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[ascl:1007.004]
CMBEASY: An object-oriented code for the cosmic microwave background

CMBEASY is a software package for calculating the evolution of density fluctuations in the universe. Most notably, the Cosmic Microwave Background temperature anisotropies. It features a Markov Chain Monte Carlo driver and many routines to compute likelihoods of any given model. It is based on the CMBFAST package by Uros Seljak and Matias Zaldarriaga.

[ascl:1010.047]
ISW and Weak Lensing Likelihood Code

ISW and Weak Lensing Likelihood code is the likelihood code that calculates the likelihood of Integrated Sachs Wolfe and Weak Lensing of Cosmic Microwave Background using the WMAP 3year CMB maps with mass tracers such as 2MASS (2-Micron All Sky Survey), SDSS LRG (Sloan Digital Sky Survey Luminous Red Galaxies), SDSS QSOs (Sloan Digital Sky Survey Quasars) and NVSS (NRAO VLA All Sky Survey) radio sources. The details of the analysis (*thus the likelihood code) can be understood by reading the papers ISW paper and Weak lensing paper. The code does brute force theoretical matter power spectrum and calculations with CAMB. See the paper for an introduction, descriptions, and typical results from some pre-WMAP data. The code is designed to be integrated into CosmoMC. For further information concerning the integration, see Code Modification for integration into COSMOMC.

[ascl:1904.028]
covdisc: Disconnected covariance of 2-point functions in large-scale structure of the Universe

covdisc computes the disconnected part of the covariance matrix of 2-point functions in large-scale structure studies, accounting for the survey window effect. This method works for both power spectrum and correlation function, and applies to the covariances for various probes including the multi- poles and the wedges of 3D clustering, the angular and the projected statistics of clustering and lensing, as well as their cross covariances.

[ascl:1904.027]
nbodykit: Massively parallel, large-scale structure toolkit

nbodykit provides algorithms for analyzing cosmological datasets from N-body simulations and large-scale structure surveys, and takes advantage of the abundance and availability of large-scale computing resources. The package provides a unified treatment of simulation and observational datasets by insulating algorithms from data containers, and reduces wall-clock time by scaling to thousands of cores. All algorithms are parallel and run with Message Passing Interface (MPI); the code is designed to be deployed on large super-computing facilities. nbodykit offers an interactive user interface that performs as well in a Jupyter notebook as on super-computing machines.

[ascl:1904.026]
pyRSD: Accurate predictions for the clustering of galaxies in redshift-space in Python

pyRSD computes the theoretical predictions of the redshift-space power spectrum of galaxies. It also includes functionality for fitting data measurements and finding the optimal model parameters, using both MCMC and nonlinear optimization techniques.