viscm is a Python tool for visualizing and designing colormaps using colorspacious and matplotlib.

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.

VisiOmatic is a web client for IIPImage (ascl:1408.009) and is used to visualize and navigate through large science images from remote locations. It requires STIFF (ascl:1110.006), is based on the Leaflet Javascript library, and works on both touch-based and mouse-based devices.

VisIt is a free interactive parallel visualization and graphical analysis tool for viewing scientific data on Unix and PC platforms. Users can quickly generate visualizations from their data, animate them through time, manipulate them, and save the resulting images for presentations. VisIt contains a rich set of visualization features so that you can view your data in a variety of ways. It can be used to visualize scalar and vector fields defined on two- and three-dimensional (2D and 3D) structured and unstructured meshes. VisIt was designed to handle very large data set sizes in the terascale range and yet can also handle small data sets in the kilobyte range. See the table below for more details about the tool’s features.

VisIt was developed by the Department of Energy (DOE) Advanced Simulation and Computing Initiative (ASCI) to visualize and analyze the results of terascale simulations. It was developed as a framework for adding custom capabilities and rapidly deploying new visualization technologies. Although the primary driving force behind the development of VisIt was for visualizing terascale data, it is also well suited for visualizing data from typical simulations on desktop systems.

VisIVO is an integrated suite of tools and services specifically designed for the Virtual Observatory. This suite constitutes a software framework for effective visual discovery in currently available (and next-generation) very large-scale astrophysical datasets. VisIVO consists of VisiVO Desktop - a stand alone application for interactive visualization on standard PCs, VisIVO Server - a grid-enabled platform for high performance visualization and VisIVO Web - a custom designed web portal supporting services based on the VisIVO Server functionality. The main characteristic of VisIVO is support for high-performance, multidimensional visualization of very large-scale astrophysical datasets. Users can obtain meaningful visualizations rapidly while preserving full and intuitive control of the relevant visualization parameters. This paper focuses on newly developed integrated tools in VisIVO Server allowing intuitive visual discovery with 3D views being created from data tables. VisIVO Server can be installed easily on any web server with a database repository. We discuss briefly aspects of our implementation of VisiVO Server on a computational grid and also outline the functionality of the services offered by VisIVO Web. Finally we conclude with a summary of our work and pointers to future developments.

Vissage (VISualisation Software for Astronomical Gigantic data cubEs) is a FITS browser primarily targeting FITS data cubes obtained from ALMA. Vissage offers basic functionality for viewing three-dimensional data cubes, integrated intensity map, flipbook, channel map, and P-V diagram. It has several color sets and color scales available, offers panning and zooming, and can connect with the ALMA WebQL system and the JVO Subaru Image Cutout Service.

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.

vKompth fits the energy-dependent rms-amplitude and phase-lag spectra of low-frequency quasi-periodic oscillations in low mass black-hole X-ray binaries using a variable Comptonization model. The accretion disc is modeled as a multi-temperature blackbody source emitting soft photons which are then Compton up-scattered in a spherical corona, including feedback of Comptonized photons that return to the disc.

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.

The high-contrast imager SPHERE at the Very Large Telescope combines extreme adaptive optics and coronagraphy to directly image exoplanets in the near-infrared. The vlt-sphere package enables easy reduction of the data coming from IRDIS and IFS, the two near-infrared subsystems of SPHERE. The package relies on the official ESO pipeline (ascl:1402.010), which must be installed separately.

VOBOZ (VOronoi BOund Zones) is an algorithm to find haloes in an N-body dark matter simulation which has little dependence on free parameters.

ZOBOV (ZOnes Bordering On Voidness) is an algorithm that finds density depressions in a set of points without any free parameters or assumptions about shape. It uses the Voronoi tessellation to estimate densities to find both voids and subvoids. It also measures probabilities that each void or subvoid arises from Poisson fluctuations.

voevent-parse, written in Python, parses, manipulates, and generates VOEvent XML packets; it is built atop lxml.objectify. Details of transients detected by many projects, including Fermi, Swift, and the Catalina Sky Survey, are currently made available as VOEvents, which is also the standard alert format by future facilities such as LSST and SKA. However, working with XML and adhering to the sometimes lengthy VOEvent schema can be a tricky process. voevent-parse provides convenience routines for common tasks, while allowing the user to utilise the full power of the lxml library when required. An earlier version of voevent-parse was part of the pysovo (ascl:1411.002) library.

