Results 1101-1150 of 1895 (1870 ASCL, 25 submitted)
The parallel Python framework MLZ (Machine Learning and photo-Z) computes fast and robust photometric redshift PDFs using Machine Learning algorithms. It uses a supervised technique with prediction trees and random forest through TPZ that can be used for a regression or a classification problem, or a unsupervised methods with self organizing maps and random atlas called SOMz. These machine learning implementations can be efficiently combined into a more powerful one resulting in robust and accurate probability distributions for photometric redshifts.
The Python script/package pyExtinction computes and plots total atmospheric extinction from decomposition into physical components (Rayleigh attenuation, ozone absorption, aerosol extinction). Its default extinction parameters are adapted to mean Mauna Kea summit conditions.
GPU-D is a GPU-accelerated implementation of the inverse ray-shooting technique used to generate cosmological microlensing magnification maps. These maps approximate the source plane magnification patterns created by an ensemble of stellar-mass compact objects within a foreground macrolens galaxy. Unlike other implementations, GPU-D solves the gravitational lens equation without any approximation. Due to the high computational intensity and high degree of parallelization inherent in the algorithm, it is ideal for brute-force implementation on GPUs. GPU-D uses CUDA for GPU acceleration and require NVIDIA devices to run.
MGHalofit is a modified gravity extension of the fitting formula for the matter power spectrum of HALOFIT and its improvement by Takahashi et al. MGHalofit is implemented in MGCAMB, which is based on CAMB. MGHalofit calculates the nonlinear matter power spectrum P(k) for the Hu-Sawicki model. Comparing MGHalofit predictions at various redshifts (z<=1) to the f(R) simulations, the accuracy on P(k) is 6% at k<1 h/Mpc and 12% at 1<k<10 h/Mpc respectively.
PyWiFeS is a Python-based data reduction pipeline for the Wide Field Spectrograph (WiFeS). Its core data processing routines are built on standard scientific Python packages commonly used in astronomical applications. It includes an implementation of a global optical model of the spectrograph which provides wavelengths solutions accurate to ˜0.05 Å (RMS) across the entire detector. Through scripting, PyWiFeS can enable batch processing of large quantities of data.
Libsharp is a collection of algorithms for efficient conversion between maps on the sphere and their spherical harmonic coefficients. It supports a wide range of pixelisations (including HEALPix, GLESP, and ECP). This library is a successor of libpsht (ascl:1010.020); it adds MPI support for distributed memory systems and SHTs of fields with arbitrary spin, and also supports new developments in CPU instruction sets like the Advanced Vector Extensions (AVX) or fused multiply-accumulate (FMA) instructions. libsharp is written in portable C99; it provides an interface accessible to other programming languages such as C++, Fortran, and Python.
HALOFIT provides an explanatory framework for galaxy bias and clustering and has been incorporated into CMB packages such as CMBFAST (ascl:9909.004) and CAMB (ascl:1102.026). It attains a reasonable level of precision, though the halo model does not match N-body data perfectly. The code is written in Fortran 77. HALOFIT tends to underpredict the power on the smallest scales in standard LCDM universes (although HALOFIT was designed to work for a much wider range of power spectra); its accuracy can be improved by using a supplied correction.
gyrfalcON (GalaxY simulatoR using falcON) is a full-fledged N-body code using Dehnen’s force algorithm of complexity O(N) (falcON); this algorithm is approximately 10 times faster than an optimally coded tree code. The code features individual adaptive time steps and individual (but fixed) softening lengths. gyrfalcON is included in and requires NEMO to run.
P2SAD computes the Particle Phase Space Average Density (P2SAD) in galactic haloes. The model for the calculation is based on the stable clustering hypothesis in phase space, the spherical collapse model, and tidal disruption of substructures. The multiscale prediction for P2SAD computed by this IDL code can be used to estimate signals sensitive to the small scale structure of dark matter distributions (e.g. dark matter annihilation). The code computes P2SAD averaged over the whole virialized region of a Milky-Way-size halo at redshift zero.
wssa_utils contains utilities for accessing the full-sky, high-resolution maps of the WSSA 12 micron data release. Implementations in both Python and IDL are included. The code allows users to sample values at (longitude, latitude) coordinates of interest with ease, transparently mapping coordinates to WSSA tiles and performing interpolation. The wssa_utils software also serves to define a unique WSSA 12 micron flux at every location on the sky.
