class MontePythonLike::Likelihood_mpk

[No description available]

Inherits from MontePythonLike.Likelihood, MontePythonLike.Likelihood, object

Public Functions

Name
definit(self self, path path, data data, command_line command_line, common common =False, common_dict common_dict ={})
defa2maxpos(self self, a1val a1val)
defa2min1pos(self self, a1val a1val)
defa2min2pos(self self, a1val a1val)
defa2min3pos(self self, a1val a1val)
defa2minfinalpos(self self, a1val a1val)
defa2minneg(self self, a1val a1val)
defa2max1neg(self self, a1val a1val)
defa2max2neg(self self, a1val a1val)
defa2max3neg(self self, a1val a1val)
defa2maxfinalneg(self self, a1val a1val)
deftesta1a2(self self, a1val a1val, a2val a2val)
defadd_common_knowledge(self self, common_dictionary common_dictionary)
defloglkl(self self, cosmo cosmo, data data)
defremove_bao(self self, k_in k_in, pk_in pk_in)
definit(self self, path path, data data, command_line command_line, common common =False, common_dict common_dict ={})
defa2maxpos(self self, a1val a1val)
defa2min1pos(self self, a1val a1val)
defa2min2pos(self self, a1val a1val)
defa2min3pos(self self, a1val a1val)
defa2minfinalpos(self self, a1val a1val)
defa2minneg(self self, a1val a1val)
defa2max1neg(self self, a1val a1val)
defa2max2neg(self self, a1val a1val)
defa2max3neg(self self, a1val a1val)
defa2maxfinalneg(self self, a1val a1val)
deftesta1a2(self self, a1val a1val, a2val a2val)
defadd_common_knowledge(self self, common_dictionary common_dictionary)
defloglkl(self self, cosmo cosmo, data data)
defremove_bao(self self, k_in k_in, pk_in pk_in)

Public Attributes

Name
use_halofit
use_sdssDR7
k_size
mu_size
k
kh
use_giggleZ
use_giggleZPP0
k_fid_size
fiducial_SDSSDR7_nlratio
has_regions
num_regions
num_regions_used
used_region
n_size
window
P_obs
P_err
use_covmat
use_invcov
invcov
P_fid
k_fid
zerowindowfxn
zerowindowfxnsubtractdat
zerowindowfxnsubtractdatnorm
a1list
a2list
fiducial_SDSSDR7

Additional inherited members

Public Functions inherited from MontePythonLike.Likelihood

Name
defraise_fiducial_model_err(self self)
defread_from_file(self self, path path, data data, command_line command_line)
defget_cl(self self, cosmo cosmo, l_max l_max =-1)
defget_unlensed_cl(self self, cosmo cosmo, l_max l_max =-1)
defneed_cosmo_arguments(self self, data data, dictionary dictionary)
defread_contamination_spectra(self self, data data)
defadd_contamination_spectra(self self, cl cl, data data)
defadd_nuisance_prior(self self, lkl lkl, data data)
defcomputeLikelihood(self self, ctx ctx)
defraise_fiducial_model_err(self self)
defread_from_file(self self, path path, data data, command_line command_line)
defget_cl(self self, cosmo cosmo, l_max l_max =-1)
defget_unlensed_cl(self self, cosmo cosmo, l_max l_max =-1)
defneed_cosmo_arguments(self self, data data, dictionary dictionary)
defread_contamination_spectra(self self, data data)
defadd_contamination_spectra(self self, cl cl, data data)
defadd_nuisance_prior(self self, lkl lkl, data data)
defcomputeLikelihood(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
defraise_fiducial_model_err(self self)
defread_from_file(self self, path path, data data, command_line command_line)
defget_cl(self self, cosmo cosmo, l_max l_max =-1)
defget_unlensed_cl(self self, cosmo cosmo, l_max l_max =-1)
defneed_cosmo_arguments(self self, data data, dictionary dictionary)
defread_contamination_spectra(self self, data data)
defadd_contamination_spectra(self self, cl cl, data data)
defadd_nuisance_prior(self self, lkl lkl, data data)
defcomputeLikelihood(self self, ctx ctx)
defraise_fiducial_model_err(self self)
defread_from_file(self self, path path, data data, command_line command_line)
defget_cl(self self, cosmo cosmo, l_max l_max =-1)
defget_unlensed_cl(self self, cosmo cosmo, l_max l_max =-1)
defneed_cosmo_arguments(self self, data data, dictionary dictionary)
defread_contamination_spectra(self self, data data)
defadd_contamination_spectra(self self, cl cl, data data)
defadd_nuisance_prior(self self, lkl lkl, data data)
defcomputeLikelihood(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,
    common common =False,
    common_dict common_dict ={}
)

