meld.remd.adaptor¶
- class meld.remd.adaptor.AcceptanceCounter(n_replicas)[source]¶
Class to keep track of acceptance rates.
- class meld.remd.adaptor.AdaptationPolicy(growth_factor, burn_in, adapt_every)[source]¶
Repeat adaptation on a regular schedule with an optional burn-in and increasing adaptation times.
Parameters: - growth_factor – increase adapt_every by a factor of growth_factor every adaptation
- burn_in – number of steps to ignore at the beginning
- adapt_every – how frequently to adapt (in picoseconds)
- class AdaptationRequired¶
AdaptationRequired(adapt_now, reset_now)
- adapt_now¶
Alias for field number 0
- reset_now¶
Alias for field number 1
- AdaptationPolicy.should_adapt(step)[source]¶
Is adaptation required?
Parameters: step – the current simulation step Returns: an AdaptationPolicy.AdaptationRequired object indicating if adaptation or resetting is necessary
- class meld.remd.adaptor.EqualAcceptanceAdaptor(n_replicas, adaptation_policy, min_acc_prob=0.1)[source]¶
Adaptor based on making acceptance rates uniform.
Parameters: - n_replicas – number of replicas
- min_acc_prob – all acceptence probabilities below this value will be raised to this value
- adapt(previous_lambdas, step)[source]¶
Compute new optimal values of lambda.
Parameters: - previous_lambdas – a list of the previous lambda values
- step – the current simulation step
Returns: a list of the new, optimized lambda values