matflow.subset_simulation.markov_chain.MarkovChainResult

class matflow.subset_simulation.markov_chain.MarkovChainResult(x, g, num_components_accepted, num_components_proposed, num_subset_accepts, num_subset_trials, num_outer_moves, jump_distance_sum, num_fine_evals, num_coarse_evals=0, jump_distances=None)

Bases: object

Result of generating one completed conditional Markov chain.

Methods

Attributes

component_acceptance_rate	Return the average MMH component acceptance rate.
dimension	Dimension of each Markov-chain state.
jump_distances	Per-transition RMS jump distances, if retained.
mean_jump_distance	Return the mean RMS distance between adjacent stored states.
num_coarse_evals	Number of coarse performance-function evaluations.
num_states	Number of stored states, including the initial chain seed.
num_transitions	Number of attempted outer-chain transitions.
outer_move_rate	Return the fraction of stored outer transitions that change state.
subset_acceptance_rate	Return the fraction of candidates passing the fine subset condition.
x	Stored chain states, with shape (states, dimensions).
g	Fine performance values associated with the stored states.
num_components_accepted	Total number of accepted MMH component proposals.
num_components_proposed	Total number of attempted MMH component proposals.
num_subset_accepts	Number of candidates passing the fine-model subset condition.
num_subset_trials	Number of candidates tested against the fine-model subset condition.
num_outer_moves	Number of stored outer-chain transitions that change state.
jump_distance_sum	Sum of RMS distances between adjacent stored chain states.
num_fine_evals	Number of fine performance-function evaluations.

Parameters:

• x (ndarray) –

• g (ndarray) –

• num_components_accepted (int) –

• num_components_proposed (int) –

• num_subset_accepts (int) –

• num_subset_trials (int) –

• num_outer_moves (int) –

• jump_distance_sum (float) –

• num_fine_evals (int) –

• num_coarse_evals (int) –

• jump_distances (ndarray | None) –

property component_acceptance_rate: float

Return the average MMH component acceptance rate.

The rate includes component proposals belonging to candidate states that subsequently fail the Subset Simulation condition.

property dimension: int

Dimension of each Markov-chain state.

g: ndarray

Fine performance values associated with the stored states.

jump_distance_sum: float

Sum of RMS distances between adjacent stored chain states.

jump_distances: ndarray | None = None

Per-transition RMS jump distances, if retained.

property mean_jump_distance: float

Return the mean RMS distance between adjacent stored states.

Rejected outer transitions contribute a zero jump distance.

num_coarse_evals: int = 0

Number of coarse performance-function evaluations.

num_components_accepted: int

Total number of accepted MMH component proposals.

num_components_proposed: int

Total number of attempted MMH component proposals.

num_fine_evals: int

Number of fine performance-function evaluations.

num_outer_moves: int

Number of stored outer-chain transitions that change state.

property num_states: int

Number of stored states, including the initial chain seed.

num_subset_accepts: int

Number of candidates passing the fine-model subset condition.

num_subset_trials: int

Number of candidates tested against the fine-model subset condition.

property num_transitions: int

Number of attempted outer-chain transitions.

property outer_move_rate: float

Return the fraction of stored outer transitions that change state.

property subset_acceptance_rate: float

Return the fraction of candidates passing the fine subset condition.

x: ndarray

Stored chain states, with shape (states, dimensions).