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.

The VOLK2 (VLBI Observation for transient Localization Keen Searcher) pipeline conducts single pulse searches and localization in regular VLBI observations as well as single pulse detections from known sources in dedicated observations. In VOLKS2, the search and localization are two independent steps. The search step takes the idea of geodetic VLBI post processing, which fully utilizes the cross spectrum fringe phase information to maximize the signal power. Compared with auto spectrum based method, it is able to extract single pulses from highly RFI contaminated data. The localization uses the geodetic VLBI solving methods, which derives the single pulse location by solving a set of linear equations given the relation between the residual delay and the offset to a priori position.

VOMegaPlot, a Java based tool, has been developed for visualizing astronomical data that is available in VOTable format. It has been specifically optimized for handling large number of points (in the range of millions). It has the same look and feel as VOPlot (ascl:1309.006) and both these tools have certain common functionality.

VOPlot is a tool for visualizing astronomical data. It was developed in Java and acts on data available in VOTABLE, ASCII and FITS formats. VOPlot is available as a stand alone version, which is to be installed on the user's machine, or as a web-based version fully integrated with the VizieR database.

VorBin (Voronoi binning method) bins two-dimensional data to a constant signal-to-noise ratio per bin. It optimally solves the problem of preserving the maximum spatial resolution of general two-dimensional data, given a constraint on the minimum signal-to-noise ratio. The method is available in both IDL and Python.

Astrophysical turbulent flows display an intrinsically multi-scale nature, making their numerical simulation and the subsequent analyses of simulated data a complex problem. In particular, two fundamental steps in the study of turbulent velocity fields are the Helmholtz-Hodge decomposition (compressive+solenoidal; HHD) and the Reynolds decomposition (bulk+turbulent; RD). These problems are relatively simple to perform numerically for uniformly-sampled data, such as the one emerging from Eulerian, fix-grid simulations; but their computation is remarkably more complex in the case of non-uniformly sampled data, such as the one stemming from particle-based or meshless simulations. In this paper, we describe, implement and test vortex-p, a publicly available tool evolved from the vortex code, to perform both these decompositions upon the velocity fields of particle-based simulations, either from smoothed particle hydrodynamics (SPH), moving-mesh or meshless codes. The algorithm relies on the creation of an ad-hoc adaptive mesh refinement (AMR) set of grids, on which the input velocity field is represented. HHD is then addressed by means of elliptic solvers, while for the RD we adapt an iterative, multi-scale filter. We perform a series of idealised tests to assess the accuracy, convergence and scaling of the code. Finally, we present some applications of the code to various SPH and meshless finite-mass (MFM) simulations of galaxy clusters performed with OpenGadget3, with different resolutions and physics, to showcase the capabilities of the code.

vortex performs a Helmholtz-Hodge decomposition on vector fields defined on AMR grids, decomposing a vector field in its solenoidal (divergence-less) and compressive (curl-less) parts. It works natively on vector fields defined on Adaptive Mesh Refinement (AMR) grids, so that it can perform the decomposition over large dynamical ranges; it is also applicable to particle-based simulations. As vortex is devised primarily to investigate the properties of the turbulent velocity field in the Intracluster Medium (ICM), it also includes routines for multi-scale filtering the velocity field.

VOSpec is a multi-wavelength spectral analysis tool with access to spectra, theoretical models and atomic and molecular line databases registered in the VO. The standard tools of VOSpec include line and continuum fitting, redshift and reddening correction, spectral arithmetic and convolution between spectra, equivalent width and flux calculations, and a best fitting algorithm for fitting selected SEDs to a TSAP service. VOSpec offers several display modes (tree vs table) and organising functionalities according to the available metadata for each service, including distance from the observation position.

VOStat allows astronomers to use both simple and sophisticated statistical routines on large datasets. This tool uses the large public-domain statistical computing package R. Datasets can be uploaded in either ASCII or VOTABLE (preferred) format. The statistical computations are performed by the VOStat and results are returned to the user.

