class EnergyAccumulator:
"""returns energy of each configuration in a dictionary.
Keys and their meanings can be found in energy.energy """
def __init__(self, mol, threshold=10, **kwargs):
self.mol = mol
self.threshold = threshold
if hasattr(mol, "a"):
print("EnergyAccumulator using Ewald\n", kwargs)
self.ewald = Ewald(mol, **kwargs)
def compute_energy(mol, configs, wf, threshold):
ee, ei, ii = self.ewald.energy(configs)
ecp_val = energy.get_ecp(mol, configs, wf, threshold)
ke = energy.kinetic(configs, wf)
return {
"ke": ke,
"ee": ee,
"ei": ei,
"ecp": ecp_val,
"total": ke + ee + ei + ecp_val + ii,
}
self.compute_energy = compute_energy
else:
self.compute_energy = energy.energy
def __call__(self, configs, wf):
return self.compute_energy(self.mol, configs, wf, self.threshold)
def avg(self, configs, wf):
d = {}
for k, it in self(configs, wf).items():
d[k] = np.mean(it, axis=0)
return d
def __init__(self, mol, threshold=10, **kwargs):
self.mol = mol
self.threshold = threshold
if hasattr(mol, "a"):
ewald = Ewald(mol, **kwargs)
self.compute_energy = ewald.compute_total_energy
else:
self.compute_energy = energy.energy
def __init__(self, mol, threshold=10, **kwargs):
self.mol = mol
self.threshold = threshold
if hasattr(mol, "a"):
self.ewald = Ewald(mol, **kwargs)
def compute_energy(mol, configs, wf, threshold):
ee, ei, ii = self.ewald.energy(configs)
ecp_val = energy.get_ecp(mol, configs, wf, threshold)
ke = energy.kinetic(configs, wf)
return {
"ke": ke,
"ee": ee,
"ei": ei,
"ecp": ecp_val,
"total": ke + ee + ei + ecp_val + ii,
}
self.compute_energy = compute_energy
else:
self.compute_energy = energy.energy