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.

ROGER (Reconstructing Orbits of Galaxies in Extreme Regions) predicts the dynamical properties of galaxies using the projected phase-space information. Written in R, it offers a choice of machine learning methods to classify the dynamical properties of galaxies. An interface for online use of the software is available at https://mdelosrios.shinyapps.io/roger_shiny/.

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.

Rockstar (Robust Overdensity Calculation using K-Space Topologically Adaptive Refinement) identifies dark matter halos, substructure, and tidal features. The approach is based on adaptive hierarchical refinement of friends-of-friends groups in six phase-space dimensions and one time dimension, which allows for robust (grid-independent, shape-independent, and noise-resilient) tracking of substructure. Our method is massively parallel (up to 10^5 CPUs) and runs on the largest current simulations (>10^10 particles) with high efficiency (10 CPU hours and 60 gigabytes of memory required per billion particles analyzed). Rockstar offers significant improvement in substructure recovery as compared to several other halo finders.

Roche is a visualization and analysis tool for drawing the Roche-lobe geometry of evolving binaries. Roche can be used as a standalone program reading data from the command line or from a file generated by SeBa (ascl:1201.003). Eventually Roche will be able to read data from any other binary evolution program. Roche requires Starlab (ascl:1010.076) version 4.1.1 or later and the pgplot (ascl:1103.002) libraries. Roche creates a series of images, based on the SeBa output file SeBa.data, displaying the evolutionary state of a binary.

The DR25 Kepler Robovetter is a robotic decision-making code that dispositions each Threshold Crossing Event (TCE) from the final processing (DR 25) of the Kepler data into Planet Candidates (PCs) and False Positives (FPs). The Robovetter provides four major flags to designate each FP TCE as Not Transit-Like (NTL), a Stellar Eclipse (SS), a Centroid Offset (CO), and/or an Ephemeris Match (EM). It produces a score ranging from 0.0 to 1.0 that indicates the Robovetter's disposition confidence, where 1.0 indicates strong confidence in PC, and 0.0 indicates strong confidence in FP. Finally, the Robovetter provides comments in a text string that indicate the specific tests each FP TCE fails and provides supplemental information on all TCEs as necessary.

ROBOSPECT, written in C, automatically measures and deblends line equivalent widths for absorption and emission spectra. ROBOSPECT should not be used for stars with spectra in which there is no discernible continuum over large wavelength regions, nor for the most carbon-enhanced stars for which spectral synthesis would be favored. Although ROBOSPECT was designed for metal-poor stars, it is capable of fitting absorption and emission features in a variety of astronomical sources.

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).

ROBAST (ROOT-based simulator for ray tracing) is a non-sequential ray-tracing simulation library developed for wide use in optical simulations of gamma-ray and cosmic-ray telescopes. The library is written in C++ and fully utilizes the geometry library of the ROOT analysis framework, and can build the complex optics geometries typically used in cosmic ray experiments and ground-based gamma-ray telescopes.

ROA (Running Optimal Average) describes time series data. This model uses a Gaussian window function that moves through the data giving stronger weights to points close to the center of the Gaussian. Therefore, the width of the window function, delta, controls the flexibility of the model, with a small delta providing a very flexible model. The function also calculates the effective number of parameters, as a very flexible model will correspond to large number of parameters while a rigid model (low delta) has a low effective number of parameters. Knowing the effective number of parameters can be used to optimize the window width, e.g., using the Bayesian information criterion (BIC). An error envelope, which expands appropriately where there are gaps in the data, is also calculated for the model.

This program determines stellar population parameters (e.g. age, metallicity, IMF slope,...), using as input a pair of line-strength indices, through the interpolation in SSP model predictions. Both linear and bivariate fits are computed to perform the interpolation.

RMNest directly fits the Stokes Q and U (and V) spectra of a radio signal to measure the effects of Faraday rotation (or conversion) induced by propagation through a magnetized plasma along the line of sight. The software makes use of the Bayesian Inference Library (Bilby; ascl:1901.011) as an interface to the dynesty (ascl:1809.013) nested sampling algorithm.