The VPFIT program fits multiple Voigt profiles (convolved with the instrument profiles) to spectroscopic data that is in FITS or an ASCII file. It requires CFITSIO (ascl:1010.001) and PGPLOT (ascl:1103.002); the tarball includes RDGEN (ascl:1408.017), which can be used with VPFIT to set up the fits, fit the profiles, and examine the result in interactive mode for setting up initial guesses; vpguess (ascl:1408.016) can also be used to set up an initial file.

vpguess facilitates the fitting of multiple Voigt profiles to spectroscopic data. It is a graphical interface to VPFIT (ascl:1408.015). Originally meant to simplify the process of setting up first guesses for a subsequent fit with VPFIT, it has developed into a full interface to VPFIT. It may also be used independently of VPFIT for displaying data, playing around with data and models, "chi-by-eye" fits, displaying the result of a proper fit, pretty plots, etc. vpguess is written in C, and the graphics are based on PGPLOT (ascl:1103.002).

VPLanet (Virtual Planetary Laboratory) 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.

VStar is a multi-platform, easy-to-use variable star data visualization and analysis tool. Data for a star can be read from the AAVSO (American Association of Variable Star Observers) database or from CSV and TSV files. VStar displays light curves and phase plots, can produce a mean curve, and analyzes time-frequency with Weighted Wavelet Z-Transform. It offers tools for period analysis, filtering, and other functions.

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.

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.

WALDO (Waveform AnomaLy DetectOr) flags possible anomalous Gravitational Waves from Numerical Relativity catalogs using deep learning. It uses a U-Net architecture to learn the waveform features of a dataset. After computing the mismatch between those waveforms and the neural predictions, WALDO isolates high mismatch evaluations for anomaly search.

WaldoInSky finds anomalous astronomical light curves and their analogs. The package contains four methods: an adaptation of the Unsupervised Random Forest for anomaly detection in light curves that operates on the light curve points and their power spectra; two manifold-learning methods (the t-SNE and UMAP) that operate on the DMDT maps (image representations of the light curves), and that can be used to find analog light curves in the low-dimensional representation; and an Isolation Forest method for evaluating approaches of light curve pre-processing, before they are passed to the anomaly detectors. WaldoInSky also contain code for random sparsification of light curves.

walter calculates the number density of stars detected in a given observation aiming to resolve a stellar population. The code also calculates the exposure time needed to reach certain population features, such as the horizontal branch, and provides an estimate of the crowding limit. walter was written with the expectation that such calculations will be very useful for planning surveys with the Nancy Grace Roman Space Telescope (RST, formerly WFIRST).

Warpfield (Winds And Radiation Pressure: Feedback Induced Expansion, colLapse and Dissolution) calculates shell dynamics and shell structure simultaneously for isolated massive clouds (≥10⁵ 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.

WarpX is an advanced electromagnetic & electrostatic Particle-In-Cell code. It supports many features including Perfectly-Matched Layers (PML), mesh refinement, and the boosted-frame technique. A highly-parallel and highly-optimized code, WarpX can run on GPUs and multi-core CPUs, includes load balancing capabilities, and scales to the largest supercomputers.

Wavetrack recognizes and tracks CME shock waves, filaments, and other solar objects. The code creates base images by averaging а series of images a few minutes prior to the start of the eruption and constructs base difference images by subtracting base images from the current raw image of the sequence. This enhances the change in intensity caused by coronal bright fronts, omits static details, and reduces noise. Wavetrack then chooses an appropriate intensity interval and decomposes the base difference or running difference image with an A-Trous wavelet transform, where each wavelet coefficient is obtained by convolving the image array with a corresponding iteration of the wavelet kernel. When the maximum value of the wavelet coefficients for a connected set of pixels satisfies certain conditions, this region is considered as a structure on the respective wavelet coefficient. Separate stand-alone object masks are obtained with a clustering algorithm and objects are renumbered according to the number of the quadrant they belong at each iteration.

The graphical user interface Wavelength Calibrator facilitates wavelength calibration. Although developed for astronomical data reduction, it can also be used in any place where wavelength calibration is needed.

WCSLIB is a C library, supplied with a full set of Fortran wrappers, that implements the "World Coordinate System" (WCS) standard in FITS (Flexible Image Transport System). It also includes a PGPLOT-based routine, PGSBOX, for drawing general curvilinear coordinate graticules and a number of utility programs.

WCSTools is a package of programs and a library of utility subroutines for setting and using the world coordinate systems (WCS) in the headers of the most common astronomical image formats, FITS and IRAF .imh, to relate image pixels to sky coordinates. In addition to dealing with image WCS information, WCSTools has extensive catalog search, image header manipulation, and coordinate and time conversion tasks. This software is all written in very portable C, so it should compile and run on any computer with a C compiler.

