Results 901-950 of 1932 (1899 ASCL, 33 submitted)

[ascl:1408.009]
IIPImage: Large-image visualization

IIPImage is an advanced high-performance feature-rich image server system that enables online access to full resolution floating point (as well as other bit depth) images at terabyte scales. Paired with the VisiOmatic (ascl:1408.010) celestial image viewer, the system can comfortably handle gigapixel size images as well as advanced image features such as both 8, 16 and 32 bit depths, CIELAB colorimetric images and scientific imagery such as multispectral images. Streaming is tile-based, which enables viewing, navigating and zooming in real-time around gigapixel size images. Source images can be in either TIFF or JPEG2000 format. Whole images or regions within images can also be rapidly and dynamically resized and exported by the server from a single source image without the need to store multiple files in various sizes.

[ascl:1408.010]
VisiOmatic: Celestial image viewer

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

[ascl:1408.011]
GALAPAGOS-C: Galaxy Analysis over Large Areas

GALAPAGOS-C is a C implementation of the IDL code GALAPAGOS (ascl:1203.002). It processes a complete set of survey images through automation of source detection via SExtractor (ascl:1010.064), postage stamp cutting, object mask preparation, sky background estimation and complex two-dimensional light profile Sérsic modelling via GALFIT (ascl:1104.010). GALAPAGOS-C uses MPI-parallelization, thus allowing quick processing of large data sets. The code can fit multiple Sérsic profiles to each galaxy, each representing distinct galaxy components (e.g. bulge, disc, bar), and optionally can fit asymmetric Fourier mode distortions.

[ascl:1408.012]
LightcurveMC: An extensible lightcurve simulation program

LightcurveMC is a versatile and easily extended simulation suite for testing the performance of time series analysis tools under controlled conditions. It is designed to be highly modular, allowing new lightcurve types or new analysis tools to be introduced without excessive development overhead. The statistical tools are completely agnostic to how the lightcurve data is generated, and the lightcurve generators are completely agnostic to how the data will be analyzed. The use of fixed random seeds throughout guarantees that the program generates consistent results from run to run.

LightcurveMC can generate periodic light curves having a variety of shapes and stochastic light curves having a variety of correlation properties. It features two error models (Gaussian measurement and signal injection using a randomized sample of base light curves), testing of C1 shape statistic, periodograms, ΔmΔt plots, autocorrelation function plots, peak-finding plots, and Gaussian process regression. The code is written in C++ and R.

[ascl:1408.013]
NumCosmo: Numerical Cosmology

NumCosmo is a free software C library whose main purposes are to test cosmological models using observational data and to provide a set of tools to perform cosmological calculations. The software implements three different probes: cosmic microwave background (CMB), supernovae type Ia (SNeIa) and large scale structure (LSS) information, such as baryonic acoustic oscillations (BAO) and galaxy cluster abundance. The code supports a joint analysis of these data and the parameter space can include cosmological and phenomenological parameters. NumCosmo matter power spectrum and CMB codes were written independent of other implementations such as CMBFAST (ascl:9909.004), CAMB (ascl:1102.026), etc.

The library structure simplifies the inclusion of non-standard cosmological models. Besides the functions related to cosmological quantities, this library also implements mathematical and statistical tools. The former were developed to enable the inclusion of other probes and/or theoretical models and to optimize the codes. The statistical framework comprises algorithms which define likelihood functions, minimization, Monte Carlo, Fisher Matrix and profile likelihood methods.

[ascl:1408.014]
pieflag: CASA task to efficiently flag bad data

pieflag compares bandpass-calibrated data to a clean reference channel and identifies and flags essentially all bad data. pieflag compares visibility amplitudes in each frequency channel to a 'reference' channel that is rfi-free (or manually ensured to be rfi-free). pieflag performs this comparison independently for each correlation on each baseline, but will flag all correlations if threshold conditions are met. To operate effectively, pieflag must be supplied with bandpass-calibrated data. pieflag has two core modes of operation (static and dynamic flagging) with an additional extend mode; the type of data largely determines which mode to choose. Instructions for pre-processing data and selecting the mode of operation are provided in the help file. Once pre-processing and selecting the mode of operation are done, pieflag should work well 'out of the box' with its default parameters.

