Classes

class SampleSchedule (tree_sampler: TreeMutationSampler, leaf_sampler: LeafNodeSampler, sigma_sampler: SigmaSampler)

The SampleSchedule class is responsible for handling the ordering of sampling within a Gibbs step It is useful to encapsulate this logic if we wish to expand the model

Parameters

tree_sampler : TreeMutationSampler

How to sample tree mutation space

leaf_sampler : LeafNodeSampler

How to sample leaf node predictions

sigma_sampler : SigmaSampler

How to sample sigma values

Expand source code

class SampleSchedule:
    """
    The SampleSchedule class is responsible for handling the ordering of sampling within a Gibbs step
    It is useful to encapsulate this logic if we wish to expand the model

    Parameters
    ----------
    tree_sampler: TreeMutationSampler
        How to sample tree mutation space
    leaf_sampler: LeafNodeSampler
        How to sample leaf node predictions
    sigma_sampler: SigmaSampler
        How to sample sigma values
    """

    def __init__(self,
                 tree_sampler: TreeMutationSampler,
                 leaf_sampler: LeafNodeSampler,
                 sigma_sampler: SigmaSampler):
        self.leaf_sampler = leaf_sampler
        self.sigma_sampler = sigma_sampler
        self.tree_sampler = tree_sampler

    def steps(self, model: Model) -> Generator[Tuple[Text, Callable[[], float]], None, None]:
        """
        Create a generator of the steps that need to be called to complete a full Gibbs sample

        Parameters
        ----------
        model: Model
            The model being sampled

        Returns
        -------
        Generator[Callable[[Model], Sampler], None, None]
            A generator a function to be called
        """
        for tree in model.refreshed_trees():
            yield "Tree", lambda: self.tree_sampler.step(model, tree)

            for leaf_node in tree.leaf_nodes:
                yield "Node", lambda: self.leaf_sampler.step(model, leaf_node)
        yield "Node", lambda: self.sigma_sampler.step(model, model.sigma)

Methods

def steps(self, model: Model) ‑> Generator[Tuple[str, Callable[[], float]], None, None]

Create a generator of the steps that need to be called to complete a full Gibbs sample

Parameters

model : Model

The model being sampled

Returns

Generator[Callable[[Model], Sampler], None, None]

A generator a function to be called

Expand source code

def steps(self, model: Model) -> Generator[Tuple[Text, Callable[[], float]], None, None]:
    """
    Create a generator of the steps that need to be called to complete a full Gibbs sample

    Parameters
    ----------
    model: Model
        The model being sampled

    Returns
    -------
    Generator[Callable[[Model], Sampler], None, None]
        A generator a function to be called
    """
    for tree in model.refreshed_trees():
        yield "Tree", lambda: self.tree_sampler.step(model, tree)

        for leaf_node in tree.leaf_nodes:
            yield "Node", lambda: self.leaf_sampler.step(model, leaf_node)
    yield "Node", lambda: self.sigma_sampler.step(model, model.sigma)