Results 1201-1250 of 2160 (2122 ASCL, 38 submitted)
The Fermi-LAT Background Estimator (BKGE) is a publicly available open-source tool that can estimate the expected background of the Fermi-LAT for any observational conguration and duration. It produces results in the form of text files, ROOT files, gtlike source-model files (for LAT maximum likelihood analyses), and PHA I/II FITS files (for RMFit/XSpec spectral fitting analyses). Its core is written in C++ and its user interface in Python.
sic (Sparse Inpainting Code) generates Gaussian, isotropic CMB realizations, masks them, and recovers the large-scale masked data using sparse inpainting; it is written in Fortran90.
The SPT lensing likelihood code, written in Fortran90, performs a Gaussian likelihood based upon the lensing potential power spectrum using a file from CAMB (ascl:1102.026) which contains the normalization required to get the power spectrum that the likelihood call is expecting.
CGS3DR is data reduction software for the UKIRT CGS3 mid-infrared grating spectrometer instrument. It includes a command-line interface and a GUI. The software, originally on VMS, was ported to Unix. It uses Starlink (ascl:1110.012) infrastructure libraries.
The Extensible N-Dimensional Data Format (NDF) stores bulk data in the form of N-dimensional arrays of numbers. It is typically used for storing spectra, images and similar datasets with higher dimensionality. The NDF format is based on the Hierarchical Data System (HDS) and is extensible; not only does it provide a comprehensive set of standard ancillary items to describe the data, it can also be extended indefinitely to handle additional user-defined information of any type. The NDF library is used to read and write files in the NDF format. It is distributed with the Starlink software (ascl:1110.012).
Starlink Figaro is an independently-maintained fork of Figaro (ascl:1203.013) that runs in the Starlink software environment (ascl:1110.012). It is a general-purpose data reduction package targeted mainly at optical/IR spectroscopy. It uses the NDF data format and the ADAM libraries for parameters and messaging.
POSTMORTEM is the visibility data reduction and map making package from MRAO (Mullard Radio Astronomy Observatory) and is used with the Ryle and CLFST telescopes at Cambridge. It contains sub-systems for nonitoring telescope performance, displaying and editing the visibility data, performing calibrations, removing flux from interfering bright sources, and map-making. It requires PGPLOT (ascl:1103.002), SLALIB (ascl:1403.025), and NAG numerical routines, all of which are distributed with the STARLINK software collection (ascl:1110.012) or available separately.
COADD was used to reduce photometry and continuum data from the UKT14 instrument on the James Clerk Maxwell Telescope in the 1990s. The software can co-add multiple observations and perform sigma clipping and Kolmogorov-Smirnov statistical analysis. Additional information on the software is available in the JCMT Spring 1993 newsletter (large PDF).
Anmap analyses and processes images and spectral data. Originally written for use in radio astronomy, much of its functionality is applicable to other disciplines; additional algorithms and analysis procedures allow direct use in, for example, NMR imaging and spectroscopy. Anmap emphasizes the analysis of data to extract quantitative results for comparison with theoretical models and/or other experimental data. To achieve this, Anmap provides a wide range of tools for analysis, fitting and modelling (including standard image and data processing algorithms). It also provides a powerful environment for users to develop their own analysis/processing tools either by combining existing algorithms and facilities with the very powerful command (scripting) language or by writing new routines in FORTRAN that integrate seamlessly with the rest of Anmap.
The GPI data pipeline allows users to reduce and calibrate raw GPI data into spectral and polarimetric datacubes, and to apply various PSF subtraction methods to those data. Written in IDL and available in a compiled version, the software includes an integrated calibration database to manage reference files and an interactive data viewer customized for high contrast imaging that allows exploration and manipulation of data.
ECCSAMPLES solves the inverse cumulative density function (CDF) of a Beta distribution, sometimes called the IDF or inverse transform sampling. This allows one to sample from the relevant priors directly. ECCSAMPLES actually provides joint samples for both the eccentricity and the argument of periastron, since for transiting systems they display non-zero covariance.
