https://github.com/julienpeloton/lenscov
Full CMB and lensing covariances
https://github.com/julienpeloton/lenscov
cmb covariance lensing
Last synced: 3 months ago
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Full CMB and lensing covariances
- Host: GitHub
- URL: https://github.com/julienpeloton/lenscov
- Owner: JulienPeloton
- License: gpl-3.0
- Created: 2016-12-03T21:23:46.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2019-03-08T06:35:34.000Z (about 6 years ago)
- Last Synced: 2025-01-16T04:10:44.590Z (5 months ago)
- Topics: cmb, covariance, lensing
- Language: Fortran
- Homepage:
- Size: 1.89 MB
- Stars: 5
- Watchers: 5
- Forks: 3
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
lenscov
==
#### The package
This package contains scripts for computing CMB and lensing covariances
as described in Peloton et al. 2016 (https://arxiv.org/abs/1611.01446)
It has routines for:
* Spectra
* computing (analytically) the N0 bias (curve- and flat-sky available)
* computing (analytically) the N1 bias (only flat-sky available)
* computing CMB lensed power spectra using series-expansion
* computing CMB lensed power spectra using correlation functions
* Covariances
* computing (analytically) the covariance matrix of
CMB lensed spectra up to second order in lensing potential power-spectrum
* computing (analytically) the covariance matrix of
lensing potential spectrum
* computing (analytically) the cross-covariance matrix of
CMB lensed spectra and lensing potential spectrum up to
second order in lensing potential power-spectrum
* Additional
* computing derivatives of spectra using correlation functions
* computing wigner (small) d-matrix efficiently
The code performs computation in the full-sky formalism, except the computation of N1
biases and their derivatives (see the LensingBiases package).
The code is fully-parallelized using mpi4py,
and some Fortran parts make use of openmp (computation of N1).
### Before starting
This code has the following dependencies:
* numpy, pylab, etc (required)
* scipy (required, for C interfacing)
* f2py (required, for Fortran interfacing)
* mpi4py (optional, to use parallel computing)
* LensingBiases (optional, to compute lensing biases)
Make sure you update your PYTHONPATH to use the code.
Just add in your bashrc:
```bash
COVPATH=/path/to/the/package
export PYTHONPATH=$PYTHONPATH:$COVPATH:$COVPATH/src
```
### Compilation of C and Fortran
The code is primarily written in Python, although the low-level routines
(wigner3-j, nested loops, etc) are implemented in Fortran and C,
and interfaced with Python. The compilation of C is done on-the-fly
through scipy.weave. The compilation of Fortran is done either using the
setup file, by running:
```bash
python setup.py build_ext --inplace --fcompiler=gfortran
```
Depending on system, you may need to specify a different fortran compiler.
The compilation has been tested successfully with gfortran (gcc version 5.1.0) and ifort.
For the purist, we also provide a Makefile for a direct compilation.
### Usage
You can find a launcher (run_covariances.sh) to have a quick usage.
We also provide a batch file for usage on cluster.
You have pre-defined experimental configurations in misc.py.
### License
GNU License (see the LICENSE file for details) covers all files
in the lenscov repository unless stated otherwise.