Estimators

Estimator implementations live in the alchemrs::estimators module.

Shared assumptions

For UNkMatrix-based estimators, the current implementation assumes:

• one-dimensional lambda states
• consistent evaluated-state grids across windows
• sampled_state is set and present in evaluated_states
• state temperatures are consistent across all windows

If those invariants are violated, the estimators fail early.

TI

Types:

• TiEstimator
• TiOptions
• IntegrationMethod::{Trapezoidal, Simpson}

Input:

• slice of DhdlSeries

Behavior:

• sorts windows by lambda
• computes the mean dH/dlambda for each window
• integrates across lambda using trapezoidal or Simpson integration

Current uncertainty behavior:

• trapezoidal mode reports an uncertainty estimate
• Simpson mode currently returns no uncertainty

BAR

Types:

• BarEstimator
• BarOptions
• BarMethod::{FalsePosition, SelfConsistentIteration, Bisection}

Input:

• slice of UNkMatrix

Behavior:

• expects windows mapped to sampled states on one evaluated-state grid
• computes work values between adjacent states
• fills a full pairwise DeltaFMatrix

Important limitation:

• uncertainty is only computed for adjacent windows
• non-adjacent uncertainties are reported as NaN

This matches the current CLI documentation and the reference-comparison tests in the repository.

MBAR

Types:

• MbarEstimator
• MbarOptions

Important options:

• max_iterations
• tolerance
• initial_f_k
• compute_uncertainty
• parallel

Input:

• slice of UNkMatrix

Behavior:

• combines windows into a shared reduced-energy representation
• solves for free energies iteratively
• returns a full DeltaFMatrix

The analysis crate uses MBAR-derived log weights to compute overlap diagnostics.

EXP and DEXP

Types:

• ExpEstimator
• ExpOptions

Input:

• slice of UNkMatrix

Behavior:

• computes exponential averaging from each sampled-state window to all evaluated states
• returns a full pairwise DeltaFMatrix

CLI direction conventions:

• exp reports the forward direction
• dexp reports the reverse direction

DEXP is not a separate estimator type in the library; it is a CLI convention over the same estimator results.

Parallel execution

Some estimators support a parallel option and use Rayon-backed parallel loops internally.

Parallelism affects performance, not the conceptual API.