def initial_path (f, s, c):
"""
This is called with pure MM PES f(s) to get some initial
path. Somewhat ad-hoc.
"""
# The input geometry s may be reasonable, but it may not be an
# exact minimum. Reoptimize:
s, info = minimize (f, s, maxit=100, ftol=5.0e-4, xtol=5.0e-4, algo=1)
print ("converged=", info["converged"], "in", info["iterations"])
# The value of reaction coordinate in the initial geometry:
c0 = c(s)
print ("XXX: rc(0)=", c0)
it = 0
ss = []
qs = []
algo = 1
while c(s) > -c0:
it += 1
# write_xyz ("in-%03d.xyz" % it, trafo (s))
print ("XXX: rc(0)=", c(s))
s, info = cminimize (f, s, Array (c), maxit=200, ftol=5.0e-3, xtol=5.0e-3, algo=algo)
# Collect optimized geometries and the corresponding
# values of reaction coordinate:
ss.append (s)
qs.append (c(s))
print ("converged=", info["converged"], "in", info["iterations"])
print ("XXX: rc(1)=", c(s))
# write_xyz ("out-%03d.xyz" % it, trafo (s))
# Here c.fprime(s) is how much that reaction coordinate
# will change if you modify the coordinates. Hacky way to
# chage a geometry so that the RC is modified too:
s = s - 0.1 * c.fprime (s)
ss = asarray (ss)
qs = asarray (qs)
print ("qs=", qs)
p = Path (ss, qs)
print ("path=", p)
qs = linspace (c0, -c0, 21)
print ("qs=", qs)
ss = map (p, qs)
res = map (lambda s: cminimize (f, s, Array (c), maxit=200, ftol=1.0e-3, xtol=1.0e-3, algo=algo), ss)
infos = [inf for _, inf in res]
ss = [s for s, _ in res]
for info in infos:
print ("converged=", info["converged"], "in", info["iterations"])
for i, s in enumerate (ss):
write_xyz ("out-%03d.xyz" % i, trafo (s))
return qs, ss
def copt(s, maxit):
sm, info = cminimize(e,
s,
Array(c),
maxit=maxit,
ftol=1.0e-3,
xtol=1.0e-3,
algo=0)
print("converged=", info["converged"], "in",
info["iterations"])
return sm
def initial_path(f, s, c):
"""
This is called with pure MM PES f(s) to get some initial
path. Somewhat ad-hoc.
"""
# The input geometry s may be reasonable, but it may not be an
# exact minimum. Reoptimize:
s, info = minimize(f, s, maxit=100, ftol=5.0e-4, xtol=5.0e-4, algo=1)
print("converged=", info["converged"], "in", info["iterations"])
# The value of reaction coordinate in the initial geometry:
c0 = c(s)
print("XXX: rc(0)=", c0)
it = 0
ss = []
qs = []
algo = 1
while c(s) > -c0:
it += 1
# write_xyz ("in-%03d.xyz" % it, trafo (s))
print("XXX: rc(0)=", c(s))
s, info = cminimize(f,
s,
Array(c),
maxit=200,
ftol=5.0e-3,
xtol=5.0e-3,
algo=algo)
# Collect optimized geometries and the corresponding
# values of reaction coordinate:
ss.append(s)
qs.append(c(s))
print("converged=", info["converged"], "in", info["iterations"])
print("XXX: rc(1)=", c(s))
# write_xyz ("out-%03d.xyz" % it, trafo (s))
# Here c.fprime(s) is how much that reaction coordinate
# will change if you modify the coordinates. Hacky way to
# chage a geometry so that the RC is modified too:
s = s - 0.1 * c.fprime(s)
ss = asarray(ss)
qs = asarray(qs)
print("qs=", qs)
p = Path(ss, qs)
print("path=", p)
qs = linspace(c0, -c0, 21)
print("qs=", qs)
ss = map(p, qs)
res = map(
lambda s: cminimize(
f, s, Array(c), maxit=200, ftol=1.0e-3, xtol=1.0e-3, algo=algo),
ss)
infos = [inf for _, inf in res]
ss = [s for s, _ in res]
for info in infos:
print("converged=", info["converged"], "in", info["iterations"])
for i, s in enumerate(ss):
write_xyz("out-%03d.xyz" % i, trafo(s))
return qs, ss
def copt (s, maxit):
sm, info = cminimize (e, s, Array (c), maxit=maxit, ftol=1.0e-3, xtol=1.0e-3, algo=0)
print ("converged=", info["converged"], "in", info["iterations"])
return sm
