https://github.com/msyriac/weak-lensing

Implement KSB methods for determining cosmic shear and confirm the emergence of bias. Explore Bayesian methods of inferring shear.
https://github.com/msyriac/weak-lensing

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Implement KSB methods for determining cosmic shear and confirm the emergence of bias. Explore Bayesian methods of inferring shear.

• Host: GitHub
• URL: https://github.com/msyriac/weak-lensing
• Owner: msyriac
• Created: 2013-08-17T17:59:55.000Z (almost 12 years ago)
• Default Branch: master
• Last Pushed: 2014-06-23T19:45:46.000Z (almost 11 years ago)
• Last Synced: 2025-02-07T16:19:54.736Z (4 months ago)
• Language: Python
• Size: 605 KB
• Stars: 2
• Watchers: 3
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
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weak-lensing

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Implement KSB methods for determining cosmic shear and confirm the emergence of bias. Explore Bayesian methods of inferring shear.

toy.py

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uncorrelated galaxies for a given shear

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Do not use the -p option 

E.g.

python toy.py -n  -1  -2  -e  -s  -t  -i  

Add -d if you want to display average time per galaxy

This will save a file "gi.csv" to "data/"

where  is a time stamp and  is the index you specified above. Make sure you provide unique indices to each cluster job so that the jobs don't write over each other and make a mess.

The CSV files are comma separated with the format P,Q1,Q2,R11,R12,R22.

correlated pairs

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Use the -p option but don't specify -1 or -2

E.g.

python toy.py -p -n  -e  -s  -t  -i  

This will draw n pairs (g,h) from generate_pairs.py.

It will calculate P,Q,R for these pairs.

And it will save files "gi.csv" and "hi.csv" to "data/"

where  is a time stamp and  is the index you specified above. Make sure you provide unique indices to each cluster job so that the jobs don't write over each other and make a mess.

The CSV files are comma separated with the format P,Q1,Q2,R11,R12,R22.

postprocess.py (for uncorrelated galaxies of a given shear)

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This will process every CSV file in a specified directory assuming they contain P,Q,R for uncorrelated galaxies of a specified shear.

And it will infer that shear.

No command line options yet.

pairs_postprocess.py (for correlated pairs)

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This will process every CSV file in a specified directory assuming they contain P,Q,R for correlated pairs.

And it will try to infer the covmat.

No command line options yet.