cosmicpy.fisher – Fisher forecasts¶

class cosmicpy.fisher.fisher(fid_cosmo, fid_survey, params, margin_params=[])[source]¶

Bases: object

Base class to perform a Fisher Analysis from specified cosmology, survey and cosmological parameters.

Fij(param_i, param_j)[source]¶

Returns the matrix element of the Fisher matrix for parameters param_i and param_j

FoM[source]¶

Total figure of merit – ln (1/det(F^{-1}))

FoM_DETF[source]¶

Computes the figure of merit from the Dark Energy Task Force Albrecht et al 2006 FoM = 1/sqrt(det(F^-1_{w0,wa}))

corner_plot(nstd=2, labels=None, **kwargs)[source]¶

Makes a corner plot including all the parameters in the Fisher analysis

invFij(param_i, param_j)[source]¶

Returns the matrix element of the inverse Fisher matrix for parameters param_i and param_j

invmat[source]¶

Returns the inverse fisher matrix

mat[source]¶

Returns the fisher matrix marginalised over nuisance parameters

plot(p1, p2, nstd=2, ax=None, **kwargs)[source]¶

Plots confidence contours corresponding to the parameters provided.

sub_matrix(subparams)[source]¶

Extracts a submatrix from the current fisher matrix using the parameters in params

class cosmicpy.fisher.fisher3d(fid_cosmo, fid_survey, params, margin_params=, []cutNonLinearScales=True)[source]¶

Bases: cosmicpy.fisher.fisher

Full 3D fisher analysis using the Spherical Fourier-Bessel expansion

class cosmicpy.fisher.fisherTomo(fid_cosmo, fid_survey, params, probes, margin_params=, []cutNonLinearScales=None, lmax=10000, nl=200, lmin=2, diagonal=False)[source]¶

Bases: cosmicpy.fisher.fisher

Tomographic Fisher matrix