firecrown.likelihood.gauss_family.statistic.statistic.GuardedStatistic

firecrown.likelihood.gauss_family.statistic.statistic.GuardedStatistic#

class firecrown.likelihood.gauss_family.statistic.statistic.GuardedStatistic(stat)[source]#

Bases: Updatable

An internal class used to maintain state on statistics.

GuardedStatistic is used by the framework to maintain and validate the state of instances of classes derived from Statistic.

Parameters:

stat (Statistic) –

Public Methods:

__init__(stat)

Initialize the GuardedStatistic to contain the given Statistic.

read(sacc_data)

Read whatever data is needed from the given sacc.Sacc object.

get_data_vector()

Return the contained Statistic's data vector.

compute_theory_vector(tools)

Return the contained Statistic's 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(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:

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.


compute_theory_vector(tools)[source]#

Return the contained Statistic’s computed theory vector.

GuardedStatistic ensures that read() has been called. first.

Parameters:

tools (ModelingTools) –

Return type:

TheoryVector

get_data_vector()[source]#

Return the contained Statistic’s data vector.

GuardedStatistic ensures that read() has been called. first.

Return type:

DataVector

read(sacc_data)[source]#

Read whatever data is needed from the given sacc.Sacc object.

After this function is called, the object should be prepared for the calling of the methods get_data_vector() and compute_theory_vector().

Parameters:

sacc_data (Sacc) –

Return type:

None