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Bug/jon/gp update #71

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merged 4 commits into from
Sep 25, 2019
Merged

Bug/jon/gp update #71

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c209682
remove set_L_alpha call from update_db
jonpvandermause Sep 24, 2019
d6db013
add par=True default to otf parser
jonpvandermause Sep 24, 2019
3580e42
Minimizing calls to set_L_alpha
stevetorr Sep 25, 2019
059ec02
Add constant-time check that alpha is up to date in predict method
stevetorr Sep 25, 2019
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2 changes: 0 additions & 2 deletions flare/gp.py
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Original file line number Diff line number Diff line change
Expand Up @@ -74,8 +74,6 @@ def update_db(self, struc: Structure, forces: list,
# create numpy array of training labels
self.training_labels_np = self.force_list_to_np(self.training_labels)

self.set_L_alpha()

def add_one_env(self, env: AtomicEnvironment,
force: np.array, train: bool = False, **kwargs):
"""
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4 changes: 3 additions & 1 deletion flare/gp_from_aimd.py
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Expand Up @@ -156,6 +156,7 @@ def pre_run(self):
train_atoms.append(atom)

self.update_gp_and_print(frame, train_atoms, train=False)
self.gp.set_L_alpha()
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# These conditions correspond to if either the GP was never trained
# or if data was added to it during the pre-run.
Expand Down Expand Up @@ -207,6 +208,8 @@ def run(self):

if self.train_count < self.max_trains:
self.train_gp()
else:
self.gp.set_L_alpha()

self.output.conclude_run()

Expand Down Expand Up @@ -234,7 +237,6 @@ def update_gp_and_print(self, frame: Structure, train_atoms: List[int],

# update gp model
self.gp.update_db(frame, frame.forces, custom_range=train_atoms)
self.gp.set_L_alpha()

if train:
self.train_gp()
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5 changes: 3 additions & 2 deletions flare/otf_parser.py
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Expand Up @@ -44,7 +44,7 @@ def __init__(self, filename, calculate_energy=False):

def make_gp(self, cell=None, kernel=None, kernel_grad=None, algo=None,
call_no=None, cutoffs=None, hyps=None, init_gp=None,
energy_force_kernel=None, hyp_no=None):
energy_force_kernel=None, hyp_no=None, par=True):

if init_gp is None:
# Use run's values as extracted from header
Expand All @@ -71,7 +71,8 @@ def make_gp(self, cell=None, kernel=None, kernel_grad=None, algo=None,
gp_model = \
gp.GaussianProcess(kernel, kernel_grad, gp_hyps,
cutoffs, opt_algorithm=algo,
energy_force_kernel=energy_force_kernel)
energy_force_kernel=energy_force_kernel,
par=par)
else:
gp_model = init_gp
call_no = len(self.gp_position_list)
Expand Down