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planck2015_simple module
Simplified Likelihood function of CMB from Planck 2015 TT TE EE data
Name: planck2015_simple
File: cosmosis-standard-library/likelihood/planck2015_simple/planck2015_simple.py
Version: 2
Author(s):
- The Planck Collaboration (Data)
- CosmoSIS Team (Code)
URL:
Cite:
Rules:
- Please cite the appropriate Planck paper
Assumptions:
- Highly accurate CMB calculations are required
- In the high-ell regime models for the foregrounds and secondary anisotropies are assumed
Explanation
See the Planck2015 module for general information about Planck.
This module provides a greatly simplified form of the Planck likelihood supplied
in plik_lite_v18_TT.clik, which should not be used for high-precision cosmology
but should be alright for e.g. Fisher matrix forecasting.
It turns the data in that file into just a Gaussian likelihood, ignoring the nuisance
parameter.
##Parameters
These parameters can be set in the module's section in the ini parameter file.
If no default is specified then the parameter is required.
Parameter | Description |
---|---|
data_file | (String; default=data.txt) Text file containing ell in col 1 and TT TE and EE in col 2 (no ell(ell+1) factor) |
covmat_file | (String; default=covmat.txt) Numpy format file containing covariance matrix |
##Inputs
These parameters and data are inputs to the module, either supplied as parameters by the sampler or computed by some previous module. They are loaded from the data block.
Section | Parameter | Description |
---|---|---|
cmb_cl | ell | Integer vector of angular frequencies for CMB spectra |
tt | Double vector of temperature spectra in l*(l+1) C_ell / uK^2 (if using TT data) | |
ee | Double vector of E-mode polarization spectra in l*(l+1) C_ell / uK^2 (if using pol data) | |
te | Double vector of cross spectra in l*(l+1) C_ell / uK^2 (if using pol data) |
##Outputs
These parameters and data are computed as outputs from the module
Section | Parameter | Description |
---|---|---|
likelihoods | planck2014_simple_like | (real; only if data_1 specified) Log-likelihood from first file |
Updated