class MontePythonLike::Likelihood_mpk

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Inherits from MontePythonLike.Likelihood, MontePythonLike.Likelihood, object

Public Functions #

Public Attributes #

Additional inherited members #

Public Functions inherited from MontePythonLike.Likelihood

Public Attributes inherited from MontePythonLike.Likelihood

Public Functions inherited from MontePythonLike.Likelihood

Public Attributes inherited from MontePythonLike.Likelihood

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/main/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/main/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 12:57:54 +0000