Flicker calculates the mean stellar density of a star by inputting the flicker observed in a photometric time series. Written in Fortran90, its output may be used as an informative prior on stellar density when fitting transit light curves.
SPOTROD is a model for planetary transits of stars with an arbitrary limb darkening law and a number of homogeneous, circular spots on their surface. It facilitates analysis of anomalies due to starspot eclipses, and is a free, open source implementation written in C with a Python API.
NAFE (Noise Adaptive Fuzzy Equalization) is an image processing method allowing for visualization of fine structures in SDO AIA high dynamic range images. It produces artifact-free images and gives significantly better results than methods based on convolution or Fourier transform.
NEAT is a fully automated code which carries out a complete analysis of lists of emission lines to estimate the amount of interstellar extinction, calculate representative temperatures and densities, compute ionic abundances from both collisionally excited lines and recombination lines, and finally to estimate total elemental abundances using an ionization correction scheme. NEAT uses a Monte Carlo technique to robustly propagate uncertainties from line flux measurements through to the derived abundances.
The util_2comp software utilities generate predictions of far-infrared Galactic dust emission and reddening based on a two-component dust emission model fit to Planck HFI, DIRBE and IRAS data from 100 GHz to 3000 GHz. These predictions and the associated dust temperature map have angular resolution of 6.1 arcminutes and are available over the entire sky. Implementations in IDL and Python are included.
PyMGC3 is a Python toolkit to apply the Modified Great Circle Cell Counts (mGC3) method to search for tidal streams in the Galactic Halo. The code computes pole count maps using the full mGC3/nGC3/GC3 family of methods. The original GC3 method (Johnston et al., 1996) uses positional information to search for 'great-circle-cell structures'; mGC3 makes use of full 6D data and nGC3 uses positional and proper motion data.
Raga (Relaxation in Any Geometry) is a Monte Carlo simulation method for gravitational dynamics of non-spherical stellar systems. It is based on the SMILE software (ascl:1308.001) for orbit analysis. It can simulate stellar systems with a much smaller number of particles N than the number of stars in the actual system, represent an arbitrary non-spherical potential with a basis-set or spline spherical-harmonic expansion with the coefficients of expansion computed from particle trajectories, and compute particle trajectories independently and in parallel using a high-accuracy adaptive-timestep integrator. Raga can also model two-body relaxation by local (position-dependent) velocity diffusion coefficients (as in Spitzer's Monte Carlo formulation) and adjust the magnitude of relaxation to the actual number of stars in the target system, and model the effect of a central massive black hole.
iDealCam is an IDL GUI toolkit for processing multi-extension FITS file produced by CanariCam, the facility mid-IR instrument of Gran Telescopio CANARIAS (GTC). iDealCam is optimized for CanariCam data, but is also compatible with data generated by other instruments using similar detectors and data format (e.g., Michelle and T-ReCS at Gemini). iDealCam provides essential capabilities to examine, reduce, and analyze data obtained in the standard imaging or polarimetric imaging mode of CanariCam.
galpy is a python package for galactic dynamics. It supports orbit integration in a variety of potentials, evaluating and sampling various distribution functions, and the calculation of action-angle coordinates for all static potentials.
The Python package segueSelect automatically models the SDSS/SEGUE selection fraction -- the fraction of stars with good spectra -- as a continuous function of apparent magnitude for each plate. The selection function can be determined for any desired sample cuts in signal-to-noise ratio, u-g, r-i, and E(B-V). The package requires Pyfits (ascl:1207.009) and, for coordinate transformations, galpy (ascl:1411.008). It can calculate the KS probability that the spectropscopic sample was drawn from the underlying photometric sample with the model selection function, plot the cumulative distribution function in r-band apparent magnitude of the spectroscopic sample (red) and the photometric sample+selection-function-model for this plate, and, if galpy is installed, can transform velocities into the Galactic coordinate frame. The code can also determine the selection function for SEGUE K stars.