[ascl:1408.015]
VPFIT: Voigt profile fitting program

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

[ascl:1408.016]
vpguess: Fitting multiple Voigt profiles to spectroscopic data

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

[ascl:1408.017]
RDGEN: Routines for data handling, display, and adjusting

RDGEN is a collection of routines for data handling, display, and adjusting, with a facility which helps to set up files for using with VPFIT (ascl:1408.015); it is included in the VPFIT distribution file. It is useful for setting region boundaries and initial guesses for VPFIT, for displaying the accumulated results, for examining by eye particular redshift systems and fits to them, testing that the error array is a true reflection of the rms scatter in the data, comparing spectra and generally examining and even modifying the data.

[ascl:1408.018]
CosmoPhotoz: Photometric redshift estimation using generalized linear models

de Souza, Rafael S.; Elliott, Jonathan; Krone-Martins, Alberto; Ishida, Emille E. O.; Hilbe, Joseph; Cameron, Ewan

CosmoPhotoz determines photometric redshifts from galaxies utilizing their magnitudes. The method uses generalized linear models which reproduce the physical aspects of the output distribution. The code can adopt gamma or inverse gaussian families, either from a frequentist or a Bayesian perspective. A set of publicly available libraries and a web application are available. This software allows users to apply a set of GLMs to their own photometric catalogs and generates publication quality plots with no involvement from the user. The code additionally provides a Shiny application providing a simple user interface.

[ascl:1408.019]
O_{2}scl: Object-oriented scientific computing library

O_{2}scl 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. O_{2}scl 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. O_{2}scl can be used on Linux, Mac and Windows (Cygwin) platforms and has extensive documentation.

[ascl:1408.020]
bamr: Bayesian analysis of mass and radius observations

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 O_{2}scl (ascl:1408.019) be installed before compilation.

[ascl:1408.021]
APS: Active Parameter Searching

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.

[ascl:1408.022]
PhotoRApToR: PHOTOmetric Research APplication TO Redshifts

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.

[ascl:1408.023]
WSClean: Widefield interferometric imager

Offringa, A. R.; McKinley, B.; Hurley-Walker, N.; Briggs, F. H.; Wayth, R. B.; Kaplan, D. L.; Bell, M. E.; Feng, L.; Neben, A. R.; Hughes, J. D.; Rhee, J.; Murphy, T.; Bhat, N. D. R.; Bernardi, G.; Bowman, J. D.; Cappallo, R. J.; Corey, B. E.; Deshpande, A. A.; Emrich, D.; Ewall-Wice, A.; Gaensler, B. M.; Goeke, R.; Greenhill, L. J.; Hazelton, B. J.; Hindson, L.; Johnston-Hollitt, M.; Jacobs, D. C.; Kasper, J. C.; Kratzenberg, E.; Lenc, E.; Lonsdale, C. J.; Lynch, M. J.; McWhirter, S. R.; Mitchell, D. A.; Morales, M. F.; Morgan, E.; Kudryavtseva, N.; Oberoi, D.; Ord, S. M.; Pindor, B.; Procopio, P.; Prabu, T.; Riding, J.; Roshi, D. A.; Shankar, N. Udaya; Srivani, K. S.; Subrahmanyan, R.; Tingay, S. J.; Waterson, M.; Webster, R. L.; Whitney, A. R.; Williams, A.; Williams, C. L.

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.

[ascl:1409.001]
mixT: single-temperature fit for a multi-component thermal plasma

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.

[ascl:1409.002]
Tsyganenko Geomagnetic Field Models

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.

[ascl:1409.003]
LANL*: Radiation belt drift shell modeling

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.

