Results 1301-1350 of 2056 (2027 ASCL, 29 submitted)

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SpacePy: Python-Based Tools for the Space Science Community

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.

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PyMidas: Interface from Python to Midas

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.

[ascl:1401.004]
Reflex: Graphical workflow engine for data reduction

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.

[ascl:1401.005]
PyDrizzle: Python version of Drizzle

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.

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convolve_image.pro: Common-Resolution Convolution Kernels for Space- and Ground-Based Telescopes

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.

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abundance: High Redshift Cluster Abundance

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.

[ascl:1401.008]
massconvert: Halo Mass Conversion

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.

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PPF module for CAMB

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.

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SunPy: Python for Solar Physicists

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.

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SERPent: Scripted E-merlin Rfi-mitigation PipelinE for iNTerferometry

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.

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WND-CHARM: Multi-purpose image classifier

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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IMCOM: IMage COMbination

IMCOM allows for careful treatment of aliasing in undersampled imaging data and can be used to test the feasibility of multi-exposure observing strategies for space-based survey missions. IMCOM can also been used to explore focal plane undersampling for an optical space mission such as Euclid.

[ascl:1312.004]
BIE: Bayesian Inference Engine

The Bayesian Inference Engine (BIE) is an object-oriented library of tools written in C++ designed explicitly to enable Bayesian update and model comparison for astronomical problems. To facilitate "what if" exploration, BIE provides a command line interface (written with Bison and Flex) to run input scripts. The output of the code is a simulation of the Bayesian posterior distribution from which summary statistics e.g. by taking moments, or determine confidence intervals and so forth, can be determined. All of these quantities are fundamentally integrals and the Markov Chain approach produces variates $ heta$ distributed according to $P( heta|D)$ so moments are trivially obtained by summing of the ensemble of variates.

[ascl:1312.005]
XAssist: Automatic analysis of X-ray astrophysics data

XAssist provides automation of X-ray astrophysics, specifically data reprocessing, source detection, and preliminary spatial, temporal and spectral analysis for each source with sufficient counts, with an emphasis on galaxies. It has been used for data from Chandra, ROSAT, XMM-Newton, and other various projects.

[ascl:1312.006]
LTL: The Little Template Library

LTL provides dynamic arrays of up to 7-dimensions, subarrays and slicing, support for fixed-size vectors and matrices including basic linear algebra operations, expression templates-based evaluation, and I/O facilities for ascii and FITS format files. Utility classes for command-line processing and configuration-file processing are provided as well.

[ascl:1312.007]
SkyNet: Neural network training tool for machine learning in astronomy

SkyNet is an efficient and robust neural network training code for machine learning. It is able to train large and deep feed-forward neural networks, including autoencoders, for use in a wide range of supervised and unsupervised learning applications, such as regression, classification, density estimation, clustering and dimensionality reduction. SkyNet is implemented in C/C++ and fully parallelized using MPI.

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BAMBI: Blind Accelerated Multimodal Bayesian Inference

BAMBI (Blind Accelerated Multimodal Bayesian Inference) is a Bayesian inference engine that combines the benefits of SkyNet (ascl:1312.007) with MultiNest (ascl:1109.006). It operated by simultaneously performing Bayesian inference using MultiNest and learning the likelihood function using SkyNet. Once SkyNet has learnt the likelihood to sufficient accuracy, inference finishes almost instantaneously.

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YODA: Yet another Object Detection Application

YODA, implemented in C++, performs object detection, photometry and star-galaxy classification on astronomical images. Developed specifically to cope with the multi-band imaging data common in modern extragalactic imaging surveys, it is modular and therefore easily adaptable to specific needs. YODA works under conditions of inhomogeneous background noise across the detection frame, and performs accurate aperture photometry in image sets not sharing a common coordinate system or pixel scale as is often the case in present-day extragalactic survey work.

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GalaxyCount: Galaxy counts and variance calculator

GalaxyCount calculates the number and standard deviation of galaxies in a magnitude limited observation of a given area. The methods to calculate both the number and standard deviation may be selected from different options. Variances may be computed for circular, elliptical and rectangular window functions.

