PhotoCov#

class cosmicjellyfish.LSSsurvey.photo_cov.PhotoCov(cosmopars, photopars, IApars, biaspars, fiducial_Cls=None, enable_cache=True, cache_size=32, *, configuration=None)[source]#

Bases: object

getcls(allpars)[source]#

Function to calculate the angular power spectrum

Parameters:: allpars (dict) – a dictionary with all parameters needed to compute the angular power spectrum
Returns:: a dictionary with all the auto and cross correlation angular power spectra
Return type:: dict

getclsnoise(cls)[source]#

Obtain the angular power spectrum with noise

Parameters:: cls (dict) – a dictionary with all the auto and cross correlation angular power spectra
Returns:: a dictionary with all the auto and cross correlation angular power spectra with noise added to it
Return type:: dict

Note

Implements the following equation:

\[ \begin{align}\begin{aligned}N_{ij}^{YX}(\ell) = \frac{\sigma_X^2}{\bar{n}_i}\,\delta_{XY}\,\delta_{ij}\\\sigma_L = \sigma_\epsilon \quad , \quad \sigma_G = 1\end{aligned}\end{align} \]

get_covmat(noisy_cls)[source]#

Computes the covariance matrix from the noisy angular power spectrum

Parameters:: noisy_cls (dict) – a dictionary with all the auto and cross correlation angular power spectra with noise added to it
Returns:: A list of pandas.DataFrame objects that store the covariance matrix for each multipole
Return type:: list

compute_covmat()[source]#

Computes the fiducial covariance matrix for the Fisher matrix.

Returns:

dict – a dictionary with all the auto and cross correlation fiducial angular power spectra with noise added to it
list – A list of pandas.DataFrame objects that store the covariance matrix for each multipole

compute_derivs(print_info_specs=False, *, derivative_provider=None)[source]#

computes the derivatives of the angular power spectrum needed to compute the Fisher matrix

Returns:: a dictionary containing the derivatives of the angular power spectrum at the fiducial for all free parameters
Return type:: dict