firecrown.models.cluster.recipes.cluster_recipe.ClusterRecipe#
- class firecrown.models.cluster.recipes.cluster_recipe.ClusterRecipe(parameter_prefix=None)[source]#
Bases:
Updatable,ABCAbstract class defining a cluster recipe.
A cluster recipe is a combination of different cluster theoretrical predictions and models that produces a single prediction for an observable.
- Parameters:
parameter_prefix (
None|str) –
Public Methods:
__init__([parameter_prefix])Updatable initialization.
evaluate_theory_prediction(cluster_theory, ...)Evaluate the theory prediction for this cluster recipe.
Inherited from
Updatable__init__([parameter_prefix])Updatable initialization.
__setattr__(key, value)Set the attribute named
keyto 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.
Determine if the object has been updated.
reset()Reset the updatable.
Returns all information about parameters required by this object.
Return the names of the parameters required by this object.
Returns a collection of derived parameters.
Private Methods:
Inherited from
Updatable
- abstract evaluate_theory_prediction(cluster_theory, this_bin, sky_area, average_on=None)[source]#
Evaluate the theory prediction for this cluster recipe.
- Parameters:
cluster_theory (
ClusterAbundance) –this_bin (
SaccBin) –sky_area (
float) –average_on (
None|ClusterProperty) –
- Return type:
float