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A_phot: Photon Asymmetry

Photon asymmetry is a novel robust substructure statistic for X-ray cluster observations with only a few thousand counts; it exhibits better stability than power ratios and centroid shifts and has a smaller statistical uncertainty than competing substructure parameters, allowing for low levels of substructure to be measured with confidence. A_phot computes the photon asymmetry (A_phot) parameter for morphological classification of clusters and allows quantifying substructure in samples of distant clusters covering a wide range of observational signal-to-noise ratios. The python scripts are completely automatic and can be used to rapidly classify galaxy cluster morphology for large numbers of clusters without human intervention.

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BINGO: BI-spectra and Non-Gaussianity Operator

The BI-spectra and Non-Gaussianity Operator (BINGO) code, written in Fortran, computes the scalar bi-spectrum and the non-Gaussianity parameter fNL in single field inflationary models involving the canonical scalar field. BINGO can calculate all the different contributions to the bi-spectrum and the parameter fNL for an arbitrary triangular configuration of the wavevectors.

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CJAM: First and second velocity moments calculations

CJAM calculates first and second velocity moments using the Jeans Anisotropic MGE (JAM) models of Cappellari (2008) and Cappellari (2012). These models have been extended to calculate all three (x, y, z) first moments and all six (xx, yy, zz, xy, xz, yz) second moments. CJAM, written in C, is based on the IDL implementation of the line-of-sight calculations by Michele Cappellari.

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SL1M: Synthesis through L1 Minimization

SL1M deconvolves radio synthesis images based on direct inversion of the measured visibilities that can deal with the non-coplanar base line effect and can be applied to telescopes with direction dependent gains. The code is more computationally demanding than some existing methods, but is highly parallelizable and scale well to clusters of CPUs and GPUs. The algorithm is also extremely flexible, allowing the solution of the deconvolution problem on arbitrarily placed pixels.

[ascl:1311.001]
SciDB: Open Source DMAS for Scientific Research

SciDB is a DMAS (Data Management and Analytics Software System) optimized for data management of big data and for big analytics. SciDB is organized around multidimensional array storage, a generalization of relational tables, and is designed to be scalable up to petabytes and beyond. Complex analytics are simplified with SciDB because arrays and vectors are first-class objects with built-in optimized operations. Spatial operators and time-series analysis are easy to express. Interfaces to common scientific tools like R as well as programming languages like C++ and Python are provided.

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PyCOOL: Cosmological Object-Oriented Lattice code

PyCOOL is a Python + CUDA program that solves the evolution of interacting scalar fields in an expanding universe. PyCOOL uses modern GPUs to solve this evolution and to make the computation much faster. The code includes numerous post-processing functions that provide useful information about the cosmological model, including various spectra and statistics of the fields.

[ascl:1311.003]
AstroAsciiData: ASCII table Python module

ASCII tables continue to be one of the most popular and widely used data exchange formats in astronomy. AstroAsciiData, written in Python, imports all reasonably well-formed ASCII tables. It retains formatting of data values, allows column-first access, supports SExtractor style headings, performs column sorting, and exports data to other formats, including FITS, Numpy/Numarray, and LaTeX table format. It also offers interchangeable comment character, column delimiter and null value.

[ascl:1311.004]
PlanetPack: Radial-velocity time-series analysis tool

PlanetPack facilitates and standardizes the advanced analysis of radial velocity (RV) data for the goal of exoplanets detection, characterization, and basic dynamical N-body simulations. PlanetPack is a command-line interpreter that can run either in an interactive mode or in a batch mode of automatic script interpretation.

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Spheroid: Electromagnetic Scattering by Spheroids

Spheroid determines the size distribution of polarizing interstellar dust grains based on electromagnetic scattering by spheroidal particles. It contains subroutines to treat the case of complex refractive indices, and also includes checks for some limiting cases.

