matflow.subset_simulation.markov_chain.DAMarkovChainResult#

class matflow.subset_simulation.markov_chain.DAMarkovChainResult(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, gc=None, num_coarse_accepts=0, num_coarse_proposals=0, num_endpoint_moves=0, num_fine_subset_passes=0, num_fine_correction_accepts=0, num_coarse_and_fine_subset_passes=0)#

Bases: MarkovChainResult

Result of generating one delayed-acceptance Markov chain.

Methods

Attributes

`coarse_acceptance_rate`	Fraction of inner coarse-MH proposals accepted.
`coarse_given_fine`	Fraction of fine-subset endpoints also in the coarse subset.
`component_acceptance_rate`	Return the average MMH component acceptance rate.
`dimension`	Dimension of each Markov-chain state.
`endpoint_move_rate`	Fraction of coarse subchains whose endpoint moved.
`fine_correction_acceptance_rate`	Fraction of fine-subset endpoints accepted by DA correction.
`fine_eval_rate`	Fraction of outer transitions requiring a fine evaluation.
`fine_subset_pass_rate`	Fraction of fine-evaluated endpoints in the fine subset.
`gc`
`jump_distances`	Per-transition RMS jump distances, if retained.
`mean_jump_distance`	Return the mean RMS distance between adjacent stored states.
`num_coarse_accepts`
`num_coarse_and_fine_subset_passes`
`num_coarse_evals`	Number of coarse performance-function evaluations.
`num_coarse_proposals`
`num_endpoint_moves`
`num_fine_correction_accepts`
`num_fine_subset_passes`
`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) –
gc (ndarray | None) –
num_coarse_accepts (int) –
num_coarse_proposals (int) –
num_endpoint_moves (int) –
num_fine_subset_passes (int) –
num_fine_correction_accepts (int) –
num_coarse_and_fine_subset_passes (int) –

property coarse_acceptance_rate: float#: Fraction of inner coarse-MH proposals accepted.

property coarse_given_fine: float#: Fraction of fine-subset endpoints also in the coarse subset.

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.

property endpoint_move_rate: float#: Fraction of coarse subchains whose endpoint moved.

property fine_correction_acceptance_rate: float#: Fraction of fine-subset endpoints accepted by DA correction.

property fine_eval_rate: float#: Fraction of outer transitions requiring a fine evaluation.

property fine_subset_pass_rate: float#: Fraction of fine-evaluated endpoints in the fine subset.

g: ndarray#: Fine performance values associated with the stored states.

gc: ndarray | None = None#

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_accepts: int = 0#

num_coarse_and_fine_subset_passes: int = 0#

num_coarse_evals: int = 0#: Number of coarse performance-function evaluations.

num_coarse_proposals: int = 0#

num_components_accepted: int#: Total number of accepted MMH component proposals.

num_components_proposed: int#: Total number of attempted MMH component proposals.

num_endpoint_moves: int = 0#

num_fine_correction_accepts: int = 0#

num_fine_evals: int#: Number of fine performance-function evaluations.

num_fine_subset_passes: int = 0#

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).