d models the distribution of water vapor in protoplanetary disks. Given a distribution of gas and dust, rac-2d first solves the dust temperature distribution with a Monte Carlo method and then solves the gas temperature distribution and chemical composition. Although the geometry is symmetric with respect to rotation around the central axis and reflection about the midplane, the photon propagation is done in full three dimensions. After establishing the dust temperature distribution, the disk chemistry is evolved for 1 Myr; the heating and cooling processes are coupled with chemistry, allowing the gas temperature to be evolved in tandem with chemistry based on the heating and cooling rates.

[ascl:1711.014]
Gammapy: Python toolbox for gamma-ray astronomy

Gammapy analyzes gamma-ray data and creates sky images, spectra and lightcurves, from event lists and instrument response information; it can also determine the position, morphology and spectra of gamma-ray sources. It is used to analyze data from H.E.S.S., Fermi-LAT, and the Cherenkov Telescope Array (CTA).

[ascl:1711.013]
HO-CHUNK: Radiation Transfer code

HO-CHUNK calculates radiative equilibrium temperature solution, thermal and PAH/vsg emission, scattering and polarization in protostellar geometries. It is useful for computing spectral energy distributions (SEDs), polarization spectra, and images.

[ascl:1711.012]
megaman: Manifold Learning for Millions of Points

megaman is a scalable manifold learning package implemented in python. It has a front-end API designed to be familiar to scikit-learn but harnesses the C++ Fast Library for Approximate Nearest Neighbors (FLANN) and the Sparse Symmetric Positive Definite (SSPD) solver Locally Optimal Block Precodition Gradient (LOBPCG) method to scale manifold learning algorithms to large data sets. It is designed for researchers and as such caches intermediary steps and indices to allow for fast re-computation with new parameters.

[ascl:1711.011]
galkin: Milky Way rotation curve data handler

galkin is a compilation of kinematic measurements tracing the rotation curve of our Galaxy, together with a tool to treat the data. The compilation is optimized to Galactocentric radii between 3 and 20 kpc and includes the kinematics of gas, stars and masers in a total of 2780 measurements collected from almost four decades of literature. The user-friendly software provided selects, treats and retrieves the data of all source references considered. This tool is especially designed to facilitate the use of kinematic data in dynamical studies of the Milky Way with various applications ranging from dark matter constraints to tests of modified gravity.

[ascl:1711.010]
galstreams: Milky Way streams footprint library and toolkit

galstreams provides a compilation of spatial information for known stellar streams and overdensities in the Milky Way and includes Python tools for visualizing them. ASCII tables are also provided for quick viewing of the stream's footprints using TOPCAT (ascl:1101.010).

[ascl:1711.009]
Lightning: SED Fitting Package

Lightning is a spectral energy distribution (SED) fitting procedure that quickly and reliably recovers star formation history (SFH) and extinction parameters. The SFH is modeled as discrete steps in time. The code consists of a fully vectorized inversion algorithm to determine SFH step intensities and combines this with a grid-based approach to determine three extinction parameters.

[ascl:1711.008]
clustep: Initial conditions for galaxy cluster halo simulations

clustep generates a snapshot in GADGET-2 (ascl:0003.001) format containing a galaxy cluster halo in equilibrium; this snapshot can also be read in RAMSES (ascl:1011.007) using the DICE patch. The halo is made of a dark matter component and a gas component, with the latter representing the ICM. Each of these components follows a Dehnen density profile, with gamma=0 or gamma=1. If gamma=1, then the profile corresponds to a Hernquist profile.

[ascl:1711.007]
galstep: Initial conditions for spiral galaxy simulations

galstep generates initial conditions for disk galaxy simulations with GADGET-2 (ascl:0003.001), RAMSES (ascl:1011.007) and GIZMO (ascl:1410.003), including a stellar disk, a gaseous disk, a dark matter halo and a stellar bulge. The first two components follow an exponential density profile, and the last two a Dehnen density profile with gamma=1 by default, corresponding to a Hernquist profile.

[ascl:1711.006]
RGW: Goodman-Weare Affine-Invariant Sampling

RGW is a lightweight R-language implementation of the affine-invariant Markov Chain Monte Carlo sampling method of Goodman & Weare (2010). The implementation is based on the description of the python package emcee (ascl:1303.002).

[ascl:1711.005]
correlcalc: Two-point correlation function from redshift surveys

correlcalc calculates two-point correlation function (2pCF) of galaxies/quasars using redshift surveys. It can be used for any assumed geometry or Cosmology model. Using BallTree algorithms to reduce the computational effort for large datasets, it is a parallelised code suitable for running on clusters as well as personal computers. It takes redshift (z), Right Ascension (RA) and Declination (DEC) data of galaxies and random catalogs as inputs in form of ascii or fits files. If random catalog is not provided, it generates one of desired size based on the input redshift distribution and mangle polygon file (in .ply format) describing the survey geometry. It also calculates different realisations of (3D) anisotropic 2pCF. Optionally it makes healpix maps of the survey providing visualization.

[ascl:1711.004]
BayesVP: Full Bayesian Voigt profile fitting

BayesVP offers a Bayesian approach for modeling Voigt profiles in absorption spectroscopy. The code fits the absorption line profiles within specified wavelength ranges and generates posterior distributions for the column density, Doppler parameter, and redshifts of the corresponding absorbers. The code uses publicly available efficient parallel sampling packages to sample posterior and thus can be run on parallel platforms. BayesVP supports simultaneous fitting for multiple absorption components in high-dimensional parameter space. The package includes additional utilities such as explicit specification of priors of model parameters, continuum model, Bayesian model comparison criteria, and posterior sampling convergence check.

[ascl:1711.003]
FTbg: Background removal using Fourier Transform

FTbg performs Fourier transforms on FITS images and separates low- and high-spatial frequency components by a user-specified cut. Both components are then inverse Fourier transformed back to image domain. FTbg can remove large-scale background/foreground emission in many astrophysical applications. FTbg has been designed to identify and remove Galactic background emission in Herschel/Hi-GAL continuum images, but it is applicable to any other (e.g., Planck) images when background/foreground emission is a concern.

[ascl:1711.002]
inhomog: Biscale kinematical backreaction analytical evolution

The inhomog library provides Raychaudhuri integration of cosmological domain-wise average scale factor evolution using an analytical formula for kinematical backreaction Q_D evolution. The inhomog main program illustrates biscale examples. The library routine lib/Omega_D_precalc.c is callable by RAMSES (ascl:1011.007) using the RAMSES extension ramses-scalav.

[ascl:1711.001]
SpcAudace: Spectroscopic processing and analysis package of Audela software

SpcAudace processes long slit spectra with automated pipelines and performs astrophysical analysis of the latter data. These powerful pipelines do all the required steps in one pass: standard preprocessing, masking of bad pixels, geometric corrections, registration, optimized spectrum extraction, wavelength calibration and instrumental response computation and correction. Both high and low resolution long slit spectra are managed for stellar and non-stellar targets. Many types of publication-quality figures can be easily produced: pdf and png plots or annotated time series plots. Astrophysical quantities can be derived from individual or large amount of spectra with advanced functions: from line profile characteristics to equivalent width and periodogram. More than 300 documented functions are available and can be used into TCL scripts for automation. SpcAudace is based on Audela open source software.

[ascl:1710.024]
pred_loggs: Predicting individual galaxy G/S probability distributions

Eckert, Kathleen D.; Kannappan, Sheila J.; Stark, David V.; Moffett, Amanda J.; Norris, Mark A.; Snyder, Elaine M.; Hoversten, Erik A.

pred_loggs models the entire PGF probability density field, enabling iterative statistical modeling of upper limits and prediction of full G/S probability distributions for individual galaxies.

[ascl:1710.023]
LIMEPY: Lowered Isothermal Model Explorer in PYthon

LIMEPY solves distribution function (DF) based lowered isothermal models. It solves Poisson's equation used on input parameters and offers fast solutions for isotropic/anisotropic, single/multi-mass models, normalized DF values, density and velocity moments, projected properties, and generates discrete samples.

[ascl:1710.022]
galario: Gpu Accelerated Library for Analyzing Radio Interferometer Observations

The galario library exploits the computing power of modern graphic cards (GPUs) to accelerate the comparison of model predictions to radio interferometer observations. It speeds up the computation of the synthetic visibilities given a model image (or an axisymmetric brightness profile) and their comparison to the observations.

[ascl:1710.021]
OSIRIS Toolbox: OH-Suppressing InfraRed Imaging Spectrograph pipeline

Lyke, Jim; Do, Tuan; Boehle, Anna; Campbell, Randy; Chappell, Sam; Fitzgerald, Mike; Gasawy, Tom; Iserlohe, Christof; Krabbe, Alfred; Larkin, James; Lockhart, Kelly; Lu, Jessica; Mieda, Etsuko; McElwain, Mike; Perrin, Marshall; Rudy, Alex; Sitarski, Breann; Vayner, Andrey; Walth, Greg; Weiss, Jason; Wizanski, Tommer; Wright, Shelley

OSIRIS Toolbox reduces data for the Keck OSIRIS instrument, an integral field spectrograph that works with the Keck Adaptive Optics System. It offers real-time reduction of raw frames into cubes for display and basic analysis. In this real-time mode, it takes about one minute for a preliminary data cube to appear in the “quicklook” display package. The reduction system also includes a growing set of final reduction steps including correction of telluric absorption and mosaicing of multiple cubes.

[ascl:1710.020]
PSPLINE: Princeton Spline and Hermite cubic interpolation routines

PSPLINE is a collection of Spline and Hermite interpolation tools for 1D, 2D, and 3D datasets on rectilinear grids. Spline routines give full control over boundary conditions, including periodic, 1st or 2nd derivative match, or divided difference-based boundary conditions on either end of each grid dimension. Hermite routines take the function value and derivatives at each grid point as input, giving back a representation of the function between grid points. Routines are provided for creating Hermite datasets, with appropriate boundary conditions applied. The 1D spline and Hermite routines are based on standard methods; the 2D and 3D spline or Hermite interpolation functions are constructed from 1D spline or Hermite interpolation functions in a straightforward manner. Spline and Hermite interpolation functions are often much faster to evaluate than other representations using e.g. Fourier series or otherwise involving transcendental functions.

[ascl:1710.019]
GASOLINE: Smoothed Particle Hydrodynamics (SPH) code

Gasoline solves the equations of gravity and hydrodynamics in astrophysical problems, including simulations of planets, stars, and galaxies. It uses an SPH method that features correct mixing behavior in multiphase fluids and minimal artificial viscosity. This method is identical to the SPH method used in the ChaNGa code (ascl:1105.005), allowing users to extend results to problems requiring >100,000 cores. Gasoline uses a fast, memory-efficient O(N log N) KD-Tree to solve Poisson's Equation for gravity and avoids artificial viscosity in non-shocking compressive flows.

[ascl:1710.018]
FITSFH: Star Formation Histories

FITSFH derives star formation histories from photometry of resolved stellar populations by populating theoretical isochrones according to a chosen stellar initial mass function (IMF) and searching for the linear combination of isochrones with different ages and metallicities that best matches the data. In comparing the synthetic and real data, observational errors and incompleteness are taken into account, and a rudimentary treatment of the effect of unresolved binaries is also implemented. The code also allows for an age-dependent range of extinction values to be included in the modelling.

[ascl:1710.017]
ATLAS9: Model atmosphere program with opacity distribution functions

ATLAS9 computes model atmospheres using a fixed set of pretabulated opacities, allowing one to work on huge numbers of stars and interpolate in large grids of models to determine parameters quickly. The code works with two different sets of opacity distribution functions (ODFs), one with “big” wavelength intervals covering the whole spectrum and the other with 1221 “little” wavelength intervals covering the whole spectrum. The ODFs use a 12-step representation; the radiation field is computed starting with the highest step and working down. If a lower step does not matter because the line opacity is small relative to the continuum at all depths, all the lower steps are lumped together and not computed to save time.

[ascl:1710.016]
LGMCA: Local-Generalized Morphological Component Analysis

LGMCA (Local-Generalized Morphological Component Analysis) is an extension to GMCA (ascl:1710.015). Similarly to GMCA, it is a Blind Source Separation method which enforces sparsity. The novel aspect of LGMCA, however, is that the mixing matrix changes across pixels allowing LGMCA to deal with emissions sources which vary spatially. These IDL scripts compute the CMB map from WMAP and Planck data; running LGMCA on the WMAP9 temperature products requires the main script and a selection of mandatory files, algorithm parameters and map parameters.

[ascl:1710.015]
GMCALab: Generalized Morphological Component Analysis

GMCALab solves Blind Source Separation (BSS) problems from multichannel/multispectral/hyperspectral data. In essence, multichannel data provide different observations of the same physical phenomena (e.g. multiple wavelengths), which are modeled as a linear combination of unknown elementary components or sources. Written as a set of Matlab toolboxes, it provides a generic framework that can be extended to tackle different matrix factorization problems.

[ascl:1710.014]
GBART: Determination of the orbital elements of spectroscopic binaries

GBART is an improved version of the code for determining the orbital elements for spectroscopic binaries originally written by Bertiau & Grobben (1968).

[ascl:1710.013]
Ramses-GPU: Second order MUSCL-Handcock finite volume fluid solver

RamsesGPU is a reimplementation of RAMSES (ascl:1011.007) which drops the adaptive mesh refinement (AMR) features to optimize 3D uniform grid algorithms for modern graphics processor units (GPU) to provide an efficient software package for astrophysics applications that do not need AMR features but do require a very large number of integration time steps. RamsesGPU provides an very efficient C++/CUDA/MPI software implementation of a second order MUSCL-Handcock finite volume fluid solver for compressible hydrodynamics as a magnetohydrodynamics solver based on the constraint transport technique. Other useful modules includes static gravity, dissipative terms (viscosity, resistivity), and forcing source term for turbulence studies, and special care was taken to enhance parallel input/output performance by using state-of-the-art libraries such as HDF5 and parallel-netcdf.

[ascl:1710.012]
FSFE: Fake Spectra Flux Extractor

The fake spectra flux extractor generates simulated quasar absorption spectra from a particle or adaptive mesh-based hydrodynamic simulation. It is implemented as a python module. It can produce both hydrogen and metal line spectra, if the simulation includes metals. The cloudy table for metal ionization fractions is included. Unlike earlier spectral generation codes, it produces absorption from each particle close to the sight-line individually, rather than first producing an average density in each spectral pixel, thus substantially preserving more of the small-scale velocity structure of the gas. The code supports both Gadget (ascl:0003.001) and AREPO.

[ascl:1710.011]
mTransport: Two-point-correlation function calculator

mTransport computes the 2-point-correlation function of the curvature and tensor perturbations in multifield models of inflation in the presence of a curved field space. It is a Mathematica implementation of the transport method which encompasses scenarios with violations of slow-roll conditions and turns of the trajectory in field space. It can be used for an arbitrary mass spectrum, including massive modes, particle production and models with quasi-single-field dynamics.

[ascl:1710.010]
PyTransport: Calculate inflationary correlation functions

PyTransport calculates the 2-point and 3-point function of inflationary perturbations produced during multi-field inflation. The core of PyTransport is C++ code which is automatically edited and compiled into a Python module once an inflationary potential is specified. This module can then be called to solve the background inflationary cosmology as well as the evolution of correlations of inflationary perturbations. PyTransport includes two additional modules written in Python, one to perform the editing and compilation, and one containing a suite of functions for common tasks such as looping over the core module to construct spectra and bispectra.

[ascl:1710.009]
CppTransport: Two- and three-point function transport framework for inflationary cosmology

CppTransport solves the 2- and 3-point functions of the perturbations produced during an inflationary epoch in the very early universe. It is implemented for models with canonical kinetic terms, although the underlying method is quite general and could be scaled to handle models with a non-trivial field-space metric or an even more general non-canonical Lagrangian.

[ascl:1710.008]
Binary: Accretion disk evolution

Binary computes the evolution of an accretion disc interacting with a binary system. It has been developed and used to study the coupled evolution of supermassive BH binaries and gaseous accretion discs.

[ascl:1710.007]
FLAG: Exact Fourier-Laguerre transform on the ball

FLAG is a fast implementation of the Fourier-Laguerre Transform, a novel 3D transform exploiting an exact quadrature rule of the ball to construct an exact harmonic transform in 3D spherical coordinates. The angular part of the Fourier-Laguerre transform uses the MW sampling theorem and the exact spherical harmonic transform implemented in the SSHT code. The radial sampling scheme arises from an exact quadrature of the radial half-line using damped Laguerre polynomials. The radial transform can in fact be used to compute the spherical Bessel transform exactly, and the Fourier-Laguerre transform is thus closely related to the Fourier-Bessel transform.

[ascl:1710.006]
MOSFiT: Modular Open-Source Fitter for Transients

Guillochon, James; Nicholl, Matt; Villar, V. Ashley; Mockler, Brenna; Narayan, Gautham; Mandel, Kaisey S.; Berger, Edo; Williams, Peter K. G.

MOSFiT (Modular Open-Source Fitter for Transients) downloads transient datasets from open online catalogs (e.g., the Open Supernova Catalog), generates Monte Carlo ensembles of semi-analytical light curve fits to those datasets and their associated Bayesian parameter posteriors, and optionally delivers the fitting results back to those same catalogs to make them available to the rest of the community. MOSFiT helps bridge the gap between observations and theory in time-domain astronomy; in addition to making the application of existing models and creation of new models as simple as possible, MOSFiT yields statistically robust predictions for transient characteristics, with a standard output format that includes all the setup information necessary to reproduce a given result.

[ascl:1710.005]
SkyNet: Modular nuclear reaction network library

The general-purpose nuclear reaction network SkyNet evolves the abundances of nuclear species under the influence of nuclear reactions. SkyNet can be used to compute the nucleosynthesis evolution in all astrophysical scenarios where nucleosynthesis occurs. Any list of isotopes can be evolved and SkyNet supports various different types of nuclear reactions. SkyNet is modular, permitting new or existing physics, such as nuclear reactions or equations of state, to be easily added or modified.

[ascl:1710.004]
SPIPS: Spectro-Photo-Interferometry of Pulsating Stars

SPIPS (Spectro-Photo-Interferometry of Pulsating Stars) combines radial velocimetry, interferometry, and photometry to estimate physical parameters of pulsating stars, including presence of infrared excess, color excess, Teff, and ratio distance/p-factor. The global model-based parallax-of-pulsation method is implemented in Python. Derived parameters have a high level of confidence; statistical precision is improved (compared to other methods) due to the large number of data taken into account, accuracy is improved by using consistent physical modeling and reliability of the derived parameters is strengthened by redundancy in the data.

[ascl:1710.003]
EXOFASTv2: Generalized publication-quality exoplanet modeling code

EXOFASTv2 improves upon EXOFAST (ascl:1207.001) for exoplanet modeling. It uses a differential evolution Markov Chain Monte Carlo code to fit an arbitrary number of transits (each with their own error scaling, normalization, TTV, and/or detrending parameters), an arbitrary number of RV sources (each with their own zero point and jitter), and an arbitrary number of planets, changing nothing but command line arguments and configuration files. The global model includes integrated isochrone and SED models to constrain the stellar properties and can accept priors on any fitted or derived quantities (e.g., parallax from Gaia). It is easily extensible to add additional effects or parameters.

[ascl:1710.002]
rfpipe: Radio interferometric transient search pipeline

rfpipe supports Python-based analysis of radio interferometric data (especially from the Very Large Array) and searches for fast radio transients. This extends on the rtpipe library (ascl:1706.002) with new approaches to parallelization, acceleration, and more portable data products. rfpipe can run in standalone mode or be in a cluster environment.

[ascl:1710.001]
vysmaw: Fast visibility stream muncher

The vysmaw client library facilitates the development of code for processes to tap into the fast visibility stream on the National Radio Astronomy Observatory's Very Large Array correlator back-end InfiniBand network. This uses the vys protocol to allow loose coupling to clients that need to remotely access memory over an Infiniband network.

[ascl:1709.011]
FLaapLUC: Fermi-LAT automatic aperture photometry light curve

Most high energy sources detected with Fermi-LAT are blazars, which are highly variable sources. High cadence long-term monitoring simultaneously at different wavelengths being prohibitive, the study of their transient activities can help shed light on our understanding of these objects. The early detection of such potentially fast transient events is the key for triggering follow-up observations at other wavelengths. FLaapLUC (Fermi-LAT automatic aperture photometry Light C↔Urve) uses the simple aperture photometry approach to effectively detect relative flux variations in a set of predefined sources and alert potential users. Such alerts can then be used to trigger observations of these sources with other facilities. The FLaapLUC pipeline is built on top of the Science Tools provided by the Fermi-LAT collaboration and quickly generates short- or long-term Fermi-LAT light curves.

[ascl:1709.010]
MagIC: Fluid dynamics in a spherical shell simulator

MagIC simulates fluid dynamics in a spherical shell. It solves for the Navier-Stokes equation including Coriolis force, optionally coupled with an induction equation for Magneto-Hydro Dynamics (MHD), a temperature (or entropy) equation and an equation for chemical composition under both the anelastic and the Boussinesq approximations. MagIC uses either Chebyshev polynomials or finite differences in the radial direction and spherical harmonic decomposition in the azimuthal and latitudinal directions. The time-stepping scheme relies on a semi-implicit Crank-Nicolson for the linear terms of the MHD equations and a Adams-Bashforth scheme for the non-linear terms and the Coriolis force.

[ascl:1709.009]
bmcmc: MCMC package for Bayesian data analysis

bmcmc is a general purpose Markov Chain Monte Carlo package for Bayesian data analysis. It uses an adaptive scheme for automatic tuning of proposal distributions. It can also handle Bayesian hierarchical models by making use of the Metropolis-Within-Gibbs scheme.

[ascl:1709.008]
celerite: Scalable 1D Gaussian Processes in C++, Python, and Julia

celerite provides fast and scalable Gaussian Process (GP) Regression in one dimension and is implemented in C++, Python, and Julia. The celerite API is designed to be familiar to users of george and, like george, celerite is designed to efficiently evaluate the marginalized likelihood of a dataset under a GP model. This is then be used alongside a non-linear optimization or posterior inference library for the best results.

[ascl:1709.007]
MSSC: Multi-Source Self-Calibration

Multi-Source Self-Calibration (MSSC) provides direction-dependent calibration to standard phase referencing. The code combines multiple faint sources detected within the primary beam to derive phase corrections. Each source has its CLEAN model divided into the visibilities which results in multiple point sources that are stacked in the uv plane to increase the S/N, thus permitting self-calibration. This process applies only to wide-field VLBI data sets that detect and image multiple sources within one epoch.

