- class liesel.model.model.Model(nodes_and_vars, grow=True, copy=False)#
A model with a static graph.
bool) – Whether the nodes and variables should be copied upon initialization. (default:
Returns an unfrozen deep copy of the model nodes and variables.
Collects the groups from all nodes and variables.
Pops the nodes and variables out of this model.
Splits and sets the seed / PRNG key.
Updates the model state simulating from the probability distributions in the model using a provided random seed, optionally skipping specified nodes.
Updates the target nodes and their recursive inputs if they are outdated.
Whether to update the model automatically if the value of a node is modified.
The log-likelihood of the model.
The log-prior of the model.
The (unnormalized) log-probability / log-posterior of the model.
The directed graph of the model nodes.
A mapping of the model nodes with their names as keys.
The state of the model as a dict of node names and states.
The directed graph of the model variables.
A mapping of the model variables with their names as keys.