[ascl:1409.004]
IFSRED: Data Reduction for Integral Field Spectrographs

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).

[ascl:1409.005]
IFSFIT: Spectral Fitting for Integral Field Spectrographs

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.

[ascl:1409.006]
iSpec: Stellar atmospheric parameters and chemical abundances

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).

[ascl:1409.007]
ORBS: A reduction software for SITELLE and SpiOMM data

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).

[ascl:1409.008]
CHLOE: A tool for automatic detection of peculiar galaxies

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.

[ascl:1409.009]
Nahoon: Time-dependent gas-phase chemical model

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 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.

[ascl:1409.010]
Slim: Numerical data compression for scientific data sets

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.

[ascl:1409.011]
rmfit: Forward-folding spectral analysis software

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.

[ascl:1409.012]
CosmoSIS: Cosmological parameter estimation

Zuntz, Joe; Paterno, Marc; Jennings, Elise; Rudd, Douglas; Manzotti, Alessandro; Dodelson, Scott; Bridle, Sarah; Sehrish, Saba; Kowalkowski, James

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.

[ascl:1409.013]
IM3SHAPE: Maximum likelihood galaxy shear measurement code for cosmic gravitational lensing

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.

[ascl:1410.001]
DIAMONDS: high-DImensional And multi-MOdal NesteD Sampling

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.

[ascl:1410.002]
MEPSA: Multiple Excess Peak Search Algorithm

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.

[ascl:1410.003]
GIZMO: Multi-method magneto-hydrodynamics+gravity code

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).

[ascl:1410.004]
UVOTPY: Swift UVOT grism data reduction

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.

[ascl:1410.005]
RICH: Numerical simulation of compressible hydrodynamics on a moving Voronoi mesh

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.

[ascl:1411.001]
pyGadgetReader: GADGET snapshot reader for python

pyGadgetReader is a universal GADGET snapshot reader for python that supports type-1, type-2, HDF5, and TIPSY (ascl:1111.015) binary formats. It additionally supports reading binary outputs from FoF_Special, P-StarGroupFinder, Rockstar (ascl:1210.008), and Rockstar-Galaxies.

[ascl:1411.002]
pysovo: A library for implementing alerts triggered by VOEvents

pysovo contains basic tools to work with VOEvents. Though written for specific needs, others interested in VOEvents may find it useful to examine.

[ascl:1411.003]
voevent-parse: Parse, manipulate, and generate VOEvent XML packets

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.

[ascl:1411.004]
OPERA: Open-source Pipeline for Espadons Reduction and Analysis

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.

[ascl:1411.005]
HOPE: Just-in-time Python compiler for astrophysical computations

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.

[ascl:1411.006]
RC3 mosaicking pipeline: Creating mosaics for the RC3 Catalogue

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

http://lcdm.astro.illinois.edu/data/rc3/search.html.

[ascl:1411.007]
segueSelect: SDSS/SEGUE selection function modelling

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.

[ascl:1411.008]
galpy: Galactic dynamics package

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.

[ascl:1411.009]
iDealCam: Interactive Data Reduction and Analysis for CanariCam

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.

[ascl:1411.010]
Raga: Monte Carlo simulations of gravitational dynamics of non-spherical stellar systems

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.

[ascl:1411.011]
PyMGC3: Finding stellar streams in the Galactic Halo using a family of Great Circle Cell counts methods

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.

[ascl:1411.012]
util_2comp: Planck-based two-component dust model utilities

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.

[ascl:1411.013]
NEAT: Nebular Empirical Analysis Tool

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.

[ascl:1411.014]
NAFE: Noise Adaptive Fuzzy Equalization

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.

[ascl:1411.015]
SPOTROD: Semi-analytic model for transits of spotted stars

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.

[ascl:1411.016]
Flicker: Mean stellar densities from flicker

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.

[ascl:1411.017]
ECCSAMPLES: Bayesian Priors for Orbital Eccentricity

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.

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