[ascl:1709.006]
DCMDN: Deep Convolutional Mixture Density Network

Deep Convolutional Mixture Density Network (DCMDN) estimates probabilistic photometric redshift directly from multi-band imaging data by combining a version of a deep convolutional network with a mixture density network. The estimates are expressed as Gaussian mixture models representing the probability density functions (PDFs) in the redshift space. In addition to the traditional scores, the continuous ranked probability score (CRPS) and the probability integral transform (PIT) are applied as performance criteria. DCMDN is able to predict redshift PDFs independently from the type of source, e.g. galaxies, quasars or stars and renders pre-classification of objects and feature extraction unnecessary; the method is extremely general and allows the solving of any kind of probabilistic regression problems based on imaging data, such as estimating metallicity or star formation rate in galaxies.

[ascl:1709.005]
DanIDL: IDL solutions for science and astronomy

DanIDL provides IDL functions and routines for many standard astronomy needs, such as searching for matching points between two coordinate lists of two-dimensional points where each list corresponds to a different coordinate space, estimating the full-width half-maximum (FWHM) and ellipticity of the PSF of an image, calculating pixel variances for a set of calibrated image data, and fitting a 3-parameter plane model to image data. The library also supplies astrometry, general image processing, and general scientific applications.

[ascl:1709.004]
DOOp: DAOSPEC Output Optimizer pipeline

Cantat-Gaudin, Tristan; Donati, Paolo; Pancino, Elena; Bragaglia, Angela; Vallenari, Antonella; Friel, Eileen D.; Sordo, Rosanna; Jacobson, Heather R.; Magrini, Laura

The DAOSPEC Output Optimizer pipeline (DOOp) runs efficient and convenient equivalent widths measurements in batches of hundreds of spectra. It uses a series of BASH scripts to work as a wrapper for the FORTRAN code DAOSPEC (ascl:1011.002) and uses IRAF (ascl:9911.002) to automatically fix some of the parameters that are usually set by hand when using DAOSPEC. This allows batch-processing of quantities of spectra that would be impossible to deal with by hand. DOOp was originally built for the large quantity of UVES and GIRAFFE spectra produced by the Gaia-ESO Survey, but just like DAOSPEC, it can be used on any high resolution and high signal-to-noise ratio spectrum binned on a linear wavelength scale.

[ascl:1709.003]
MeshLab: 3D triangular meshes processing and editing

MeshLab processes and edits 3D triangular meshes. It includes tools for editing, cleaning, healing, inspecting, rendering, texturing and converting meshes, and offers features for processing raw data produced by 3D digitization tools and devices and for preparing models for 3D printing.

[ascl:1709.002]
PHANTOM: Smoothed particle hydrodynamics and magnetohydrodynamics code

Price, Daniel J.; Wurster, James; Nixon, Chris; Tricco, Terrence S.; Toupin, Stéven; Pettitt, Alex; Chan, Conrad; Laibe, Guillaume; Glover, Simon; Dobbs, Clare; Nealon, Rebecca; Liptai, David; Worpel, Hauke; Bonnerot, Clément; Dipierro, Giovanni; Ragusa, Enrico; Federrath, Christoph; Iaconi, Roberto; Reichardt, Thomas; Forgan, Duncan; Hutchison, Mark; Constantino, Thomas; Ayliffe, Ben; Mentiplay, Daniel; Hirsh, Kieran; Lodato, Giuseppe

Phantom is a smoothed particle hydrodynamics and magnetohydrodynamics code focused on stellar, galactic, planetary, and high energy astrophysics. It is modular, and handles sink particles, self-gravity, two fluid and one fluid dust, ISM chemistry and cooling, physical viscosity, non-ideal MHD, and more. Its modular structure makes it easy to add new physics to the code.

[ascl:1709.001]
SPHYNX: SPH hydrocode for subsonic hydrodynamical instabilities and strong shocks

SPHYNX addresses subsonic hydrodynamical instabilities and strong shocks; it is Newtonian, grounded on the Euler-Lagrange formulation of the smoothed-particle hydrodynamics technique, and density based. SPHYNX uses an integral approach for estimating gradients, a flexible family of interpolators to suppress pairing instability, and incorporates volume elements to provides better partition of the unity.

[ascl:1708.030]
GAMBIT: Global And Modular BSM Inference Tool

The GAMBIT Collaboration; Athron, Peter; Balazs, Csaba; Bringmann, Torsten; Buckley, Andy; Chrząszcz, Marcin; Conrad, Jan; Cornell, Jonathan M.; Dal, Lars A.; Dickinson, Hugh; Edsjö, Joakim; Farmer, Ben; Jackson, Paul; Krislock, Abram; Kvellestad, Anders; Lundberg, Johan; McKay, James; Mahmoudi, Farvah; Martinez, Gregory D.; Putze, Antje Raklev, Are; Ripken, Joachim; Rogan, Christopher; Saavedra, Aldo; Savage, Christopher; Scott, Pat; Seo, Seon-Hee; Serra, Nicola; Weniger, Christoph; White, Martin; Wild, Sebastian

GAMBIT (Global And Modular BSM Inference Tool) performs statistical global fits of generic physics models using a wide range of particle physics and astrophysics data. Modules provide native simulations of collider and astrophysics experiments, a flexible system for interfacing external codes (the backend system), a fully featured statistical and parameter scanning framework, and additional tools for implementing and using hierarchical models.

[ascl:1708.029]
iSEDfit: Bayesian spectral energy distribution modeling of galaxies

iSEDfit uses Bayesian inference to extract the physical properties of galaxies from their observed broadband photometric spectral energy distribution (SED). In its default mode, the inputs to iSEDfit are the measured photometry (fluxes and corresponding inverse variances) and a measurement of the galaxy redshift. Alternatively, iSEDfit can be used to estimate photometric redshifts from the input photometry alone.

After the priors have been specified, iSEDfit calculates the marginalized posterior probability distributions for the physical parameters of interest, including the stellar mass, star-formation rate, dust content, star formation history, and stellar metallicity. iSEDfit also optionally computes K-corrections and produces multiple "quality assurance" (QA) plots at each stage of the modeling procedure to aid in the interpretation of the prior parameter choices and subsequent fitting results. The software is distributed as part of the impro IDL suite.

[ascl:1708.028]
ANA: Astrophysical Neutrino Anisotropy

ANA calculates the likelihood function for a model comprised of two components to the astrophysical neutrino flux detected by IceCube. The first component is extragalactic. Since point sources have not been found and there is increasing evidence that one source catalog cannot describe the entire data set, ANA models the extragalactic flux as isotropic. The second component is galactic. A variety of catalogs of interest are also provided. ANA takes the galactic contribution to be proportional to the matter density of the universe. The likelihood function has one free parameter fgal that is the fraction of the astrophysical flux that is galactic. ANA finds the best fit value of fgal and scans over 0<f_{gal}<1.

[ascl:1708.027]
empiriciSN: Supernova parameter generator

empiriciSN generates realistic supernova parameters given photometric observations of a potential host galaxy, based entirely on empirical correlations measured from supernova datasets. It is intended to be used to improve supernova simulation for DES and LSST. It is extendable such that additional datasets may be added in the future to improve the fitting algorithm or so that additional light curve parameters or supernova types may be fit.

[ascl:1708.026]
XDGMM: eXtreme Deconvolution Gaussian Mixture Modeling

XDGMM uses Gaussian mixtures to do density estimation of noisy, heterogenous, and incomplete data using extreme deconvolution (XD) algorithms which is compatible with the scikit-learn machine learning methods. It implements both the astroML and Bovy et al. (2011) algorithms, and extends the BaseEstimator class from scikit-learn so that cross-validation methods work. It allows the user to produce a conditioned model if values of some parameters are known.

[ascl:1708.025]
extinction-distances: Estimating distances to dark clouds

Extinction-distances uses the number of foreground stars and a Galactic model of the stellar distribution to estimate the distance to dark clouds. It exploits the relatively narrow range of intrinsic near-infrared colors of stars to separate foreground from background stars. An advantage of this method is that the distribution of stellar colors in the Galactic model need not be precisely correct, only the number density as a function of distance from the Sun.

[ascl:1708.024]
ComEst: Completeness Estimator

ComEst calculates the completeness of CCD images conducted in astronomical observations saved in the FITS format. It estimates the completeness of the source finder SExtractor (ascl:1010.064) on the optical and near-infrared (NIR) imaging of point sources or galaxies as a function of flux (or magnitude) directly from the image itself. It uses PyFITS (ascl:1207.009) and GalSim (ascl:1402.009) to perform the end-to-end estimation of the completeness and can also estimate the purity of the source detection.

[ascl:1708.023]
ExoSOFT: Exoplanet Simple Orbit Fitting Toolbox

ExoSOFT provides orbital analysis of exoplanets and binary star systems. It fits any combination of astrometric and radial velocity data, and offers four parameter space exploration techniques, including MCMC. It is packaged with an automated set of post-processing and plotting routines to summarize results, and is suitable for performing orbital analysis during surveys with new radial velocity and direct imaging instruments.

[ascl:1708.022]
Naima: Derivation of non-thermal particle distributions through MCMC spectral fitting

Naima computes non-thermal radiation from relativistic particle populations. It includes tools to perform MCMC fitting of radiative models to X-ray, GeV, and TeV spectra using emcee (ascl:1303.002), an affine-invariant ensemble sampler for Markov Chain Monte Carlo. Naima is an Astropy (ascl:1304.002) affiliated package.

[ascl:1708.020]
4DAO: DAOSPEC interface

4DAO launches DAOSPEC (ascl:1011.002) for a large sample of spectra. Written in Fortran, the software allows one to easily manage the input and output files of DAOSPEC, optimize the main DAOSPEC parameters, and mask specific spectral regions. It also provides suitable graphical tools to evaluate the quality of the solution and provides final, normalized, zero radial velocity spectra.

[ascl:1708.019]
SINFONI Pipeline: Data reduction pipeline for the Very Large Telescope SINFONI spectrograph

The SINFONI pipeline reduces data from the Very Large Telescope's SINFONI (Spectrograph for INtegral Field Observations in the Near Infrared) instrument. It can evaluate the detector linearity and generate a corresponding non linear pixel map, create a master dark and a hot-pixel map, a master flat and a map of pixels which have intensities greater than a given threshold. It can also compute the optical distortions and slitlets distances, and perform wavelength calibration, PSF, telluric standard and other science data reduction, and can coadd bad pixel maps, collapse a cube to an image over a given wavelength range, perform cube arithmetics, among other useful tasks.

[ascl:1708.018]
CUTEX: CUrvature Thresholding EXtractor

CuTEx analyzes images in the infrared bands and extracts sources from complex backgrounds, particularly star-forming regions that offer the challenges of crowding, having a highly spatially variable background, and having no-psf profiles such as protostars in their accreting phase. The code is composed of two main algorithms, the first an algorithm for source detection, and the second for flux extraction. The code is originally written in IDL language and it was exported in the license free GDL language. CuTEx could be used in other bands or in scientific cases different from the native case.

This software is also available as an on-line tool from the Multi-Mission Interactive Archive web pages dedicated to the Herschel Observatory.

[ascl:1708.017]
LCC: Light Curves Classifier

Light Curves Classifier uses data mining and machine learning to obtain and classify desired objects. This task can be accomplished by attributes of light curves or any time series, including shapes, histograms, or variograms, or by other available information about the inspected objects, such as color indices, temperatures, and abundances. After specifying features which describe the objects to be searched, the software trains on a given training sample, and can then be used for unsupervised clustering for visualizing the natural separation of the sample. The package can be also used for automatic tuning parameters of used methods (for example, number of hidden neurons or binning ratio).

Trained classifiers can be used for filtering outputs from astronomical databases or data stored locally. The Light Curve Classifier can also be used for simple downloading of light curves and all available information of queried stars. It natively can connect to OgleII, OgleIII, ASAS, CoRoT, Kepler, Catalina and MACHO, and new connectors or descriptors can be implemented. In addition to direct usage of the package and command line UI, the program can be used through a web interface. Users can create jobs for ”training” methods on given objects, querying databases and filtering outputs by trained filters. Preimplemented descriptors, classifier and connectors can be picked by simple clicks and their parameters can be tuned by giving ranges of these values. All combinations are then calculated and the best one is used for creating the filter. Natural separation of the data can be visualized by unsupervised clustering.

[ascl:1708.016]
pyLCSIM: X-ray lightcurves simulator

pyLCSIM simulates X-ray lightcurves from coherent signals and power spectrum models. Coherent signals can be specified as a sum of one or more sinusoids, each with its frequency, pulsed fraction and phase shift; or as a series of harmonics of a fundamental frequency (each with its pulsed fraction and phase shift). Power spectra can be simulated from a model of the power spectrum density (PSD) using as a template one or more of the built-in library functions. The user can also define his/her custom models. Models are additive.

[ascl:1708.021]
KERTAP: Strong lensing effects of Kerr black holes

KERTAP computes the strong lensing effects of Kerr black holes, including the effects on polarization. The key ingredients of KERTAP are a graphic user interface, a backward ray-tracing algorithm, a polarization propagator dealing with gravitational Faraday rotation, and algorithms computing observables such as flux magnification and polarization angles.

[ascl:1708.015]
TWO-POP-PY: Two-population dust evolution model

TWO-POP-PY runs a two-population dust evolution model that follows the upper end of the dust size distribution and the evolution of the dust surface density profile and treats dust surface density, maximum particle size, small and large grain velocity, and fragmentation. It derives profiles that describe the dust-to-gas ratios and the dust surface density profiles well in protoplanetary disks, in addition to the radial flux by solid material rain out.

[ascl:1708.014]
PACSman: IDL Suite for Herschel/PACS spectrometer data

PACSman provides an alternative for several reduction and analysis steps performed in HIPE (ascl:1111.001) on PACS spectroscopic data; it is written in IDL. Among the operations possible with it are transient correction, line fitting, map projection, and map analysis, and unchopped scan, chop/nod, and the decommissioned wavelength switching observation modes are supported.

[ascl:1708.013]
GMM: Gaussian Mixture Modeling

GMM (Gaussian Mixture Modeling) tests the existence of bimodality in globular cluster color distributions. GMM uses three indicators to distinguish unimodal and bimodal distributions: the kurtosis of the distribution, the separation of the peaks, and the probability of obtaining the same χ2 from a unimodal distribution.

[ascl:1708.012]
GANDALF: Gas AND Absorption Line Fitting

Sarzi, Marc; Falcón-Barroso, Jesús; Davies, Roger L.; Bacon, Roland; Bureau, Martin; Cappellari, Michele; de Zeeuw, P. Tim; Emsellem, Eric; Fathi, Kambiz; Krajnović, Davor; Kuntschner, Harald; McDermid, Richard M.; Peletier, Reynier F.

GANDALF (Gas AND Absorption Line Fitting) accurately separates the stellar and emission-line contributions to observed spectra. The IDL code includes reddening by interstellar dust and also returns formal errors on the position, width, amplitude and flux of the emission lines. Example wrappers that make use of pPXF (ascl:1210.002) to derive the stellar kinematics are included.

[ascl:1708.011]
RM-CLEAN: RM spectra cleaner

RM-CLEAN reads in dirty Q and U cubes, generates rmtf based on the frequencies given in an ASCII file, and cleans the RM spectra following the algorithm given by Brentjens (2007). The output cubes contain the clean model components and the CLEANed RM spectra. The input cubes must be reordered with mode=312, and the output cubes will have the same ordering and thus must be reordered after being written to disk. RM-CLEAN runs as a MIRIAD (ascl:1106.007) task and a Python wrapper is included with the code.

[ascl:1708.010]
BAGEMASS: Bayesian age and mass estimates for transiting planet host stars

BAGEMASS calculates the posterior probability distribution for the mass and age of a star from its observed mean density and other observable quantities using a grid of stellar models that densely samples the relevant parameter space. It is written in Fortran and requires FITSIO (ascl:1010.001).

[ascl:1708.009]
FIEStool: Automated data reduction for FIber-fed Echelle Spectrograph (FIES)

FIEStool automatically reduces data obtained with the FIber-fed Echelle Spectrograph (FIES) at the Nordic Optical Telescope, a high-resolution spectrograph available on a stand-by basis, while also allowing the basic properties of the reduction to be controlled in real time by the user. It provides a Graphical User Interface and offers bias subtraction, flat-fielding, scattered-light subtraction, and specialized reduction tasks from the external packages IRAF (ascl:9911.002) and NumArray. The core of FIEStool is instrument-independent; the software, written in Python, could with minor modifications also be used for automatic reduction of data from other instruments.

[ascl:1708.008]
ALCHEMIC: Advanced time-dependent chemical kinetics

ALCHEMIC solves chemical kinetics problems, including gas-grain interactions, surface reactions, deuterium fractionization, and transport phenomena and can model the time-dependent chemical evolution of molecular clouds, hot cores, corinos, and protoplanetary disks.

[ascl:1708.007]
PBMC: Pre-conditioned Backward Monte Carlo code for radiative transport in planetary atmospheres

PBMC (Pre-Conditioned Backward Monte Carlo) solves the vector Radiative Transport Equation (vRTE) and can be applied to planetary atmospheres irradiated from above. The code builds the solution by simulating the photon trajectories from the detector towards the radiation source, *i.e.* in the reverse order of the actual photon displacements. In accounting for the polarization in the sampling of photon propagation directions and pre-conditioning the scattering matrix with information from the scattering matrices of prior (in the BMC integration order) photon collisions, PBMC avoids the unstable and biased solutions of classical BMC algorithms for conservative, optically-thick, strongly-polarizing media such as Rayleigh atmospheres.

[ascl:1708.006]
DISORT: DIScrete Ordinate Radiative Transfer

DISORT (DIScrete Ordinate Radiative Transfer) solves the problem of 1D scalar radiative transfer in a single optical medium, such as a planetary atmosphere. The code correctly accounts for multiple scattering by an isotropic or plane-parallel beam source, internal Planck sources, and reflection from a lower boundary. Provided that polarization effects can be neglected, DISORT efficiently calculates accurate fluxes and intensities at any user-specified angle and location within the user-specified medium.

[ascl:1708.005]
STools: IDL Tools for Spectroscopic Analysis

STools contains a variety of simple tools for spectroscopy, such as reading an IRAF-formatted (multispec) echelle spectrum in FITS, measuring the wavelength of the center of a line, Gaussian convolution, deriving synthetic photometry from an input spectrum, and extracting and interpolating a MARCS model atmosphere (standard composition).

[ascl:1708.004]
Astroquery: Access to online data resources

Ginsburg, Adam; Parikh, Madhura; Woillez, Julien; Groener, Austen; Liedtke, Simon; Sipocz, Brigitta; Robitaille, Thomas; Deil, Christoph; Svoboda, Brian; Tollerud, Erik; Persson, Magnus Vilhelm; Séguin-Charbonneau, Loïc; Armstrong, Caden; Mirocha, Jordan; Droettboom, Michael; Allen, James; Moolekamp, Fred; Egeland, Ricky; Singer, Leo; Barbary, Kyle; Grollier, Frédéric; Shiga, David; Moritz Günther, Hans; Parejko, John; Booker, Joseph; Rol, Evert; Edward; Miller, Adam; Willett, Kyle

Astroquery allows users to access online astronomical data from a wide range of sources; it is an Astropy-affiliated package. Each web service has its own sub-package for interfacing with a particular data source.

[ascl:1708.003]
CRISPRED: CRISP imaging spectropolarimeter data reduction pipeline

CRISPRED reduces data from the CRISP imaging spectropolarimeter at the Swedish 1 m Solar Telescope (SST). It performs fitting routines, corrects optical aberrations from atmospheric turbulence as well as from the optics, and compensates for inter-camera misalignments, field-dependent and time-varying instrumental polarization, and spatial variation in the detector gain and in the zero level offset (bias). It has an object-oriented IDL structure with computationally demanding routines performed in C subprograms called as dynamically loadable modules (DLMs).

[ascl:1708.002]
CINE: Comet INfrared Excitation

CINE calculates infrared pumping efficiencies that can be applied to the most common molecules found in cometary comae such as water, hydrogen cyanide or methanol. One of the main mechanisms for molecular excitation in comets is the fluorescence by the solar radiation followed by radiative decay to the ground vibrational state. This command-line tool calculates the effective pumping rates for rotational levels in the ground vibrational state scaled by the heliocentric distance of the comet. Fluorescence coefficients are useful for modeling rotational emission lines observed in cometary spectra at sub-millimeter wavelengths. Combined with computational methods to solve the radiative transfer equations based, e.g., on the Monte Carlo algorithm, this model can retrieve production rates and rotational temperatures from the observed emission spectrum.

[ascl:1708.001]
ATOOLS: A command line interface to the AST library

The ATOOLS package of applications provides an interface to the AST library (ascl:1404.016), allowing quick experiments to be performed from the shell. It manipulates descriptions of coordinate frames and mappings in the form of AST objects and performs other functions, with each application within the package corresponding closely to one of the functions in the AST library.

[ascl:1707.007]
swot: Super W Of Theta

SWOT (Super W Of Theta) computes two-point statistics for very large data sets, based on “divide and conquer” algorithms, mainly, but not limited to data storage in binary trees, approximation at large scale, parellelization (open MPI), and bootstrap and jackknife resampling methods “on the fly”. It currently supports projected and 3D galaxy auto and cross correlations, galaxy-galaxy lensing, and weighted histograms.

[ascl:1707.006]
Gala: Galactic astronomy and gravitational dynamics

Gala is a Python package (and Astropy affiliated package) for Galactic astronomy and gravitational dynamics. The bulk of the package centers around implementations of gravitational potentials, numerical integration, nonlinear dynamics, and astronomical velocity transformations (i.e. proper motions). Gala uses the Astropy units and coordinates subpackages extensively to provide a clean, pythonic interface to these features but does any heavy-lifting in C and Cython for speed.

[ascl:1707.005]
PyMOC: Multi-Order Coverage map module for Python

PyMOC manipulates Multi-Order Coverage (MOC) maps. It supports reading and writing the three encodings mentioned in the IVOA MOC recommendation: FITS, JSON and ASCII.

[ascl:1707.004]
CCFpams: Atmospheric stellar parameters from cross-correlation functions

CCFpams allows the measurement of stellar temperature, metallicity and gravity within a few seconds and in a completely automated fashion. Rather than performing comparisons with spectral libraries, the technique is based on the determination of several cross-correlation functions (CCFs) obtained by including spectral features with different sensitivity to the photospheric parameters. Literature stellar parameters of high signal-to-noise (SNR) and high-resolution HARPS spectra of FGK Main Sequence stars are used to calibrate the stellar parameters as a function of CCF areas.

[ascl:1707.003]
pyaneti: Multi-planet radial velocity and transit fitting

Pyaneti is a multi-planet radial velocity and transit fit software. The code uses Markov chain Monte Carlo (MCMC) methods with a Bayesian approach and a parallelized ensemble sampler algorithm in Fortran which makes the code fast. It creates posteriors, correlations, and ready-to-publish plots automatically, and handles circular and eccentric orbits. It is capable of multi-planet fitting and handles stellar limb darkening, systemic velocities for multiple instruments, and short and long cadence data, and offers additional capabilities.