Commander 2 is a Gibbs sampling code for joint CMB estimation and component separation. The Commander framework uses a parametrized physical model of the sky to perform statistically-rigorous analyses of multi-frequency, multi-resolution CMB data on the full and partial (flat) sky, as well as cross-correlation analyses with large-scale structure datasets.
Darth Fader is a wavelet-based method for extracting spectral features from very noisy spectra. Spectra for which a reliable redshift cannot be measured are identified and removed from the input data set automatically, resulting in a clean catalogue that gives an extremely low rate of catastrophic failures even when the spectra have a very low S/N. This technique may offer a significant boost in the number of faint galaxies with accurately determined redshifts.
athena is a 2d-tree code that estimates second-order correlation functions from input galaxy catalogues. These include shear-shear correlations (cosmic shear), position-shear (galaxy-galaxy lensing) and position-position (spatial angular correlation). Written in C, it includes a power-spectrum estimator implemented in Python; this script also calculates the aperture-mass dispersion. A test data set is available.
Using the 2-point correlation function, BAOlab aids the study of Baryon Acoustic Oscillations (BAO). The code generates a model-dependent covariance matrix which can change the results both for BAO detection and for parameter constraints.
QuickReduce quickly reduces data for ODI and is optimized for a first data inspection during acquisition at the the telescope. When installed on the ODI observer's interface, QuickReduce, coded in Python, performs all basic reduction steps as well as more advanced corrections for pupil-ghost removal, fringe correction and masking of persistent pixels and is capable enough for science-quality data reductions. It can also add an accurate astrometric WCS solution based on the 2MASS reference system as well as photometric zeropoint calibration for frames covered by the SDSS foot-print. The pipeline makes use of multiple CPU-cores wherever possible, resulting in an execution time of only a few seconds per frame, thus offering the ODI observer a convenient way to closely monitor data quality.
HydraLens generates gravitational lens model files for Lenstool, PixeLens, glafic and Lensmodel and can also translate lens model files among these four lens model codes. Through a GUI, the user enters a new model by specifying the type of model and is then led through screens to collect the data. Written in MS Visual Basic, the code can also translate an existing model from any of the four supported codes to any of the other three.
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.
Glue, written in Python, links visualizations of scientific datasets across many files, allowing for interactive, linked statistical graphics of multiple files. It supports many file formats including common image formats (jpg, tiff, png), ASCII tables, astronomical image and table formats (FITS, VOT, IPAC), and HDF5. Custom data loaders can also be easily added. Glue is highly scriptable and extendable.
Astropoltlib is a multi-language astronomical library of plots, a collection of templates useful for creating paper-quality figures. Most of the codes for producing the plots are written in IDL and/or Python; a very few are written in Mathematica. Any plot can be downloaded and customized to one's own needs.
PyVO provides access to remote data and services of the Virtual observatory (VO) using Python. It allows archive searches for data of a particular type or related to a particular topic and query submissions to obtain data to a particular archive to download selected data products. PyVO supports querying the VAO registry; simple data access services (DAL) to access images (SIA), source catalog records (Cone Search), spectra (SSA), and spectral line emission/absorption data (SLAP); and object name resolution (for converting names of objects in the sky into positions). PyVO requires both AstroPy and NumPy.
Aladin Lite is a lightweight version of the Aladin tool, running in the browser and geared towards simple visualization of a sky region. It allows visualization of image surveys (JPEG multi-resolution HEALPix all-sky surveys) and permits superimposing tabular (VOTable) and footprints (STC-S) data. Aladin Lite is powered by HTML5 canvas technology and is easily embeddable on any web page and can also be controlled through a Javacript API.
Munipack provides easy-to-use tools for all astronomical astrometry and photometry, access to Virtual Observatory as well as FITS files operations and a simple user interface along with a powerful processing engine. Its many features include a FITS images viewer that allows for basic (astronomical) operations with frames, advanced image processor supporting an infinite dynamic range and advanced color management, and astrometric calibration of images. The astrometry module uses robust statistical estimators and algorithms. The photometry module provides the classical method detection of stars and implements the aperture photometry, calibrated on the basis of photon statistics, and allows for the automatic detection and aperture photometry of stars; calibration on absolute fluxes is possible. The software also provides a standard way to correct for all the bias, dark and flat-field frames, and many other features.
