firecrown.connector.numcosmo.numcosmo.NumCosmoGaussCov

class firecrown.connector.numcosmo.numcosmo.NumCosmoGaussCov

Bases: DataGaussCov

NumCosmoGaussCov is a subclass of Ncm.DataGaussCov.

This subclass implements NumCosmo likelihood object virtual methods using the prefix do_. This class implements a Gaussian likelihood.

Public Methods:

__init__()	Initialize a NumCosmoGaussCov object.
new_from_likelihood(likelihood, model_list, ...)	Initialize a NumCosmoGaussCov object.
do_get_length()	Implements the virtual Ncm.Data method get_length.
do_get_dof()	Implements the virtual Ncm.Data method get_dof.
do_begin()	Implements the virtual Ncm.Data method begin.
do_prepare(mset)	Implements the virtual method Ncm.Data prepare.
do_mean_func(_, mean_vector)	Implements the virtual Ncm.DataGaussCov method mean_func.
do_get_property(pspec)
do_set_property(pspec, value)

Inherited from DataGaussCov

do_cov_func	NumCosmoMath.Matrix) -> bool
do_get_size	get_size(self) -> int
do_lnNorma2	float)
do_lnNorma2_bs	NumCosmoMath.Bootstrap, m2lnL:float)
do_mean_func	NumCosmoMath.Vector)
do_set_size	int)

Inherited from Data

do_begin	begin(self)
do_fisher_matrix	NumCosmoMath.Matrix
do_fisher_matrix_bias	NumCosmoMath.Vector) -> IM:NumCosmoMath.Matrix, delta_theta:NumCosmoMath.Vector
do_get_dof	get_dof(self) -> int
do_get_length	get_length(self) -> int
do_inv_cov_UH	NumCosmoMath.Matrix)
do_inv_cov_Uf	NumCosmoMath.Vector)
do_leastsquares_f	NumCosmoMath.Vector)
do_m2lnL_val	float
do_mean_vector	NumCosmoMath.Vector)
do_prepare	NumCosmoMath.MSet)
do_resample	NumCosmoMath.RNG)

Inherited from Object

get_data(self, key)
get_qdata(self, quark)
set_data(self, key[, data])
steal_data(self, key)
steal_qdata(self, quark)
replace_data(*args, **kargs)
replace_qdata(*args, **kargs)
bind_property_full(self, source_property, ...)
compat_control(what[, data])
interface_find_property(g_iface, property_name)
interface_install_property(g_iface, pspec)
interface_list_properties(g_iface)
notify_by_pspec(self, pspec)
watch_closure(self, closure)
ref(self)
ref_sink(self)
unref(self)
force_floating(self)
get_property(self, property_name, value)
get_properties
set_property(self, property_name, value)
set_properties
bind_property(self, source_property, target, ...)
connect
connect_after
connect_object
connect_object_after
disconnect_by_func
handler_block_by_func
handler_unblock_by_func
emit
chain
weak_ref
__copy__
__deepcopy__
freeze_notify()	Freezes the object's property-changed notification queue.
connect_data(detailed_signal, handler, ...)	Connect a callback to the given signal with optional user data.
handler_block(handler_id)	Blocks the signal handler from being invoked until handler_unblock() is called.
handler_unblock	int)
disconnect	int)
handler_disconnect	int)
handler_is_connected	int) -> bool
stop_emission_by_name	str)
stop_emission(detailed_signal)	Deprecated, please use stop_emission_by_name.
emit_stop_by_name(detailed_signal)	Deprecated, please use stop_emission_by_name.

Inherited from Object

find_property
install_properties
install_property
list_properties
override_property

Inherited from GObject

__repr__()	Return repr(self).
__hash__()	Return hash(self).
__setattr__(name, value, /)	Implement setattr(self, name, value).
__delattr__(name, /)	Implement delattr(self, name).
__lt__(value, /)	Return self<value.
__le__(value, /)	Return self<=value.
__eq__(value, /)	Return self==value.
__ne__(value, /)	Return self!=value.
__gt__(value, /)	Return self>value.
__ge__(value, /)	Return self>=value.
__init__(*args, **kwargs)
get_property
get_properties
set_property
set_properties
bind_property
connect
connect_after
connect_object
connect_object_after
disconnect_by_func
handler_block_by_func
handler_unblock_by_func
emit
chain
weak_ref
__copy__
__deepcopy__
__doc__
__gdoc__
props

Private Methods:

_get_model_list()	Return the list of models.
_set_model_list(value)	Set the list of models.
_get_nc_mapping()	Return the MappingNumCosmo object.
_set_nc_mapping(value)	Set the MappingNumCosmo object.
_configure_object()	Configure the object.
_set_likelihood_from_factory()	Deserialize the likelihood.
_get_likelihood_source()	Return the likelihood string defining the factory function.
_set_likelihood_source(value)	Set the likelihood string defining the factory function.
_get_likelihood_build_parameters()	Return the likelihood build parameters.
_set_likelihood_build_parameters(value)	Set the likelihood build parameters.

Inherited from Object

_unsupported_method(*args, **kargs)
_unsupported_data_method(*args, **kargs)

---

_configure_object()

Configure the object.

_get_likelihood_build_parameters()

Return the likelihood build parameters.

Return type:

Optional[VarDict]

_get_likelihood_source()

Return the likelihood string defining the factory function.

Return type:

Optional[str]

_get_model_list()

Return the list of models.

Return type:

list[str]

_get_nc_mapping()

Return the MappingNumCosmo object.

Return type:

MappingNumCosmo

_set_likelihood_build_parameters(value)

Set the likelihood build parameters.

Parameters:

value (Optional[VarDict]) –

_set_likelihood_from_factory()

Deserialize the likelihood.

_set_likelihood_source(value)

Set the likelihood string defining the factory function.

Parameters:

value (Optional[str]) –

_set_model_list(value)

Set the list of models.

Parameters:

value (list[str]) –

_set_nc_mapping(value)

Set the MappingNumCosmo object.

Parameters:

value (MappingNumCosmo) –

do_begin()

Implements the virtual Ncm.Data method begin.

This method usually do some groundwork in the data before the actual calculations. For example, if the likelihood involves the decomposition of a constant matrix, it can be done during begin once and then used afterwards.

do_get_dof()

Implements the virtual Ncm.Data method get_dof.

do_get_length()

Implements the virtual Ncm.Data method get_length.

do_mean_func(_, mean_vector)

Implements the virtual Ncm.DataGaussCov method mean_func.

This method should compute the theoretical mean for the gaussian distribution.

do_prepare(mset)

Implements the virtual method Ncm.Data prepare.

This method should do all the necessary calculations using mset to be able to calculate the likelihood afterwards.

Parameters:

mset (MSet) –

likelihood_build_parameters

Return the likelihood build parameters.

likelihood_source

Return the likelihood string defining the factory function.

model_list

Return the list of models.

nc_mapping

Return the MappingNumCosmo object.

classmethod new_from_likelihood(likelihood, model_list, tools, nc_mapping, likelihood_source=None, likelihood_build_parameters=None)

Initialize a NumCosmoGaussCov object.

This object represents a Gaussian likelihood with a constant covariance.

Parameters:

• likelihood (ConstGaussian) –

• model_list (list[str]) –

• tools (ModelingTools) –

• nc_mapping (MappingNumCosmo) –

• likelihood_source (Optional[str]) –

• likelihood_build_parameters (Optional[NamedParameters]) –