https://github.com/tmcclintock/catalog_analysis

This is an interface to a suite of applications that take in cluster, dark matter, and random catalogs and generates a variety of data vectors associated with them.
https://github.com/tmcclintock/catalog_analysis

Last synced: 14 days ago
JSON representation

This is an interface to a suite of applications that take in cluster, dark matter, and random catalogs and generates a variety of data vectors associated with them.

• Host: GitHub
• URL: https://github.com/tmcclintock/catalog_analysis
• Owner: tmcclintock
• Created: 2016-05-18T18:17:35.000Z (over 8 years ago)
• Default Branch: master
• Last Pushed: 2016-09-07T02:53:59.000Z (over 8 years ago)
• Last Synced: 2024-12-14T17:09:20.291Z (about 1 month ago)
• Language: Python
• Size: 76.2 KB
• Stars: 0
• Watchers: 3
• Forks: 0
• Open Issues: 1
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# catalog_analysis

This is an interface to a suite of applications that take in a path to a rockstar simulation and creates a DeltaSigma signal from them.

The algorithm will look like the following:

1) The user supplies a path to a rockstar simulation output.

2) Create halo subcatalogs that are binned in mass ranges.

3) Jackknife the halo subcatalogs.

4) Use TreeCorr on the jackknife regions to calculate correlation and cross-correlations. Resum these to get full 3D correlation functions.

5) Run the DeltaSigmaBuilder to create DeltaSigma curves for each leave-one-out JK realization. Resum these to get full DeltaSigma curves.

Required modules:

numpy

scipy

matplotlib

pygadgetreader (By Ryan Thompson)

treecorr (By Mike Jarvis)

collossus (By Benedikt Diemer)