class MontePythonLike::Likelihood_newdat
[No description available]
Inherits from MontePythonLike.Likelihood, MontePythonLike.Likelihood, object
Public Functions
| Name | |
|---|---|
| def | init(self self, path path, data data, command_line command_line) |
| def | loglkl(self self, cosmo cosmo, data data) |
| def | compute_lkl(self self, cl cl, cosmo cosmo, data data) |
| def | init(self self, path path, data data, command_line command_line) |
| def | loglkl(self self, cosmo cosmo, data data) |
| def | compute_lkl(self self, cl cl, cosmo cosmo, data data) |
Public Attributes
| Name | |
|---|---|
| calib_uncertainty | |
| has_beam_uncertainty | |
| has_xfactors | |
| obs | |
| var | |
| beam_error | |
| has_xfactor | |
| xfactor | |
| num_points | |
| inv_covmat | |
| win_min | |
| win_max | |
| has_pol | |
| window | |
| halfsteps | |
| margeweights | |
| margenorm | |
| l_max | |
| nuisance | |
| use_nuisance | |
| lkl |
Additional inherited members
Public Functions inherited from MontePythonLike.Likelihood
| Name | |
|---|---|
| def | raise_fiducial_model_err(self self) |
| def | read_from_file(self self, path path, data data, command_line command_line) |
| def | get_cl(self self, cosmo cosmo, l_max l_max =-1) |
| def | get_unlensed_cl(self self, cosmo cosmo, l_max l_max =-1) |
| def | need_cosmo_arguments(self self, data data, dictionary dictionary) |
| def | read_contamination_spectra(self self, data data) |
| def | add_contamination_spectra(self self, cl cl, data data) |
| def | add_nuisance_prior(self self, lkl lkl, data data) |
| def | computeLikelihood(self self, ctx ctx) |
| def | raise_fiducial_model_err(self self) |
| def | read_from_file(self self, path path, data data, command_line command_line) |
| def | get_cl(self self, cosmo cosmo, l_max l_max =-1) |
| def | get_unlensed_cl(self self, cosmo cosmo, l_max l_max =-1) |
| def | need_cosmo_arguments(self self, data data, dictionary dictionary) |
| def | read_contamination_spectra(self self, data data) |
| def | add_contamination_spectra(self self, cl cl, data data) |
| def | add_nuisance_prior(self self, lkl lkl, data data) |
| def | computeLikelihood(self self, ctx ctx) |
Public Attributes inherited from MontePythonLike.Likelihood
| Name | |
|---|---|
| name | |
| folder | |
| data_directory | |
| default_values | |
| need_update | |
| path | |
| dictionary |
Public Functions inherited from MontePythonLike.Likelihood
| Name | |
|---|---|
| def | raise_fiducial_model_err(self self) |
| def | read_from_file(self self, path path, data data, command_line command_line) |
| def | get_cl(self self, cosmo cosmo, l_max l_max =-1) |
| def | get_unlensed_cl(self self, cosmo cosmo, l_max l_max =-1) |
| def | need_cosmo_arguments(self self, data data, dictionary dictionary) |
| def | read_contamination_spectra(self self, data data) |
| def | add_contamination_spectra(self self, cl cl, data data) |
| def | add_nuisance_prior(self self, lkl lkl, data data) |
| def | computeLikelihood(self self, ctx ctx) |
| def | raise_fiducial_model_err(self self) |
| def | read_from_file(self self, path path, data data, command_line command_line) |
| def | get_cl(self self, cosmo cosmo, l_max l_max =-1) |
| def | get_unlensed_cl(self self, cosmo cosmo, l_max l_max =-1) |
| def | need_cosmo_arguments(self self, data data, dictionary dictionary) |
| def | read_contamination_spectra(self self, data data) |
| def | add_contamination_spectra(self self, cl cl, data data) |
| def | add_nuisance_prior(self self, lkl lkl, data data) |
| def | computeLikelihood(self self, ctx ctx) |
Public Attributes inherited from MontePythonLike.Likelihood
| Name | |
|---|---|
| name | |
| folder | |
| data_directory | |
| default_values | |
| need_update | |
| path | |
| dictionary |
Public Functions Documentation
function init
def __init__(
self self,
path path,
data data,
command_line command_line
)
Reimplements: MontePythonLike::Likelihood::init
It copies the content of self.path from the initialization routine of
the :class:`Data <data.Data>` class, and defines a handful of useful
methods, that every likelihood might need.
If the nuisance parameters required to compute this likelihood are not
defined (either fixed or varying), the code will stop.
Parameters
----------
data : class
Initialized instance of :class:`Data <data.Data>`
command_line : NameSpace
NameSpace containing the command line arguments```
### function loglkl
def loglkl( self self, cosmo cosmo, data data )
**Reimplements**: [MontePythonLike::Likelihood::loglkl](/documentation/code/colliderbit/classes/classmontepythonlike_1_1likelihood/#function-loglkl)
Placeholder to remind that this function needs to be defined for a new likelihood.
Raises
NotImplementedError```
function compute_lkl
def compute_lkl(
self self,
cl cl,
cosmo cosmo,
data data
)
function init
def __init__(
self self,
path path,
data data,
command_line command_line
)
Reimplements: MontePythonLike::Likelihood::init
It copies the content of self.path from the initialization routine of
the :class:`Data <data.Data>` class, and defines a handful of useful
methods, that every likelihood might need.
If the nuisance parameters required to compute this likelihood are not
defined (either fixed or varying), the code will stop.
Parameters
----------
data : class
Initialized instance of :class:`Data <data.Data>`
command_line : NameSpace
NameSpace containing the command line arguments```
### function loglkl
def loglkl( self self, cosmo cosmo, data data )
**Reimplements**: [MontePythonLike::Likelihood::loglkl](/documentation/code/colliderbit/classes/classmontepythonlike_1_1likelihood/#function-loglkl)
Placeholder to remind that this function needs to be defined for a new likelihood.
Raises
NotImplementedError```
function compute_lkl
def compute_lkl(
self self,
cl cl,
cosmo cosmo,
data data
)
Public Attributes Documentation
variable calib_uncertainty
calib_uncertainty;
variable has_beam_uncertainty
has_beam_uncertainty;
variable has_xfactors
has_xfactors;
variable obs
obs;
variable var
var;
variable beam_error
beam_error;
variable has_xfactor
has_xfactor;
variable xfactor
xfactor;
variable num_points
num_points;
variable inv_covmat
inv_covmat;
variable win_min
win_min;
variable win_max
win_max;
variable has_pol
has_pol;
variable window
window;
variable halfsteps
halfsteps;
variable margeweights
margeweights;
variable margenorm
margenorm;
variable l_max
l_max;
variable nuisance
nuisance;
variable use_nuisance
use_nuisance;
variable lkl
lkl;
Updated on 2022-08-03 at 12:58:16 +0000