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CIAO: Chandra Interactive Analysis of Observations

CIAO is a data analysis system written for the needs of users of the Chandra X-ray Observatory. Because Chandra data is 4-dimensional (2 spatial, time, energy) and each dimension has many independent elements, CIAO was built to handle N-dimensional data without concern about which particular axes were being analyzed. Apart from a few Chandra instrument tools, CIAO is mission independent. CIAO tools read and write several formats, including FITS images and tables (which includes event files) and IRAF imh files. CIAO is a powerful system for the analysis of many types of data.

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CUPID: Clump Identification and Analysis Package

The CUPID package allows the identification and analysis of clumps of emission within 1, 2 or 3 dimensional data arrays. Whilst targeted primarily at sub-mm cubes, it can be used on any regularly gridded 1, 2 or 3D data. A variety of clump finding algorithms are implemented within CUPID, including the established ClumpFind (ascl:1107.014) and GaussClumps algorithms. In addition, two new algorithms called FellWalker and Reinhold are also provided. CUPID allows easy inter-comparison between the results of different algorithms; the catalogues produced by each algorithm contains a standard set of columns containing clump peak position, clump centroid position, the integrated data value within the clump, clump volume, and the dimensions of the clump. In addition, pixel masks are produced identifying which input pixels contribute to each clump. CUPID is distributed as part of the Starlink (ascl:1110.012) software collection.

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CUPID: Customizable User Pipeline for IRS Data

Written in c, the Customizable User Pipeline for IRS Data (CUPID) allows users to run the Spitzer IRS Pipelines to re-create Basic Calibrated Data and extract calibrated spectra from the archived raw files. CUPID provides full access to all the parameters of the BCD, COADD, BKSUB, BKSUBX, and COADDX pipelines, as well as the opportunity for users to provide their own calibration files (e.g., flats or darks). CUPID is available for Mac, Linux, and Solaris operating systems.

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CosmoTherm: Thermalization code

CosmoTherm allows precise computation of CMB spectral distortions caused by energy release in the early Universe. Different energy-release scenarios (e.g., decaying or annihilating particles) are implemented using the Green's function of the cosmological thermalization problem, allowing fast computation of the distortion signal. The full thermalization problem can be solved on a case-by-case basis for a wide range of energy-release scenarios using the full PDE solver of CosmoTherm. A simple Monte-Carlo toolkit is included for parameter estimation and forecasts using the Green's function method.

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ARPACK: Solving large scale eigenvalue problems

ARPACK is a collection of Fortran77 subroutines designed to solve large scale eigenvalue problems. The package is designed to compute a few eigenvalues and corresponding eigenvectors of a general n by n matrix A. It is most appropriate for large sparse or structured matrices A where structured means that a matrix-vector product w <- Av requires order n rather than the usual order n2 floating point operations. This software is based upon an algorithmic variant of the Arnoldi process called the Implicitly Restarted Arnoldi Method (IRAM). When the matrix A is symmetric it reduces to a variant of the Lanczos process called the Implicitly Restarted Lanczos Method (IRLM). These variants may be viewed as a synthesis of the Arnoldi/Lanczos process with the Implicitly Shifted QR technique that is suitable for large scale problems. For many standard problems, a matrix factorization is not required; only the action of the matrix on a vector is needed. ARPACK is capable of solving large scale symmetric, nonsymmetric, and generalized eigenproblems from significant application areas.

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MUSIC: MUlti-Scale Initial Conditions

MUSIC generates multi-scale initial conditions with multiple levels of refinements for cosmological ‘zoom-in’ simulations. The code uses an adaptive convolution of Gaussian white noise with a real-space transfer function kernel together with an adaptive multi-grid Poisson solver to generate displacements and velocities following first- (1LPT) or second-order Lagrangian perturbation theory (2LPT). MUSIC achieves rms relative errors of the order of 10−4 for displacements and velocities in the refinement region and thus improves in terms of errors by about two orders of magnitude over previous approaches. In addition, errors are localized at coarse-fine boundaries and do not suffer from Fourier space-induced interference ringing.