The RC3 mosaicking pipeline creates color composite images and scientifically-calibrated FITS mosaics in all SDSS imaging bands for all the RC3 galaxies that lie within the survey’s footprint and on photographic plates taken by the Digitized Palomar Observatory Sky Survey (DPOSS) for the B, R, IR bands. The pipeline uses SExtractor (ascl:1010.064) for extraction and STIFF (ascl:1110.006) to generating color images. The mosaicking program uses a recursive algorithm for positional update first to correct the positional inaccuracy inherent in the RC3 catalog, then conducts the mosaicking procedure using the Astropy (ascl:1304.002) wrapper to IPAC's Montage (ascl:1010.036) software. The program is generalized into a pipeline that can be easily extended to future survey data or other source catalogs; an online interface is available at
HOPE is a specialized Python just-in-time (JIT) compiler designed for numerical astrophysical applications. HOPE focuses on a subset of the language and is able to translate Python code into C++ while performing numerical optimization on mathematical expressions at runtime. To enable the JIT compilation, the user only needs to add a decorator to the function definition. By using HOPE, the user benefits from being able to write common numerical code in Python while getting the performance of compiled implementation.
OPERA (Open-source Pipeline for Espadons Reduction and Analysis) is an open-source collaborative software reduction pipeline for ESPaDOnS data. ESPaDOnS is a bench-mounted high-resolution echelle spectrograph and spectro-polarimeter designed to obtain a complete optical spectrum (from 370 to 1,050 nm) in a single exposure with a mode-dependent resolving power between 68,000 and 81,000. OPERA is fully automated, calibrates on two-dimensional images and reduces data to produce one-dimensional intensity and polarimetric spectra. Spectra are extracted using an optimal extraction algorithm. Though designed for CFHT ESPaDOnS data, the pipeline is extensible to other echelle spectrographs.
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.
pysovo contains basic tools to work with VOEvents. Though written for specific needs, others interested in VOEvents may find it useful to examine.
RICH (Racah Institute Computational Hydrodynamics) is a 2D hydrodynamic code based on Godunov's method. The code, largely based on AREPO, 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 two Swift UVOT grisms provide uv (170.0-500.0 nm) and visible (285.0-660.0 nm) spectra with a resolution of R~100 and 75. To reduce the grism data, UVOTPY extracts a spectrum given source sky position, and outputs a flux calibrated spectrum. UVOTPY is a replacement for the UVOTIMGRISM FTOOL (ascl:9912.002) in the HEADAS Swift package. Its extraction uses a curved aperture for the uv spectra, accounts the coincidence losses in the detector, provides more accurate anchor positions for the wavelength scale, and is valid for the whole detector.
GIZMO is a flexible, multi-method magneto-hydrodynamics+gravity code that solves the hydrodynamic equations using a variety of different methods. It introduces new Lagrangian Godunov-type methods that allow solving the fluid equations with a moving particle distribution that is automatically adaptive in resolution and avoids the advection errors, angular momentum conservation errors, and excessive diffusion problems that seriously limit the applicability of “adaptive mesh” (AMR) codes, while simultaneously avoiding the low-order errors inherent to simpler methods like smoothed-particle hydrodynamics (SPH). GIZMO also allows the use of SPH either in “traditional” form or “modern” (more accurate) forms, or use of a mesh. Self-gravity is solved quickly with a BH-Tree (optionally a hybrid PM-Tree for periodic boundaries) and on-the-fly adaptive gravitational softenings. The code is descended from P-GADGET, itself descended from GADGET-2 (ascl:0003.001), and many of the naming conventions remain (for the sake of compatibility with the large library of GADGET work and analysis software).
MEPSA (Multiple Excess Peak Search Algorithm) identifies peaks within a uniformly sampled time series affected by uncorrelated Gaussian noise. MEPSA scans the time series at different timescales by comparing a given peak candidate with a variable number of adjacent bins. While this has originally been conceived for the analysis of gamma-ray burst light (GRB) curves, its usage can be readily extended to other astrophysical transient phenomena whose activity is recorded through different surveys. MEPSA's high flexibility permits the mask of excess patterns it uses to be tailored and optimized without modifying the code.
