def run(self):
"""
the main loop of the algorithm
"""
res = Result()
res.message = []
tol = self.tol
iprint = self.iprint
nsteps = self.nsteps
#iprint =40
X = self.X
sqrtN = np.sqrt(self.N)
i = 1
self.funcalls += 1
e, G = self.pot.getEnergyGradient(X)
res.success = False
while i < nsteps:
stp = self.getStep(X, G)
try:
X, e, G = self.adjustStepSize(X, e, G, stp)
except LineSearchError:
print "Warning: problem with adjustStepSize, ending quench"
rms = np.linalg.norm(G) / sqrtN
print " on failure: quench step", i, e, rms, self.funcalls
res.message.append( "problem with adjustStepSize" )
break
#e, G = self.pot.getEnergyGradient(X)
rms = np.linalg.norm(G) / sqrtN
if iprint > 0:
if i % iprint == 0:
print "lbfgs:", i, e, rms, self.funcalls, self.stepsize
for event in self.events:
event(coords=X, energy=e, rms=rms)
if self.alternate_stop_criterion is None:
i_am_done = rms < self.tol
else:
i_am_done = self.alternate_stop_criterion(energy=e, gradient=G,
tol=self.tol)
if i_am_done:
res.success = True
break
i += 1
res.nsteps = i
res.nfev = self.funcalls
res.coords = X
res.energy = e
res.rms = rms
res.grad = G
res.H0 = self.H0
return res
def run(self):
"""
the main loop of the algorithm
"""
res = Result()
res.message = []
tol = self.tol
iprint = self.iprint
nsteps = self.nsteps
#iprint =40
X = self.X
sqrtN = np.sqrt(self.N)
i = 1
self.funcalls += 1
e, G = self.pot.getEnergyGradient(X)
rms = np.linalg.norm(G) / sqrtN
res.success = False
while i < nsteps:
stp = self.getStep(X, G)
try:
X, e, G = self.adjustStepSize(X, e, G, stp)
except LineSearchError:
self.logger.error("problem with adjustStepSize, ending quench")
rms = np.linalg.norm(G) / sqrtN
self.logger.error(" on failure: quench step %s %s %s %s", i, e, rms, self.funcalls)
res.message.append( "problem with adjustStepSize" )
break
#e, G = self.pot.getEnergyGradient(X)
rms = np.linalg.norm(G) / sqrtN
if iprint > 0:
if i % iprint == 0:
self.logger.info("lbfgs: %s %s %s %s %s %s %s %s %s", i, "E", e,
"rms", rms, "funcalls", self.funcalls, "stepsize", self.stepsize)
for event in self.events:
event(coords=X, energy=e, rms=rms)
if self.alternate_stop_criterion is None:
i_am_done = rms < self.tol
else:
i_am_done = self.alternate_stop_criterion(energy=e, gradient=G,
tol=self.tol)
if i_am_done:
res.success = True
break
i += 1
res.nsteps = i
res.nfev = self.funcalls
res.coords = X
res.energy = e
res.rms = rms
res.grad = G
res.H0 = self.H0
return res
