Results 1901-1950 of 2075 (2041 ASCL, 34 submitted)
TomograPy is an open-source software freely available on the Python Package Index that can perform fast tomographic inversions that scale linearly with the number of measurements, linearly with the length of the reconstruction cube (and not the number of voxels) and linearly with the number of cores and can use data from different sources and with a variety of physical models. For performance, TomograPy uses a parallelized-projection algorithm. It relies on the World Coordinate System standard to manage various data sources. A variety of inversion algorithms are provided to perform the tomographic-map estimation. A test suite is provided along with the code to ensure software quality. Since it makes use of the Siddon algorithm it is restricted to rectangular parallelepiped voxels but the spherical geometry of the corona can be handled through proper use of priors.
TOPCAT is an interactive graphical viewer and editor for tabular data. Its aim is to provide most of the facilities that astronomers need for analysis and manipulation of source catalogues and other tables, though it can be used for non-astronomical data as well. It understands a number of different astronomically important formats (including FITS and VOTable) and more formats can be added.
It offers a variety of ways to view and analyse tables, including a browser for the cell data themselves, viewers for information about table and column metadata, and facilities for 1-, 2-, 3- and higher-dimensional visualisation, calculating statistics and joining tables using flexible matching algorithms. Using a powerful and extensible Java-based expression language new columns can be defined and row subsets selected for separate analysis. Table data and metadata can be edited and the resulting modified table can be written out in a wide range of output formats.
It is a stand-alone application which works quite happily with no network connection. However, because it uses Virtual Observatory (VO) standards, it can cooperate smoothly with other tools in the VO world and beyond, such as VODesktop, Aladin and ds9. Between 2006 and 2009 TOPCAT was developed within the AstroGrid project, and is offered as part of a standard suite of applications on the AstroGrid web site, where you can find information on several other VO tools.
The program is written in pure Java and available under the GNU General Public Licence. It has been developed in the UK within the Starlink and AstroGrid projects, and under PPARC and STFC grants. Its underlying table processing facilities are provided by STIL.
TORUS is a flexible radiation transfer and radiation-hydrodynamics code. The code has a basic infrastructure that includes the AMR mesh scheme that is used by several physics modules including atomic line transfer in a moving medium, molecular line transfer, photoionization, radiation hydrodynamics and radiative equilibrium. TORUS is useful for a variety of problems, including magnetospheric accretion onto T Tauri stars, spiral nebulae around Wolf-Rayet stars, discs around Herbig AeBe stars, structured winds of O supergiants and Raman-scattered line formation in symbiotic binaries, and dust emission and molecular line formation in star forming clusters. The code is written in Fortran 2003 and is compiled using a standard Gnu makefile. The code is parallelized using both MPI and OMP, and can use these parallel sections either separately or in a hybrid mode.
Toyz is a python web framework that allows scientists to interact with large images and data sets stored on a remote server. A web application is run on the server containing the data and clients are run from web browsers on the user's computer. Toyz displays large FITS images also also renders any image format supported by Pillow (a fork of the Python Imaging Library), contains a GUI to interact with linked plots, and offers a customizable framework that allows students and researchers to create their own work spaces inside a Toyz environment. Astro-Toyz extends the features of the Toyz image viewer, allowing users to view world coordinates and align images based on their WCS.
TP2VIS creates visibilities from a single dish cube; the TP visibilities can be combined with the interferometric visibilities in a joint deconvolution using, for example, CASA's tclean() method. TP2VIS requires CASA 5.4 (ascl:1107.013) or above.
TPI computes the gravitational dynamics of particles orbiting a supermassive black hole (SBH). A distinction is made to two types of particles: test particles and field particles. Field particles are assumed to move in quasi-static Keplerian orbits around the SBH that precess due to the enclosed mass (Newtonian 'mass precession') and relativistic effects. Otherwise, field-particle-field-particle interactions are neglected. Test particles are integrated in the time-dependent potential of the field particles and the SBH. Relativistic effects are included in the equations of motion (including the effects of SBH spin), and test-particle-test-particle interactions are neglected.