RMHB is a hierarchical Bayesian code for reverberation mapping (RM) that combines results of a sparsely sampled broad line region (BLR) light curve and a large sample of active galactic nuclei (AGN) to infer properties of the sample of the AGN. The key idea of RM is to measure the time lag τ between variations in the continuum emission from the accretion disc and subsequent response of the broad line region (BLR). The measurement of τ is typically used to estimate the physical size of the BLR and is combined with other measurements to estimate the black hole mass MBH. A major difficulty with RM campaigns is the large amount of data needed to measure τ. RMHB allows a clear interpretation of a posterior distribution for hyperparameters describing the sample of AGN.

Rmfit uses a forward-folding technique to obtain the best-fit parameters for a chosen model given user-selected source and background time intervals from data files containing observed count rates and a corresponding detector response matrix. rmfit displays lightcurves and spectra using a graphical interface that enables user-defined integrated or time-resolved spectral fits and binning in either time or energy. Originally developed for the analysis of BATSE Gamma-Ray Burst (GRB) spectroscopy, rmfit is a tool for the spectroscopy of transient sources; it accommodates the Fermi GBM and LAT data and Swift BAT.

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.

RM-Tools analyzes radio polarization data, specifically the use of Faraday rotation measure synthesis and Stokes QU model fitting. It contains routines for both single-pixel 1D polarized spectra as well as 3D polarization cubes. RM-Tools is intended to serve as a toolkit for studies of polarized radio sources and measurements of their Faraday rotation. RM-Tools is the core package for the pipelines used for the POlarized Sky Survey of the Universe's Magnetism (POSSUM) and the polarization component of the Very Large Array Sky Survey (VLASS). The package is maintained by the Canadian Initiative for Radio Astronomy Data Analysis (CIRADA; cirada.org).

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.

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.

RJObject provides a general approach to trans-dimensional Bayesian inference problems, using trans-dimensional MCMC embedded within a Nested Sampling algorithm. This allows exploration of the posterior distribution and calculattion of the marginal likelihood (summed over N) even if the problem contains a phase transition or other difficult features such as multimodality.

RJ-plots uses a moments of inertia method to disentangle a 2D structure's elongation from its centrally over/under-density, thus providing a means for the automated and objective classification of such structures. It may be applied to any 2D pixelated image such as column density maps or moment zero maps of molecular lines. This method is a further development of J-plots (ascl:2009.007).

riptide implements the Fast Folding Algorithm (FFA) to identify periodic signals from time series data. In order to identify faint pulsars, the code provides access to a library of functions and classes for processing dedispersed radio signals. The FFA approaches the theoretical optimum for sensitivity to periodic signals regardless of pulse period and duty cycle.

RID (Relativistic Image Doubling in water Cherenkov detectors) uses Monte Carlo simulations to find the relative fraction of charged, relativistic particles entering a HAWC-like Water Cherenkov Detector that can cause a Relativistic Image Doubling (RID) effect visible to at least one of the internal detectors. The technique is available in C++ and Fortran; RID also includes python code for the horizontal incidence of the muon inside the tank.

RichValues transforms numeric values with uncertainties and upper/lower limits to create "rich values" that can be written in plain text documents in an easily readable format and used to propagate uncertainties automatically. Rich values can also be exported in the same formatting style as the import. The RichValues library uses a specific formatting style to represent the different kinds of rich values with plain text; it can also be used to create rich values within a script. Individual rich values can be used in, for example, tuples, lists, and dictionaries, and also in arrays and tables.

RICH (Racah Institute Computational Hydrodynamics) is a 2D hydrodynamic code based on Godunov's method. The code, largely based on AREPO (ascl:1909.010), acts on an unstructured moving mesh. It differs from AREPO in the interpolation and time advancement scheme as well as a novel parallelization scheme based on Voronoi tessellation. Though not universally true, in many cases a moving mesh gives better results than a static mesh: where matter moves one way and a sound wave is traveling in the other way (such that relative to the grid the wave is not moving), a static mesh gives better results than a moving mesh. RICH is designed in an object oriented, user friendly way that facilitates incorporation of new algorithms and physical processes.

The RHT (Rolling Hough Transform) measures linear intensity as a function of orientation in images. This machine vision algorithm works on any image-space (2D) data, and quantifies the presence of linear structure as a function of orientation. The RHT can be used to identify linear features in images, to quantify the orientation of structure in images, and to map image intensity from 2D x-y space to 3D x-y-orientation space. An option in the code allows the user to quantify intensity as a function of direction (modulo 2pi) rather than orientation (modulo pi). The RHT was first used to discover that filamentary structures in neutral hydrogen emission are aligned with the ambient magnetic field.

