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WIP -- intuitive handling of minimization steps kwarg #1141

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WIP -- intuitive handling of minimization steps kwarg #1141

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4 changes: 3 additions & 1 deletion perses/dispersed/feptasks.py
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Original file line number Diff line number Diff line change
Expand Up @@ -659,7 +659,6 @@ def check_EquilibriumFEPTask(task):

def minimize(thermodynamic_state: states.ThermodynamicState, sampler_state: states.SamplerState,
max_iterations: int=100) -> states.SamplerState:
# TODO: set max iterations to 1000 and check tyk2 benchmarks
"""
Minimize the given system and state, up to a maximum number of steps.
This does not return a copy of the samplerstate; it is an update-in-place.
Expand Down Expand Up @@ -687,6 +686,9 @@ def minimize(thermodynamic_state: states.ThermodynamicState, sampler_state: stat
context, integrator = cache.global_context_cache.get_context(thermodynamic_state)
sampler_state.apply_to_context(context, ignore_velocities = True)
# TODO: Set logging for minimization
# If max_iterations = None, it means run as many iterations as needed to reach tolerance.
if max_iterations is None:
max_iterations = 0
openmm.LocalEnergyMinimizer.minimize(context, maxIterations = max_iterations)
sampler_state.update_from_context(context)

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5 changes: 3 additions & 2 deletions perses/samplers/multistate.py
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Expand Up @@ -84,7 +84,7 @@ def setup(self, n_states, temperature, storage_file, minimisation_steps=100,
sampler_state = SamplerState(positions, box_vectors=hybrid_system.getDefaultPeriodicBoxVectors())

for lambda_val in lambda_schedule:
# Create a compound thermodynamic for lambda_val and set alchemical parameters
# Create a compound thermodynamic for lambda_val and set alchemical parameters
compound_thermodynamic_state_copy = copy.deepcopy(compound_thermodynamic_state)
if factory_name == 'HybridTopologyFactory':
compound_thermodynamic_state_copy.set_alchemical_parameters(lambda_val,lambda_protocol)
Expand All @@ -93,7 +93,8 @@ def setup(self, n_states, temperature, storage_file, minimisation_steps=100,
thermodynamic_state_list.append(compound_thermodynamic_state_copy)

# Generate a sampler_state for each thermodynamic state
feptasks.minimize(compound_thermodynamic_state_copy, sampler_state, max_iterations=minimisation_steps)
if minimisation_steps != 0: # only minimize if there are specified steps != 0
feptasks.minimize(compound_thermodynamic_state_copy, sampler_state, max_iterations=minimisation_steps)
sampler_state_list.append(copy.deepcopy(sampler_state))

reporter = storage_file
Expand Down