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[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.

[submitted] encube: large-scale comparative visualisation and analysis of sets of multidimensional data

Encube is a qualitative, quantitative and comparative visualisation 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: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.

[submitted] CINE: Comet INfrared Excitation

CINE is a command-line tool for calculating 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 code 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.

[submitted] SPARTA: Subhalo and PARticle Trajectory Analysis

SPARTA is an MPI-parallelized C-code framework for the dynamical analysis or particle-based simulations. The code follows the orbits of dynamical tracers such as particles and subhalos in dark matter halos. As a first application, SPARTA can record the first apocenters of all halo particles and compute the splashback radius of halos.

[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

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.

[submitted] 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. Quickclump is primarily intended for decomposing observations of interstellar clouds into individual clumps, but it can be as well used for finding clumps in any 3D rectangular data.

[submitted] KSTAT

Code for calculating 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 (currently under development). The code is based on kd-tree structures and is parallelized using a mixture of MPI and OpenMP.

I created these codes as I have found it difficult in the past find similar ones
freely available in the public domain. I hope to keep developing them, so please
send me bug fixes,suggestions, comments/criticisms to csabiu@gmail.com

[submitted] INTRAT: INTensity RATios calculator for hydrogenic recombination lines

The Fortran program INTRAT computes INTensity RATios of hydrogenic recombination lines for specified transitions at temperatures and densities. It utilizes the linear or logarithmic interpolation over temperatures and densities to calculate line emissivities and total recombination coefficients for cases A and B of all hydrogenic ions through oxygen.

[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.

[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: Corner plots

corner 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 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 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.

[submitted] Lizard: an extensible Cyclomatic Complexity Analyzer

Lizard is an extensible Cyclomatic Complexity Analyzer for many imperative programming languages including C/C++.

[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.

[submitted] DiskSim: Modeling Accretion Disk Dynamics with SPH

DiskSim is a source-code distribution of the SPH accretion disk modeling code described in Simpson & Wood (1998) and Wood, Thomas, & Simpson (2009). The code had been released in a Windows executable form as FITDisk (Dolence, Wood & Simpson 2005; ascl:1305.011). The code released now is the full research code in Fortran, which can be modified as needed by the user.

[submitted] 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:1612.022] REPS: REscaled Power Spectra for initial conditions with massive neutrinos

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

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

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, an, the Rp/R* ratio and all the orbital parameters based on the nonlinear limb darkening model (Claret 2000).

[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.

[submitted] pygad: Analysing 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: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

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

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 Epeak, 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 pNT. OXAF accounts for opacity effects where the accretion disk is ionized because it inherits the ‘color correction’ of OPTXAGNF, the physical model upon which OXAF is based.

[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 ∫ dz 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) module which allows the modelling of 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.

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