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.

RH 1.5D performs Zeeman multi-level non-local thermodynamical equilibrium calculations with partial frequency redistribution for an arbitrary amount of chemical species. Derived from the RH code and written in C, it calculates spectra from 3D, 2D or 1D atmospheric models on a column-by-column basis (or 1.5D). It includes optimization features to speed up or improve convergence, which are particularly useful in dynamic models of chromospheres. While one should be aware of its limitations, the calculation of spectra using the 1.5D or column-by-column is a good approximation in many cases, and generally allows for faster convergence and more flexible methods of improving convergence. RH 1.5D scales well to at least tens of thousands of CPU cores.

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).

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.

Rfits reads and writes FITS images, tables, and headers. Written in R, Rfits works with all types of compressed images, and both ASCII and binary tables. It uses CFITSIO (ascl:1010.001) for all low level FITS IO, so in general should be as fast as other CFITSIO-based software. For images, Rfits offers fully featured memory mapping and on-the-fly subsetting (by pixel and coordinate) and sparse pixel sampling, allowing for efficient inspection of very large (larger than memory) images.

Residual Feature Extraction Pipeline carries out feature extraction of residual substructure within the residual images produced by popular galaxy structural-fitting routines such as GALFIT (ascl:1104.010) and GIM2D (ascl:1004.001). It extracts faint low surface brightness features by isolating flux-wise and area-wise significant contiguous pixels regions by rigorous masking routine. The code accepts the image cubes (original image, model image, residual image) and generates several data products, such as an image with extracted features, a source extraction based segmentation map, and the background sky mask and the residual extraction mask. It uses a Monte Carlo approach-based area threshold above which the extracted features are identified. The pipeline also creates a catalog entry indicating the surface brightness and its error.

RFCDE provides an implementation of random forests designed for conditional density estimation. It computes a kernel density estimate of y with nearest neighbor weightings defined by the location of the evaluation point x relative to the leaves in the random forest.

rfast ingests tables of opacities and generates synthetic spectra of worlds and retrieves real or simulated spectral observations. It can add noise, perform inverse modeling, and plot results. The tool can be applied to simulated and real observations spanning reflected-light, thermal emission, and transit transmission. Retrieval parameters can be toggled and parameters can be retrieved in log or linear space and adopt a Gaussian or flat prior.

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.

RESOLVE is a Bayesian inference algorithm for image reconstruction in radio interferometry. It is optimized for extended and diffuse sources. Features include parameter-free Bayesian reconstruction of radio continuum data with a focus on extended and weak diffuse sources, reconstruction with uncertainty propagation dependent on measurement noise, and estimation of the spatial correlation structure of the radio astronomical source. RESOLVE provides full support for measurement sets and includes a simulation tool (if uv-coverage is provided).

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.

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.

reproject implements image reprojection (resampling) methods for astronomical images using various techniques via a uniform interface. Reprojection re-grids images from one world coordinate system to another (for example changing the pixel resolution, orientation, coordinate system). reproject works on celestial images by interpolation, as well as by finding the exact overlap between pixels on the celestial sphere. It can also reproject to/from HEALPIX projections by relying on the astropy-healpix package.

The RePrimAnd library supports numerical simulations of general relativistic magnetohydrodynamics. It provides methods for recovering primitive variables such as pressure and velocity from the variables evolved in quasi-conservative formulations. Further, it provides a general framework for handling matter equations of state (EOS). Python bindings are automatically built together with the library, provided a Python3 installation containing the pybind11 package is detected. RePrimAnd also provides an (experimental) thorn that builds the library within an Einstein Toolkit (ascl:1102.014) environment using the ExternalLibraries mechanism.

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.

reMASTERed reconstructs ensemble-averaged pseudo-$C_\ell$ to effectively exact precision, with significant improvements over traditional estimators for cases where the map and mask are correlated. The code can compute the results given an arbitrary map and mask; it can also compute the results in the ensemble average for certain types of threshold masks.

relxill self-consistently connects an angle-dependent reflection model constructed with XILLVER (http://www.srl.caltech.edu/personnel/javier/xillver/index.html) with the relativistic blurring code RELLINE (ascl:1505.021). It calculates the proper emission angle of the radiation at each point on the accretion disk and then takes the corresponding reflection spectrum into account.

relline calculates relativistic line profiles; it is compatible with the common X-ray data analysis software XSPEC (ascl:9910.005) and ISIS (ascl:1302.002). The two basic forms are an additive line model (RELLINE) and a convolution model to calculate relativistic smearing (RELCONV).