[ascl:1707.002]
SASRST: Semi-Analytic Solutions for 1-D Radiative Shock Tubes

SASRST, a small collection of Python scripts, attempts to reproduce the semi-analytical one-dimensional equilibrium and non-equilibrium radiative shock tube solutions of Lowrie & Rauenzahn (2007) and Lowrie & Edwards (2008), respectively. The included code calculates the solution for a given set of input parameters and also plots the results using Matplotlib. This software was written to provide validation for numerical radiative shock tube solutions produced by a radiation hydrodynamics code.

[ascl:1707.001]
HRM: HII Region Models

HII Region Models fits HII region models to observed radio recombination line and radio continuum data. The algorithm includes the calculations of departure coefficients to correct for non-LTE effects. HII Region Models has been used to model star formation in the nucleus of IC 342.

[ascl:1706.012]
KeplerSolver: Kepler equation solver

KeplerSolver solves Kepler's equation for arbitrary epoch and eccentricity, using continued fractions. It is written in C and its speed is nearly the same as the SWIFT routines, while achieving machine precision. It comes with a test program to demonstrate usage.

[ascl:1706.011]
PyPulse: PSRFITS handler

PyPulse handles PSRFITS files and performs subsequent analyses on pulse profiles.

[ascl:1706.010]
EXOSIMS: Exoplanet Open-Source Imaging Mission Simulator

EXOSIMS generates and analyzes end-to-end simulations of space-based exoplanet imaging missions. The software is built up of interconnecting modules describing different aspects of the mission, including the observatory, optical system, and scheduler (encoding mission rules) as well as the physical universe, including the assumed distribution of exoplanets and their physical and orbital properties. Each module has a prototype implementation that is inherited by specific implementations for different missions concepts, allowing for the simulation of widely variable missions.

[submitted]
KERN

KERN is a bi-annually released set of radio astronomical software packages. It should contain most of the standard tools that a radio astronomer needs to work with radio telescope data. The goal of KERN to is to save time and frustration in setting up of scientific pipelines, and to assist in achieving scientific reproducibility.

[submitted]
Kliko - The Scientific Compute Container Format

We present Kliko, a Docker based container specification for running one or multiple related compute jobs. The key concepts of Kliko is the encapsulation of data processing software into a container and the formalisation of the input, output and task parameters. Formalisation is realised by bundling a container with a Kliko file, which describes the IO and task parameters. This Kliko container can then be opened and run by a Kliko runner. The Kliko runner will parse the Kliko definition and gather the values for these parameters, for example by requesting user input or pre defined values in a script. Parameters can be various primitive types, for example float, int or the path to a file. This paper will also discuss the implementation of a support library named Kliko which can be used to create Kliko containers, parse Kliko definitions, chain Kliko containers in workflows using, for example, Luigi a workflow manager. The Kliko library can be used inside the container interact with the Kliko runner. Finally this paper will discuss two reference implementations based on Kliko: RODRIGUES, a web based Kliko container schedular and output visualiser specifically for astronomical data, and VerMeerKAT, a multi container workflow data reduction pipeline which is being used as a prototype pipeline for the commisioning of the MeerKAT radio telescope.

[ascl:1706.009]
sick: Spectroscopic inference crank

sick infers astrophysical parameters from noisy observed spectra. Phenomena that can alter the data (e.g., redshift, continuum, instrumental broadening, outlier pixels) are modeled and simultaneously inferred with the astrophysical parameters of interest. This package relies on emcee (ascl:1303.002); it is best suited for situations where a grid of model spectra already exists, and one would like to infer model parameters given some data.

[ascl:1706.008]
the-wizz: Clustering redshift estimation code

the-wizz clusters redshift estimates for any photometric unknown sample in a survey. The software is composed of two main parts: a pair finder and a pdf maker. The pair finder finds spatial pairs and stores the indices of all closer pairs around target reference objects in an output HDF5 data file. Users then query this data file using the indices of their unknown sample to produce an output clustering-z.

[ascl:1706.007]
encube: Large-scale comparative visualization and analysis of sets of multidimensional data

Vohl, Dany; Barnes, David G.; Fluke, Christopher J.; Poudel, Govinda; Georgiou-Karistianis, Nellie; Hassan, Amr H.; Benovitski, Yuri; Wong, Tsz Ho; Kaluza, Owen; Nguyen, Toan D.; Bonnington, C. Paul

Encube is a qualitative, quantitative and comparative visualization and analysis framework, with application to high-resolution, immersive three-dimensional environments and desktop displays, providing a capable visual analytics experience across the display ecology. Encube includes mechanisms for the support of: 1) interactive visual analytics of sufficiently large subsets of data; 2) synchronous and asynchronous collaboration; and 3) documentation of the discovery workflow. The framework is modular, allowing additional functionalities to be included as required.

[ascl:1706.006]
GenPK: Power spectrum generator

GenPK generates the 3D matter power spectra for each particle species from a Gadget snapshot. Written in C++, it requires both FFTW3 and GadgetReader.

[ascl:1706.005]
LMC: Logarithmantic Monte Carlo

LMC is a Markov Chain Monte Carlo engine in Python that implements adaptive Metropolis-Hastings and slice sampling, as well as the affine-invariant method of Goodman & Weare, in a flexible framework. It can be used for simple problems, but the main use case is problems where expensive likelihood evaluations are provided by less flexible third-party software, which benefit from parallelization across many nodes at the sampling level. The parallel/adaptive methods use communication through MPI, or alternatively by writing/reading files, and mostly follow the approaches pioneered by CosmoMC (ascl:1106.025).

[ascl:1706.004]
Dark Sage: Semi-analytic model of galaxy evolution

DARK SAGE is a semi-analytic model of galaxy formation that focuses on detailing the structure and evolution of galaxies' discs. The code-base, written in C, is an extension of SAGE (ascl:1601.006) and maintains the modularity of SAGE. DARK SAGE runs on any N-body simulation with trees organized in a supported format and containing a minimum set of basic halo properties.

[ascl:1706.003]
DaMaSCUS: Dark Matter Simulation Code for Underground Scatterings

DaMaSCUS calculates the density and velocity distribution of dark matter (DM) at any detector of given depth and latitude to provide dark matter particle trajectories inside the Earth. Provided a strong enough DM-matter interaction, the particles scatter on terrestrial atoms and get decelerated and deflected. The resulting local modifications of the DM velocity distribution and number density can have important consequences for direct detection experiments, especially for light DM, and lead to signatures such as diurnal modulations depending on the experiment's location on Earth. The code involves both the Monte Carlo simulation of particle trajectories and generation of data as well as the data analysis consisting of non-parametric density estimation of the local velocity distribution functions and computation of direct detection event rates.

[ascl:1706.002]
rtpipe: Searching for Fast Radio Transients in Interferometric Data

rtpipe (real-time pipeline) analyzes radio interferometric data with an emphasis on searching for transient or variable astrophysical sources. The package combines single-dish concepts such as dedispersion and filters with interferometric concepts, including images and the uv-plane. In contrast to time-domain data recorded with large single-dish telescopes, visibilities from interferometers can precisely localize sources anywhere in the entire field of view. rtpipe opens interferometers to the study of fast transient sky, including sources like pulsars, stellar flares, rotating radio transients, and fast radio bursts. Key portions of the search pipeline, such as image generation and dedispersion, have been accelerated. That, in combination with its multi-threaded, multi-node design, makes rtpipe capable of searching millisecond timescale data in real time on small compute clusters.

[ascl:1706.001]
Exotrending: Fast and easy-to-use light curve detrending software for exoplanets

The simple, straightforward Exotrending code detrends exoplanet transit light curves given a light curve (flux versus time) and good ephemeris (epoch of first transit and orbital period). The code has been tested with Kepler and K2 light curves and should work with any other light curve.

[ascl:1705.017]
supernovae: Photometric classification of supernovae

Supernovae classifies supernovae using their light curves directly as inputs to a deep recurrent neural network, which learns information from the sequence of observations. Observational time and filter fluxes are used as inputs; since the inputs are agnostic, additional data such as host galaxy information can also be included.

[ascl:1705.016]
astroABC: Approximate Bayesian Computation Sequential Monte Carlo sampler

astroABC is a Python implementation of an Approximate Bayesian Computation Sequential Monte Carlo (ABC SMC) sampler for parameter estimation. astroABC allows for massive parallelization using MPI, a framework that handles spawning of processes across multiple nodes. It has the ability to create MPI groups with different communicators, one for the sampler and several others for the forward model simulation, which speeds up sampling time considerably. For smaller jobs the Python multiprocessing option is also available.

[ascl:1705.015]
WeirdestGalaxies: Outlier Detection Algorithm on Galaxy Spectra

WeirdestGalaxies finds the weirdest galaxies in the Sloan Digital Sky Survey (SDSS) by using a basic outlier detection algorithm. It uses an unsupervised Random Forest (RF) algorithm to assign a similarity measure (or distance) between every pair of galaxy spectra in the SDSS. It then uses the distance matrix to find the galaxies that have the largest distance, on average, from the rest of the galaxies in the sample, and defined them as outliers.

[ascl:1705.014]
NPTFit: Non-Poissonian Template Fitting

NPTFit is a specialized Python/Cython package that implements Non-Poissonian Template Fitting (NPTF), originally developed for characterizing populations of unresolved point sources. It offers fast evaluation of likelihoods for NPTF analyses and has an easy-to-use interface for performing non-Poissonian (as well as standard Poissonian) template fits using MultiNest (ascl:1109.006) or other inference tools. It allows inclusion of an arbitrary number of point source templates, with an arbitrary number of degrees of freedom in the modeled flux distribution, and has modules for analyzing and plotting the results of an NPTF.

[ascl:1705.013]
PSOAP: Precision Spectroscopic Orbits A-Parametrically

PSOAP (Precision Spectroscopic Orbits A-Parametrically) uses Gaussian processes to infer component spectra of single-lined and double-lined spectroscopic binaries, while simultaneously exploring the posteriors of the orbital parameters and the spectra themselves. PSOAP accounts for the natural λ-covariances in each spectrum, thus providing a natural "de-noising" of the spectra typically offered by Fourier techniques.

[ascl:1705.012]
fd3: Spectral disentangling of double-lined spectroscopic binary stars

The spectral disentangling technique can be applied on a time series of observed spectra of a spectroscopic double-lined binary star (SB2) to determine the parameters of orbit and reconstruct the spectra of component stars, without the use of template spectra. fd3 disentangles the spectra of SB2 stars, capable also of resolving the possible third companion. It performs the separation of spectra in the Fourier space which is faster, but in several respects less versatile than the wavelength-space separation. (Wavelength-space separation is implemented in the twin code CRES.) fd3 is written in C and is designed as a command-line utility for a Unix-like operating system. fd3 is a new version of FDBinary (ascl:1705.011), which is now deprecated.

[ascl:1705.011]
FDBinary: A tool for spectral disentangling of double-lined spectroscopic binary stars

FDBinary disentangles spectra of SB2 stars. The spectral disentangling technique can be applied on a time series of observed spectra of an SB2 to determine the parameters of orbit and reconstruct the spectra of component stars, without the use of template spectra. The code is written in C and is designed as a command-line utility for a Unix-like operating system. FDBinary uses the Fourier-space approach in separation of composite spectra. This code has been replaced with the newer fd3 (ascl:1705.012).

[ascl:1705.010]
PROFILER: 1D galaxy light profile decomposition

Written in Python, PROFILER analyzes the radial surface brightness profiles of galaxies. It accurately models a wide range of galaxies and galaxy components, such as elliptical galaxies, the bulges of spiral and lenticular galaxies, nuclear sources, discs, bars, rings, and spiral arms with a variety of parametric functions routinely employed in the field (Sérsic, core-Sérsic, exponential, Gaussian, Moffat and Ferrers). In addition, Profiler can employ the broken exponential model (relevant for disc truncations or antitruncations) and two special cases of the edge-on disc model: namely along the major axis (in the disc plane) and along the minor axis (perpendicular to the disc plane).

[ascl:1705.009]
LensPop: Galaxy-galaxy strong lensing population simulation

LensPop simulates observations of the galaxy-galaxy strong lensing population in the Dark Energy Survey (DES), the Large Synoptic Survey Telescope (LSST), and Euclid surveys.

[ascl:1705.008]
MBProj2: Multi-Band x-ray surface brightness PROJector 2

MBProj2 obtains thermodynamic profiles of galaxy clusters. It forward-models cluster X-ray surface brightness profiles in multiple bands, optionally assuming hydrostatic equilibrium. The code is a set of Python classes the user can use or extend. When modelling a cluster assuming hydrostatic equilibrium, the user chooses a form for the density profile (e.g. binning or a beta model), the metallicity profile, and the dark matter profile (e.g. NFW). If hydrostatic equilibrium is not assumed, a temperature profile model is used instead of the dark matter profile. The code uses the emcee Markov Chain Monte Carlo code (ascl:1303.002) to sample the model parameters, using these to produce chains of thermodynamic profiles.

[submitted]
HHTpywrapper: Python Wrapper for Hilbert–Huang Transform MATLAB Package

HHTpywrapper is a python interface to call the Hilbert–Huang Transform (HHT) MATLAB package. HHT is a time-frequency analysis method to adaptively decompose a signal, that could be generated by non-stationary and/or nonlinear processes, into basis components at different timescales, and then Hilbert transform these components into instantaneous phases, frequencies and amplitudes as functions of time. HHT has been successfully applied to analyzing X-ray quasi-periodic oscillations (QPOs) from the active galactic nucleus RE J1034+396 (Hu et al. 2014) and two black hole X-ray binaries, XTE J1550–564 (Su et al. 2015) and GX 339-4 (Su et al. 2017). HHTpywrapper provides examples of reproducing HHT analysis results in Su et al. (2015) and Su et al. (2017). This project is originated from the Astro Hack Week 2015.

[ascl:1705.007]
getimages: Background derivation and image flattening method

*getimages* performs background derivation and image flattening for high-resolution images obtained with space observatories. It is based on median filtering with sliding windows corresponding to a range of spatial scales from the observational beam size up to a maximum structure width X. The latter is a single free parameter of *getimages* that can be evaluated manually from the observed image. The median filtering algorithm provides a background image for structures of all widths below X. The same median filtering procedure applied to an image of standard deviations derived from a background-subtracted image results in a flattening image. Finally, a flattened image is computed by dividing the background-subtracted by the flattening image. Standard deviations in the flattened image are now uniform outside sources and filaments. Detecting structures in such radically simplified images results in much cleaner extractions that are more complete and reliable. *getimages* also reduces various observational and map-making artifacts and equalizes noise levels between independent tiles of mosaicked images. The code (a Bash script) uses FORTRAN utilities from *getsources* (ascl:1507.014), which must be installed.

[ascl:1705.006]
f3: Full Frame Fotometry for Kepler Full Frame Images

Light curves from the Kepler telescope rely on "postage stamp" cutouts of a few pixels near each of 200,000 target stars. These light curves are optimized for the detection of short-term signals like planet transits but induce systematics that overwhelm long-term variations in stellar flux. Longer-term effects can be recovered through analysis of the Full Frame Images, a set of calibration data obtained monthly during the Kepler mission. The Python package f3 analyzes the Full Frame Images to infer long-term astrophysical variations in the brightness of Kepler targets, such as magnetic activity or sunspots on slowly rotating stars.

[ascl:1705.005]
SPTCLASS: SPecTral CLASSificator code

SPTCLASS assigns semi-automatic spectral types to a sample of stars. The main code includes three spectral classification schemes: the first one is optimized to classify stars in the mass range of TTS (K5 or later, hereafter LATE-type scheme); the second one is optimized to classify stars in the mass range of IMTTS (F late to K early, hereafter Gtype scheme), and the third one is optimized to classify stars in the mass range of HAeBe (F5 or earlier, hereafter HAeBe scheme). SPTCLASS has an interactive module that allows the user to select the best result from the three schemes and analyze the input spectra.

[ascl:1705.004]
PCAT: Probabilistic Cataloger

PCAT (Probabilistic Cataloger) samples from the posterior distribution of a metamodel, i.e., union of models with different dimensionality, to compare the models. This is achieved via transdimensional proposals such as births, deaths, splits and merges in addition to the within-model proposals. This method avoids noisy estimates of the Bayesian evidence that may not reliably distinguish models when sampling from the posterior probability distribution of each model.

The code has been applied in two different subfields of astronomy: high energy photometry, where transdimensional elements are gamma-ray point sources; and strong lensing, where light-deflecting dark matter subhalos take the role of transdimensional elements.

[ascl:1705.003]
demc2: Differential evolution Markov chain Monte Carlo parameter estimator

demc2, also abbreviated as DE-MCMC, is a differential evolution Markov Chain parameter estimation library written in R for adaptive MCMC on real parameter spaces.

[ascl:1705.002]
DMATIS: Dark Matter ATtenuation Importance Sampling

DMATIS (Dark Matter ATtenuation Importance Sampling) calculates the trajectories of DM particles that propagate in the Earth's crust and the lead shield to reach the DAMIC detector using an importance sampling Monte-Carlo simulation. A detailed Monte-Carlo simulation avoids the deficiencies of the SGED/KS method that uses a mean energy loss description to calculate the lower bound on the DM-proton cross section. The code implementing the importance sampling technique makes the brute-force Monte-Carlo simulation of moderately strongly interacting DM with nucleons computationally feasible. DMATIS is written in Python 3 and MATHEMATICA.

[ascl:1705.001]
COSMOS: Carnegie Observatories System for MultiObject Spectroscopy

COSMOS (Carnegie Observatories System for MultiObject Spectroscopy) reduces multislit spectra obtained with the IMACS and LDSS3 spectrographs on the Magellan Telescopes. It can be used for the quick-look analysis of data at the telescope as well as for pipeline reduction of large data sets. COSMOS is based on a precise optical model of the spectrographs, which allows (after alignment and calibration) an accurate prediction of the location of spectra features. This eliminates the line search procedure which is fundamental to many spectral reduction programs, and allows a robust data pipeline to be run in an almost fully automatic mode, allowing large amounts of data to be reduced with minimal intervention.

[ascl:1704.014]
Multipoles: Potential gain for binary lens estimation

Multipoles, written in Python, calculates the quadrupole and hexadecapole approximations of the finite-source magnification: quadrupole (Wk,rho,Gamma) and hexadecapole (Wk,rho,Gamma). The code is efficient and faster than previously available methods, and could be generalized for use on large portions of the light curves.

[ascl:1704.013]
Difference-smoothing: Measuring time delay from light curves

The Difference-smoothing MATLAB code measures the time delay from the light curves of images of a gravitationally lendsed quasar. It uses a smoothing timescale free parameter, generates more realistic synthetic light curves to estimate the time delay uncertainty, and uses *X*^{2} plot to assess the reliability of a time delay measurement as well as to identify instances of catastrophic failure of the time delay estimator. A systematic bias in the measurement of time delays for some light curves can be eliminated by applying a correction to each measured time delay.

[ascl:1704.012]
XID+: Next generation XID development

XID+ is a prior-based source extraction tool which carries out photometry in the Herschel SPIRE (Spectral and Photometric Imaging Receiver) maps at the positions of known sources. It uses a probabilistic Bayesian framework that provides a natural framework in which to include prior information, and uses the Bayesian inference tool Stan to obtain the full posterior probability distribution on flux estimates.

[ascl:1704.011]
VULCAN: Chemical Kinetics For Exoplanetary Atmospheres

VULCAN describes gaseous chemistry from 500 to 2500 K using a reduced C-H-O chemical network with about 300 reactions. It uses eddy diffusion to mimic atmospheric dynamics and excludes photochemistry, and can be used to examine the theoretical trends produced when the temperature-pressure profile and carbon-to-oxygen ratio are varied.

[ascl:1704.010]
A-Track: Detecting Moving Objects in FITS images

A-Track is a fast, open-source, cross-platform pipeline for detecting moving objects (asteroids and comets) in sequential telescope images in FITS format. The moving objects are detected using a modified line detection algorithm.

[ascl:1704.009]
Photo-z-SQL: Photometric redshift estimation framework

Photo-z-SQL is a flexible template-based photometric redshift estimation framework that can be seamlessly integrated into a SQL database (or DB) server and executed on demand in SQL. The DB integration eliminates the need to move large photometric datasets outside a database for redshift estimation, and uses the computational capabilities of DB hardware. Photo-z-SQL performs both maximum likelihood and Bayesian estimation and handles inputs of variable photometric filter sets and corresponding broad-band magnitudes.

[ascl:1704.008]
Transit: Radiative-transfer code for planetary atmospheres

Cubillos, Patricio; Blecic, Jasmina; Harrington, Joe; Rojo, Patricio; Foster, Austin J.; Stemm, Madison; Challener,Ryan; Foster, Andrew S. D.

Transit calculates the transmission or emission spectrum of a planetary atmosphere with application to extrasolar-planet transit and eclipse observations, respectively. It computes the spectra by solving the one-dimensional line-by-line radiative-transfer equation for an atmospheric model.

[ascl:1704.007]
PySM: Python Sky Model

PySM generates full-sky simulations of Galactic foregrounds in intensity and polarization relevant for CMB experiments. The components simulated are thermal dust, synchrotron, AME, free-free, and CMB at a given Nside, with an option to integrate over a top hat bandpass, to add white instrument noise, and to smooth with a given beam. PySM is based on the large-scale Galactic part of Planck Sky Model code and uses some of its inputs.

[ascl:1704.006]
Quickclump: Identify clumps within a 3D FITS datacube

Quickclump finds clumps in a 3D FITS datacube. It is a fast, accurate, and automated tool written in Python. Though Quickclump is primarily intended for decomposing observations of interstellar clouds into individual clumps, it can also be used for finding clumps in any 3D rectangular data.

[ascl:1704.005]
VaST: Variability Search Toolkit

VaST (Variability Search Toolkit) finds variable objects on a series of astronomical images in FITS format. The software performs object detection and aperture photometry using SExtractor (ascl:1010.064) on each image, cross-matches lists of detected stars, performs magnitude calibration with respect to the first (reference) image and constructs a lightcurve for each object. The sigma-magnitude, Stetson's L variability index, Robust Median Statistic (RoMS) and other plots may be used to visually identify variable star candidates. The two distinguishing features of VaST are its ability to perform accurate aperture photometry of images obtained with non-linear detectors and to handle complex image distortions. VaST can be used in cases of unstable PSF (e.g., bad guiding or with digitized wide-field photographic images), and has been successfully applied to images obtained with telescopes ranging from 0.08 to 2.5m in diameter equipped with a variety of detectors including CCD, CMOS, MIC and photographic plates.

[ascl:1704.004]
STATCONT: Statistical continuum level determination method for line-rich sources

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:1704.003]
Shwirl: Meaningful coloring of spectral cube data with volume rendering

Shwirl visualizes spectral data cubes with meaningful coloring methods. The program has been developed to investigate transfer functions, which combines volumetric elements (or voxels) to set the color, and graphics shaders, functions used to compute several properties of the final image such as color, depth, and/or transparency, as enablers for scientific visualization of astronomical data. The program uses Astropy (ascl:1304.002) to handle FITS files and World Coordinate System, Qt (and PyQt) for the user interface, and VisPy, an object-oriented Python visualization library binding onto OpenGL.