Visibilities from radio interferometers have not traditionally been used to study the fast transient sky. Millisecond transients (e.g., fast radio bursts) and periodic sources (e.g., pulsars) have been studied with single-dish radio telescopes and a software stack developed over the past few decades. tpipe is an initial attempt to develop the fast transient algorithms for visibility data. Functions exist for analysis of visibilties, such as reading data, flagging data, applying interferometric gain calibration, and imaging. These functions are given equal footing as time-domain techniques like filters and dedispersion.
tpipe has been largely superseded by rtpipe (ascl:1706.002).
TPM carries out collisionless (dark matter) cosmological N-body simulations, evolving a system of N particles as they move under their mutual gravitational interaction. It combines aspects of both Tree and Particle-Mesh algorithms. After the global PM forces are calculated, spatially distinct regions above a given density contrast are located; the tree code calculates the gravitational interactions inside these denser objects at higher spatial and temporal resolution. The code is parallel and uses MPI for message passing.
TPZ, a parallel code written in python, produces robust and accurate photometric redshift PDFs by using prediction tree and random forests. The code also produces ancillary information about the sample used, such as prior unbiased errors estimations (giving an estimation of performance) and a ranking of importance of variables as well as a map of performance indicating where extra training data is needed to improve overall performance. It is designed to be easy to use and a tutorial is available.
TRADES (TRAnsits and Dynamics of Exoplanetary Systems) simultaneously fits observed radial velocities and transit times data to determine the orbital parameters of exoplanetary systems from observational data. It uses a dynamical simulator for N-body systems that also fits the available data during the orbital integration and determines the best combination of the orbital parameters using grid search, χ2 minimization, genetic algorithms, particle swarm optimization, and bootstrap analysis.
The Sloan Digital Sky Survey (SDSS) produces large amounts of data daily. transfer, written in Python, provides the effective automation needed for daily data transfer operations and management and operates essentially free of human intervention. This package has been tested and used successfully for several years.
We present an IDL graphical user interface-driven software package designed for the analysis of extrasolar planet transit light curves. The Transit Analysis Package (TAP) software uses Markov Chain Monte Carlo (MCMC) techniques to fit light curves using the analytic model of Mandel and Agol (2002). The package incorporates a wavelet based likelihood function developed by Carter and Winn (2009) which allows the MCMC to assess parameter uncertainties more robustly than classic chi-squared methods by parameterizing uncorrelated "white" and correlated "red" noise. The software is able to simultaneously analyze multiple transits observed in different conditions (instrument, filter, weather, etc). The graphical interface allows for the simple execution and interpretation of Bayesian MCMC analysis tailored to a user's specific data set and has been thoroughly tested on ground-based and Kepler photometry. AutoKep provides a similar GUI for the preparation of Kepler MAST archive data for analysis by TAP or any other analysis software. This paper describes the software release and provides instructions for its use.
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.
Transit light curves for stellar continua have only one minimum and a "U" shape. By contrast, transit curves for optically thin chromospheric emission lines can have a "W" shape because of stellar limb-brightening. We calculate light curves for an optically thin shell of emission and fit these models to time-resolved observations of Si IV absorption by the planet HD209458b. We find that the best fit Si IV absorption model has R_p,SIV/R_*= 0.34+0.07-0.12, similar to the Roche lobe of the planet. While the large radius is only at the limit of statistical significance, we develop formulae applicable to transits of all optically thin chromospheric emission lines.
Transit calculates the transmission or emission spectrum of a planetary atmosphere with application to extrasolar-planet transit and eclipse observations, respectively. It computes the spectra by solving the one-dimensional line-by-line radiative-transfer equation for an atmospheric model.
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.
The TraP is a pipeline for detecting and responding to transient and variable sources in a stream of astronomical images. Images are initially processed using a pure-Python source-extraction package, PySE (ascl:1805.026), which is bundled with the TraP. Source positions and fluxes are then loaded into a SQL database for association and variability detection. The database structure allows for estimation of past upper limits on newly detected sources, and for forced fitting of previously detected sources which have since dropped below the blind-extraction threshold. Developed with LOFAR data in mind, the TraP has been used with data from other radio observatories.
