firecrown.connector.numcosmo.numcosmo.NumCosmoGaussCov#
- class firecrown.connector.numcosmo.numcosmo.NumCosmoGaussCov[source]#
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.
Implements the virtual Ncm.Data method get_length.
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:
Return the list of models.
_set_model_list
(value)Set the list of models.
Return the
MappingNumCosmo
object._set_nc_mapping
(value)Set the MappingNumCosmo object.
Configure the object.
Deserialize the likelihood.
Return the likelihood string defining the factory function.
_set_likelihood_source
(value)Set the likelihood string defining the factory function.
Return the likelihood build parameters.
Set the likelihood build parameters.
Inherited from
Object
_unsupported_method
(*args, **kargs)_unsupported_data_method
(*args, **kargs)
- _get_likelihood_build_parameters()[source]#
Return the likelihood build parameters.
- Return type:
Optional
[VarDict
]
- _get_likelihood_source()[source]#
Return the likelihood string defining the factory function.
- Return type:
Optional
[str
]
- _get_nc_mapping()[source]#
Return the
MappingNumCosmo
object.- Return type:
- _set_likelihood_build_parameters(value)[source]#
Set the likelihood build parameters.
- Parameters:
value (
Optional
[VarDict
]) –
- _set_likelihood_source(value)[source]#
Set the likelihood string defining the factory function.
- Parameters:
value (
Optional
[str
]) –
- _set_nc_mapping(value)[source]#
Set the MappingNumCosmo object.
- Parameters:
value (
MappingNumCosmo
) –
- do_begin()[source]#
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_mean_func(_, mean_vector)[source]#
Implements the virtual Ncm.DataGaussCov method mean_func.
This method should compute the theoretical mean for the gaussian distribution.
- do_prepare(mset)[source]#
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)[source]#
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
]) –