[ascl:1704.002]
UDAT: A multi-purpose data analysis tool

UDAT is a pattern recognition tool for mass analysis of various types of data, including image and audio. Based on its WND-CHARM (ascl:1312.002) prototype, UDAT computed a large set of numerical content descriptors from each file it analyzes, and selects the most informative features using statistical analysis. The tool can perform automatic classification of galaxy images by training with annotated galaxy images. It also has unsupervised learning capabilities, such as query-by-example of galaxies based on morphology. That is, given an input galaxy image of interest, the tool can search through a large database of images to retrieve the galaxies that are the most similar to the query image. The downside of the tool is its computational complexity, which in most cases will require a small or medium cluster.

[ascl:1704.001]
pwkit: Astronomical utilities in Python

pwkit is a collection of miscellaneous astronomical utilities in Python, with an emphasis on radio astronomy, reading and writing various data formats, and convenient command-line utilities. Utilities include basic astronomical calculations, data visualization tools such as mapping arbitrary data to color scales and tracing contours, and data input and output utilities such as streaming output from other programs.

[ascl:1703.015]
Charm: Cosmic history agnostic reconstruction method

Charm (cosmic history agnostic reconstruction method) reconstructs the cosmic expansion history in the framework of Information Field Theory. The reconstruction is performed via the iterative Wiener filter from an agnostic or from an informative prior. The charm code allows one to test the compatibility of several different data sets with the LambdaCDM model in a non-parametric way.

[ascl:1703.014]
MC-SPAM: Monte-Carlo Synthetic-Photometry/Atmosphere-Model

MC-SPAM (Monte-Carlo Synthetic-Photometry/Atmosphere-Model) generates limb-darkening coefficients from models that are comparable to transit photometry; it extends the original SPAM algorithm by Howarth (2011) by taking in consideration the uncertainty on the stellar and transit parameters of the system under analysis.

[ascl:1703.013]
Atmospheric Athena: 3D Atmospheric escape model with ionizing radiative transfer

Atmospheric Athena simulates hydrodynamic escape from close-in giant planets in 3D. It uses the Athena hydrodynamics code (ascl:1010.014) with a new ionizing radiative transfer implementation to self-consistently model photoionization driven winds from the planet. The code is fully compatible with static mesh refinement and MPI parallelization and can handle arbitrary planet potentials and stellar initial conditions.

[ascl:1703.012]
ICICLE: Initial Conditions for Isolated CoLlisionless systEms

ICICLE (Initial Conditions for Isolated CoLlisionless systEms) generates stable initial conditions for isolated collisionless systems that can then be used in NBody simulations. It supports the Navarro-Frenk-White, Hernquist, King and Einasto density profiles.

[ascl:1703.011]
QtClassify: IFS data emission line candidates classifier

QtClassify is a GUI that helps classify emission lines found in integral field spectroscopic data. Input needed is a datacube as well as a catalog with emission lines and a signal-to-noise cube, such at that created by LSDCat (ascl:1612.002). The main idea is to take each detected line and guess what line it could be (and thus the redshift of the object). You would expect to see other lines that might not have been detected but are visible in the cube if you know where to look, which is why parts of the spectrum are shown where other lines are expected. In addition, monochromatic layers of the datacube are displayed, making it easy to spot additional emission lines.

[ascl:1703.010]
TransitSOM: Self-Organizing Map for Kepler and K2 transits

A self-organizing map (SOM) can be used to identify planetary candidates from Kepler and K2 datasets with accuracies near 90% in distinguishing known Kepler planets from false positives. TransitSOM classifies a Kepler or K2 lightcurve using a self-organizing map (SOM) created and pre-trained using PyMVPA (ascl:1703.009). It includes functions for users to create their own SOMs.

[ascl:1703.009]
PyMVPA: MultiVariate Pattern Analysis in Python

PyMVPA eases statistical learning analyses of large datasets. It offers an extensible framework with a high-level interface to a broad range of algorithms for classification, regression, feature selection, data import and export. It is designed to integrate well with related software packages, such as scikit-learn, shogun, and MDP.

[ascl:1703.008]
exorings: Exoring Transit Properties

Exorings is suitable for surveying entire catalogs of transiting planet candidates for exoring candidates, providing a subset of objects worthy of more detailed light curve analysis. Moreover, it is highly suited for uncovering evidence of a population of ringed planets by comparing the radius anomaly and PR-effects in ensemble studies.

[ascl:1703.007]
sidm-nbody: Monte Carlo N-body Simulation for Self-Interacting Dark Matter

Self-Interacting Dark Matter (SIDM) is a hypothetical model for cold dark matter in the Universe. A strong interaction between dark matter particles introduce a different physics inside dark-matter haloes, making the density profile cored, reduce the number of subhaloes, and trigger gravothermal collapse. sidm-nbody is an N-body simulation code with Direct Simulation Monte Carlo scattering for self interaction, and some codes to analyse gravothermal collapse of isolated haloes. The N-body simulation is based on GADGET 1.1.

[ascl:1703.006]
SNRPy: Supernova remnant evolution modeling

SNRPy (Super Nova Remnant Python) models supernova remnant (SNR) evolution and is useful for understanding SNR evolution and to model observations of SNR for obtaining good estimates of SNR properties. It includes all phases for the standard path of evolution for spherically symmetric SNRs and includes alternate evolutionary models, including evolution in a cloudy ISM, the fractional energy loss model, and evolution in a hot low-density ISM. The graphical interface takes in various parameters and produces outputs such as shock radius and velocity vs. time, SNR surface brightness profile and spectrum.

[ascl:1703.005]
starsense_algorithms: Performance evaluation of various star sensors

Sarpotdar, Mayuresh; Mathew, Joice; Sreejith, A. G.; Nirmal, K.; Ambily, S.; Prakash, Ajin; Safonova, Margarita; Murthy, Jayant

The Matlab starsense_algorithms package evaluates the performance of various star sensors through the implementation of centroiding, geometric voting and QUEST algorithms. The physical parameters of a star sensor are parametrized and by changing these parameters, performance estimators such as sky coverage, memory requirement, and timing requirements can be estimated for the selected star sensor.

[ascl:1703.004]
PHOTOMETRYPIPELINE: Automated photometry pipeline

PHOTOMETRYPIPELINE (PP) provides calibrated photometry from imaging data obtained with small to medium-sized observatories. PP uses Source Extractor (ascl:1010.064) and SCAMP (ascl:1010.063) to register the image data and perform aperture photometry. Calibration is obtained through matching of field stars with reliable photometric catalogs. PP has been specifically designed for the measurement of asteroid photometry, but can also be used to obtain photometry of fixed sources.

[ascl:1703.003]
Corrfunc: Blazing fast correlation functions on the CPU

Corrfunc is a suite of high-performance clustering routines. The code can compute a variety of spatial correlation functions on Cartesian geometry as well Landy-Szalay calculations for spatial and angular correlation functions on a spherical geometry and is useful for, for example, exploring the galaxy-halo connection. The code is written in C and can be used on the command-line, through the supplied python extensions, or the C API.

[ascl:1703.002]
COCOA: Simulating Observations of Star Cluster Simulations

COCOA (Cluster simulatiOn Comparison with ObservAtions) creates idealized mock photometric observations using results from numerical simulations of star cluster evolution. COCOA is able to present the output of realistic numerical simulations of star clusters carried out using Monte Carlo or N-body codes in a way that is useful for direct comparison with photometric observations. The code can simulate optical observations from simulation snapshots in which positions and magnitudes of objects are known. The parameters for simulating the observations can be adjusted to mimic telescopes of various sizes. COCOA also has a photometry pipeline that can use standalone versions of DAOPHOT (ascl:1104.011) and ALLSTAR to produce photometric catalogs for all observed stars.

[ascl:1703.001]
Larch: X-ray Analysis for Synchrotron Applications using Python

Larch is an open-source library and toolkit written in Python for processing and analyzing X-ray spectroscopic data. The primary emphasis is on X-ray spectroscopic and scattering data collected at modern synchrotron sources. Larch provides a wide selection of general-purpose processing, analysis, and visualization tools for processing X-ray data; its related target application areas include X-ray absorption fine structure (XAFS), micro-X-ray fluorescence (XRF) maps, quantitative X-ray fluorescence, X-ray absorption near edge spectroscopy (XANES), and X-ray standing waves and surface scattering. Larch provides a complete set of XAFS Analysis tools and has support for visualizing and analyzing XRF maps and spectra, and additional tools for X-ray spectral analysis, data handling, and general-purpose data modeling.

[ascl:1702.012]
GRIM: General Relativistic Implicit Magnetohydrodynamics

GRIM (General Relativistic Implicit Magnetohydrodynamics) evolves a covariant extended magnetohydrodynamics model derived by treating non-ideal effects as a perturbation of ideal magnetohydrodynamics. Non-ideal effects are modeled through heat conduction along magnetic field lines and a difference between the pressure parallel and perpendicular to the field lines. The model relies on an effective collisionality in the disc from wave-particle scattering and velocity-space (mirror and firehose) instabilities. GRIM, which runs on CPUs as well as on GPUs, combines time evolution and primitive variable inversion needed for conservative schemes into a single step using only the residuals of the governing equations as inputs. This enables the code to be physics agnostic as well as flexible regarding time-stepping schemes.

[ascl:1702.011]
Chempy: A flexible chemical evolution model for abundance fitting

Chempy models Galactic chemical evolution (GCE); it is a parametrized open one-zone model within a Bayesian framework. A Chempy model is specified by a set of 5-10 parameters that describe the effective galaxy evolution along with the stellar and star-formation physics: e.g. the star-formation history (SFH), the feedback efficiency, the stellar initial mass function (IMF) and the incidence of supernova of type Ia (SN Ia). Chempy can sample the posterior probability distribution in the full model parameter space and test data-model matches for different nucleosynthetic yield sets, performing essentially as a chemical evolution fitting tool. Chempy can be used to confront predictions from stellar nucleosynthesis with complex abundance data sets and to refine the physical processes governing the chemical evolution of stellar systems.

ChempyMulti (ascl:1909.006) is available as an update to the ChempyScoring package.

[ascl:1702.010]
streamgap-pepper: Effects of peppering streams with many small impacts

streamgap-pepper computes the effect of subhalo fly-bys on cold tidal streams based on the action-angle representation of streams. A line-of-parallel-angle approach is used to calculate the perturbed distribution function of a given stream segment by undoing the effect of all impacts. This approach allows one to compute the perturbed stream density and track in any coordinate system in minutes for realizations of the subhalo distribution down to 10^5 Msun, accounting for the stream's internal dispersion and overlapping impacts. This code uses galpy (ascl:1411.008) and the streampepperdf.py galpy extension, which implements the fast calculation of the perturbed stream structure.

[ascl:1702.009]
stream-stream: Stellar and dark-matter streams interactions

Stream-stream analyzes the interaction between a stellar stream and a disrupting dark-matter halo. It requires galpy (ascl:1411.008), NEMO (ascl:1010.051), and the usual common scientific Python packages.

[ascl:1702.008]
HOURS: Simulation and analysis software for the KM3NeT

The Hellenic Open University Reconstruction & Simulation (HOURS) software package contains a realistic simulation package of the detector response of very large (km3-scale) underwater neutrino telescopes, including an accurate description of all the relevant physical processes, the production of signal and background as well as several analysis strategies for triggering and pattern recognition, event reconstruction, tracking and energy estimation. HOURS also provides tools for simulating calibration techniques and other studies for estimating the detector sensitivity to several neutrino sources.

[ascl:1702.007]
KEPLER: General purpose 1D multizone hydrodynamics code

KEPLER is a general purpose stellar evolution/explosion code that incorporates implicit hydrodynamics and a detailed treatment of nuclear burning processes. It has been used to study the complete evolution of massive and supermassive stars, all major classes of supernovae, hydrostatic and explosive nucleosynthesis, and x- and gamma-ray bursts on neutron stars and white dwarfs.

[ascl:1702.006]
GalaxyGAN: Generative Adversarial Networks for recovery of galaxy features

GalaxyGAN uses Generative Adversarial Networks to reliably recover features in images of galaxies. The package uses machine learning to train on higher quality data and learns to recover detailed features such as galaxy morphology by effectively building priors. This method opens up the possibility of recovering more information from existing and future imaging data.

[ascl:1702.005]
JetCurry: Modeling 3D geometry of AGN jets from 2D images

Written in Python, JetCurry models the 3D geometry of jets from 2-D images. JetCurry requires NumPy and SciPy and incorporates emcee (ascl:1303.002) and AstroPy (ascl:1304.002), and optionally uses VPython. From a defined initial part of the jet that serves as a reference point, JetCurry finds the position of highest flux within a bin of data in the image matrix and fits along the *x* axis for the general location of the bends in the jet. A spline fitting is used to smooth out the resulted jet stream.

[ascl:1702.004]
Validation: Codes to compare simulation data to various observations

Validation provides codes to compare several observations to simulated data with stellar mass and star formation rate, simulated data stellar mass function with observed stellar mass function from PRIMUS or SDSS-GALEX in several redshift bins from 0.01-1.0, and simulated data B band luminosity function with observed stellar mass function, and to create plots for various attributes, including stellar mass functions, and stellar mass to halo mass. These codes can model predictions (in some cases alongside observational data) to test other mock catalogs.

[ascl:1702.003]
juwvid: Julia code for time-frequency analysis

Juwvid performs time-frequency analysis. Written in Julia, it uses a modified version of the Wigner distribution, the pseudo Wigner distribution, and the short-time Fourier transform from MATLAB GPL programs, tftb-0.2. The modification includes the zero-padding FFT, the non-uniform FFT, the adaptive algorithm by Stankovic, Dakovic, Thayaparan 2013, the S-method, the L-Wigner distribution, and the polynomial Wigner-Ville distribution.

[ascl:1702.002]
corner.py: Corner plots

*corner.py* uses matplotlib to visualize multidimensional samples using a scatterplot matrix. In these visualizations, each one- and two-dimensional projection of the sample is plotted to reveal covariances. *corner.py* was originally conceived to display the results of Markov Chain Monte Carlo simulations and the defaults are chosen with this application in mind but it can be used for displaying many qualitatively different samples. An earlier version of *corner.py* was known as triangle.py.

[ascl:1702.001]
ORBE: Orbital integrator for educational purposes

ORBE performs numerical integration of an arbitrary planetary system composed by a central star and up to 100 planets and minor bodies. ORBE calculates the orbital evolution of a system of bodies by means of the computation of the time evolution of their orbital elements. It is easy to use and is suitable for educational use by undergraduate students in the classroom as a first approach to orbital integrators.

[ascl:1701.012]
SONG: Second Order Non-Gaussianity

SONG computes the non-linear evolution of the Universe in order to predict cosmological observables such as the bispectrum of the Cosmic Microwave Background (CMB). More precisely, it is a second-order Boltzmann code, as it solves the Einstein and Boltzmann equations up to second order in the cosmological perturbations.

[ascl:1701.011]
GWFrames: Manipulate gravitational waveforms

GWFrames eliminates all rotational behavior, thus simplifying the waveform as much as possible and allowing direct generalizations of methods for analyzing nonprecessing systems. In the process, the angular velocity of a waveform is introduced, which also has important uses, such as supplying a partial solution to an important inverse problem.

[ascl:1701.010]
kcorrect: Calculate K-corrections between observed and desired bandpasses

kcorrect fits very restricted spectral energy distribution models to galaxy photometry or spectra in the restframe UV, optical and near-infrared. The main purpose of the fits are for calculating K-corrections. The templates used for the fits may also be interpreted physically, since they are based on the Bruzual-Charlot stellar evolution synthesis codes. Thus, for each fit galaxy kcorrect can provide an estimate of the stellar mass-to-light ratio.

[ascl:1701.009]
GrayStarServer: Stellar atmospheric modeling and spectrum synthesis

GrayStarServer is a stellar atmospheric modeling and spectrum synthesis code of pedagogical accuracy that is accessible in any web browser on commonplace computational devices and that runs on a timescale of a few seconds.

[ascl:1701.008]
GrayStar: Web-based pedagogical stellar modeling

GrayStar is a web-based pedagogical stellar model. It approximates stellar atmospheric and spectral line modeling in JavaScript with visualization in HTML. It is suitable for a wide range of education and public outreach levels depending on which optional plots and print-outs are turned on. All plots and renderings are pure basic HTML and the plotting module contains original HTML procedures for automatically scaling and graduating x- and y-axes.

[ascl:1701.007]
Forecaster: Mass and radii of planets predictor

Forecaster predicts the mass (or radius) from the radius (or mass) for objects covering nine orders-of-magnitude in mass. It is an unbiased forecasting model built upon a probabilistic mass-radius relation conditioned on a sample of 316 well-constrained objects. It accounts for observational errors, hyper-parameter uncertainties and the intrinsic dispersions observed in the calibration sample.

[ascl:1701.006]
MSWAVEF: Momentum-Space Wavefunctions

MSWAVEF calculates hydrogenic and non-hydrogenic momentum-space electronic wavefunctions. Such wavefunctions are often required to calculate various collision processes, such as excitation and line broadening cross sections. The hydrogenic functions are calculated using the standard analytical expressions. The non-hydrogenic functions are calculated within quantum defect theory according to the method of Hoang Binh and van Regemorter (1997). Required Hankel transforms have been determined analytically for angular momentum quantum numbers ranging from zero to 13 using Mathematica. Calculations for higher angular momentum quantum numbers are possible, but slow (since calculated numerically). The code is written in IDL.

[ascl:1701.005]
KAULAKYS: Inelastic collisions between hydrogen atoms and Rydberg atoms

KAULAKYS calculates cross sections and rate coefficients for inelastic collisions between Rydberg atoms and hydrogen atoms according to the free electron model of Kaulakys (1986, 1991). It is written in IDL and requires the code MSWAVEF (ascl:1701.006) to calculate momentum-space wavefunctions. KAULAKYS can be easily adapted to collisions with perturbers other than hydrogen atoms by providing the appropriate scattering amplitudes.

[ascl:1701.004]
CosmoSlik: Cosmology sampler of likelihoods

CosmoSlik quickly puts together, runs, and analyzes an MCMC chain for analysis of cosmological data. It is highly modular and comes with plugins for CAMB (ascl:1102.026), CLASS (ascl:1106.020), the Planck likelihood, the South Pole Telescope likelihood, other cosmological likelihoods, emcee (ascl:1303.002), and more. It offers ease-of-use, flexibility, and modularity.

[ascl:1701.003]
Spectra: Time series power spectrum calculator

Spectra calculates the power spectrum of a time series equally spaced or not based on the Spectral Correlation Coefficient (Ferraz-Mello 1981, Astron. Journal 86 (4), 619). It is very efficient for detection of low frequencies.

[ascl:1701.002]
Vizic: Jupyter-based interactive visualization tool for astronomical catalogs

Vizic is a Python visualization library that builds the connection between images and catalogs through an interactive map of the sky region. The software visualizes catalog data over a custom background canvas using the shape, size and orientation of each object in the catalog and displays interactive and customizable objects in the map. Property values such as redshift and magnitude can be used to filter or apply colormaps, and objects can be selected for further analysis through standard Python functions from inside a Jupyter notebook.

Vizic allows custom overlays to be appended dynamically on top of the sky map; included are Voronoi, Delaunay, Minimum Spanning Tree and HEALPix layers, which are helpful for visualizing large-scale structure. Overlays can be generated, added or removed dynamically with one line of code. Catalog data is kept in a non-relational database. The Jupyter Notebook allows the user to create scripts to analyze and plot the data selected/displayed in the interactive map, making Vizic a powerful and flexible interactive analysis tool. Vizic be used for data inspection, clustering analysis, galaxy alignment studies, outlier identification or simply large-scale visualizations.

[ascl:1701.001]
The Joker: A custom Monte Carlo sampler for binary-star and exoplanet radial velocity data

Given sparse or low-quality radial-velocity measurements of a star, there are often many qualitatively different stellar or exoplanet companion orbit models that are consistent with the data. The consequent multimodality of the likelihood function leads to extremely challenging search, optimization, and MCMC posterior sampling over the orbital parameters. The Joker is a custom-built Monte Carlo sampler that can produce a posterior sampling for orbital parameters given sparse or noisy radial-velocity measurements, even when the likelihood function is poorly behaved. The method produces correct samplings in orbital parameters for data that include as few as three epochs. The Joker can therefore be used to produce proper samplings of multimodal pdfs, which are still highly informative and can be used in hierarchical (population) modeling.

[ascl:1612.022]
REPS: REscaled Power Spectra for initial conditions with massive neutrinos

Zennaro, Matteo; Bel, Julien; Villaescusa-Navarro, Francisco; Carbone, Carmelita; Sefusatti, Emiliano; Guzzo, Luigi

REPS (REscaled Power Spectra) provides accurate, one-percent level, numerical simulations of the initial conditions for massive neutrino cosmologies, rescaling the late-time linear power spectra to the simulation initial redshift.

[ascl:1612.021]
BaTMAn: Bayesian Technique for Multi-image Analysis

Casado, J.; Ascasibar, Y.; García-Benito, R.; Guidi, G.; Choudhury, O. S.; Bellocchi, E.; Sánchez, S. F.; Díaz, A. I.

Bayesian Technique for Multi-image Analysis (BaTMAn) characterizes any astronomical dataset containing spatial information and performs a tessellation based on the measurements and errors provided as input. The algorithm iteratively merges spatial elements as long as they are statistically consistent with carrying the same information (i.e. identical signal within the errors). The output segmentations successfully adapt to the underlying spatial structure, regardless of its morphology and/or the statistical properties of the noise. BaTMAn identifies (and keeps) all the statistically-significant information contained in the input multi-image (e.g. an IFS datacube). The main aim of the algorithm is to characterize spatially-resolved data prior to their analysis.

[ascl:1612.020]
Grackle: Chemistry and radiative cooling library for astrophysical simulations

Smith, Britton D.; Bryan, Greg L.; Glover, Simon C. O.; Goldbaum, Nathan J.; Turk, Matthew J.; Regan, John; Wise, John H.; Schive, Hsi-Yu; Abel, Tom; Emerick, Andrew; O'Shea, Brian W.; Anninos, Peter; Hummels, Cameron B.; Khochfar, Sadegh

The chemistry and radiative cooling library Grackle provides options for primordial chemistry and cooling, photo-heating and photo-ionization from UV backgrounds, and support for user-provided arrays of volumetric and specific heating rates for astrophysical simulations and models. The library provides functions to update chemistry species; solve radiative cooling and update internal energy; and calculate cooling time, temperature, pressure, and ratio of specific heats (gamma), and has interfaces for C, C++, Fortran, and Python codes.

[ascl:1612.019]
Trident: Synthetic spectrum generator

Trident creates synthetic absorption-line spectra from astrophysical hydrodynamics simulations. It uses the yt package (ascl:1011.022) to read in simulation datasets and extends it to provide realistic synthetic observations appropriate for studies of the interstellar, circumgalactic, and intergalactic media.