TreeCorr efficiently computes two-point correlation functions. It can compute correlations of regular number counts, weak lensing shears, or scalar quantities such as convergence or CMB temperature fluctuations. Two-point correlations may be auto-correlations or cross-correlations, including any combination of shear, kappa, and counts. Two-point functions can be done with correct curved-sky calculation using RA, Dec coordinates, on a Euclidean tangent plane, or in 3D using RA, Dec and a distance. The front end is written in Python, which can be used as a Python module or as a standalone executable using configuration files; the actual computation of the correlation functions is done in C++ using ball trees (similar to kd trees), making the calculation extremely efficient, and when available, OpenMP is used to run in parallel on multi-core machines.
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.
Trilogy automatically scales and combines FITS images to produce color or grayscale images using Python scripts. The user assigns images to each color channel (RGB) or a single image to grayscale luminosity. Trilogy determines the intensity scaling automatically and independently in each channel to display faint features without saturating bright features. Each channel's scaling is determined based on a sample of the image (or summed images) and two input parameters. One parameter sets the output luminosity of "the noise," currently determined as 1-sigma above the sigma-clipped mean. The other parameter sets what fraction of the data (if any) in the sample region should be allowed to saturate. Default values for these parameters (0.15% and 0.001%, respectively) work well, but the user is able to adjust them. The scaling is accomplished using the logarithmic function y = a log(kx + 1) clipped between 0 and 1, where a and k are constants determined based on the data and desired scaling parameters as described above.
TRIP is an interactive computer algebra system that is devoted to perturbation series computations, and specially adapted to celestial mechanics. Its development started in 1988, as an upgrade of the special purpose FORTRAN routines elaborated by J. Laskar for the demonstration of the chaotic behavior of the Solar System. TRIP is a mature and efficient tool for handling multivariate generalized power series, and embeds two kernels, a symbolic and a numerical kernel. This numerical kernel communicates with Gnuplot or Grace to plot the graphics and allows one to plot the numerical evaluation of symbolic objects.
Written in IDL, TRIPP performs CCD time series reduction and analysis. It provides an on-line check of the incoming frames, performs relative aperture photometry and provides a set of time series tools, such as calculation of periodograms including false alarm probability determination, epoc folding, sinus fitting, and light curve simulations.
TRIPPy (TRailed Image Photometry in Python) uses a pill-shaped aperture, a rectangle described by three parameters (trail length, angle, and radius) to improve photometry of moving sources over that done with circular apertures. It can generate accurate model and trailed point-spread functions from stationary background sources in sidereally tracked images. Appropriate aperture correction provides accurate, unbiased flux measurement. TRIPPy requires numpy, scipy, matplotlib, Astropy (ascl:1304.002), and stsci.numdisplay; emcee (ascl:1303.002) and SExtractor (ascl:1010.064) are optional.
TRISTAN-MP is a fully relativistic Particle-In-Cell (PIC) code for plasma physics computations and self-consistently solves the full set of Maxwell’s equations, along with the relativistic equations of motion for the charged particles. Fields are discretized on a finite 3D or 2D mesh, the computational grid; the code then uses time-centered and space-centered finite difference schemes to advance the equations in time via the Lorentz force equation, and to calculate spatial derivatives, so that the algorithm is second order accurate in space and time. The charges and currents derived from the particles' velocities and positions are then used as source terms to re-calculate the electromagnetic fields. TRISTAN-MP is based on the original TRISTAN code by O. Buneman (1999).
TRUVOT decontaminates Swift UVOT grism spectra for transient objects. The technique makes use of template images in a process similar to image subtraction.
TSP is an astronomical data reduction package that handles time series data and polarimetric data from a variety of different instruments, and is distributed as part of the Starlink software collection (ascl:1110.012).
The Tsyganenko models are semi-empirical best-fit representations for the magnetic field, based on a large number of satellite observations (IMP, HEOS, ISEE, POLAR, Geotail, GOES, etc). The models include the contributions from major external magnetospheric sources: ring current, magnetotail current system, magnetopause currents, and large-scale system of field-aligned currents.
TTVFast efficiently calculates transit times for n-planet systems and the corresponding radial velocities. The code uses a symplectic integrator with a Keplerian interpolator for the calculation of transit times (Nesvorny et al. 2013); it is available in both C and Fortran.
