class MontePythonLike::Likelihood_mock_cmb
[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 | |
|---|---|
| noise_from_file Noise spectrum. | |
| noise_T | |
| noise_P | |
| Nldd | |
| no_small_l_pol | |
| l_max_TT | |
| Bmodes implementation of default settings for flags describing the likelihood: # | |
| delensing | |
| LensingExtraction | |
| neglect_TD | |
| unlensed_clTTTEEE | |
| ExcludeTTTEEE | |
| noise_delensing Delensing noise: implemented by S. | |
| index_B Read data for TT, EE, TE, [eventually BB or phi-phi, phi-T] #. | |
| index_pp | |
| index_tp | |
| Cl_fid | |
| fid_values_exist |
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 | |
| use_nuisance | |
| nuisance | |
| 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 | |
| use_nuisance | |
| nuisance | |
| 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/darkbit/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/darkbit/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 noise_from_file
noise_from_file;
Noise spectrum.
variable noise_T
noise_T;
variable noise_P
noise_P;
variable Nldd
Nldd;
variable no_small_l_pol
no_small_l_pol;
variable l_max_TT
l_max_TT;
variable Bmodes
Bmodes;
implementation of default settings for flags describing the likelihood: #
variable delensing
delensing;
variable LensingExtraction
LensingExtraction;
variable neglect_TD
neglect_TD;
variable unlensed_clTTTEEE
unlensed_clTTTEEE;
variable ExcludeTTTEEE
ExcludeTTTEEE;
variable noise_delensing
noise_delensing;
Delensing noise: implemented by S.
Clesse #
variable index_B
index_B;
Read data for TT, EE, TE, [eventually BB or phi-phi, phi-T] #.
variable index_pp
index_pp;
variable index_tp
index_tp;
variable Cl_fid
Cl_fid;
variable fid_values_exist
fid_values_exist;
Updated on 2022-08-03 at 12:58:01 +0000