[ascl:1612.018]
pylightcurve: Exoplanet lightcurve model

pylightcurve is a model for light-curves of transiting planets. It uses the four coefficients law for the stellar limb darkening and returns the relative flux, *F*(*t*), as a function of the limb darkening coefficients, *a _{n}*, the

[ascl:1612.017]
GAMER: GPU-accelerated Adaptive MEsh Refinement code

GAMER (GPU-accelerated Adaptive MEsh Refinement) serves as a general-purpose adaptive mesh refinement + GPU framework and solves hydrodynamics with self-gravity. The code supports adaptive mesh refinement (AMR), hydrodynamics with self-gravity, and a variety of GPU-accelerated hydrodynamic and Poisson solvers. It also supports hybrid OpenMP/MPI/GPU parallelization, concurrent CPU/GPU execution for performance optimization, and Hilbert space-filling curve for load balance. Although the code is designed for simulating galaxy formation, it can be easily modified to solve a variety of applications with different governing equations. All optimization strategies implemented in the code can be inherited straightforwardly.

[ascl:1612.016]
CELib: Software library for simulations of chemical evolution

CELib (Chemical Evolution Library) simulates chemical evolution of galaxy formation under the simple stellar population (SSP) approximation and can be used by any simulation code that uses the SSP approximation, such as particle-base and mesh codes as well as semi-analytical models. Initial mass functions, stellar lifetimes, yields from type II and Ia supernovae, asymptotic giant branch stars, and neutron star mergers components are included and a variety of models are available for use. The library allows comparisons of the impact of individual models on the chemical evolution of galaxies by changing control flags and parameters of the library.

[ascl:1612.015]
Superplot: Graphical interface for plotting and analyzing data

Superplot calculates and plots statistical quantities relevant to parameter inference from a "chain" of samples drawn from a parameter space produced by codes such as MultiNest (ascl:1109.006), BAYES-X (ascl:1505.027), and PolyChord (ascl:1502.011). It offers a graphical interface for browsing a chain of many variables quickly and can produce numerous kinds of publication quality plots, including one- and two-dimensional profile likelihood, three-dimensional scatter plots, and confidence intervals and credible regions. Superplot can also save plots in PDF format, create a summary text file, and export a plot as a pickled object for importing and manipulating in a Python interpreter.

[ascl:1612.014]
AUTOSTRUCTURE: General program for calculation of atomic and ionic properties

AUTOSTRUCTURE calculates atomic and ionic energy levels, radiative rates, autoionization rates, photoionization cross sections, plane-wave Born and distorted-wave excitation cross sections in LS- and intermediate-coupling using non- or (kappa-averaged) relativistic wavefunctions. These can then be further processed to form Auger yields, fluorescence yields, partial and total dielectronic and radiative recombination cross sections and rate coefficients, photoabsorption cross sections, and monochromatic opacities, among other properties.

[ascl:1612.013]
InversionKit: Linear inversions from frequency data

InversionKit is an interactive Java program that performs rotational and structural linear inversions from frequency data.

[ascl:1612.012]
Meso-NH: Non-hydrostatic mesoscale atmospheric model

Meso-NH is the non-hydrostatic mesoscale atmospheric model of the French research community jointly developed by the Laboratoire d'Aérologie (UMR 5560 UPS/CNRS) and by CNRM (UMR 3589 CNRS/Météo-France). Meso-NH incorporates a non-hydrostatic system of equations for dealing with scales ranging from large (synoptic) to small (large eddy) scales while calculating budgets and has a complete set of physical parameterizations for the representation of clouds and precipitation. It is coupled to the surface model SURFEX for representation of surface atmosphere interactions by considering different surface types (vegetation, city, ocean, lake) and allows a multi-scale approach through a grid-nesting technique. Meso-NH is versatile, vectorized, parallelized, and operates in 1D, 2D or 3D; it is coupled with a chemistry module (including gas-phase, aerosol, and aqua-phase components) and a lightning module, and has observation operators that compare model output directly with satellite observations, radar, lidar and GPS.

[ascl:1612.011]
QSFit: Quasar Spectral FITting

QSFit performs automatic analysis of Active Galactic Nuclei (AGN) optical spectra. It provides estimates of: AGN continuum luminosities and slopes at several restframe wavelengths; luminosities, widths and velocity offsets of 20 emission lines; luminosities of iron blended lines at optical and UV wavelengths; host galaxy luminosities. The whole fitting process is customizable for specific needs, and can be extended to analyze spectra from other data sources. The ultimate purpose of QSFit is to allow astronomers to run standardized recipes to analyze the AGN data, in a simple, replicable and shareable way.

[ascl:1612.010]
Earthshine simulator: Idealized images of the Moon

Terrestrial albedo can be determined from observations of the relative intensity of earthshine. Images of the Moon at different lunar phases can be analyzed to derive the semi-hemispheric mean albedo of the Earth, and an important tool for doing this is simulations of the appearance of the Moon for any time. This software produces idealized images of the Moon for arbitrary times. It takes into account the libration of the Moon and the distances between Sun, Moon and the Earth, as well as the relevant geometry. The images of the Moon are produced as FITS files. User input includes setting the Julian Day of the simulation. Defaults for image size and field of view are set to produce approximately 1x1 degree images with the Moon in the middle from an observatory on Earth, currently set to Mauna Loa.

[ascl:1612.009]
CRETE: Comet RadiativE Transfer and Excitation

CRETE (Comet RadiativE Transfer and Excitation) is a one-dimensional water excitation and radiation transfer code for sub-millimeter wavelengths based on the RATRAN code (ascl:0008.002). The code considers rotational transitions of water molecules given a Haser spherically symmetric distribution for the cometary coma and produces FITS image cubes that can be analyzed with tools like MIRIAD (ascl:1106.007). In addition to collisional processes to excite water molecules, the effect of infrared radiation from the Sun is approximated by effective pumping rates for the rotational levels in the ground vibrational state.

[ascl:1612.008]
PyORBIT: Exoplanet orbital parameters and stellar activity

PyORBIT handles several kinds of datasets, such as radial velocity (RV), activity indexes, and photometry, to simultaneously characterize the orbital parameters of exoplanets and the noise induced by the activity of the host star. RV computation is performed using either non-interacting Kepler orbits or n-body integration. Stellar activity can be modeled either with sinusoids at the rotational period and its harmonics or Gaussian process. In addition, the code can model offsets and systematics in measurements from several instruments. The PyORBIT code is modular; new methods for stellar activity modeling or parameter estimation can easily be incorporated into the code.

[ascl:1612.007]
dacapo_calibration: Photometric calibration code

dacapo_calibration implements the DaCapo algorithm used in the Planck/LFI 2015 data release for photometric calibration. The code takes as input a set of TODs and calibrates them using the CMB dipole signal. DaCapo is a variant of the well-known family of destriping algorithms for map-making.

[ascl:1612.006]
flexCE: Flexible one-zone chemical evolution code

flexCE (flexible Chemical Evolution) computes the evolution of a one-zone chemical evolution model with inflow and outflow in which gas is instantaneously and completely mixed. It can be used to demonstrate the sensitivity of chemical evolution models to parameter variations, show the effect of CCSN yields on chemical evolution models, and reproduce the 2D distribution in [O/Fe]{[Fe/H] by mixing models with a range of inflow and outflow histories. It can also post-process cosmological simulations to predict element distributions.

[ascl:1612.005]
PyProfit: Wrapper for libprofit

pyprofit is a python wrapper for libprofit (ascl:1612.003).

[ascl:1612.004]
ProFit: Bayesian galaxy fitting tool

ProFit is a Bayesian galaxy fitting tool that uses the fast C++ image generation library libprofit (ascl:1612.003) and a flexible R interface to a large number of likelihood samplers. It offers a fully featured Bayesian interface to galaxy model fitting (also called profiling), using mostly the same standard inputs as other popular codes (e.g. GALFIT ascl:1104.010), but it is also able to use complex priors and a number of likelihoods.

[ascl:1612.003]
libprofit: Image creation from luminosity profiles

libprofit is a C++ library for image creation based on different luminosity profiles. It offers fast and accurate two-dimensional integration for a useful number of profiles, including Sersic, Core-Sersic, broken-exponential, Ferrer, Moffat, empirical King, point-source and sky, with a simple mechanism for adding new profiles. libprofit provides a utility to read the model and profile parameters from the command-line and generate the corresponding image. It can output the resulting image as text values, a binary stream, or as a simple FITS file. It also provides a shared library exposing an API that can be used by any third-party application. R and Python interfaces are available: ProFit (ascl:1612.004) and PyProfit (ascl:1612.005).

[ascl:1612.002]
LSDCat: Line Source Detection and Cataloguing Tool

LSDCat is a conceptually simple but robust and efficient detection package for emission lines in wide-field integral-field spectroscopic datacubes. The detection utilizes a 3D matched-filtering approach for compact single emission line objects. Furthermore, the software measures fluxes and extents of detected lines. LSDCat is implemented in Python, with a focus on fast processing of large data-volumes.

[ascl:1612.001]
Python-CPL: Python interface for the ESO Common Pipeline Library

Python-CPL is a framework to configure and execute pipeline recipes written with the Common Pipeline Library (CPL) (ascl:1402.010) with Python2 or Python3. The input, calibration and output data can be specified as FITS files or as astropy.io.fits objects in memory. The package is used to implement the MUSE pipeline in the AstroWISE data management system.

[ascl:1611.021]
SlicerAstro: Astronomy (HI) extension for 3D Slicer

SlicerAstro extends 3D Slicer, a multi-platform package for visualization and medical image processing, to provide a 3-D interactive viewer with 3-D human-machine interaction features, based on traditional 2-D input/output hardware, and analysis capabilities.

[submitted]
Fast Template Periodogram

The Fast Template Periodogram extends the Generalised Lomb Scargle periodogram (Zechmeister and Kurster 2009) for arbitrary (periodic) signal shapes. A template is first approximated by a truncated Fourier series of length H. The Nonequispaced Fast Fourier Transform NFFT is used to efficiently compute frequency-dependent sums. Template fitting can now be done in NlogN time, improving existing algorithms by an order of magnitude for even small datasets. The FTP can be used in conjunction with gradient descent to accelerate a non-linear model fit, or be used in place of the multi-harmonic periodogram for non-sinusoidal signals with a priori known shapes.

[ascl:1611.020]
CMCIRSED: Far-infrared spectral energy distribution fitting for galaxies near and far

The Caitlin M. Casey Infra Red Spectral Energy Distribution model (CMCIRSED) provides a simple SED fitting technique suitable for a wide range of IR data, from sources which have only three IR photometric points to sources with >10 photometric points. These SED fits produce accurate estimates to a source's integrated IR luminosity, dust temperature and dust mass. CMCIRSED is based on a single dust temperature greybody fit linked to a MIR power law, fitted simultaneously to data across ∼5–2000 μm.

[ascl:1611.019]
phase_space_cosmo_fisher: Fisher matrix 2D contours

phase_space_cosmo_fisher produces Fisher matrix 2D contours from which the constraints on cosmological parameters can be derived. Given a specified redshift array and cosmological case, 2D marginalized contours of cosmological parameters are generated; the code can also plot the derivatives used in the Fisher matrix. In addition, this package can generate 3D plots of qH^2 and other cosmological quantities as a function of redshift and cosmology.

[ascl:1611.018]
Icarus: Stellar binary light curve synthesis tool

Icarus is a stellar binary light curve synthesis tool that generates a star, given some basic binary parameters, by solving the gravitational potential equation, creating a discretized stellar grid, and populating the stellar grid with physical parameters, including temperature and surface gravity. Icarus also evaluates the outcoming flux from the star given an observer's point of view (*i.e.*, orbital phase and orbital orientation).

[ascl:1611.017]
SNCosmo: Python library for supernova cosmology

Barbary, Kyle; Barclay, Tom; Biswas, Rahul; Craig, Matt; Feindt, Ulrich; Friesen, Brian; Goldstein, Danny; Jha, Saurabh; Rodney, Steve; Sofiatti, Caroline; Thomas, Rollin C.; Wood-Vasey, Michael

SNCosmo synthesizes supernova spectra and photometry from SN models, and has functions for fitting and sampling SN model parameters given photometric light curve data. It offers fast implementations of several commonly used extinction laws and can be used to construct SN models that include dust. The SNCosmo library includes supernova models such as SALT2, MLCS2k2, Hsiao, Nugent, PSNID, SNANA and Whalen models, as well as a variety of built-in bandpasses and magnitude systems, and provides convenience functions for reading and writing peculiar data formats used in other packages. The library is extensible, allowing new models, bandpasses, and magnitude systems to be defined using an object-oriented interface.

[ascl:1611.016]
Carpet: Adaptive Mesh Refinement for the Cactus Framework

Carpet is an adaptive mesh refinement and multi-patch driver for the Cactus Framework (ascl:1102.013). Cactus is a software framework for solving time-dependent partial differential equations on block-structured grids, and Carpet acts as driver layer providing adaptive mesh refinement, multi-patch capability, as well as parallelization and efficient I/O.

[ascl:1611.015]
Pippi: Parse and plot MCMC chains

Pippi (parse it, plot it) operates on MCMC chains and related lists of samples from a function or distribution, and can merge, parse, and plot sample ensembles ('chains') either in terms of the likelihood/fitness function directly, or as implied posterior probability densities. Pippi is compatible with ASCII text and hdf5 chains, operates out of core, and can post-process chains on the fly.

[ascl:1611.014]
AIMS: Asteroseismic Inference on a Massive Scale

AIMS (Asteroseismic Inference on a Massive Scale) estimates stellar parameters and credible intervals/error bars in a Bayesian manner from a set of seismic frequency data and so-called classic constraints. To achieve reliable parameter estimates and computational efficiency it searches through a grid of pre-computed models using an MCMC algorithm; interpolation within the grid of models is performed by first tessellating the grid using a Delaunay triangulation and then doing a linear barycentric interpolation on matching simplexes. Inputs for the modeling consists of individual frequencies from peak-bagging, which can be complemented with classic spectroscopic constraints.

[ascl:1611.013]
pyGMMis: Mixtures-of-Gaussians density estimation method

pyGMMis is a mixtures-of-Gaussians density estimation method that accounts for arbitrary incompleteness in the process that creates the samples as long as the incompleteness is known over the entire feature space and does not depend on the sample density (missing at random). pyGMMis uses the Expectation-Maximization procedure and generates its best guess of the unobserved samples on the fly. It can also incorporate an uniform "background" distribution as well as independent multivariate normal measurement errors for each of the observed samples, and then recovers an estimate of the error-free distribution from which both observed and unobserved samples are drawn. The code automatically segments the data into localized neighborhoods, and is capable of performing density estimation with millions of samples and thousands of model components on machines with sufficient memory.

[ascl:1611.012]
EarthShadow: Calculator for dark matter particle velocity distribution after Earth-scattering

EarthShadow calculates the impact of Earth-scattering on the distribution of Dark Matter (DM) particles. The code calculates the speed and velocity distributions of DM at various positions on the Earth and also helps with the calculation of the average scattering probabilities. Tabulated data for DM-nuclear scattering cross sections and various numerical results, plots and animations are also included in the code package.

[ascl:1611.011]
OXAF: Ionizing spectra of Seyfert galaxies for photoionization modeling

Thomas, Adam D.; Groves, Brent A.; Sutherland, Ralph S.; Dopita, Michael A.; Jin, Chichuan; Kewley, Lisa J.

OXAF provides a simplified model of Seyfert Active Galactic Nucleus (AGN) continuum emission designed for photoionization modeling. It removes degeneracies in the effects of AGN parameters on model spectral shapes and reproduces the diversity of spectral shapes that arise in physically-based models. OXAF accepts three parameters which directly describe the shape of the output ionizing spectrum: the energy of the peak of the accretion disk emission *E _{peak}*, the photon power-law index of the non-thermal X-ray emission Γ, and the proportion of the total flux which is emitted in the non-thermal component

[ascl:1611.010]
Kapteyn Package: Tools for developing astronomical applications

The Kapteyn Package provides tools for the development of astronomical applications with Python. It handles spatial and spectral coordinates, WCS projections and transformations between different sky systems; spectral translations (e.g., between frequencies and velocities) and mixed coordinates are also supported. Kapteyn offers versatile tools for writing small and dedicated applications for the inspection of FITS headers, the extraction and display of (FITS) data, interactive inspection of this data (color editing) and for the creation of plots with world coordinate information. It includes utilities for use with matplotlib such as obtaining coordinate information from plots, interactively modifiable colormaps and timer events (module mplutil); tools for parsing and interpreting coordinate information entered by the user (module positions); a function to search for gaussian components in a profile (module profiles); and a class for non-linear least squares fitting (module kmpfit).

[ascl:1611.009]
RHOCUBE: 3D density distributions modeling code

RHOCUBE models 3D density distributions on a discrete Cartesian grid and their integrated 2D maps. It can be used for a range of applications, including modeling the electron number density in LBV shells and computing the emission measure. The RHOCUBE Python package provides several 3D density distributions, including a powerlaw shell, truncated Gaussian shell, constant-density torus, dual cones, and spiralling helical tubes, and can accept additional distributions. RHOCUBE provides convenient methods for shifts and rotations in 3D, and if necessary, an arbitrary number of density distributions can be combined into the same model cube and the integration ∫ d*z* performed through the joint density field.

[ascl:1611.008]
Transit Clairvoyance: Predicting multiple-planet systems for TESS

Transit Clairvoyance uses Artificial Neural Networks (ANNs) to predict the most likely short period transiters to have additional transiters, which may double the discovery yield of the TESS (Transiting Exoplanet Survey Satellite). Clairvoyance is a simple 2-D interpolant that takes in the number of planets in a system with period less than 13.7 days, as well as the maximum radius amongst them (in Earth radii) and orbital period of the planet with maximum radius (in Earth days) in order to predict the probability of additional transiters in this system with period greater than 13.7 days.

[ascl:1611.007]
GRASP2K: Relativistic Atomic Structure Package

GRASP2K is a revised and greatly expanded version of GRASP (ascl:1609.008) and is adapted for 64-bit computer architecture. It includes new angular libraries, can transform from *jj*- to *LSJ*-coupling, and coefficients of fractional parentage have been extended to *j*=9/2, making calculations feasible for the lanthanides and actinides. GRASP2K identifies each atomic state by the total energy and a label for the configuration state function with the largest expansion coefficient in *LSJLSJ* intermediate coupling.

[ascl:1611.006]
GalPot: Galaxy potential code

GalPot finds the gravitational potential associated with axisymmetric density profiles. The package includes code that performs transformations between commonly used coordinate systems for both positions and velocities (the class OmniCoords), and that integrates orbits in the potentials. GalPot is a stand-alone version of Walter Dehnen's GalaxyPotential C++ code taken from the falcON code in the NEMO Stellar Dynamics Toolbox (ascl:1010.051).

[ascl:1611.005]
Exo-Transmit: Radiative transfer code for calculating exoplanet transmission spectra

Exo-Transmit calculates the transmission spectrum of an exoplanet atmosphere given specified input information about the planetary and stellar radii, the planet's surface gravity, the atmospheric temperature-pressure (T-P) profile, the location (in terms of pressure) of any cloud layers, the composition of the atmosphere, and opacity data for the atoms and molecules that make up the atmosphere. The code solves the equation of radiative transfer for absorption of starlight passing through the planet's atmosphere as it transits, accounting for the oblique path of light through the planetary atmosphere along an Earth-bound observer's line of sight. The fraction of light absorbed (or blocked) by the planet plus its atmosphere is calculated as a function of wavelength to produce the wavelength-dependent transmission spectrum. Functionality is provided to simulate the presence of atmospheric aerosols in two ways: an optically thick (gray) cloud deck can be generated at a user-specified height in the atmosphere, and the nominal Rayleigh scattering can be increased by a specified factor.

[ascl:1611.004]
PRECESSION: Python toolbox for dynamics of spinning black-hole binaries

PRECESSION is a comprehensive toolbox for exploring the dynamics of precessing black-hole binaries in the post-Newtonian regime. It allows study of the evolution of the black-hole spins along their precession cycles, performs gravitational-wave-driven binary inspirals using both orbit-averaged and precession-averaged integrations, and predicts the properties of the merger remnant through fitting formulas obtained from numerical-relativity simulations. PRECESSION can add the black-hole spin dynamics to larger-scale numerical studies such as gravitational-wave parameter estimation codes, population synthesis models to predict gravitational-wave event rates, galaxy merger trees and cosmological simulations of structure formation, and provides fast and reliable integration methods to propagate statistical samples of black-hole binaries from/to large separations where they form to/from small separations where they become detectable, thus linking gravitational-wave observations of spinning black-hole binaries to their astrophysical formation history. The code is also useful for computing initial parameters for numerical-relativity simulations targeting specific precessing systems.

[ascl:1611.003]
MPDAF: MUSE Python Data Analysis Framework

MPDAF, the MUSE Python Data Analysis Framework, provides tools to work with MUSE-specific data (for example, raw data and pixel tables), and with more general data such as spectra, images, and data cubes. Originally written to work with MUSE data, it can also be used for other data, such as that from the Hubble Space Telescope. MPDAF also provides MUSELET, a SExtractor-based tool to detect emission lines in a data cube, and a format to gather all the information on a source in one FITS file. MPDAF was developed and is maintained by CRAL (Centre de Recherche Astrophysique de Lyon).

[ascl:1611.002]
tf_unet: Generic convolutional neural network U-Net implementation in Tensorflow

tf_unet mitigates radio frequency interference (RFI) signals in radio data using a special type of Convolutional Neural Network, the U-Net, that enables the classification of clean signal and RFI signatures in 2D time-ordered data acquired from a radio telescope. The code is not tied to a specific segmentation and can be used, for example, to detect radio frequency interference (RFI) in radio astronomy or galaxies and stars in widefield imaging data. This U-Net implementation can outperform classical RFI mitigation algorithms.

[ascl:1611.001]
UltraNest: Pythonic Nested Sampling Development Framework and UltraNest

This three-component package provides a Pythonic implementation of the Nested Sampling integration algorithm for Bayesian model comparison and parameter estimation. It offers multiple implementations for constrained drawing functions and a test suite to evaluate the correctness, accuracy and efficiency of various implementations. The three components are:

- a modular framework for nested sampling algorithms (nested_sampling) and their development;
- a test framework to evaluate the performance and accuracy of algorithms (testsuite); and
- UltraNest, a fast C implementation of a mixed RadFriends/MCMC nested sampling algorithm.

[ascl:1610.016]
PyMC3: Python probabilistic programming framework

PyMC3 performs Bayesian statistical modeling and model fitting focused on advanced Markov chain Monte Carlo and variational fitting algorithms. It offers powerful sampling algorithms, such as the No U-Turn Sampler, allowing complex models with thousands of parameters with little specialized knowledge of fitting algorithms, intuitive model specification syntax, and optimization for finding the maximum a posteriori (MAP) point. PyMC3 uses Theano to compute gradients via automatic differentiation as well as compile probabilistic programs on-the-fly to C for increased speed.