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 a2maxpos

def a2maxpos( self self, a1val a1val )



### function a2min1pos

def a2min1pos( self self, a1val a1val )



### function a2min2pos

def a2min2pos( self self, a1val a1val )



### function a2min3pos

def a2min3pos( self self, a1val a1val )



### function a2minfinalpos

def a2minfinalpos( self self, a1val a1val )



### function a2minneg

def a2minneg( self self, a1val a1val )



### function a2max1neg

def a2max1neg( self self, a1val a1val )



### function a2max2neg

def a2max2neg( self self, a1val a1val )



### function a2max3neg

def a2max3neg( self self, a1val a1val )



### function a2maxfinalneg

def a2maxfinalneg( self self, a1val a1val )



### function testa1a2

def testa1a2( self self, a1val a1val, a2val a2val )



### function add_common_knowledge

def add_common_knowledge( self self, common_dictionary common_dictionary )





Add to a class the content of a shared dictionary of attributes

The purpose of this method is to set some attributes globally for a Pk likelihood, that are shared amongst all the redshift bins (in WiggleZ.data for instance, a few flags and numbers are defined that will be transfered to wigglez_a, b, c and d```

function loglkl

def loglkl(
    self self,
    cosmo cosmo,
    data data
)

Reimplements: MontePythonLike::Likelihood::loglkl

Placeholder to remind that this function needs to be defined for a
new likelihood.

Raises
------
NotImplementedError```


### function remove_bao

def remove_bao( self self, k_in k_in, pk_in pk_in )



### function __init__

def init( self self, path path, data data, command_line command_line, common common =False, common_dict common_dict ={} )



**Reimplements**: [MontePythonLike::Likelihood::__init__](/documentation/code/darkbit/classes/classmontepythonlike_1_1likelihood/#function---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 a2maxpos

def a2maxpos(
    self self,
    a1val a1val
)

function a2min1pos

def a2min1pos(
    self self,
    a1val a1val
)

function a2min2pos

def a2min2pos(
    self self,
    a1val a1val
)

function a2min3pos

def a2min3pos(
    self self,
    a1val a1val
)

function a2minfinalpos

def a2minfinalpos(
    self self,
    a1val a1val
)

function a2minneg

def a2minneg(
    self self,
    a1val a1val
)

function a2max1neg

def a2max1neg(
    self self,
    a1val a1val
)

function a2max2neg

def a2max2neg(
    self self,
    a1val a1val
)

function a2max3neg

def a2max3neg(
    self self,
    a1val a1val
)

function a2maxfinalneg

def a2maxfinalneg(
    self self,
    a1val a1val
)

function testa1a2

def testa1a2(
    self self,
    a1val a1val,
    a2val a2val
)

function add_common_knowledge

def add_common_knowledge(
    self self,
    common_dictionary common_dictionary
)
Add to a class the content of a shared dictionary of attributes

The purpose of this method is to set some attributes globally for a Pk
likelihood, that are shared amongst all the redshift bins (in
WiggleZ.data for instance, a few flags and numbers are defined that
will be transfered to wigglez_a, b, c and d```


### 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 remove_bao

def remove_bao(
    self self,
    k_in k_in,
    pk_in pk_in
)

Public Attributes Documentation

variable use_halofit

use_halofit;

variable use_sdssDR7

use_sdssDR7;

variable k_size

k_size;

variable mu_size

mu_size;

variable k

k;

variable kh

kh;

variable use_giggleZ

use_giggleZ;

variable use_giggleZPP0

use_giggleZPP0;

variable k_fid_size

k_fid_size;

variable fiducial_SDSSDR7_nlratio

fiducial_SDSSDR7_nlratio;

variable has_regions

has_regions;

variable num_regions

num_regions;

variable num_regions_used

num_regions_used;

variable used_region

used_region;

variable n_size

n_size;

variable window

window;

variable P_obs

P_obs;

variable P_err

P_err;

variable use_covmat

use_covmat;

variable use_invcov

use_invcov;

variable invcov

invcov;

variable P_fid

P_fid;

variable k_fid

k_fid;

variable zerowindowfxn

zerowindowfxn;

variable zerowindowfxnsubtractdat

zerowindowfxnsubtractdat;

variable zerowindowfxnsubtractdatnorm

zerowindowfxnsubtractdatnorm;

variable a1list

a1list;

variable a2list

a2list;

variable fiducial_SDSSDR7

fiducial_SDSSDR7;

Updated on 2022-08-03 at 12:58:01 +0000