ProposalBasedSampler#
- class cuqi.experimental.mcmc.ProposalBasedSampler(target=None, proposal=None, scale=1, **kwargs)#
Abstract base class for samplers that use a proposal distribution.
- __init__(target=None, proposal=None, scale=1, **kwargs)#
Initializer for abstract base class for samplers that use a proposal distribution.
Any subclassing samplers should simply store input parameters as part of the __init__ method.
Initialization of the sampler should be done in the _initialize method.
See
Sampler
for additional details.- Parameters:
target (cuqi.density.Density) – The target density.
proposal (cuqi.distribution.Distribution, optional) – The proposal distribution. If not specified, the default proposal is used.
scale (float, optional) – The scale parameter for the proposal distribution.
**kwargs (dict) – Additional keyword arguments passed to the
Sampler
initializer.
Methods
__init__
([target, proposal, scale])Initializer for abstract base class for samplers that use a proposal distribution.
Return the history of the sampler.
Return the samples.
Return the state of the sampler.
Initialize the sampler by setting and allocating the state and history before sampling starts.
load_checkpoint
(path)Load the state of the sampler from a file.
Re-initialize the sampler.
sample
(Ns[, batch_size, sample_path])Sample Ns samples from the target density.
save_checkpoint
(path)Save the state of the sampler to a file.
set_history
(history)Set the history of the sampler.
set_state
(state)Set the state of the sampler.
step
()Perform one step of the sampler by transitioning the current point to a new point according to the sampler's transition kernel.
tune
(skip_len, update_count)Tune the parameters of the sampler.
Validate the proposal distribution.
Validate the target is compatible with the sampler.
warmup
(Nb[, tune_freq])Warmup the sampler by drawing Nb samples.
Attributes