SPLAT is a graphical tool for displaying, comparing, modifying and analyzing astronomical spectra stored in NDF, FITS and TEXT files as well as in NDX format. It can read in many spectra at the same time and then display these as line plots. Display windows can show one or several spectra at the same time and can be interactively zoomed and scrolled, centered on specific wavelengths, provide continuous coordinate readout, produce printable hardcopy and be configured in many ways. Analysis facilities include the fitting of a polynomial to selected parts of a spectrum, the fitting of Gaussian, Lorentzian and Voigt profiles to emission and absorption lines and the filtering of spectra using average, median and line-shape window functions as well as wavelet denoising. SPLAT also supports a full range of coordinate systems for spectra, which allows coordinates to be displayed and aligned in many different coordinate systems (wavelength, frequency, energy, velocity) and transformed between these and different standards of rest (topocentric, heliocentric, dynamic and kinematic local standards of rest, etc). SPLAT is distributed as part of the Starlink (ascl:1110.012) software collection.
SPLAT-VO is an extension of the SPLAT (Spectral Analysis Tool, ascl:1402.007) graphical tool for displaying, comparing, modifying and analyzing astronomical spectra; it includes facilities that allow it to work as part of the Virtual Observatory (VO). SPLAT-VO comes in two different forms, one for querying and downloading spectra from SSAP servers and one for interoperating with VO tools, such as TOPCAT (ascl:1101.010).
GalSim is a fast, modular software package for simulation of astronomical images. Though its primary purpose is for tests of weak lensing analysis methods, it can be used for other purposes. GalSim allows galaxies and PSFs to be represented in a variety of ways, and can apply shear, magnification, dilation, or rotation to a galaxy profile including lensing-based models from a power spectrum or NFW halo profile. It can write images in regular FITS files, FITS data cubes, or multi-extension FITS files. It can also compress the output files using various compressions including gzip, bzip2, and rice. The user interface is in python or via configuration scripts, and the computations are done in C++ for speed.
The Common Pipeline Library (CPL) is a set of ISO-C libraries that provide a comprehensive, efficient and robust software toolkit to create automated astronomical data reduction pipelines. Though initially developed as a standardized way to build VLT instrument pipelines, the CPL may be more generally applied to any similar application. The code also provides a variety of general purpose image- and signal-processing functions, making it an excellent framework for the creation of more generic data handling packages. The CPL handles low-level data types (images, tables, matrices, strings, property lists, etc.) and medium-level data access methods (a simple data abstraction layer for FITS files). It also provides table organization and manipulation, keyword/value handling and management, and support for dynamic loading of recipe modules using programs such as EsoRex (ascl:1504.003).
KROME, given a chemical network (in CSV format), automatically generates all the routines needed to solve the kinetics of the system modeled as a system of coupled Ordinary Differential Equations. It provides a large set of physical processes connected to chemistry, including photochemistry, cooling, heating, dust treatment, and reverse kinetics. KROME is flexible and can be used for a wide range of astrophysical simulations. The package contains a network for primordial chemistry, a small metal network appropriate for the modeling of low metallicities environments, a detailed network for the modeling of molecular clouds, and a network for planetary atmospheres as well as a framework for the modelling of the dust grain population.
QUICKCV is an IDL sample variance/cosmic variance calculator for some geometry for galaxies in given stellar mass bins as a function of mean redshift and redshift bin size.
CASSIS (Centre d'Analyse Scientifique de Spectres Infrarouges et Submillimetriques), written in Java, is suited for broad-band spectral surveys to speed up the scientific analysis of high spectral resolution observations. It uses a local spectroscopic database made of the two molecular spectroscopic databases JPL and CDMS, as well as the atomic spectroscopic database NIST. Its tools include a LTE model and the RADEX model connected to the LAMDA molecular collisional database. CASSIS can build a line list fitting the various transitions of a given species and to directly produce rotational diagrams from these lists. CASSIS is fully integrated into HIPE, the Herschel Interactive Processing Environment, as a plug-in.