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ETC: Exposure Time Calculator

Hirata, Christopher M.; Gehrels, Neil; Kneib, Jean-Paul; Kruk, Jeffrey; Rhodes, Jason; Wang, Yun; Zoubian, Julien

Written for the Wide-Field Infrared Survey Telescope (WFIRST) high-latitude survey, the exposure time calculator (ETC) works in both imaging and spectroscopic modes. In addition to the standard ETC functions (e.g. background and S/N determination), the calculator integrates over the galaxy population and forecasts the density and redshift distribution of galaxy shapes usable for weak lensing (in imaging mode) and the detected emission lines (in spectroscopic mode). The program may be useful outside of WFIRST but no warranties are made regarding its suitability for general purposes. The software is available for download; IPAC maintains a web interface for those who wish to run a small number of cases without having to download the package.

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ORAC-DR: Astronomy data reduction pipeline

ORAC-DR is a generic data reduction pipeline infrastructure; it includes specific data processing recipes for a number of instruments. It is used at the James Clerk Maxwell Telescope, United Kingdom Infrared Telescope, AAT, and LCOGT. This pipeline runs at the JCMT Science Archive hosted by CADC to generate near-publication quality data products; the code has been in use since 1998.

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PyMSES: Python modules for RAMSES

PyMSES provides a python solution for getting data out of RAMSES (ascl:1011.007) astrophysical fluid dynamics simulations. It permits transparent manipulation of large simulations and interfaces with common Python libraries and existing code, and can serve as a post-processing toolbox for data analysis. It also does three-dimensional volume rendering with a specific algorithm optimized to work on RAMSES distributed data (Guillet et al. 2011 and Jones et a. 2011).

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AIDA: Adaptive Image Deconvolution Algorithm

AIDA is an implementation and extension of the MISTRAL myopic deconvolution method developed by Mugnier et al. (2004) (see J. Opt. Soc. Am. A 21:1841-1854). The MISTRAL approach has been shown to yield object reconstructions with excellent edge preservation and photometric precision when used to process astronomical images. AIDA improves upon the original MISTRAL implementation. AIDA, written in Python, can deconvolve multiple frame data and three-dimensional image stacks encountered in adaptive optics and light microscopic imaging.

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AIRY: Astronomical Image Restoration in interferometrY

Carbillet, Marcel; Fini, Luca; Anconelli, Barbara; Desiderà, Gabriele; La Camera, Andrea; Bertero, Mario; Boccacci, Patrizia

AIRY simulates optical and near-infrared interferometric observations; it can also perform subsequent image restoration or deconvolution. It is based on the CAOS (ascl:1106.017) Problem Solving Environment. Written in IDL, it consists of a set of specific modules, each handling a particular task.

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ASPRO 2: Astronomical Software to PRepare Observations

ASPRO 2 (Astronomical Software to PRepare Observations) is an observation preparation tool for interferometric observations with the VLTI or other interferometers such as CHARA and SUSI. It is a Java standalone program that provides a dynamic graphical interface to simulate the projected baseline evolution during observations (super-synthesis) and derive visibilities for targets (i.e., single star, binaries, user defined FITS image). It offers other useful functions such as the ability to load and save your observation settings and generate Observing Blocks.

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AIPSLite: ParselTongue extension for distributed AIPS processing

AIPSLite is an extension for ParselTongue (ascl:1208.020) that allows machines without an AIPS (ascl:9911.003) distribution to bootstrap themselves with a minimal AIPS environment. This allows deployment of AIPS routines on distributed systems, which is useful when data can be easily be split into smaller chunks and handled independently.

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SMURF: SubMillimeter User Reduction Facility

Jenness, Tim; Chapin, Edward L.; Berry, David S.; Gibb, Andy G.; Tilanus, Remo P. J.; Balfour, Jennifer; Tilanus, Vincent; Currie, Malcolm J.

SMURF reduces submillimeter single-dish continuum and heterodyne data. It is mainly targeted at data produced by the James Clerk Maxwell Telescope but data from other telescopes have been reduced using the package. SMURF is released as part of the bundle that comprises Starlink (ascl:1110.012) and most of the packages that use it. The two key commands are MAKEMAP for the creation of maps from sub millimeter continuum data and MAKECUBE for the creation of data cubes from heterodyne array instruments. The software can also convert data from legacy JCMT file formats to the modern form to allow it to be processed by MAKECUBE. SMURF is a core component of the ORAC-DR (ascl:1310.001) data reduction pipeline for JCMT.