DIAMONDS (high-DImensional And multi-MOdal NesteD Sampling) provides Bayesian parameter estimation and model comparison by means of the nested sampling Monte Carlo (NSMC) algorithm, an efficient and powerful method very suitable for high-dimensional and multi-modal problems; it can be used for any application involving Bayesian parameter estimation and/or model selection in general. Developed in C++11, DIAMONDS is structured in classes for flexibility and configurability. Any new model, likelihood and prior PDFs can be defined and implemented upon a basic template.
Im3shape forward-fits a galaxy model to each data image it is supplied with and reports the parameters of the best fitting model, including the ellipticity components. It uses the Discrete Fourier Transform (DFT) to render images of convolved galaxy profiles, calculates the maximum likelihood parameter values, and corrects for noise bias. IM3SHAPE is a modular C code with a significant amount of Python glue code to enable setting up new models and their options automatically.
CosmoSIS is a cosmological parameter estimation code. It structures cosmological parameter estimation to ease re-usability, debugging, verifiability, and code sharing in the form of calculation modules. Witten in python, CosmoSIS consolidates and connects existing code for predicting cosmic observables and maps out experimental likelihoods with a range of different techniques.
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.
Slim performs lossless compression on binary data files. Written in C++, it operates very rapidly and achieves better compression on noisy physics data than general-purpose tools designed primarily for text.
Nahoon is a gas-phase chemical model that computes the chemical evolution in a 1D temperature and density structure. It uses chemical networks downloaded from the KInetic Database for Astrochemistry (KIDA) but the model can be adapted to any network. The program is written in Fortran 90 and uses the DLSODES (double precision) solver from the ODEPACK package (ascl:1905.021) to solve the coupled stiff differential equations. The solver computes the chemical evolution of gas-phase species at a fixed temperature and density and can be used in one dimension (1D) if a grid of temperature, density, and visual extinction is provided. Grains, both neutral and negatively charged, and electrons are considered as chemical species and their concentrations are computed at the same time as those of the other species. Nahoon contains a test to check the temperature range of the validity of the rate coefficients and avoid extrapolations outside this range. A test is also included to check for duplication of chemical reactions, defined over complementary ranges of temperature.
CHLOE is an image analysis unsupervised learning algorithm that detects peculiar galaxies in datasets of galaxy images. The algorithm first computes a large set of numerical descriptors reflecting different aspects of the visual content, and then weighs them based on the standard deviation of the values computed from the galaxy images. The weighted Euclidean distance of each galaxy image from the median is measured, and the peculiarity of each galaxy is determined based on that distance.
ORBS merges, corrects, transforms and calibrates interferometric data cubes and produces a spectral cube of the observed region for analysis. It is a fully automatic data reduction software for use with SITELLE (installed at the Canada-France-Hawaii Telescope) and SpIOMM (a prototype attached to the Observatoire du Mont Mégantic); these imaging Fourier transform spectrometers obtain a hyperspectral data cube which samples a 12 arc-minutes field of view into 4 millions of visible spectra. ORBS is highly parallelized; its core classes (ORB) have been designed to be used in a suite of softwares for data analysis (ORCS and OACS), data simulation (ORUS) and data acquisition (IRIS).
iSpec is an integrated software framework written in Python for the treatment and analysis of stellar spectra and abundances. Spectra treatment functions include cosmic rays removal, continuum normalization, resolution degradation, and telluric lines identification. It can also perform radial velocity determination and correction and resampling. iSpec can also determine atmospheric parameters (i.e effective temperature, surface gravity, metallicity, micro/macroturbulence, rotation) and individual chemical abundances by using either the synthetic spectra fitting technique or equivalent widths method. The synthesis is performed with SPECTRUM (ascl:9910.002).
IFSFIT is a general-purpose IDL library for fitting the continuum, emission lines, and absorption lines in integral field spectra. It uses PPXF (ascl:1210.002) to find the best fit stellar continuum (using a user-defined library of stellar templates and including additive polynomials), or optionally a user-defined method to find the best fit continuum. It uses MPFIT (ascl:1208.019) to simultaneously fit Gaussians to any number of emission lines and emission line velocity components. It will also fit the NaI D feature using analytic absorption and/or emission-line profiles.