ARTIST is a suite of tools for comprehensive multi-dimensional radiative transfer calculations of dust and line emission, as well as their polarization, to help interpret observations from submillimeter telescopes. The ARTIST package consists of LIME, a radiative transfer code that uses adaptive gridding allowing simulations of sources with arbitrary multi-dimensional (1D, 2D, 3D) and time-dependent structures, thus ensuring rapid convergence; the DustPol and LinePol tools for modeling the polarization of the line and dust emission; and an interface run from Python scripts that manages the interaction between a general model library and LIME, and a graphical interface to simulate images.
The "busy function" accurately describes the characteristic double-horn HI profile of many galaxies. Implemented in a C/C++ library and Python module called BF_dist, it is a continuous, differentiable function that consists of only two basic functions, the error function, erf(x), and a polynomial, |x|^n, of degree n >= 2. BF_dist offers great flexibility in fitting a wide range of HI profiles from the Gaussian profiles of dwarf galaxies to the broad, asymmetric double-horn profiles of spiral galaxies, and can be used to parametrize observed HI spectra of galaxies and the construction of spectral templates for simulations and matched filtering algorithms accurately and efficiently.
FAMA (Fast Automatic MOOG Analysis), written in Perl, computes the atmospheric parameters and abundances of a large number of stars using measurements of equivalent widths (EWs) automatically and independently of any subjective approach. Based on the widely-used MOOG code, it simultaneously searches for three equilibria, excitation equilibrium, ionization balance, and the relationship between logn(FeI) and the reduced EWs. FAMA also evaluates the statistical errors on individual element abundances and errors due to the uncertainties in the stellar parameters. Convergence criteria are not fixed "a priori" but instead are based on the quality of the spectra.
UVMULTIFIT, written in Python, is a versatile library for fitting models directly to visibility data. These models can depend on frequency and fitting parameters in an arbitrary algebraic way. The results from the fit to the visibilities of sources with sizes smaller than the diffraction limit of the interferometer are superior to the output obtained from a mere analysis of the deconvolved images. Though UVMULTIFIT is based on the CASA package, it can be easily adapted to other analysis packages that have a Python API.
TARDIS creates synthetic spectra for supernova ejecta and is sufficiently fast to allow exploration of the complex parameter spaces of models for SN ejecta. TARDIS uses Monte Carlo methods to obtain a self-consistent description of the plasma state and to compute a synthetic spectrum. It is written in Python with a modular design that facilitates the implementation of a range of physical approximations that can be compared to assess both accuracy and computational expediency; this allows users to choose a level of sophistication appropriate for their application.
ANAigm offers an updated version of the Madau model for the attenuation by the intergalactic neutral hydrogen against the radiation from distant objects. This new model is written in Fortran90 and predicts, for some redshifts, more than 0.5--1 mag different attenuation magnitudes through usual broad-band filters relative to the original Madau model.
XNS solves for the axisymmetric equilibrium configuration of neutron stars in general relativity. It can model differentially rotating and magnetic fields that are either purely toroidal, purely poloidal or in the mixed twisted torus configuration. Einsten's equations are solved using the XCFC approximation for the metric in spherical coordinates.
PyGFit measures PSF-matched photometry from images with disparate pixel scales and PSF sizes; its primary purpose is to extract robust spectral energy distributions (SEDs) from crowded images. It fits blended sources in crowded, low resolution images with models generated from a higher resolution image, thus minimizing the impact of crowding and also yielding consistently measured fluxes in different filters which minimizes systematic uncertainty in the final SEDs.
DexM (Deus ex Machina) efficiently generates density, halo, and ionization fields on very large scales and with a large dynamic range through seminumeric simulation. These properties are essential for reionization studies, especially those involving rare, massive QSOs, since one must be able to statistically capture the ionization field. DexM can also generate ionization fields directly from the evolved density field to account for the ionizing contribution of small halos. Semi-numerical simulations use more approximate physics than numerical simulations, but independently generate 3D cosmological realizations. DexM is portable and fast, and allows for explorations of wide swaths of astrophysical parameter space and an unprecedented dynamic range.
The use of graphics processing units offers an attractive alternative to specialized hardware, like GRAPE. The Kirin library mimics the behavior of the GRAPE hardware and uses the GPU to execute the force calculations. It is compatible with the GRAPE6 library; existing code that uses the GRAPE6 library can be recompiled and relinked to use the GPU equivalents of the GRAPE6 functions. All functions in the GRAPE6 library have an equivalent GPU implementation. Kirin can be used for direct N-body simulations as well as for treecodes; it can be run with shared-time steps or with block time-steps and allows non-softened potentials. As Kirin makes use of CUDA, it works only on NVIDIA GPUs.