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SPECX: Spectral Line Data Reduction Package

SPECX is a general purpose line data reduction system. It can read and write FITS data cubes but has specialist support for the GSD format data from the James Clerk Maxwell Telescope. It includes commands to store and retrieve intermediate spectra in storage registers and perform the fitting and removal of polynomial, harmonic and Gaussian baselines.

SPECX can filter and edit spectra and list and display spectra on a graphics terminal. It is able to perform Fourier transform and power spectrum calculations, process up to eight spectra (quadrants) simultaneously with either the same or different center, and assemble a number of reduced individual spectra into a map file and contour or greyscale any plane or planes of the resulting cube.

Two versions of SPECX are distributed. Version 6.x is the VMS and Unix version and is distributed as part of the Starlink software collection. Version 7.x is a complete rewrite of SPECX distributed for Windows.

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AstroImageJ: ImageJ for Astronomy

AstroImageJ is generic ImageJ (ascl:1206.013) with customizations to the base code and a packaged set of astronomy specific plugins. It reads and writes FITS images with standard headers, displays astronomical coordinates for images with WCS, supports photometry for developing color-magnitude data, offers flat field, scaled dark, and non-linearity processing, and includes tools for precision photometry that can be used during real-time data acquisition.

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VAPHOT: Precision differential aperture photometry package

VAPHOT is an aperture photometry package for precise time−series photometry of uncrowded fields, geared towards the extraction of target lightcurves of eclipsing or transiting systems. Its photometric main routine works within the IRAF (ascl:9911.002) environment and is built upon the standard aperture photometry task 'phot' from IRAF, using optimized aperture sizes. The associated analysis program 'VANALIZ' works in the IDL environment. It performs differential photometry with graphical and numerical output. VANALIZ produces plots indicative of photometric stability and permits the interactive evaluation and weighting of comparison stars. Also possible is the automatic or manual suppression of data-points and the output of statistical analyses. Several methods for the calculation of the reference brightness are offered. Specific routines for the analysis of transit 'on'-'off' photometry, comparing the target brightness inside against outside a transit are also available.

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LOSP: Liège Orbital Solution Package

LOSP is a FORTRAN77 numerical package that computes the orbital parameters of spectroscopic binaries. The package deals with SB1 and SB2 systems and is able to adjust either circular or eccentric orbits through a weighted fit.

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Spherical: Geometry operations and searches on spherical surfaces

The Spherical Library provides an efficient and accurate mathematical representation of shapes on the celestial sphere, such as sky coverage and footprints. Shapes of arbitrary complexity and size can be dynamically created from simple building blocks, whose exact area is also analytically computed. This methodology is also perfectly suited for censoring problematic parts of datasets, e.g., bad seeing, satellite trails or diffraction spikes of bright stars.

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SATMC: SED Analysis Through Monte Carlo

SATMC is a general purpose, MCMC-based SED fitting code written for IDL and Python. Following Bayesian statistics and Monte Carlo Markov Chain algorithms, SATMC derives the best fit parameter values and returns the sampling of parameter space used to construct confidence intervals and parameter-parameter confidence contours. The fitting may cover any range of wavelengths. The code is designed to incorporate any models (and potential priors) of the user's choice. The user guide lists all the relevant details for including observations, models and usage under both IDL and Python.

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VOPlot: Toolkit for Scientific Discovery using VOTables

Kale, Sonali; Vijayaraman, T. M.; Kembhavi, Ajit; Krishnan, P. R.; Navelkar, Amey, Hedge, Hrishikesh; Kulkarni, Pallavi; Balaji, K. D.

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.

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VOMegaPlot: Plotting millions of points

Urunkar, Nilesh; Kembhavi, Ajit K.; Navelkar, Ameya; Pandya, Jagruti; Moosani, Vivekananda; Nair, Prameela; Shaikh, Mohasin

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.

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