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Astrophysics Source Code Library

Making codes discoverable since 1999

Searching for codes credited to 'Amara, A'

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[ascl:1010.034] iCosmo: An Interactive Cosmology Package

iCosmo is a software package to perform interactive cosmological calculations for the low redshift universe. The computation of distance measures, the matter power spectrum, and the growth factor is supported for any values of the cosmological parameters. It also performs the computation of observables for several cosmological probes such as weak gravitational lensing, baryon acoustic oscillations and supernovae. The associated errors for these observables can be derived for customised surveys, or for pre-set values corresponding to current or planned instruments. The code also allows for the calculation of cosmological forecasts with Fisher matrices which can be manipulated to combine different surveys and cosmological probes. The code is written in the IDL language and thus benefits from the convenient interactive features and scientific library available in this language. iCosmo can also be used as an engine to perform cosmological calculations in batch mode, and forms a convenient evolutive platform for the development of further cosmological modules. With its extensive documentation, it may also serve as a useful resource for teaching and for newcomers in the field of cosmology.

[ascl:1010.041] FASTLens (FAst STatistics for weak Lensing): Fast Method for Weak Lensing Statistics and Map Making

The analysis of weak lensing data requires to account for missing data such as masking out of bright stars. To date, the majority of lensing analyses uses the two point-statistics of the cosmic shear field. These can either be studied directly using the two-point correlation function, or in Fourier space, using the power spectrum. The two-point correlation function is unbiased by missing data but its direct calculation will soon become a burden with the exponential growth of astronomical data sets. The power spectrum is fast to estimate but a mask correction should be estimated. Other statistics can be used but these are strongly sensitive to missing data. The solution that is proposed by FASTLens is to properly fill-in the gaps with only NlogN operations, leading to a complete weak lensing mass map from which one can compute straight forwardly and with a very good accuracy any kind of statistics like power spectrum or bispectrum.

[ascl:1303.003] CosmoHammer: Cosmological parameter estimation with the MCMC Hammer

CosmoHammer is a Python framework for the estimation of cosmological parameters. The software embeds the Python package emcee by Foreman-Mackey et al. (2012) and gives the user the possibility to plug in modules for the computation of any desired likelihood. The major goal of the software is to reduce the complexity when one wants to extend or replace the existing computation by modules which fit the user's needs as well as to provide the possibility to easily use large scale computing environments. CosmoHammer can efficiently distribute the MCMC sampling over thousands of cores on modern cloud computing infrastructure.

[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:1501.001] PynPoint: Exoplanet image data analysis

PynPoint uses principal component analysis to detect and estimate the flux of exoplanets in two-dimensional imaging data. It processes many, typically several thousands, of frames to remove the light from the star so as to reveal the companion planet.

The code has been significantly rewritten and expanded; please see ascl:1812.010.

[ascl:1607.019] HIDE: HI Data Emulator

HIDE (HI Data Emulator) forward-models the process of collecting astronomical radio signals in a single dish radio telescope instrument and outputs pixel-level time-ordered-data. Written in Python, HIDE models the noise and RFI modeling of the data and with its companion code SEEK (ascl:1607.020) provides end-to-end simulation and processing of radio survey data.

[ascl:1607.020] SEEK: Signal Extraction and Emission Kartographer

SEEK (Signal Extraction and Emission Kartographer) processes time-ordered-data from single dish radio telescopes or from the simulation pipline HIDE (ascl:1607.019), removes artifacts from Radio Frequency Interference (RFI), automatically applies flux calibration, and recovers the astronomical radio signal. With its companion code HIDE (ascl:1607.019), it provides end-to-end simulation and processing of radio survey data.

[ascl:1804.012] Lenstronomy: Multi-purpose gravitational lens modeling software package

Lenstronomy is a multi-purpose open-source gravitational lens modeling python package. Lenstronomy reconstructs the lens mass and surface brightness distributions of strong lensing systems using forward modelling and supports a wide range of analytic lens and light models in arbitrary combination. The software is also able to reconstruct complex extended sources as well as point sources. Lenstronomy is flexible and numerically accurate, with a clear user interface that could be deployed across different platforms. Lenstronomy has been used to derive constraints on dark matter properties in strong lenses, measure the expansion history of the universe with time-delay cosmography, measure cosmic shear with Einstein rings, and decompose quasar and host galaxy light.

[ascl:1812.010] PynPoint 0.6.0: Pipeline for processing and analysis of high-contrast imaging data

PynPoint processes and analyzes high-contrast imaging data of exoplanets and circumstellar disks. The generic, end-to-end pipeline's modular architecture separates the core functionalities and the pipeline modules. These modules have specific tasks such as background subtraction, frame selection, centering, PSF subtraction with principal component analysis, estimation of detection limits, and photometric and astrometric analysis. All modules store their results in a central database. Management of the available hardware by the backend of the pipeline is in particular an advantage for data sets containing thousands of images, as is common in the mid-infrared wavelength regime. This version of PynPoint is a significant rewrite of the earlier PynPoint package (ascl:1501.001).