SpacePy provides data analysis and visualization tools for the space science community. Written in Python, it builds on the capabilities of the NumPy and MatPlotLib packages to make basic data analysis, modeling and visualization easier. It contains modules for handling many complex time formats, obtaining data from the OMNI database, and accessing the powerful Onera library. It contains a library of commonly used empirical relationships, performs association analysis, coordinate transformations, radiation belt modeling, and CDF reading, and creates publication quality plots.
PyMidas is an interface between Python and MIDAS, the major ESO legacy general purpose data processing system. PyMidas allows a user to exploit both the rich legacy of MIDAS software and the power of Python scripting in a unified interactive environment. PyMidas also allows the usage of other Python-based astronomical analysis systems such as PyRAF.
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.
PyDrizzle provides a semi-automated interface for computing the parameters necessary for running Drizzle. PyDrizzle performs the task of determining the parameters necessary for aligning images based on the WCS information in the input image headers, as well as any supplemental alignment information provided in shift files, and combines the images onto the same WCS. Though it does not identify cosmic rays, it has the ability to ignore pixels flagged as bad, such as pixels identified by other programs as affected by cosmic rays.
The IDL package convolve_image.pro transforms images between different instrumental point spread functions (PSFs). It can load an image file and corresponding kernel and return the convolved image, thus preserving the colors of the astronomical sources. Convolution kernels are available for images from Spitzer (IRAC MIPS), Herschel (PACS SPIRE), GALEX (FUV NUV), WISE (W1 - W4), Optical PSFs (multi- Gaussian and Moffat functions), and Gaussian PSFs; they allow the study of the Spectral Energy Distribution (SED) of extended objects and preserve the characteristic SED in each pixel.
abundance, written in Fortran, provides driver and fitting routines to compute the predicted number of clusters in a ΛCDM cosmology that agrees with CMB, SN, BAO, and H0 measurements (up to 2010) at some specified parameter confidence and the mass that would rule out that cosmology at some specified sample confidence. It also computes the expected number of such clusters in the light cone and the Eddington bias factor that must be applied to observed masses.
massconvert, written in Fortran, provides driver and fitting routines for converting halo mass definitions from one spherical overdensity to another assuming an NFW density profile. In surveys that probe ever lower cluster masses and temperatures, sample variance is generally comparable to or greater than shot noise and thus cannot be neglected in deriving precision cosmological constraints; massconvert offers an accurate fitting formula for the conversion between different definitions of halo mass.
The main CAMB code supports smooth dark energy models with constant equation of state and sound speed of one, or a quintessence model based on a potential. This modified code generalizes it to support a time-dependent equation of state w(a) that is allowed to cross the phantom divide, i.e. w=-1 multiple times by implementing a Parameterized Post-Friedmann(PPF) prescription for the dark energy perturbations.
SunPy is a community-developed free and open-source software package for solar physics and is an alternative to the SolarSoft data analysis environment. SunPy provides data structures for representing the most common solar data types (images, lightcurves, and spectra) and integration with the Virtual Solar Observatory (VSO) and the Heliophysics Event Knowledgebase (HEK) for data acquisition.
SERPent is an automated reduction and RFI-mitigation procedure that uses the SumThreshold methodology. It was originally developed for the LOFAR pipeline. SERPent is written in Parseltongue, enabling interaction with the Astronomical Image Processing Software (AIPS) program. Moreover, SERPent is a simple "out of the box" Python script, which is easy to set up and is free of compilers.
WND-CHARM quantitatively analyzes morphologies of galaxy mergers and associate galaxies by their morphology. It computes a large set (up to ~2700) of image features for each image based on the WND-CHARM algorithm. It can then split the images into training and test sets and classify them. The software extracts the image content descriptor from raw images, image transforms, and compound image transforms. The most informative features are then selected, and the feature vector of each image is used for classification and similarity measurement using Fisher discriminant scores and a variation of Weighted Nearest Neighbor analysis. WND-CHARM's results comparable favorably to the performance of task-specific algorithms developed for tested datasets. The simple user interface allows researchers who are not knowledgeable in computer vision methods and have no background in computer programming to apply image analysis to their data.
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