firecrown.likelihood.gauss_family.statistic.statistic.Statistic#
- class firecrown.likelihood.gauss_family.statistic.statistic.Statistic(parameter_prefix=None)[source]#
Bases:
Updatable
The abstract base class for all physics-related statistics.
Statistics read data from a SACC object as part of a multi-phase initialization. They manage a
DataVector
and, given aModelingTools
object, can compute aTheoryVector
.Statistics represent things like two-point functions and mass functions.
- Parameters:
parameter_prefix (
Optional
[str
]) –
Public Methods:
__init__
([parameter_prefix])Updatable initialization.
read
(_)Read the data for this statistic and mark it as ready for use.
get_data_vector
()Gets the statistic data vector.
compute_theory_vector
(tools)Compute a statistic from sources, applying any systematics.
get_theory_vector
()Returns the last computed theory vector.
Inherited from
Updatable
__init__
([parameter_prefix])Updatable initialization.
__setattr__
(key, value)Set the attribute named
key
to the supplied value.set_parameter
(key, value)Sets the parameter to the given value.
set_internal_parameter
(key, value)Assure this InternalParameter has not already been set, and then set it.
set_sampler_parameter
(key, value)Assure this SamplerParameter has not already been set, and then set it.
update
(params)Update self by calling to prepare for the next MCMC sample.
is_updated
()Determine if the object has been updated.
reset
()Reset the updatable.
required_parameters
()Returns a RequiredParameters object.
get_derived_parameters
()Returns a collection of derived parameters.
Private Methods:
_reset
()Reset this statistic.
_compute_theory_vector
(tools)Compute a statistic from sources, concrete implementation.
Inherited from
Updatable
_update
(params)Method for auxiliary updates to be made to an updatable.
_reset
()Abstract method implemented by all concrete classes to update self.
_required_parameters
()Return a RequiredParameters object containing the information for this class.
_get_derived_parameters
()Returns the derived parameters of an implementation.
- abstract _compute_theory_vector(tools)[source]#
Compute a statistic from sources, concrete implementation.
- Parameters:
tools (
ModelingTools
) –- Return type:
- final compute_theory_vector(tools)[source]#
Compute a statistic from sources, applying any systematics.
- Parameters:
tools (
ModelingTools
) –- Return type:
- get_theory_vector()[source]#
Returns the last computed theory vector.
Raises a RuntimeError if the vector has not been computed.
- Return type:
- read(_)[source]#
Read the data for this statistic and mark it as ready for use.
Derived classes that override this function should make sure to call the base class method using:
super().read(sacc_data)
as the last thing they do in __init__.
Note that currently the argument is not used; it is present so that this method will have the correct argument type for the override.
- Parameters:
_ (
Sacc
) –- Return type:
None