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NBODYKIT: A Massively Parallel, Large-Scale Structure Toolkit, Other Cosmology Tools and Products

Posted: Fri Nov 09, 2018 2:39 pm
by Eli
NBODYKIT is an open source project written in Python that provides a set of state-of-the-art, large-scale structure algorithms useful in the analysis of cosmological datasets from N-body simulations and observational surveys. All algorithms are massively parallel and run using the Message Passing Interface (MPI). You can dive straight and deploy NbodyKit in an interactive environment containing Jupyter Notebooks (see The Cookbook Recipes) available to users via the BinderHub service (see also BinderHub and JupyterHub with Kubernetes ), by just clicking the "launch binder" button at https://nbodykit.readthedocs.io/en/latest/index.html to get started.

NbodyKit has tons of modules and functionalities available here. See the The Cookbook and the API Reference for a quick start.

NbodyKit is compatible with Python versions 2.7, 3.5, and 3.6, and the source code is publicly available on https://github.com/bccp/nbodykit. NbodyKit has pre-built binaries and all of its dependencies available via Anaconda distribution that are compatible with Linux and macOS platforms. To avoid dependency conflicts, it is recommended to install nbodykit into a fresh virtual environment, achieved with the following commands:

  1. $ conda create --name nbodykit-env python=3 # or use python=2 for python 2.7*
  2. $ source activate nbodykit-env
  3. $ conda install -c bccp nbodykit


If you need Jupyter Notebook, you can install it using Python’s package manager, pip or Anaconda.

If using pip, first, ensure that you have the latest pip (older versions may have trouble with some dependencies):

pip3 install --upgrade pip

Then install the Jupyter Notebook using:

pip3 install jupyter

Use pip instead of pip3 if using Python 2.x.

You can then launch Jupyter Notebook as:

$jupyter notebook

If you get an error AttributeError: type object 'IOLoop' has no attribute 'initialized', just do the following:

  1. $pip uninstall tornado //Successfully uninstalled tornado-5.1
  2. $pip install tornado==4.5.3


See reasons here.

After launching the notebook, follow instructions displayed in the Terminal:

"Copy/paste this URL into your browser when you connect for the first time,
to login with a token:
http://localhost:8888/?token=c5a1a49859 ... 023a07b14a
"

See also Interactive Parallel Computing with IPython -ipyparallel

Re: NBODYKIT: A Massively Parallel, Large-Scale Structure Toolkit

Posted: Fri Apr 19, 2019 10:23 pm
by Eli
Here is another useful cosmological code:

CAMB (Code for Anisotropies in the Microwave Background), a cosmology code for calculating CMB, lensing, galaxy count, dark-age 21cm power spectra, matter power spectra and transfer functions, see Demos. The main code is written in Python with numerical calculations implemented efficiently in Python-wrapped modern Fortran. The code includes other general utility function for cosmological calculations. You can git clone it up from its GitHub repository -- CAMB.

You can run the power spectra calculations on Binder (see also gke.mybinder.org):

https://notebooks.gesis.org/binder/jupy ... demo.ipynb

Re: NBODYKIT: A Massively Parallel, Large-Scale Structure Toolkit

Posted: Mon Sep 09, 2019 1:09 pm
by Eli
Filling in cosmic microwave background map missing data using constrained Gaussian realizations

https://academic.oup.com/mnras/article/ ... 694/975988

Re: NBODYKIT: A Massively Parallel, Large-Scale Structure Toolkit

Posted: Tue Sep 10, 2019 10:58 pm
by Eli
LensPix: Fast MPI full sky transforms for HEALPix

https://cosmologist.info/lenspix/

Re: NBODYKIT: A Massively Parallel, Large-Scale Structure Toolkit

Posted: Tue Sep 17, 2019 2:54 pm
by Eli
Here is another useful astronomical software, DS9:
http://ds9.si.edu/site/Home.html

Re: NBODYKIT: A Massively Parallel, Large-Scale Structure Toolkit

Posted: Fri Sep 20, 2019 12:49 am
by Eli

Re: NBODYKIT: A Massively Parallel, Large-Scale Structure Toolkit

Posted: Fri Sep 20, 2019 9:37 pm
by Eli
Planck Sky Model http://www.apc.univ-paris7.fr/~delabrou/PSM/psm.html

PolSpice pseudo-\( C_{\ell} \) code (Chon et al. 2004): https://academic.oup.com/mnras/article/350/3/914/971848

Re: NBODYKIT: A Massively Parallel, Large-Scale Structure Toolkit, Other Cosmology Tools and Products

Posted: Sat Sep 21, 2019 3:01 pm
by Eli
Haslam 408 MHz all-sky map with filtering and strong sources removed, and Haslam 408 MHz all-sky map with no filtering -- Legacy Archive for Microwave Background Data Analysis (LAMBDA) Data Products

https://lambda.gsfc.nasa.gov/product/fo ... am_get.cfm

See also Haslam 408 MHz All-Sky Map

An improved source-subtracted and destriped Haslam 408 MHz all-sky map

http://www.jb.man.ac.uk/research/cosmos/haslam_map/

Max Planck Institute for Radio Astronomy (MPIfR ) Survey Sampler website

http://www3.mpifr-bonn.mpg.de/survey.html

Re: NBODYKIT: A Massively Parallel, Large-Scale Structure Toolkit, Other Cosmology Tools and Products

Posted: Mon Sep 23, 2019 12:56 pm
by Eli
This wiki site maintained by the European Space Agency (ESA) contains 2015 CMB spectra and likelihood code, and description of various CMB measurements likelihood and power spectra.

The 2015 Explanatory Supplement is contained in this location.

The latest Planck Legacy Explanatory Supplement contains the descriptions of all the Planck products, including the 2013, 2015 and 2018 data releases. Previous instances of the Explanatory Supplement (2013 and 2015), including this one, are not fully up-to-date and have been discontinued during 2018.

The up-to-date link is associated to the famous Planck papers:

Planck 2013 results. XVI. Cosmological parameters

https://arxiv.org/abs/1303.5076

Planck 2015 results. XIII. Cosmological parameters

https://arxiv.org/abs/1502.01589

Planck 2018 results. VI. Cosmological parameters

https://arxiv.org/abs/1807.06209

Re: NBODYKIT: A Massively Parallel, Large-Scale Structure Toolkit, Other Cosmology Tools and Products

Posted: Fri Oct 04, 2019 10:10 pm
by Eli
FastICA: a fast algorithm for Independent Component Analysis

https://scikit-learn.org/stable/modules ... stICA.html

Test Jupyter notebook yourself.