[ascl:1610.015]
NuPyCEE: NuGrid Python Chemical Evolution Environment

The NuGrid Python Chemical Evolution Environment (NuPyCEE) simulates the chemical enrichment and stellar feedback of stellar populations. It contains three modules. The Stellar Yields for Galactic Modeling Applications module (SYGMA) models the enrichment and feedback of simple stellar populations which can be included in hydrodynamic simulations and semi-analytic models of galaxies. It is the basic building block of the One-zone Model for the Evolution of GAlaxies (OMEGA, ascl:1806.018) module which models the chemical evolution of galaxies such as the Milky Way and its dwarf satellites. The STELLAB (STELLar ABundances) module provides a library of observed stellar abundances useful for comparing predictions of SYGMA and OMEGA.

[ascl:1610.014]
Freddi: Fast Rise Exponential Decay accretion Disk model Implementation

Freddi (Fast Rise Exponential Decay: accretion Disk model Implementation) solves 1-D evolution equations of the Shakura-Sunyaev accretion disk. It simulates fast rise exponential decay (FRED) light curves of low mass X-ray binaries (LMXBs). The basic equation of the viscous evolution relates the surface density and viscous stresses and is of diffusion type; evolution of the accretion rate can be found on solving the equation. The distribution of viscous stresses defines the emission from the source. The standard model for the accretion disk is implied; the inner boundary of the disk is at the ISCO or can be explicitely set. The boundary conditions in the disk are the zero stress at the inner boundary and the zero accretion rate at the outer boundary. The conditions are suitable during the outbursts in X-ray binary transients with black holes. In a binary system, the accretion disk is radially confined. In Freddi, the outer radius of the disk can be set explicitely or calculated as the position of the tidal truncation radius.

[ascl:1610.013]
MC^{3}: Multi-core Markov-chain Monte Carlo code

Cubillos, Patricio; Harrington, Joseph; Lust, Nate; Foster, AJ; Stemm, Madison; Loredo, Tom; Stevenson, Kevin; Campo, Chris; Hardin, Matt; Hardy, Ryan

MC^{3} (Multi-core Markov-chain Monte Carlo) is a Bayesian statistics tool that can be executed from the shell prompt or interactively through the Python interpreter with single- or multiple-CPU parallel computing. It offers Markov-chain Monte Carlo (MCMC) posterior-distribution sampling for several algorithms, Levenberg-Marquardt least-squares optimization, and uniform non-informative, Jeffreys non-informative, or Gaussian-informative priors. MC^{3} can share the same value among multiple parameters and fix the value of parameters to constant values, and offers Gelman-Rubin convergence testing and correlated-noise estimation with time-averaging or wavelet-based likelihood estimation methods.

[ascl:1610.012]
Fourierdimredn: Fourier dimensionality reduction model for interferometric imaging

Fourierdimredn (Fourier dimensionality reduction) implements Fourier-based dimensionality reduction of interferometric data. Written in Matlab, it derives the theoretically optimal dimensionality reduction operator from a singular value decomposition perspective of the measurement operator. Fourierdimredn ensures a fast implementation of the full measurement operator and also preserves the i.i.d. Gaussian properties of the original measurement noise.

[ascl:1610.011]
BXA: Bayesian X-ray Analysis

BXA connects the nested sampling algorithm MultiNest (ascl:1109.006) to the X-ray spectral analysis environments Xspec/Sherpa for Bayesian parameter estimation and model comparison. It provides parameter estimation in arbitrary dimensions and plotting of spectral model vs. the data for best fit, posterior samples, or each component. BXA allows for model selection; it computes the evidence for the considered model, ready for use in computing Bayes factors and is not limited to nested models. It also visualizes deviations between model and data with Quantile-Quantile (QQ) plots, which do not require binning and are more comprehensive than residuals.

[ascl:1610.010]
BurnMan: Lower mantle mineral physics toolkit

BurnMan determines seismic velocities for the lower mantle. Written in Python, BurnMan calculates the isotropic thermoelastic moduli by solving the equations-of-state for a mixture of minerals defined by the user. The user may select from a list of minerals applicable to the lower mantle included or can define one. BurnMan provides choices in methodology, both for the EoS and for the multiphase averaging scheme and the results can be visually or quantitatively compared to observed seismic models.

[ascl:1610.009]
velbin: radial velocity corrected for binary orbital motions

Velbin convolves the radial velocity offsets due to binary orbital motions with a Gaussian to model an observed velocity distribution. This can be used to measure the mean velocity and velocity dispersion from an observed radial velocity distribution, corrected for binary orbital motions. Velbin fits single- or multi-epoch data with any arbitrary binary orbital parameter distribution (as long as it can be sampled properly), however it always assumes that the intrinsic velocity distribution (i.e. corrected for binary orbital motions) is a Gaussian. Velbin samples (and edits) a binary orbital parameter distribution, fits an observed radial velocity distribution, and creates a mock radial velocity distribution that can be used to provide the fitted radial velocities in the single_epoch or multi_epoch methods.

[ascl:1610.008]
cluster-in-a-box: Statistical model of sub-millimeter emission from embedded protostellar clusters

Cluster-in-a-box provides a statistical model of sub-millimeter emission from embedded protostellar clusters and consists of three modules grouped in two scripts. The first (cluster_distribution) generates the cluster based on the number of stars, input initial mass function, spatial distribution and age distribution. The second (cluster_emission) takes an input file of observations, determines the mass-intensity correlation and generates outflow emission for all low-mass Class 0 and I sources. The output is stored as a FITS image where the flux density is determined by the desired resolution, pixel scale and cluster distance.

[ascl:1610.007]
gatspy: General tools for Astronomical Time Series in Python

Gatspy contains efficient, well-documented implementations of several common routines for Astronomical time series analysis, including the Lomb-Scargle periodogram, the Supersmoother method, and others.

[ascl:1610.006]
C^{3}: Command-line Catalogue Crossmatch for modern astronomical surveys

The Command-line Catalogue Cross-matching (C^{3}) software efficiently performs the positional cross-match between massive catalogues from modern astronomical surveys, whose size have rapidly increased in the current data-driven science era. Based on a multi-core parallel processing paradigm, it is executed as a stand-alone command-line process or integrated within any generic data reduction/analysis pipeline. C^{3} provides its users with flexibility in portability, parameter configuration, catalogue formats, angular resolution, region shapes, coordinate units and cross-matching types.

[ascl:1610.005]
GSGS: In-Focus Phase Retrieval Using Non-Redundant Mask Data

GSGS does phase retrieval on images given an estimate of the pupil phase (from a non-redundant mask or other interferometric approach), the pupil geometry, and the in-focus image. The code uses a modified Gerchberg-Saxton algorithm that iterates between pupil plane and image plane to measure the pupil phase.

[ascl:1610.004]
MUSE-DRP: MUSE Data Reduction Pipeline

The MUSE pipeline turns the complex raw data of the MUSE integral field spectrograph into a ready-to-use datacube for scientific analysis.

[ascl:1610.003]
DSDEPROJ: Direct Spectral Deprojection

Deprojection of X-ray data by methods such as PROJCT, which are model dependent, can produce large and unphysical oscillating temperature profiles. Direct Spectral Deprojection (DSDEPROJ) solves some of the issues inherent to model-dependent deprojection routines. DSDEPROJ is a model-independent approach, assuming only spherical symmetry, which subtracts projected spectra from each successive annulus to produce a set of deprojected spectra.

[ascl:1610.002]
CERES: Collection of Extraction Routines for Echelle Spectra

The Collection of Extraction Routines for Echelle Spectra (CERES) constructs automated pipelines for the reduction, extraction, and analysis of echelle spectrograph data. This modular code includes tools for handling the different steps of the processing: CCD reductions, tracing of the echelle orders, optimal and simple extraction, computation of the wave-length solution, estimation of radial velocities, and rough and fast estimation of the atmospheric parameters. The standard output of pipelines constructed with CERES is a FITS cube with the optimally extracted, wavelength calibrated and instrumental drift-corrected spectrum for each of the science images. Additionally, CERES includes routines for the computation of precise radial velocities and bisector spans via the cross-correlation method, and an automated algorithm to obtain an estimate of the atmospheric parameters of the observed star.

[ascl:1610.001]
Piccard: Pulsar timing data analysis package

Piccard is a Bayesian-inference pipeline for Pulsar Timing Array (PTA) data and interacts with Tempo2 (ascl:1210.015) through libstempo. The code is used mainly for single-pulsar analysis and gravitational-wave detection purposes of full Pulsar Timing Array datasets. Modeling of the data can include correlated signals per frequency or modeled spectrum, with uniform, dipolar, quadrupolar, or anisotropic correlations; multiple error bars and EFACs per pulsar; and white and red noise. Timing models can be numerically included, either by using the design matrix (linear timing model), or by calling libstempo for the full non-linear timing model. Many types of samplers are included. For common-mode mitigation, the signals can be reconstructed mitigating arbitrary signals simultaneously.

[ascl:1609.025]
PYESSENCE: Generalized Coupled Quintessence Linear Perturbation Python Code

PYESSENCE evolves linearly perturbed coupled quintessence models with multiple (cold dark matter) CDM fluid species and multiple DE (dark energy) scalar fields, and can be used to generate quantities such as the growth factor of large scale structure for any coupled quintessence model with an arbitrary number of fields and fluids and arbitrary couplings.

[ascl:1609.024]
AdaptiveBin: Adaptive Binning

AdaptiveBin takes one or more images and adaptively bins them. If one image is supplied, then the pixels are binned by fractional error on the intensity. If two or more images are supplied, then the pixels are fractional binned by error on the combined color.

[ascl:1609.023]
contbin: Contour binning and accumulative smoothing

Contbin bins X-ray data using contours on an adaptively smoothed map. The generated bins closely follow the surface brightness, and are ideal where the surface brightness distribution is not smooth, or the spectral properties are expected to follow surface brightness. Color maps can be used instead of surface brightness maps.

[ascl:1609.022]
PyPHER: Python-based PSF Homogenization kERnels

Boucaud, Alexandre; Bocchio, Marco; Abergel, Alain; Orieux, François; Dole, Hervé; Amine Hadj-Youcef, Mohamed

PyPHER (Python-based PSF Homogenization kERnels) computes an homogenization kernel between two PSFs; the code is well-suited for PSF matching applications in both an astronomical or microscopy context. It can warp (rotation + resampling) the PSF images (if necessary), filter images in Fourier space using a regularized Wiener filter, and produce a homogenization kernel. PyPHER requires the pixel scale information to be present in the FITS files, which can if necessary be added by using the provided ADDPIXSCL method.

[ascl:1609.021]
TIDEV: Tidal Evolution package

TIDEV (Tidal Evolution package) calculates the evolution of rotation for tidally interacting bodies using Efroimsky-Makarov-Williams (EMW) formalism. The package integrates tidal evolution equations and computes the rotational and dynamical evolution of a planet under tidal and triaxial torques. TIDEV accounts for the perturbative effects due to the presence of the other planets in the system, especially the secular variations of the eccentricity. Bulk parameters include the mass and radius of the planet (and those of the other planets involved in the integration), the size and mass of the host star, the Maxwell time and Andrade's parameter. TIDEV also calculates the time scale that a planet takes to be tidally locked as well as the periods of rotation reached at the end of the spin-orbit evolution.

[ascl:1609.020]
Askaryan Module: Askaryan electric fields predictor

The Askaryan Module is a C++ class that predicts the electric fields that Askaryan-based detectors detect; it is computationally efficient and accurate, performing fully analytic calculations requiring no *a priori* MC analysis to compute the entire field, for any frequencies, times, or viewing angles chosen by the user.

[ascl:1609.019]
SuperBoL: Module for calculating the bolometric luminosities of supernovae

SuperBoL calculates the bolometric lightcurves of Type II supernovae using observed photometry; it includes three different methods for calculating the bolometric luminosity: quasi-bolometric, direct, and bolometric correction. SuperBoL propagates uncertainties in the input data through the calculations made by the code, allowing for error bars to be included in plots of the lightcurve.

[ascl:1609.018]
SIP: Systematics-Insensitive Periodograms

SIP (Systematics-Insensitive Periodograms) extends the generative model used to create traditional sine-fitting periodograms for finding the frequency of a sinusoid by including systematic trends based on a set of eigen light curves in the generative model in addition to using a sum of sine and cosine functions over a grid of frequencies, producing periodograms with vastly reduced systematic features. Acoustic oscillations in giant stars and measurement of stellar rotation periods can be recovered from the SIP periodograms without detrending. The code can also be applied to detection other periodic phenomena, including eclipsing binaries and short-period exoplanet candidates.

[ascl:1609.017]
spectral-cube: Read and analyze astrophysical spectral data cubes

Spectral-cube provides an easy way to read, manipulate, analyze, and write data cubes with two positional dimensions and one spectral dimension, optionally with Stokes parameters. It is a versatile data container for building custom analysis routines. It provides a uniform interface to spectral cubes, robust to the wide range of conventions of axis order, spatial projections, and spectral units that exist in the wild, and allows easy extraction of cube sub-regions using physical coordinates. It has the ability to create, combine, and apply masks to datasets and is designed to work with datasets too large to load into memory, and provide basic summary statistic methods like moments and array aggregates.

[ascl:1609.016]
PKDGRAV3: Parallel gravity code

Pkdgrav3 is an 𝒪(*N*) gravity calculation method; it uses a binary tree algorithm with fifth order fast multipole expansion of the gravitational potential, using cell-cell interactions. Periodic boundaries conditions require very little data movement and allow a high degree of parallelism; the code includes GPU acceleration for all force calculations, leading to a significant speed-up with respect to previous versions (ascl:1305.005). Pkdgrav3 also has a sophisticated time-stepping criterion based on an estimation of the local dynamical time.

[ascl:1609.015]
FIT3D: Fitting optical spectra

Sánchez, S. F.; Pérez, E.; Sánchez-Blázquez, P.; González, J. J.; Rosales-Ortega, F. F.; Cano-Díaz, M.; López-Cobá, C.; Marino, R. A.; Gil de Paz, A.; Mollá, M.; López-Sánchez, A. R.; Ascasibar, Y.; Barrera-Ballesteros, J.

FIT3D fits optical spectra to deblend the underlying stellar population and the ionized gas, and extract physical information from each component. FIT3D is focused on the analysis of Integral Field Spectroscopy data, but is not restricted to it, and is the basis of Pipe3D, a pipeline used in the analysis of datasets like CALIFA, MaNGA, and SAMI. It can run iteratively or in an automatic way to derive the parameters of a large set of spectra.

[ascl:1609.014]
Sky3D: Time-dependent Hartree-Fock equation solver

Written in Fortran 90, Sky3D solves the static or dynamic equations on a three-dimensional Cartesian mesh with isolated or periodic boundary conditions and no further symmetry assumptions. Pairing can be included in the BCS approximation for the static case. The code can be easily modified to include additional physics or special analysis of the results and requires LAPACK and FFTW3.

[ascl:1609.013]
21cmSense: Calculating the sensitivity of 21cm experiments to the EoR power spectrum

21cmSense calculates the expected sensitivities of 21cm experiments to the Epoch of Reionization power spectrum. Written in Python, it requires NumPy, SciPy, and AIPY (ascl:1609.012).

[ascl:1609.012]
AIPY: Astronomical Interferometry in PYthon

AIPY collects together tools for radio astronomical interferometry. In addition to pure-python phasing, calibration, imaging, and deconvolution code, this package includes interfaces to MIRIAD (ascl:1106.007) and HEALPix (ascl:1107.018), and math/fitting routines from SciPy.

[ascl:1609.011]
Photutils: Photometry tools

Bradley, Larry; Sipocz, Brigitta; Robitaille, Thomas; Tollerud, Erik; Deil, Christoph; Vinícius, Zè; Barbary, Kyle; Günther, Hans Moritz; Bostroem, Azalee; Droettboom, Michael; Bray, Erik; Bratholm, Lars Andersen; Pickering, T. E.; Craig, Matt; Pascual, Sergio; Greco, Johnny; Donath, Axel; Kerzendorf, Wolfgang; Littlefair, Stuart; Barentsen, Geert; D'Eugenio, Francesco; Weaver, Benjamin Alan

Photutils provides tools for detecting and performing photometry of astronomical sources. It can estimate the background and background rms in astronomical images, detect sources in astronomical images, estimate morphological parameters of those sources (e.g., centroid and shape parameters), and perform aperture and PSF photometry. Written in Python, it is an affiliated package of Astropy (ascl:1304.002).

[ascl:1609.010]
CuBANz: Photometric redshift estimator

CuBAN*z* is a photometric redshift estimator code for high redshift galaxies that uses the back propagation neural network along with clustering of the training set, making it very efficient. The training set is divided into several self learning clusters with galaxies having similar photometric properties and spectroscopic redshifts within a given span. The clustering algorithm uses the color information (i.e. u-g, g-r etc.) rather than the apparent magnitudes at various photometric bands, as the photometric redshift is more sensitive to the flux differences between different bands rather than the actual values. The clustering method enables accurate determination of the redshifts. CuBAN*z* considers uncertainty in the photometric measurements as well as uncertainty in the neural network training. The code is written in C.

[ascl:1609.009]
NSCool: Neutron star cooling code

NSCool is a 1D (i.e., spherically symmetric) neutron star cooling code written in Fortran 77. The package also contains a series of EOSs (equation of state) to build stars, a series of pre-built stars, and a TOV (Tolman- Oppenheimer-Volkoff) integrator to build stars from an EOS. It can also handle “strange stars” that have a huge density discontinuity between the quark matter and the covering thin baryonic crust. NSCool solves the heat transport and energy balance equations in whole GR, resulting in a time sequence of temperature profiles (and, in particular, a Teff - age curve). Several heating processes are included, and more can easily be incorporated. In particular it can evolve a star undergoing accretion with the resulting deep crustal heating, under a steady or time-variable accretion rate. NSCool is robust, very fast, and highly modular, making it easy to add new subroutines for new processes.

[ascl:1609.008]
GRASP: General-purpose Relativistic Atomic Structure Package

GRASP (General-purpose Relativistic Atomic Structure Package) calculates atomic structure, including energy levels, radiative rates (A-values) and lifetimes; it is a fully relativistic code based on the *jj* coupling scheme. This code has been superseded by GRASP2K (ascl:1611.007).

[ascl:1609.007]
Weighted EMPCA: Weighted Expectation Maximization Principal Component Analysis

Weighted EMPCA performs principal component analysis (PCA) on noisy datasets with missing values. Estimates of the measurement error are used to weight the input data such that the resulting eigenvectors, when compared to classic PCA, are more sensitive to the true underlying signal variations rather than being pulled by heteroskedastic measurement noise. Missing data are simply limiting cases of weight = 0. The underlying algorithm is a noise weighted expectation maximization (EM) PCA, which has additional benefits of implementation speed and flexibility for smoothing eigenvectors to reduce the noise contribution.

[ascl:1609.006]
SCIMES: Spectral Clustering for Interstellar Molecular Emission Segmentation

SCIMES identifies relevant molecular gas structures within dendrograms of emission using the spectral clustering paradigm. It is useful for decomposing objects in complex environments imaged at high resolution.

[ascl:1609.005]
FISHPACK90: Efficient FORTRAN Subprograms for the Solution of Separable Elliptic Partial Differential Equations

FISHPACK90 is a modernization of the original FISHPACK (ascl:1609.004), employing Fortran90 to slightly simplify and standardize the interface to some of the routines. This collection of Fortran programs and subroutines solves second- and fourth-order finite difference approximations to separable elliptic Partial Differential Equations (PDEs). These include Helmholtz equations in cartesian, polar, cylindrical, and spherical coordinates, as well as more general separable elliptic equations. The solvers use the cyclic reduction algorithm. When the problem is singular, a least-squares solution is computed. Singularities induced by the coordinate system are handled, including at the origin r=0 in cylindrical coordinates, and at the poles in spherical coordinates. Test programs are provided for the 19 solvers. Each serves two purposes: as a template to guide you in writing your own codes utilizing the FISHPACK90 solvers, and as a demonstration on your computer that you can correctly produce FISHPACK90 executables.

[ascl:1609.004]
FISHPACK: Efficient FORTRAN Subprograms for the Solution of Separable Elliptic Partial Differential Equations

The FISHPACK collection of Fortran77 subroutines solves second- and fourth-order finite difference approximations to separable elliptic Partial Differential Equations (PDEs). These include Helmholtz equations in cartesian, polar, cylindrical, and spherical coordinates, as well as more general separable elliptic equations. The solvers use the cyclic reduction algorithm. When the problem is singular, a least-squares solution is computed. Singularities induced by the coordinate system are handled, including at the origin r=0 in cylindrical coordinates, and at the poles in spherical coordinates.

[ascl:1609.003]
Kranc: Cactus modules from Mathematica equations

Kranc turns a tensorial description of a time dependent partial differential equation into a module for the Cactus Computational Toolkit (ascl:1102.013). This Mathematica application takes a simple continuum description of a problem and generates highly efficient and portable code, and can be used both for rapid prototyping of evolution systems and for high performance supercomputing.

[ascl:1609.002]
StarPy: Quenched star formation history parameters of a galaxy using MCMC

Smethurst, R. J.; Lintott, C. J.; Simmons, B. D.; Schawinski, K.; Marshall, P. J.; Bamford, S.; Fortson, L.; Kaviraj, S.; Masters, K. L.; Melvin, T.; Nichol, R. C.; Skibba, R. A.; Willett, K. W.

StarPy derives the quenching star formation history (SFH) of a single galaxy through the Bayesian Markov Chain Monte Carlo method code *emcee* (ascl:1303.002). The sample function implements the emcee EnsembleSampler function for the galaxy colors input. Burn-in is run and calculated for the length specified before the sampler is reset and then run for the length of steps specified. StarPy provides the ability to use the look-up tables provided or creating your own.

[ascl:1609.001]
T-PHOT: PSF-matched, prior-based, multiwavelength extragalactic deconfusion photometry

Merlin, E.; Fontana, A.; Ferguson, H. C.; Dunlop, J. S.; Elbaz, D.; Bourne, N.; Bruce, V. A.; Buitrago, F.; Castellano, M.; Schreiber, C.; Grazian, A.; McLure, R. J.; Okumura, K.; Shu, X.; Wang, T.; Amorín, R.; Boutsia, K.; Cappelluti, N.; Comastri, A.; Derriere, S.; Faber, S. M.; Santini, P.

T-PHOT extracts accurate photometry from low-resolution images of extragalactic fields, where the blending of sources can be a serious problem for accurate and unbiased measurement of fluxes and colors. It gathers data from a high-resolution image of a region of the sky and uses the source positions and morphologies to obtain priors for the photometric analysis of the lower resolution image of the same field. T-PHOT handles different types of datasets as input priors, including a list of objects that will be used to obtain cutouts from the real high-resolution image, a set of analytical models (as .fits stamps), and a list of unresolved, point-like sources, useful for example for far-infrared wavelength domains. T-PHOT yields accurate estimations of fluxes within the intrinsic uncertainties of the method when systematic errors are taken into account (which can be done using a flagging code given in the output), and handles multiwavelength optical to far-infrared image photometry. T-PHOT was developed as part of the ASTRODEEP project (www.astrodeep.eu).