Wilson-Devinney binary star modeling code (WD) is a complete package for modeling binary stars and their eclipes and consists of two main modules. The LC module generates light and radial velocity curves, spectral line profiles, images, conjunction times, and timing residuals; the DC module handles differential corrections, performing parameter adjustment of light curves, velocity curves, and eclipse timings by the Least Squares criterion. WD handles eccentric orbits and asynchronous rotation, and can compute velocity curves (with proximity and eclipse effects). It offers options for detailed reflection and nonlinear (logarithmic law) limb darkening, adjustment of spot parameters, an optional provision for spots to drift over the surface, and can follow light curve development over large numbers of orbits. Absolute flux solution allow Direct Distance Estimation (DDE) and there are improved solutions for ellipsoidal variables and for eclipsing binaries (EBs) with very shallow eclipses. Absolute flux solutions also can estimate temperatures of both EB components under suitable circumstances.

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.

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.

WDMWaveletTransforms implements the fast forward and inverse WDM wavelet transforms in Python from both the time and frequency domains. The frequency domain transforms are inherently faster and more accurate. The wavelet domain->frequency domain and frequency domain->wavelet domain transforms are nearly exact numerical inverses of each other for a variety of inputs tested, including Gaussian random noise. WDMWaveletTransforms has both command line and Python interfaces.

WDPhotTools generates color-color diagrams and color-magnitude diagrams in various photometric systems, plots cooling profiles from different models, and computes theoretical white dwarf luminosity functions based on the built-in or supplied models of the (1) initial mass function, (2) total stellar evolution lifetime, (3) initial-final mass relation, and (4) white dwarf cooling time. The software has three main parts: the formatters that handle the output models from various works in the format as they are downloaded; the photometric fitter that solves for the WD parameters based on the photometry, with or without distance and reddening; and the generator of the white dwarf luminosity function in bolometric magnitudes or in any of the photometric systems available from the atmosphere model.

wdtools characterizes the atmospheric parameters of white dwarfs using spectroscopic data. The flagship class is the generative fitting pipeline (GFP), which fits ab initio theoretical models to observed spectra in a Bayesian framework using high-speed neural networks to interpolate synthetic spectra.

wdwarfdate derives the Bayesian total age of a white dwarf from an effective temperature and a surface gravity. It runs a chain of models assuming single star evolution and estimates the following parameters and their uncertainties: total age of the object, mass and cooling age of the white dwarf, and mass and lifetime of the progenitor star.

WeakLensingDeblending provides weak lensing fast simulations and analysis for the LSST Dark Energy Science Collaboration. It is used to study the effects of overlapping sources on shear estimation, photometric redshift algorithms, and deblending algorithms. Users can run their own simulations (of LSST and other surveys) or download the galaxy catalog and simulation outputs to use with their own code.

WeakLensingQML implements the Quadratic Maximum Likelihood (QML) estimator and applies it to simulated cosmic shear data and compares the results to a Pseudo-Cl implementation. The package computes and saves relevant data files for later processes, such as the fiduciary cosmic shear power spectrum used in the analysis, the sky mask, and computing an analytic version of the QML's covariance matrix. The core of the package implements a conjugate-gradient approach for the quadratic estimator, and is parallelized for maximum performance. The code relies on the Eigen linear algebra package and the HealPix spherical harmonic transform library. A post-processing script analyzes the results and compares the QML's estimates with those from the Pseudo-Cl estimator; it then produces an array of plots highlighting the results.

WebbPSF provides a PSF simulation tool in a flexible and easy-to-use software package implemented in Python. Functionality includes support for spectroscopic modes of JWST NIRISS, MIRI, and NIRSpec, including modeling of slit losses and diffractive line spread functions.

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.

This code, which requires HEALPix 2.x (ascl:1107.018), allows you to generate power spectrum estimators from WMAP 5-year maps and generate hybrid cross- and auto- power spectrum and covariance from general foreground-cleaned maps. In addition, it allows you to simulate combined maps or combinations of maps for individual detectors and do MPI spherical transforms of arrays of maps, calculate coupling matrices etc. The code includes all of LensPix (ascl:1102.025), the MPI framework used for doing spherical transforms (based on HealPix).

WeightWatcher is a program that combines weight-maps, flag-maps and polygon data in order to produce control maps which can directly be used in astronomical image-processing packages like Drizzle, SWarp or SExtractor.

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.