TTVFaster implements analytic formulae for transit time variations (TTVs) that are accurate to first order in the planet–star mass ratios and in the orbital eccentricities; the implementations are available in several languages, including IDL, Julia, Python and C. These formulae compare well with more computationally expensive N-body integrations in the low-eccentricity, low mass-ratio regime when applied to simulated and to actual multi-transiting Kepler planet systems.
turboGL is a fast Mathematica code based on a stochastic approach to cumulative weak lensing. It can easily compute the lensing PDF relative to arbitrary halo mass distributions, selection biases, number of observations, halo profiles and evolutions, making it a useful tool to study how lensing depends on cosmological parameters and impact on observations.
TurboSETI analyzes filterbank data (frequency vs. time) for narrow band drifting signals; its main purpose is to search for signals of extraterrestrial origin. TurboSETI can search the data for hundreds of drift rates (in Hz/sec) and handles either .fil or .h5 file formats. It has several dependencies, including Blimpy (ascl:1906.002) and Astropy (ascl:1304.002).
Turbospectrum is a 1D LTE spectrum synthesis code which covers 600 molecules, is fast with many lines, and uses the treatment of line broadening described by Barklem & O’Mara (1998).
TurbuStat implements a variety of turbulence-based statistics described in the astronomical literature and defines distance metrics for each statistic to quantitatively compare spectral-line data cubes, as well as column density, integrated intensity, or other moment maps. The software can simulate observations of fractional Brownian Motion fields, including 2-D images and optically thin H I data cubes. TurbuStat also offers multicore fast-Fourier-transform support and provides a segmented linear model for fitting lines with a break point.
TVD solves the magnetohydrodynamic (MHD) equations by updating the fluid variables along each direction using the flux-conservative, second-order, total variation diminishing (TVD), upwind scheme of Jin & Xin. The magnetic field is updated separately in two-dimensional advection-constraint steps. The electromotive force (EMF) is computed in the advection step using the TVD scheme, and this same EMF is used immediately in the constraint step in order to preserve ∇˙B=0 without the need to store intermediate fluxes. The code is extended to three dimensions using operator splitting, and Runge-Kutta is used to get second-order accuracy in time. TVD offers high-resolution per grid cell, second-order accuracy in space and time, and enforcement of the ∇˙B=0 constraint to machine precision. Written in Fortran, It has no memory overhead and is fast. It is also available in a fully scalable message-passing parallel MPI implementation.
TWO-POP-PY runs a two-population dust evolution model that follows the upper end of the dust size distribution and the evolution of the dust surface density profile and treats dust surface density, maximum particle size, small and large grain velocity, and fragmentation. It derives profiles that describe the dust-to-gas ratios and the dust surface density profiles well in protoplanetary disks, in addition to the radial flux by solid material rain out.
TWODSPEC offers programs for the reduction and analysis of long-slit and optical fiber array spectra, implemented as extensions to the FIGARO package (ascl:1203.013). The software are currently distributed as part of the Starlink software collection (ascl:1110.012). These programs are designed to do as much as possible for the user, to assist quick reduction and analysis of data; for example, LONGSLIT can fit multiple Gaussians to line profiles in batch and decides how many components to fit.
TwoDSSM solves the equations of self-gravitating hydrodynamics in the shearing sheet, with cooling. TwoDSSM is configured to use a simple, exponential cooling model, although it contains code for a more complicated (and perhaps more realistic) cooling model based on a one-zone vertical model. The complicated cooling model can be switched on using a flag.
TYCHO is a general, one dimensional (spherically symmetric) stellar evolution code written in structured Fortran 77; it is designed for hydrostatic and hydrodynamic stages including mass loss, accretion, pulsations and explosions. Mixing and convection algorithms are based on 3D time-dependent simulations. It offers extensive on-line graphics using Tim Pearson's PGPLOT with X-windows and runs effectively on Linux and Mac OS X laptop and desktop computers.
NOTE: This code is no longer being supported.
