def run(self, ff):
from yaff import CartesianDOF, QNOptimizer, OptScreenLog
#prevpos = ff.system.pos[:].copy()
#energy0 = ff.compute()
#ff.system.pos[:] = self.refpos
#energy1 = ff.compute()
#if energy1 > energy0:
ff.system.pos[:] = self.refpos#*np.random.uniform(0.99, 1.01, ff.system.pos.shape)
dof = CartesianDOF(ff, gpos_rms=1e-8)
sl = OptScreenLog(step=20)
self.opt = QNOptimizer(dof, hooks=[sl], hessian0=self.hessian0)
self.opt.run(5000)
return {
'energy': ff.energy,
'pos': ff.system.pos.copy(),
'gpos': ff.gpos.copy(),
}
class GeoOptSimulation(Simulation):
def __init__(self, name, system, **kwargs):
self.refpos = system.pos.copy()
self.hessian0 = kwargs.pop('hessian0', None)
Simulation.__init__(self, name, system, **kwargs)
def run(self, ff):
from yaff import CartesianDOF, QNOptimizer, OptScreenLog
#prevpos = ff.system.pos[:].copy()
#energy0 = ff.compute()
#ff.system.pos[:] = self.refpos
#energy1 = ff.compute()
#if energy1 > energy0:
ff.system.pos[:] = self.refpos#*np.random.uniform(0.99, 1.01, ff.system.pos.shape)
dof = CartesianDOF(ff, gpos_rms=1e-8)
sl = OptScreenLog(step=20)
self.opt = QNOptimizer(dof, hooks=[sl], hessian0=self.hessian0)
self.opt.run(5000)
return {
'energy': ff.energy,
'pos': ff.system.pos.copy(),
'gpos': ff.gpos.copy(),
}
