https://github.com/tmcclintock/ccv_preparation

This is a collection of scripts needed to prepare SV and Y1 data for computing the CCV covariance matrices.
https://github.com/tmcclintock/ccv_preparation

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This is a collection of scripts needed to prepare SV and Y1 data for computing the CCV covariance matrices.

• Host: GitHub
• URL: https://github.com/tmcclintock/ccv_preparation
• Owner: tmcclintock
• License: gpl-3.0
• Created: 2016-11-29T22:02:27.000Z (about 8 years ago)
• Default Branch: master
• Last Pushed: 2017-10-25T14:51:51.000Z (about 7 years ago)
• Last Synced: 2024-10-27T11:09:02.833Z (2 months ago)
• Language: Python
• Size: 27.3 KB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# ccv_preparation

This is a collection of scripts needed to prepare SV and Y1 data 

for computing the CCV covariance matrices.

In order to run ccv you do:

./src/getmodel_g [output.fits] [zlens] [annuli_prefix] [zsource or p(z) prefix] [M200m/(h_^{-1}Msol)] ([cconc=1] [ccorr=5.0] [cell=3.7] [coff=0] [clss=0])

For zlens right now we are assuming z=0.24533 since we only have 

templates at the redshift for now. For the annuli prefix we can use 

thetas_z0_l0 for now. We only have pz for our p(z) prefix for now, 

but we will have one later for each redshift bin.

The amplitudes are unknown at the moment. For now we will use 

1 for everything.