[ascl:1608.020]
SPIDERz: SuPport vector classification for IDEntifying Redshifts

SPIDERz (SuPport vector classification for IDEntifying Redshifts) applies powerful support vector machine (SVM) optimization and statistical learning techniques to custom data sets to obtain accurate photometric redshift (photo-z) estimations. It is written for the IDL environment and can be applied to traditional data sets consisting of photometric band magnitudes, or alternatively to data sets with additional galaxy parameters (such as shape information) to investigate potential correlations between the extra galaxy parameters and redshift.

[ascl:1608.019]
NEBULAR: Spectrum synthesis for mixed hydrogen-helium gas in ionization equilibrium

NEBULAR synthesizes the spectrum of a mixed hydrogen helium gas in collisional ionization equilibrium. It is not a spectral fitting code, but it can be used to resample a model spectrum onto the wavelength grid of a real observation. It supports a wide range of temperatures and densities. NEBULAR includes free-free, free-bound, two-photon and line emission from HI, HeI and HeII. The code will either return the composite model spectrum, or, if desired, the unrescaled atomic emission coefficients. It is written in C++ and depends on the GNU Scientific Library (GSL).

[ascl:1608.018]
LORENE: Spectral methods differential equations solver

LORENE (Langage Objet pour la RElativité NumériquE) solves various problems arising in numerical relativity, and more generally in computational astrophysics. It is a set of C++ classes and provides tools to solve partial differential equations by means of multi-domain spectral methods. LORENE classes implement basic structures such as arrays and matrices, but also abstract mathematical objects, such as tensors, and astrophysical objects, such as stars and black holes.

[ascl:1608.017]
21CMMC: Parallelized Monte Carlo Markov Chain analysis tool for the epoch of reionization (EoR)

21CMMC is an efficient Python sampler of the semi-numerical reionization simulation code 21cmFAST (ascl:1102.023). It can recover constraints on astrophysical parameters from current or future 21 cm EoR experiments, accommodating a variety of EoR models, as well as priors on individual model parameters and the reionization history. By studying the resulting impact on the EoR astrophysical constraints, 21CMMC can be used to optimize foreground cleaning algorithms; interferometer designs; observing strategies; alternate statistics characterizing the 21cm signal; and synergies with other observational programs.

[ascl:1608.016]
NICIL: Non-Ideal magnetohydrodynamics Coefficients and Ionisation Library

NICIL (Non-Ideal magnetohydrodynamics Coefficients and Ionisation Library) calculates the ionization values and the coefficients of the non-ideal magnetohydrodynamics terms of Ohmic resistivity, the Hall effect, and ambipolar diffusion. Written as a standalone Fortran90 module that can be implemented in existing codes, NICIL is fully parameterizable, allowing the user to choose which processes to include and decide the values of the free parameters. The module includes both cosmic ray and thermal ionization; the former includes two ion species and three species of dust grains (positively charged, negatively charged and neutral), and the latter includes five elements which can be doubly ionized.

[ascl:1608.015]
2DFFT: Measuring Galactic Spiral Arm Pitch Angle

Davis, Benjamin L.; Berrier, Joel C.; Shields, Douglas W.; Kennefick, Julia; Kennefick, Daniel; Seigar, Marc S.; Lacy, Claud H. S.; Puerari, Ivânio

2DFFT utilizes two-dimensional fast Fourier transformations of images of spiral galaxies to isolate and measure the pitch angles of their spiral arms; this provides a quantitative way to measure this morphological feature and allows comparison of spiral galaxy pitch angle to other galactic parameters and test spiral arm genesis theories. 2DFFT requires fourn.c from *Numerical Recipes in C* (Press et al. 1989).

P2DFFT (ascl:1806.011) is a parallelized version of 2DFFT.

[ascl:1608.014]
gevolution: General Relativity Cosmological N-body code for evolution of large scale structures

The N-body code *gevolution* complies with general relativity principles at every step; it calculates all six metric degrees of freedom in Poisson gauge. N-body particles are evolved by solving the geodesic equation written in terms of a canonical momentum to remain valid for relativistic particles. *gevolution* can be extended to include different kinds of dark energy or modified gravity models, going beyond the usually adopted quasi-static approximation. A weak field expansion is the central element of *gevolution*; this permits the code to treat settings in which no strong gravitational fields appear, including arbitrary scenarios with relativistic sources as long as gravitational fields are not very strong. The framework is well suited for cosmology, but may also be useful for astrophysical applications with moderate gravitational fields where a Newtonian treatment is insufficient.

[ascl:1608.013]
DOLPHOT: Stellar photometry

DOLPHOT is a stellar photometry package that was adapted from HSTphot for general use. It supports two modes; the first is a generic PSF-fitting package, which uses analytic PSF models and can be used for any camera. The second mode uses ACS PSFs and calibrations, and is effectively an ACS adaptation of HSTphot. A number of utility programs are also included with the DOLPHOT distribution, including basic image reduction routines.

[submitted]
ExoPlanet

ExoPlanet 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.

ExoPlanet is designed to have a minimal learning curve to allow researchers to focus more on the applicative aspect of machine learning algorithms rather than their implementation details and 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 algorithms can be adjusted to ensure the best fit for the data. Training data is read from a CSV file, and after training is complete, ExoPlanet automates the building of the visual representations for the trained model. Once training and evaluation yield satisfactory results, the model may be used to make data based predictions on a new data set.

[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.

[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

Robinson, Elliot; von Hippel, Ted; Stein, Nathan; Stenning, David; Wagner-Kaiser, Rachel; Si, Shijing; van Dyk, David

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).

[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.

[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.

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

Cubillos, Patricio; Blecic, Jasmina; Harrington, Joseph; Rojo, Patricio; Lust, Nate; Bowman, Oliver; Stemm, Madison; Foster, Andrew; Loredo, Thomas J.; Fortney, Jonathan; Madhusudhan, Nikku

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.

[ascl:1608.003]
appaloosa: Python-based flare finding code for Kepler light curves

The appaloosa suite automates flare-finding in every Kepler light curves. It builds quiescent light curve models that include long- and short-cadence data through iterative de-trending and includes completeness estimates via artificial flare injection and recovery tests.

[ascl:1608.002]
pyXSIM: Synthetic X-ray observations generator

pyXSIM simulates X-ray observations from astrophysical sources. X-rays probe the high-energy universe, from hot galaxy clusters to compact objects such as neutron stars and black holes and many interesting sources in between. pyXSIM generates synthetic X-ray observations of these sources from a wide variety of models, whether from grid-based simulation codes such as FLASH (ascl:1010.082), Enzo (ascl:1010.072), and Athena (ascl:1010.014), to particle-based codes such as Gadget (ascl:0003.001) and AREPO, and even from datasets that have been created “by hand”, such as from NumPy arrays. pyXSIM can also manipulate the synthetic observations it produces in various ways and export the simulated X-ray events to other software packages to simulate the end products of specific X-ray observatories. pyXSIM is an implementation of the PHOX (ascl:1112.004) algorithm and was initially the photon_simulator analysis module in yt (ascl:1011.022); it is dependent on yt.

[ascl:1608.001]
Stingray: Spectral-timing software

Stingray is a spectral-timing software package for astrophysical X-ray (and more) data. The package merges existing efforts for a (spectral-)timing package in Python and is composed of a library of time series methods (including power spectra, cross spectra, covariance spectra, and lags); scripts to load FITS data files from different missions; a simulator of light curves and event lists that includes different kinds of variability and more complicated phenomena based on the impulse response of given physical events (e.g. reverberation); and a GUI to ease the learning curve for new users.

[ascl:1607.020]
SEEK: Signal Extraction and Emission Kartographer

Akeret, Joel; Seehars, Sebastian; Chang, Chihway; Monstein, Christian; Amara, Adam; Refregier, Alexandre

SEEK (Signal Extraction and Emission Kartographer) processes time-ordered-data from single dish radio telescopes or from the simulation pipline HIDE (ascl:1607.019), removes artifacts from Radio Frequency Interference (RFI), automatically applies flux calibration, and recovers the astronomical radio signal. With its companion code HIDE (ascl:1607.019), it provides end-to-end simulation and processing of radio survey data.

[ascl:1607.019]
HIDE: HI Data Emulator

Akeret, Joel; Seehars, Sebastian; Chang, Chihway; Monstein, Christian; Amara, Adam; Refregier, Alexandre

HIDE (HI Data Emulator) forward-models the process of collecting astronomical radio signals in a single dish radio telescope instrument and outputs pixel-level time-ordered-data. Written in Python, HIDE models the noise and RFI modeling of the data and with its companion code SEEK (ascl:1607.020) provides end-to-end simulation and processing of radio survey data.

[ascl:1607.018]
LZIFU: IDL emission line fitting pipeline for integral field spectroscopy data

LZIFU (LaZy-IFU) is an emission line fitting pipeline for integral field spectroscopy (IFS) data. Written in IDL, the pipeline turns IFS data to 2D emission line flux and kinematic maps for further analysis. LZIFU has been applied and tested extensively to various IFS data, including the SAMI Galaxy Survey, the Wide-Field Spectrograph (WiFeS), the CALIFA survey, the S7 survey and the MUSE instrument on the VLT.

[ascl:1607.017]
BoxRemap: Volume and local structure preserving mapping of periodic boxes

BoxRemap remaps the cubical domain of a cosmological simulation into simple non-cubical shapes. It can be used for on-the-fly remappings of the simulation geometry and is volume-preserving; remapped geometry has the same volume V = L3 as the original simulation box. The remappings are structure-preserving (local neighboring structures are mapped to neighboring places) and one-to-one, with every particle/halo/galaxy/etc. appearing once and only once in the remapped volume.

[ascl:1607.016]
astLib: Tools for research astronomers

astLib is a set of Python modules for performing astronomical plots, some statistics, common calculations, coordinate conversions, and manipulating FITS images with World Coordinate System (WCS) information through PyWCSTools, a simple wrapping of WCSTools (ascl:1109.015).

[ascl:1607.015]
RT1D: 1D code for Rayleigh-Taylor instability

The parallel one-dimensional moving-mesh hydrodynamics code RT1D reproduces the multidimensional dynamics from Rayleigh-Taylor instability in supernova remnants.

[ascl:1607.014]
SOPIE: Sequential Off-Pulse Interval Estimation

SOPIE (Sequential Off-Pulse Interval Estimation) provides functions to non-parametrically estimate the off-pulse interval of a source function originating from a pulsar. The technique is based on a sequential application of P-values obtained from goodness-of-fit tests for the uniform distribution, such as the Kolmogorov-Smirnov, Cramér-von Mises, Anderson-Darling and Rayleigh goodness-of-fit tests.

[ascl:1607.013]
Kālī: Time series data modeler

The fully parallelized and vectorized software package Kālī models time series data using various stochastic processes such as continuous-time ARMA (C-ARMA) processes and uses Bayesian Markov Chain Monte-Carlo (MCMC) for inferencing a stochastic light curve. Kālī is written in c++ with Python language bindings for ease of use. Kālī is named jointly after the Hindu goddess of time, change, and power and also as an acronym for KArma LIbrary.

[ascl:1607.012]
ZASPE: Zonal Atmospheric Stellar Parameters Estimator

ZASPE (Zonal Atmospheric Stellar Parameters Estimator) computes the atmospheric stellar parameters (Teff, log(g), [Fe/H] and vsin(i)) from echelle spectra via least squares minimization with a pre-computed library of synthetic spectra. The minimization is performed only in the most sensitive spectral zones to changes in the atmospheric parameters. The uncertainities and covariances computed by ZASPE assume that the principal source of error is the systematic missmatch between the observed spectrum and the sythetic one that produces the best fit. ZASPE requires a grid of synthetic spectra and can use any pre-computed library minor modifications.

[ascl:1607.011]
HfS: Hyperfine Structure fitting tool

HfS fits the hyperfine structure of spectral lines, with multiple velocity components. The HfS_nh3 procedures included in HfS fit simultaneously the hyperfine structure of the NH_{3} (J,K)= (1,1) and (2,2) inversion transitions, and perform a standard analysis to derive the NH_{3} column density, rotational temperature T_{rot}, and kinetic temperature Tk. HfS uses a Monte Carlo approach for fitting the line parameters, with special attention to the derivation of the parameter uncertainties. HfS includes procedures that make use of parallel computing for fitting spectra from a data cube.

[ascl:1607.009]
PICsar: Particle in cell pulsar magnetosphere simulator

PICsar simulates the magnetosphere of an aligned axisymmetric pulsar and can be used to simulate other arbitrary electromagnetics problems in axisymmetry. Written in Fortran, this special relativistic, electromagnetic, charge conservative particle in cell code features stretchable body-fitted coordinates that follow the surface of a sphere, simplifying the application of boundary conditions in the case of the aligned pulsar; a radiation absorbing outer boundary, which allows a steady state to be set up dynamically and maintained indefinitely from transient initial conditions; and algorithms for injection of charged particles into the simulation domain. PICsar is parallelized using MPI and has been used on research problems with ~1000 CPUs.

[ascl:1607.010]
K2PS: K2 Planet search

K2PS is an Oxford K2 planet search pipeline. Written in Python, it searches for transit-like signals from the k2sc-detrended light curves.

[ascl:1607.008]
BLS: Box-fitting Least Squares

BLS (Box-fitting Least Squares) is a box-fitting algorithm that analyzes stellar photometric time series to search for periodic transits of extrasolar planets. It searches for signals characterized by a periodic alternation between two discrete levels, with much less time spent at the lower level.

[ascl:1607.007]
JUDE: An Utraviolet Imaging Telescope pipeline

JUDE (Jayant's UVIT Data Explorer) converts the Level 1 data (FITS binary table) from the Ultraviolet Imaging Telescope (UVIT) on ASTROSAT into three output files: a photon event list as a function of frame number (FITS binary table); a FITS image file with two extensions; and a PNG file created from the FITS image file with an automated scaling.

[ascl:1607.006]
Cholla: 3D GPU-based hydrodynamics code for astrophysical simulation

Cholla (Computational Hydrodynamics On ParaLLel Architectures) models the Euler equations on a static mesh and evolves the fluid properties of thousands of cells simultaneously using GPUs. It can update over ten million cells per GPU-second while using an exact Riemann solver and PPM reconstruction, allowing computation of astrophysical simulations with physically interesting grid resolutions (>256^3) on a single device; calculations can be extended onto multiple devices with nearly ideal scaling beyond 64 GPUs.

[ascl:1607.005]
Planetary3br: Three massive body resonance calculator

Given two planets P1 and P2 with arbitrary orbits, planetary3br calculates all possible semimajor axes that a third planet P0 can have in order for the system to be in a three body resonance; these are identified by the combination k0*P0 + k1*P1 + k2*P2. P1 and P2 are assumed to be not in an exact two-body resonance. The program also calculates three "strengths" of the resonance, one for each planet, which are only indicators of the dynamical relevance of the resonance on each planet. Sample input data are available along with the Fortran77 source code.

[ascl:1607.004]
Atlas3bgeneral: Three-body resonance calculator

For a massless test particle and given a planetary system, atlas3bgeneral calculates all three body resonances in a given range of semimajor axes with all the planets taken by pairs. Planets are assumed in fixed circular and coplanar orbits and the test particle with arbitrary orbit. A sample input data file to calculate the three-body resonances is available for use with the Fortran77 source code.

[ascl:1607.003]
Atlas2bgeneral: Two-body resonance calculator

For a massless test particle and given a planetary system, Atlas2bgeneral calculates all resonances in a given range of semimajor axes with all the planets taken one by one. Planets are assumed in fixed circular and coplanar orbits and the test particle with arbitrary orbit. A sample input data file to calculate the two-body resonances is available for use with the Fortran77 source code.

[ascl:1607.002]
DICE: Disk Initial Conditions Environment

DICE models initial conditions of idealized galaxies to study their secular evolution or their more complex interactions such as mergers or compact groups using N-Body/hydro codes. The code can set up a large number of components modeling distinct parts of the galaxy, and creates 3D distributions of particles using a N-try MCMC algorithm which does not require a prior knowledge of the distribution function. The gravitational potential is then computed on a multi-level Cartesian mesh by solving the Poisson equation in the Fourier space. Finally, the dynamical equilibrium of each component is computed by integrating the Jeans equations for each particles. Several galaxies can be generated in a row and be placed on Keplerian orbits to model interactions. DICE writes the initial conditions in the Gadget1 or Gadget2 (ascl:0003.001) format and is fully compatible with Ramses (ascl:1011.007).

[ascl:1607.001]
AGNfitter: SED-fitting code for AGN and galaxies from a MCMC approach

AGNfitter is a fully Bayesian MCMC method to fit the spectral energy distributions (SEDs) of active galactic nuclei (AGN) and galaxies from the sub-mm to the UV; it enables robust disentanglement of the physical processes responsible for the emission of sources. Written in Python, AGNfitter makes use of a large library of theoretical, empirical, and semi-empirical models to characterize both the nuclear and host galaxy emission simultaneously. The model consists of four physical emission components: an accretion disk, a torus of AGN heated dust, stellar populations, and cold dust in star forming regions. AGNfitter determines the posterior distributions of numerous parameters that govern the physics of AGN with a fully Bayesian treatment of errors and parameter degeneracies, allowing one to infer integrated luminosities, dust attenuation parameters, stellar masses, and star formation rates.

[ascl:1606.015]
FLASK: Full-sky Lognormal Astro-fields Simulation Kit

FLASK (Full-sky Lognormal Astro-fields Simulation Kit) makes tomographic realizations on the sphere of an arbitrary number of correlated lognormal or Gaussian random fields; it can create joint simulations of clustering and lensing with sub-per-cent accuracy over relevant angular scales and redshift ranges. It is C++ code parallelized with OpenMP; FLASK generates fast full-sky simulations of cosmological large-scale structure observables such as multiple matter density tracers (galaxies, quasars, dark matter haloes), CMB temperature anisotropies and weak lensing convergence and shear fields. The mutiple fields can be generated tomographically in an arbitrary number of redshift slices and all their statistical properties (including cross-correlations) are determined by the angular power spectra supplied as input and the multivariate lognormal (or Gaussian) distribution assumed for the fields. Effects like redshift space distortions, doppler distortions, magnification biases, evolution and intrinsic aligments can be introduced in the simulations via the input power spectra which must be supplied by the user.

[ascl:1606.014]
Lmfit: Non-Linear Least-Square Minimization and Curve-Fitting for Python

Newville, Matthew; Stensitzki, Till; Allen, Daniel B; Rawlik, Michal; Ingargiola, Antonino; Nelson, Andrew

Lmfit provides a high-level interface to non-linear optimization and curve fitting problems for Python. Lmfit builds on and extends many of the optimization algorithm of scipy.optimize, especially the Levenberg-Marquardt method from optimize.leastsq. Its enhancements to optimization and data fitting problems include using Parameter objects instead of plain floats as variables, the ability to easily change fitting algorithms, and improved estimation of confidence intervals and curve-fitting with the Model class. Lmfit includes many pre-built models for common lineshapes.

[ascl:1606.013]
Pulse Portraiture: Pulsar timing

Pulse Portraiture is a wideband pulsar timing code written in python. It uses an extension of the FFTFIT algorithm (Taylor 1992) to simultaneously measure a phase (TOA) and dispersion measure (DM). The code includes a Gaussian-component-based portrait modeling routine. The code uses the python interface to the pulsar data analysis package PSRCHIVE (ascl:1105.014) and also requires the non-linear least-squares minimization package lmfit (ascl:1606.014).

[ascl:1606.012]
KMDWARFPARAM: Parameters estimator for K and M dwarf stars

KMDWARFPARAM estimates the physical parameters of a star with mass M < 0.8 M_sun given one or more observational constraints. The code runs a Markov-Chain Monte Carlo procedure to estimate the parameter values and their uncertainties.

[ascl:1606.011]
FDIPS: Finite Difference Iterative Potential-field Solver

FDIPS is a finite difference iterative potential-field solver that can generate the 3D potential magnetic field solution based on a magnetogram. It is offered as an alternative to the spherical harmonics approach, as when the number of spherical harmonics is increased, using the raw magnetogram data given on a grid that is uniform in the sine of the latitude coordinate can result in inaccurate and unreliable results, especially in the polar regions close to the Sun. FDIPS is written in Fortran 90 and uses the MPI library for parallel execution.

[ascl:1606.010]
SimpLens: Interactive gravitational lensing simulator

SimpLens illustrates some of the theoretical ideas important in gravitational lensing in an interactive way. After setting parameters for elliptical mass distribution and external mass, SimpLens displays the mass profile and source position, the lens potential and image locations, and indicate the image magnifications and contours of virtual light-travel time. A lens profile can be made shallower or steeper with little change in the image positions and with only total magnification affected.

[ascl:1606.009]
Companion-Finder: Planets and binary companions in time series spectra

Companion-Finder looks for planets and binary companions in time series spectra by searching for the spectral lines of stellar companions to other stars observed with high-precision radial-velocity surveys.

[ascl:1606.008]
s2: Object oriented wrapper for functions on the sphere

The s2 package can represent any arbitrary function defined on the sphere. Both real space map and harmonic space spherical harmonic representations are supported. Basic sky representations have been extended to simulate full sky noise distributions and Gaussian cosmic microwave background realisations. Support for the representation and convolution of beams is also provided. The code requires HEALPix (ascl:1107.018) and CFITSIO (ascl:1010.001).

[ascl:1606.007]
COMB: Compact embedded object simulations

COMB supports the simulation on the sphere of compact objects embedded in a stochastic background process of specified power spectrum. Support is provided to add additional white noise and convolve with beam functions. Functionality to support functions defined on the sphere is provided by the S2 code (ascl:1606.008); HEALPix (ascl:1107.018) and CFITSIO (ascl:1010.001) are also required.

[ascl:1606.006]
uvmcmcfit: Parametric models to interferometric data fitter

Uvmcmcfit fits parametric models to interferometric data. It is ideally suited to extract the maximum amount of information from marginally resolved observations with interferometers like the Atacama Large Millimeter Array (ALMA), Submillimeter Array (SMA), and Plateau de Bure Interferometer (PdBI). uvmcmcfit uses emcee (ascl:1303.002) to do Markov Chain Monte Carlo (MCMC) and can measure the goodness of fit from visibilities rather than deconvolved images, an advantage when there is strong gravitational lensing and in other situations. uvmcmcfit includes a pure-Python adaptation of Miriad’s (ascl:1106.007) uvmodel task to generate simulated visibilities given observed visibilities and a model image and a simple ray-tracing routine that allows it to account for both strongly lensed systems (where multiple images of the lensed galaxy are detected) and weakly lensed systems (where only a single image of the lensed galaxy is detected).