IFSRED is a general-purpose library for reducing data from integral field spectrographs (IFSs). For a general IFS data cube, it contains IDL routines to: (1) find and apply a zero-point shift in a wavelength solution on a spaxel-by-spaxel basis, using sky lines; (2) find the spatial coordinates of a flux peak; (3) empirically correct for differential atmospheric refraction; (4) mosaic dithered exposures; (5) (integer) rebin; and (6) apply a telluric correction. A sky-subtraction routine for data from the Gemini Multi-Object Spectrograph and Imager (GMOS) that can be easily modified for any instrument is also included. IFSRED also contains additional software specific to reducing data from GMOS and the Gemini Near-Infrared Integral Field Spectrograph (NIFS).
LANL* calculates the magnetic drift invariant L*, used for modeling radiation belt dynamics and other space weather applications, six orders of magnitude (~ one million times) faster than convectional approaches that require global numerical field lines tracing and integration. It is based on a modern machine learning technique (feed-forward artificial neural network) by supervising a large data pool obtained from the IRBEM library, which is the traditional source for numerically calculating the L* values. The pool consists of about 100,000 samples randomly distributed within the magnetosphere (r: [1.03, 11.5] Re) and within a whole solar cycle from 1/1/1994 to 1/1/2005. There are seven LANL* models, each corresponding to its underlying magnetic field configuration that is used to create the data sample pool. This model has applications to real-time radiation belt forecasting, analysis of data sets involving tens of satellite-years of observations, and other problems in space weather.
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.
mixT accurately predicts T derived from a single-temperature fit for a multi-component thermal plasma. It can be applied in the deprojection analysis of objects with the temperature and metallicity gradients, for correction of the PSF effects, for consistent comparison of numerical simulations of galaxy clusters and groups with the X-ray observations, and for estimating how emission from undetected components can bias the global X-ray spectral analysis.
WSClean (w-stacking clean) is a fast generic widefield imager. It uses the w-stacking algorithm and can make use of the w-snapshot algorithm. It supports full-sky imaging and proper beam correction for homogeneous dipole arrays such as the MWA. WSClean allows Hogbom and Cotton-Schwab cleaning, and can clean polarizations joinedly. All operations are performed on the CPU; it is not specialized for GPUs.
PhotoRApToR (PHOTOmetric Research APplication TO Redshifts) solves regression and classification problems and is specialized for photo-z estimation. PhotoRApToR offers data table manipulation capabilities and 2D and 3D graphics tools for data visualization; it also provides a statistical report for both classification and regression experiments. The code is written in Java; the machine learning model is in C++ to increase the core execution speed.
APS finds Frequentist confidence limits on high-dimensional parameter spaces by using Gaussian Process interpolation to identify regions of parameter space for which chisquared is less than or equal to some specified limit. The code is written in C++, is robust against multi-modal chisquared functions and converges comparably fast to Monte Carlo methods. Code is also provided to draw Bayesian credible limits using the outputs of APS, though this code does not converge as well. APS requires the linear algebra libraries LAPACK, BLAS, and ARPACK (ascl:1311.010) to run.
bamr is an MPI implementation of a Bayesian analysis of neutron star mass and radius data that determines the mass versus radius curve and the equation of state of dense matter. Written in C++, bamr provides some EOS models. This code requires O2scl (ascl:1408.019) be installed before compilation.
O2scl is an object-oriented library for scientific computing in C++ useful for solving, minimizing, differentiating, integrating, interpolating, optimizing, approximating, analyzing, fitting, and more. Many classes operate on generic function and vector types; it includes classes based on GSL and CERNLIB. O2scl also contains code for computing the basic thermodynamic integrals for fermions and bosons, for generating almost all of the most common equations of state of nuclear and neutron star matter, and for solving the TOV equations. O2scl can be used on Linux, Mac and Windows (Cygwin) platforms and has extensive documentation.
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