UCL_CHEM is a time and depth dependent gas-grain chemical model that can be used to estimate the fractional abundances (with respect to hydrogen) of gas and surface species in every environment where molecules are present. The model includes both gas and surface reactions. The code starts from the most diffuse state where all the gas is in atomic form and evolve sthe gas to its final density. Depending on the temperature, atoms and molecules from the gas freeze on to the grains and they hydrogenate where possible. The advantage of this approach is that the ice composition is not assumed but it is derived by a time-dependent computation of the chemical evolution of the gas-dust interaction process. The code is very modular, has been used to model a variety of regions and can be coupled with the UCL_PDR and SMMOL codes.
UCL_PDR is a time dependent photon-dissociation regions model that calculates self consistently the thermal balance. It can be used with gas phase only species as well as with surface species. It is very modular, has the possibility of accounting for density and pressure gradients and can be coupled with UCL_CHEM as well as with SMMOL. It has been used to model small scale (e.g. knots in proto-planetary nebulae) to large scale regions (high redshift galaxies).
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.
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:
ULySS (University of Lyon Spectroscopic Analysis Software) is an open-source software package written in the GDL/IDL language to analyze astronomical data. ULySS fits a spectrum with a linear combination of non-linear components convolved with a line-of-sight velocity distribution (LOSVD) and multiplied by a polynomial continuum. ULySS is used to study stellar populations of galaxies and star clusters and atmospheric parameters of stars.
Astrochemistry database of chemical species.
UniDAM obtains a homogenized set of stellar parameters from spectrophotometric data of different surveys. Parallax and extinction data can be incorporated into the isochrone fitting method used in UniDAM to reduce distance and age estimate uncertainties for TGAS stars for distances up to 1 kpc and decrease distance Gaia end-of-mission parallax uncertainties by about a factor of 20 and age uncertainties by a factor of two for stars up to 10 kpc away from the Sun.
The equation of state (EOS) of dense matter is a crucial input for the neutron-star structure calculations. This Fortran code can obtain a "unified EOS" in the many-body calculations based on a single effective nuclear Hamiltonian, and is valid in all regions of the neutron star interior. For unified EOSs, the transitions between the outer crust and the inner crust and between the inner crust and the core are obtained as a result of many-body calculations.
UniPOPS, a suite of programs and utilities developed at the National Radio Astronomy Observatory (NRAO), reduced data from the observatory's single-dish telescopes: the Tucson 12-m, the Green Bank 140-ft, and archived data from the Green Bank 300-ft. The primary reduction programs, 'line' (for spectral-line reduction) and 'condar' (for continuum reduction), used the People-Oriented Parsing Service (POPS) as the command line interpreter. UniPOPS unified previous analysis packages and provided new capabilities; development of UniPOPS continued within the NRAO until 2004 when the 12-m was turned over to the Arizona Radio Observatory (ARO). The submitted code is version 3.5 from 2004, the last supported by the NRAO.
Univiewer is a visualisation program for HEALPix maps. It is written in C++ and uses OpenGL and the wxWidgets library for cross-platform portability. Using it you can:
In the 3D view, a HEALPix map is projected onto a ECP pixelation to create a texture which is wrapped around the sphere. In calculating the power spectrum, the spherical harmonic transforms are computed using the same ECP pixelation. This inevitably leads to some discrepancies at small scales due to repixelation effects, but they are reasonably small.
The unwise_psf Python module renders point spread function (PSF) models appropriate for use in modeling of unWISE coadd images. unwise_psf translates highly detailed single-exposure WISE PSF models in detector coordinates to the corresponding pixelized PSF models in coadd space, accounting for subtleties including the WISE scan direction and its considerable variation near the ecliptic poles. Applications of the unwise_psf module include performing forced photometry on unWISE coadds, constructing WISE-selected source catalogs based on unWISE coadds and masking unWISE coadd regions contaminated by bright stars.
UPMASK, written in R, performs membership assignment in stellar clusters. It uses photometry and spatial positions, but can take into account other types of data. UPMASK takes into account arbitrary error models; the code is unsupervised, data-driven, physical-model-free and relies on as few assumptions as possible. The approach followed for membership assessment is based on an iterative process, principal component analysis, a clustering algorithm and a kernel density estimation.
Would you like to view a random code?