[ascl:1606.005]
PyMultiNest: Python interface for MultiNest

PyMultiNest provides programmatic access to MultiNest (ascl:1109.006) and PyCuba, integration existing Python code (numpy, scipy), and enables writing Prior & LogLikelihood functions in Python. PyMultiNest can plot and visualize MultiNest's progress and allows easy plotting, visualization and summarization of MultiNest results. The plotting can be run on existing MultiNest output, and when not using PyMultiNest for running MultiNest.

[ascl:1606.004]
HIBAYES: Global 21-cm Bayesian Monte-Carlo Model Fitting

HIBAYES implements fully-Bayesian extraction of the sky-averaged (global) 21-cm signal from the Cosmic Dawn and Epoch of Reionization in the presence of foreground emission. User-defined likelihood and prior functions are called by the sampler PyMultiNest (ascl:1606.005) in order to jointly explore the full (signal plus foreground) posterior probability distribution and evaluate the Bayesian evidence for a given model. Implemented models, for simulation and fitting, include gaussians (HI signal) and polynomials (foregrounds). Some simple plotting and analysis tools are supplied. The code can be extended to other models (physical or empirical), to incorporate data from other experiments, or to use alternative Monte-Carlo sampling engines as required.

[ascl:1606.003]
Cygrid: Cython-powered convolution-based gridding module for Python

The Python module Cygrid grids (resamples) data to any collection of spherical target coordinates, although its typical application involves FITS maps or data cubes. The module supports the FITS world coordinate system (WCS) standard; its underlying algorithm is based on the convolution of the original samples with a 2D Gaussian kernel. A lookup table scheme allows parallelization of the code and is combined with the HEALPix tessellation of the sphere for fast neighbor searches. Cygrid's runtime scales between O(n) and O(nlog n), with n being the number of input samples.

[ascl:1606.002]
PAL: Positional Astronomy Library

The PAL library is a partial re-implementation of Pat Wallace's popular SLALIB library written in C using a Gnu GPL license and layered on top of the IAU's SOFA library (or the BSD-licensed ERFA) where appropriate. PAL attempts to stick to the SLA C API where possible.

[ascl:1606.001]
SWOC: Spectral Wavelength Optimization Code

SWOC (Spectral Wavelength Optimization Code) determines the wavelength ranges that provide the optimal amount of information to achieve the required science goals for a spectroscopic study. It computes a figure-of-merit for different spectral configurations using a user-defined list of spectral features, and, utilizing a set of flux-calibrated spectra, determines the spectral regions showing the largest differences among the spectra.

[ascl:1605.017]
Surprise Calculator: Estimating relative entropy and Surprise between samples

The Surprise is a measure for consistency between posterior distributions and operates in parameter space. It can be used to analyze either the compatibility of separately analyzed posteriors from two datasets, or the posteriors from a Bayesian update. The Surprise Calculator estimates relative entropy and Surprise between two samples, assuming they are Gaussian. The software requires the R package CompQuadForm to estimate the significance of the Surprise, and rpy2 to interface R with Python.

[ascl:1605.016]
zeldovich-PLT: Zel'dovich approximation initial conditions generator

zeldovich-PLT generates Zel'dovich approximation (ZA) initial conditions (i.e. first-order Lagrangian perturbation theory) for cosmological N-body simulations, optionally applying particle linear theory (PLT) corrections.

[ascl:1605.015]
SAND: Automated VLBI imaging and analyzing pipeline

The Search And Non-Destroy (SAND) is a VLBI data reduction pipeline composed of a set of Python programs based on the AIPS interface provided by ObitTalk. It is designed for the massive data reduction of multi-epoch VLBI monitoring research. It can automatically investigate calibrated visibility data, search all the radio emissions above a given noise floor and do the model fitting either on the CLEANed image or directly on the uv data. It then digests the model-fitting results, intelligently identifies the multi-epoch jet component correspondence, and recognizes the linear or non-linear proper motion patterns. The outputs including CLEANed image catalogue with polarization maps, animation cube, proper motion fitting and core light curves. For uncalibrated data, a user can easily add inline modules to do the calibration and self-calibration in a batch for a specific array.

[ascl:1605.014]
DUO: Spectra of diatomic molecules

Duo computes rotational, rovibrational and rovibronic spectra of diatomic molecules. The software, written in Fortran 2003, solves the Schrödinger equation for the motion of the nuclei for the simple case of uncoupled, isolated electronic states and also for the general case of an arbitrary number and type of couplings between electronic states. Possible couplings include spin–orbit, angular momenta, spin-rotational and spin–spin. Introducing the relevant couplings using so-called Born–Oppenheimer breakdown curves can correct non-adiabatic effects.

[ascl:1605.013]
grtrans: Polarized general relativistic radiative transfer via ray tracing

grtrans calculates ray tracing radiative transfer in the Kerr metric, including the full treatment of polarised radiative transfer and parallel transport along geodesics, for comparing theoretical models of black hole accretion flows and jets with observations. The code is written in Fortran 90 and parallelizes with OpenMP; the full code and several components have Python interfaces. grtrans includes Geokerr (ascl:1011.015) and requires cfitsio (ascl:1010.001) and pyfits (ascl:1207.009).

[ascl:1605.012]
K2SC: K2 Systematics Correction

K2SC (K2 Systematics Correction) models instrumental systematics and astrophysical variability in light curves from the K2 mission. It enables the user to remove both position-dependent systematics and time-dependent variability (e.g., for transit searches) or to remove systematics while preserving variability (for variability studies). K2SC automatically computes estimates of the period, amplitude and evolution timescale of the variability for periodic variables and can be run on ASCII and FITS light curve files. Written in Python, this pipeline requires NumPy, SciPy, MPI4Py, Astropy (ascl:1304.002), and George (ascl:1511.015).

[ascl:1605.011]
DISCO: 3-D moving-mesh magnetohydrodynamics package

DISCO evolves orbital fluid motion in two and three dimensions, especially at high Mach number, for studying astrophysical disks. The software uses a moving-mesh approach with a dynamic cylindrical mesh that can shear azimuthally to follow the orbital motion of the gas, thus removing diffusive advection errors and permitting longer timesteps than a static grid. DISCO uses an HLLD Riemann solver and a constrained transport scheme compatible with the mesh motion to implement magnetohydrodynamics.

[ascl:1605.010]
TRIPPy: Python-based Trailed Source Photometry

Fraser, Wesley C.; Alexandersen, Mike; Schwamb, Megan E.; Marsset, Michael E.; Pike, Rosemary E.; Kavelaars, JJ; Bannister, Michele T.; Benecchi, Susan; Delsanti, Audrey

TRIPPy (TRailed Image Photometry in Python) uses a pill-shaped aperture, a rectangle described by three parameters (trail length, angle, and radius) to improve photometry of moving sources over that done with circular apertures. It can generate accurate model and trailed point-spread functions from stationary background sources in sidereally tracked images. Appropriate aperture correction provides accurate, unbiased flux measurement. TRIPPy requires numpy, scipy, matplotlib, Astropy (ascl:1304.002), and stsci.numdisplay; emcee (ascl:1303.002) and SExtractor (ascl:1010.064) are optional.

[ascl:1605.009]
ASTRiDE: Automated Streak Detection for Astronomical Images

ASTRiDE detects streaks in astronomical images using a "border" of each object (i.e. "boundary-tracing" or "contour-tracing") and their morphological parameters. Fast moving objects such as meteors, satellites, near-Earth objects (NEOs), or even cosmic rays can leave streak-like traces in the images; ASTRiDE can detect not only long streaks but also relatively short or curved streaks.

[ascl:1605.008]
PDT: Photometric DeTrending Algorithm Using Machine Learning

PDT removes systematic trends in light curves. It finds clusters of light curves that are highly correlated using machine learning, constructs one master trend per cluster and detrends an individual light curve using the constructed master trends by minimizing residuals while constraining coefficients to be positive.

[ascl:1605.007]
MUSCLE: MUltiscale Spherical-ColLapse Evolution

MUSCLE (MUltiscale Spherical ColLapse Evolution) produces low-redshift approximate N-body realizations accurate to few-Megaparsec scales. It applies a spherical-collapse prescription on multiple Gaussian-smoothed scales. It achieves higher accuracy than perturbative schemes (Zel'dovich and second-order Lagrangian perturbation theory - 2LPT), and by including the void-in-cloud process (voids in large-scale collapsing regions), solves problems with a single-scale spherical-collapse scheme.

[ascl:1605.006]
CAMELOT: Cloud Archive for MEtadata, Library and Online Toolkit

Ginsburg, Adam; Kruijssen, J. M. Diederik; Longmore, Steven N.; Koch, Eric; Glover, Simon C. O.; Dale, James E.; Commerçon, Benoît; Giannetti, Andrea; McLeod, Anna F.; Testi, Leonardo; Zahorecz, Sarolta; Rathborne, Jill M.; Zhang, Qizhou; Fontani, Francesco; Beltrán, Maite T.; Rivilla, Victor M.

CAMELOT facilitates the comparison of observational data and simulations of molecular clouds and/or star-forming regions. The central component of CAMELOT is a database summarizing the properties of observational data and simulations in the literature through pertinent metadata. The core functionality allows users to upload metadata, search and visualize the contents of the database to find and match observations/simulations over any range of parameter space.

To bridge the fundamental disconnect between inherently 2D observational data and 3D simulations, the code uses key physical properties that, in principle, are straightforward for both observers and simulators to measure — the surface density (Sigma), velocity dispersion (sigma) and radius (R). By determining these in a self-consistent way for all entries in the database, it should be possible to make robust comparisons.

[ascl:1605.005]
TMBIDL: Single dish radio astronomy data reduction package

The IDL package reduces and analyzes radio astronomy data. It translates SDFITS files into TMBIDL format, and can average and display spectra, remove baselines, and fit Gaussian models.

[ascl:1605.004]
BACCHUS: Brussels Automatic Code for Characterizing High accUracy Spectra

BACCHUS (Brussels Automatic Code for Characterizing High accUracy Spectra) derives stellar parameters (T_{eff}, log *g*, metallicity, microturbulence velocity and rotational velocity), equivalent widths, and abundances. The code includes on the fly spectrum synthesis, local continuum normalization, estimation of local S/N, automatic line masking, four methods for abundance determinations, and a flagging system aiding line selection. BACCHUS relies on the grid of MARCS model atmospheres, Masseron's model atmosphere thermodynamic structure interpolator, and the radiative transfer code Turbospectrum (ascl:1205.004).

[ascl:1605.003]
Shadowfax: Moving mesh hydrodynamical integration code

Shadowfax simulates galaxy evolution. Written in object-oriented modular C++, it evolves a mixture of gas, subject to the laws of hydrodynamics and gravity, and any collisionless fluid only subject to gravity, such as cold dark matter or stars. For the hydrodynamical integration, it makes use of a (co-) moving Lagrangian mesh. The code has a 2D and 3D version, contains utility programs to generate initial conditions and visualize simulation snapshots, and its input/output is compatible with a number of other simulation codes, e.g. Gadget2 (ascl:0003.001) and GIZMO (ascl:1410.003).

[ascl:1605.002]
cluster-lensing: Tools for calculating properties and weak lensing profiles of galaxy clusters

The cluster-lensing package calculates properties and weak lensing profiles of galaxy clusters. Implemented in Python, it includes cluster mass-richness and mass-concentration scaling relations, and NFW halo profiles for weak lensing shear, the differential surface mass density ΔΣ(r), and for magnification, Σ(r). Optionally the calculation will include the effects of cluster miscentering offsets.

[ascl:1605.001]
MARZ: Redshifting Program

MARZ analyzes objects and produces high quality spectroscopic redshift measurements. Spectra not matched correctly by the automatic algorithm can be redshifted manually by cycling automatic results, manual template comparison, or marking spectral features. The software has an intuitive interface and powerful automatic matching capabilities on spectra, and can be run interactively or from the command line, and runs as a Web application. MARZ can be run on a local server; it is also available for use on a public server.

[ascl:1604.012]
TTVFaster: First order eccentricity transit timing variations (TTVs)

TTVFaster implements analytic formulae for transit time variations (TTVs) that are accurate to first order in the planet–star mass ratios and in the orbital eccentricities; the implementations are available in several languages, including IDL, Julia, Python and C. These formulae compare well with more computationally expensive N-body integrations in the low-eccentricity, low mass-ratio regime when applied to simulated and to actual multi-transiting Kepler planet systems.

[ascl:1604.011]
FDPS: Framework for Developing Particle Simulators

Iwasawa, Masaki; Tanikawa, Ataru; Hosono, Natsuki; Nitadori, Keigo; Muranushi, Takayuki; Makino, Junichiro

FDPS provides the necessary functions for efficient parallel execution of particle-based simulations as templates independent of the data structure of particles and the functional form of the interaction. It is used to develop particle-based simulation programs for large-scale distributed-memory parallel supercomputers. FDPS includes templates for domain decomposition, redistribution of particles, and gathering of particle information for interaction calculation. It uses algorithms such as Barnes-Hut tree method for long-range interactions; methods to limit the calculation to neighbor particles are used for short-range interactions. FDPS reduces the time and effort necessary to write a simple, sequential and unoptimized program of O(N^2) calculation cost, and produces compiled programs that will run efficiently on large-scale parallel supercomputers.

[ascl:1604.009]
CCSNMultivar: Core-Collapse Supernova Gravitational Waves

CCSNMultivar aids the analysis of core-collapse supernova gravitational waves. It includes multivariate regression of Fourier transformed or time domain waveforms, hypothesis testing for measuring the influence of physical parameters, and the Abdikamalov et. al. catalog for example use. CCSNMultivar can optionally incorporate additional uncertainty due to detector noise and approximate waveforms from anywhere within the parameter space.

[ascl:1604.008]
The Tractor: Probabilistic astronomical source detection and measurement

The Tractor optimizes or samples from models of astronomical objects. The approach is generative: given astronomical sources and a description of the image properties, the code produces pixel-space estimates or predictions of what will be observed in the images. This estimate can be used to produce a likelihood for the observed data given the model: assuming the model space actually includes the truth (it doesn’t, in detail), then if we had the optimal model parameters, the predicted image would differ from the actually observed image only by noise. Given a noise model of the instrument and assuming pixelwise independent noise, the log-likelihood is the negative chi-squared difference: (image - model) / noise.

[ascl:1604.007]
DNest3: Diffusive Nested Sampling

DNest3 is a C++ implementation of Diffusive Nested Sampling (ascl:1010.029), a Markov Chain Monte Carlo (MCMC) algorithm for Bayesian Inference and Statistical Mechanics. Relative to older DNest versions, DNest3 has improved performance (in terms of the sampling overhead, likelihood evaluations still dominate in general) and is cleaner code: implementing new models should be easier than it was before. In addition, DNest3 is multi-threaded, so one can run multiple MCMC walkers at the same time, and the results will be combined together.

[ascl:1604.006]
2-DUST: Dust radiative transfer code

2-DUST is a general-purpose dust radiative transfer code for an axisymmetric system that reveals the global energetics of dust grains in the shell and the 2-D projected morphologies of the shell that are strongly dependent on the mixed effects of the axisymmetric dust distribution and inclination angle. It can be used to model a variety of axisymmetric astronomical dust systems.

[ascl:1604.005]
Halotools: Galaxy-Halo connection models

Hearin, Andrew; Tollerud, Erik; Robitaille,Thomas; Droettboom, Michael; Zentner, Andrew; Bray, Erik; Craig, Matt; Bradley, Larry; Barbary, Kyle; Deil, Christoph; Tan, Kevin; Becker, Matthew R.; More, Surhud; Günther, Hans Moritz; Sipocz, Brigitta

Halotools builds and tests models of the galaxy-halo connection and analyzes catalogs of dark matter halos. The core functions of the package include fast generation of synthetic galaxy populations using HODs, abundance matching, and related methods; efficient algorithms for calculating galaxy clustering, lensing, z-space distortions, and other astronomical statistics; a modular, object-oriented framework for designing galaxy evolution models; and end-to-end support for reducing halo catalogs and caching them as hdf5 files.

[ascl:1604.004]
magicaxis: Pretty scientific plotting with minor-tick and log minor-tick support

The R suite magicaxis makes useful and pretty plots for scientific plotting and includes functions for base plotting, with particular emphasis on pretty axis labelling in a number of circumstances that are often used in scientific plotting. It also includes functions for generating images and contours that reflect the 2D quantile levels of the data designed particularly for output of MCMC posteriors where visualizing the location of the 68% and 95% 2D quantiles for covariant parameters is a necessary part of the post MCMC analysis, can generate low and high error bars, and allows clipping of values, rejection of bad values, and log stretching.

[ascl:1604.003]
LAMBDAR: Lambda Adaptive Multi-Band Deblending Algorithm in R

LAMBDAR measures galaxy fluxes from an arbitrary FITS image, covering an arbitrary photometric wave-band, when provided all parameters needed to construct galactic apertures at the required locations for multi-band matched aperture galactic photometry. Through sophisticated matched aperture photometry, the package develops robust Spectral Energy Distributions (SEDs) and accurately establishes the physical properties of galactic objects. LAMBDAR was based on a package detailed in Bourne et al. (2012) that determined galactic fluxes in low resolution Herschel images.

[ascl:1604.002]
libpolycomp: Compression/decompression library

Libpolycomp compresses and decompresses one-dimensional streams of numbers by means of several algorithms. It is well-suited for time-ordered data acquired by astronomical instruments or simulations. One of the algorithms, called "polynomial compression", combines two widely-used ideas (namely, polynomial approximation and filtering of Fourier series) to achieve substantial compression ratios for datasets characterized by smoothness and lack of noise. Notable examples are the ephemerides of astronomical objects and the pointing information of astronomical telescopes. Other algorithms implemented in this C library are well known and already widely used, e.g., RLE, quantization, deflate (via libz) and Burrows-Wheeler transform (via libbzip2). Libpolycomp can compress the timelines acquired by the Planck/LFI instrument with an overall compression ratio of ~9, while other widely known programs (gzip, bzip2) reach compression ratios less than 1.5.

[ascl:1604.001]
OpenMHD: Godunov-type code for ideal/resistive magnetohydrodynamics (MHD)

OpenMHD is a Godunov-type finite-volume code for ideal/resistive magnetohydrodynamics (MHD). It is written in Fortran 90 and is parallelized by using MPI-2 and OpenMP. The code was originally developed for studying magnetic reconnection problems and has been made publicly available in the hope that others may find it useful.

[ascl:1603.018]
PolRadTran: Polarized Radiative Transfer Model Distribution

PolRadTran is a plane-parallel polarized radiative transfer model. It is used to compute the radiance exiting a vertically inhomogeneous atmosphere containing randomly-oriented particles. Both solar and thermal sources of radiation are considered. A direct method of incorporating the polarized scattering information is combined with the doubling and adding method to produce a relatively simple formulation.

[ascl:1603.017]
HIIexplorer: Detect and extract integrated spectra of HII regions

HIIexplorer detects and extracts the integrated spectra of HII regions from IFS datacubes. The procedure assumes H ii regions are peaky/isolated structures with a strong ionized gas emission, clearly above the continuum emission and the average ionized gas emission across the galaxy and that H ii regions have a typical physical size of about a hundred or a few hundreds of parsecs, which corresponds to a typical projected size at the distance of the galaxies of a few arcsec for galaxies at z~0.016. All input parameters can be derived from either a visual inspection and/or a statistical analysis of the Hα emission line map. The algorithm produces a segmentation FITS file describing the pixels associated to each H ii region.

[ascl:1603.016]
ellc: Light curve model for eclipsing binary stars and transiting exoplanets

ellc analyzes the light curves of detached eclipsing binary stars and transiting exoplanet systems. The model represents stars as triaxial ellipsoids, and the apparent flux from the binary is calculated using Gauss-Legendre integration over the ellipses that are the projection of these ellipsoids on the sky. The code can also calculate the fluxweighted radial velocity of the stars during an eclipse (Rossiter-McLaghlin effect). ellc can model a wide range of eclipsing binary stars and extrasolar planetary systems, and can enable the use of modern Monte Carlo methods for data analysis and model testing.

[ascl:1603.015]
Dedalus: Flexible framework for spectrally solving differential equations

Dedalus solves differential equations using spectral methods. It implements flexible algorithms to solve initial-value, boundary-value, and eigenvalue problems with broad ranges of custom equations and spectral domains. Its primary features include symbolic equation entry, multidimensional parallelization, implicit-explicit timestepping, and flexible analysis with HDF5. The code is written primarily in Python and features an easy-to-use interface. The numerical algorithm produces highly sparse systems for many equations which are efficiently solved using compiled libraries and MPI.

[ascl:1603.014]
fibmeasure: Python/Cython module to find the center of back-illuminated optical fibers in metrology images

fibmeasure finds the precise locations of the centers of back-illuminated optical fibers in images. It was developed for astronomical fiber positioning feedback via machine vision cameras and is optimized for high-magnification images where fibers appear as resolvable circles. It was originally written during the design of the WEAVE pick-and-place fiber positioner for the William Herschel Telescope.

[ascl:1603.013]
PyGSM: Python interface to the Global Sky Model

PyGSM is a Python interface for the Global Sky Model (GSM, ascl:1011.010). The GSM is a model of diffuse galactic radio emission, constructed from a variety of all-sky surveys spanning the radio band (e.g. Haslam and WMAP). PyGSM uses the GSM to generate all-sky maps in Healpix format of diffuse Galactic radio emission from 10 MHz to 94 GHz. The PyGSM module provides visualization utilities, file output in FITS format, and the ability to generate observed skies for a given location and date. PyGSM requires Healpy, PyEphem (ascl:1112.014), and AstroPy (ascl:1304.002).

[ascl:1603.012]
tpipe: Searching radio interferometry data for fast, dispersed transients

Visibilities from radio interferometers have not traditionally been used to study the fast transient sky. Millisecond transients (e.g., fast radio bursts) and periodic sources (e.g., pulsars) have been studied with single-dish radio telescopes and a software stack developed over the past few decades. tpipe is an initial attempt to develop the fast transient algorithms for visibility data. Functions exist for analysis of visibilties, such as reading data, flagging data, applying interferometric gain calibration, and imaging. These functions are given equal footing as time-domain techniques like filters and dedispersion.

tpipe has been largely superseded by rtpipe (ascl:1706.002).

[ascl:1603.011]
DiskJockey: Protoplanetary disk modeling for dynamical mass derivation

DiskJockey derives dynamical masses for T Tauri stars using the Keplerian motion of their circumstellar disks, applied to radio interferometric data from the Atacama Large Millimeter Array (ALMA) and the Submillimeter Array (SMA). The package relies on RADMC-3D (ascl:1202.015) to perform the radiative transfer of the disk model. DiskJockey is designed to work in a parallel environment where the calculations for each frequency channel can be distributed to independent processors. Due to the computationally expensive nature of the radiative synthesis, fitting sizable datasets (e.g., SMA and ALMA) will require a substantial amount of CPU cores to explore a posterior distribution in a reasonable timeframe.