RelicFast computes the scale-dependent bias induced by relics of different masses, spins, and temperatures, through spherical collapse and the peak-background split. The code determines halo bias in under a second, making it possible to include this effect for different cosmologies, and light relics, at little computational cost.

RELAGN creates spectral models for the calculation of AGN SEDs, ranging from the Optical/UV (outer accretion disc) to the Hard X-ray (Innermost X-ray Corona). The code is available in two languages, Python and Fortran. The Fortran version is written to be used with the spectral fitting software XSPEC (ascl:9910.005), and is the preferred version for analyzing X-ray spectral data. The Python version provides more flexibility for modeling. Whereas the Fortran version produces only a spectrum, the Python implementation can extract the physical properties of the system (such as the physical mass accretion rate, disc size, and efficiency parameters) since these are all stored as attributes within the model. Both versions require a working installation of HEASOFT (ascl:1408.004).

The C code ReionYuga generates the Epoch of Reionization (EoR) neutral Hydrogen (HI) field (successively the redshifted 21-cm signal) within a cosmological simulation box using semi-numerical techniques. The code is based on excursion set formalism and uses a three parameter model. It is designed to work with PMN-body (ascl:2107.003) and FoF-Halo-finder (ascl:2107.004).

RegPT computes the power spectrum in flat wCDM class models based on the RegPT treatment when provided with either of transfer function or matter power spectrum. It then gives the multiple-redshift outputs for power spectrum, and optionally provides correlation function data. The Fortran code has two major options for power spectrum calculations; -fast, which quickly computes the power spectrum at two-loop level (typically a few seconds) using the pre-computed data set of PT kernels for fiducial cosmological models, and -direct, in which the code first applies the fast method, and then follows the regularized expression for power spectrum to directly evaluate the multi-dimensional integrals. The output results are the power spectrum of direct calculation and difference of the results between fast and direct method. The code also gives the data set of PT diagrams necessary for power spectrum calculations from which the power spectrum can be constructed.

RegiStax is software for alignment/stacking/processing of images; it was released over 10 years ago and continues to be developed and improved. The current version is RegiStax 6, which supports the following formats: AVI, SER, RFL (RegiStax Framelist), BMP, JPG, TIF, and FIT. This version has a shorter and simpler processing sequence than its predecessor, and optimizing isn't necessary anymore as a new image alignment method optimizes directly. The interface of RegiStax 6 has been simplified to look more uniform in appearance and functionality, and RegiStax 6 now uses Multi-core processing, allowing the user to have up to have multiple cores(recommended to use maximally 4) working simultaneous during alignment/stacking.

Reflex provides an easy and flexible way to reduce VLT/VLTI science data using the ESO pipelines. It allows graphically specifying the sequence in which the data reduction steps are executed, including conditional stops, loops and conditional branches. It eases inspection of the intermediate and final data products and allows repetition of selected processing steps to optimize the data reduction. The data organization necessary to reduce the data is built into the system and is fully automatic; advanced users can plug their own modules and steps into the data reduction sequence. Reflex supports the development of data reduction workflows based on the ESO Common Pipeline Library. Reflex is based on the concept of a scientific workflow, whereby the data reduction cascade is rendered graphically and data seamlessly flow from one processing step to the next. It is distributed with a number of complete test datasets so users can immediately start experimenting and familiarize themselves with the system.

redvsblue measures a precise redshift given a broad redshift prior. For each emission line or the full spectrum, the software runs a coarse chi2 scan as a function of redshift, using the input PCA+broadband Legendre polynomials, and finds three local minima, and does a finer chi2 scan in each minima. It then defines the global PCA redshift (ZPCA) from the best minimum of the three; ZPCA is a redshift estimator biased toward the computation of the PCA. The redshift of the line (ZLINE) is defined from the maximum of the best-fit model of the line. ZLINE is a redshift estimator un-biased toward the velocity of the line, but can be biased with respect to the cosmological redshift. The output is a FITS file, with one HDU per redshift type.