class Strain(ForceField):
def __init__(self, system, term, other_terms, cart_penalty=1e-3*angstrom):
'''
A class deriving from the Yaff ForceField class to implement the
strain of a molecular geometry associated with the term defined by
term_index.
**Arguments**
system
A Yaff System instance containing all system information.
term
a Term instance representing the term of the perturbation
trajectory of the current strain
other_terms
a list of Term instances representing all other terms for ICs
for which a strain contribution should be added
**Keyword Arguments**
cart_penalty
Magnitude of an extra term added to the strain that penalises
a deviation of the cartesian coordinates of each atom with
respect to the equilibrium coordinates. This penalty is equal
to norm(R-R_eq)**2/(2.0*3*Natoms*cart_penalty**2) and prevents
global translations, global rotations as well as rotations of
molecular fragments far from the IC under consideration.
'''
self.coords0 = system.pos.copy()
self.ndof = np.prod(self.coords0.shape)
self.cart_penalty = cart_penalty
self.cons_ic_atindexes = term.get_atoms()
#construct main strain
strain = ForcePartValence(system)
for other in other_terms:
if other.kind == 3: continue #no cross terms
strain.add_term(Harmonic(1.0, None, other.ics[0]))
#set the rest values to the equilibrium values
strain.dlist.forward()
strain.iclist.forward()
for iterm in range(strain.vlist.nv):
vterm = strain.vlist.vtab[iterm]
ic = strain.iclist.ictab[vterm['ic0']]
vterm['par1'] = ic['value']
ForceField.__init__(self, system, [strain])
#Abuse the Chebychev1 polynomial to simply get the value of q-1 and
#implement the contraint
constraint = ForcePartValence(system)
constraint.add_term(Chebychev1(-2.0,term.ics[0]))
self.constraint = ForceField(system, [constraint])
self.constrain_target = None
self.constrain_value = None
self.value = None
def gradient(self, X):
'''
Compute the gradient of the strain w.r.t. Cartesian coordinates of
the system. For the ic that needs to be constrained, a Lagrange
multiplier is included.
'''
#initialize return value
grad = np.zeros((len(X),))
#compute strain gradient
gstrain = np.zeros(self.coords0.shape)
self.update_pos(self.coords0 + X[:self.ndof].reshape((-1,3)))
self.value = self.compute(gpos=gstrain)
#compute constraint gradient
gconstraint = np.zeros(self.coords0.shape)
self.constraint.update_pos(self.coords0 + X[:self.ndof].reshape((-1,3)))
self.constrain_value = self.constraint.compute(gpos=gconstraint) + 1.0
#construct gradient
grad[:self.ndof] = gstrain.reshape((-1,)) + X[self.ndof]*gconstraint.reshape((-1,))
grad[self.ndof] = self.constrain_value - self.constrain_target
#cartesian penalty, i.e. extra penalty for deviation w.r.t. cartesian equilibrium coords
indices = np.array([[3*i,3*i+1,3*i+2] for i in range(self.ndof//3) if i not in self.cons_ic_atindexes]).ravel()
if len(indices)>0:
grad[indices] += X[indices]/(self.ndof*self.cart_penalty**2)
with log.section('PTGEN', 4, timer='PT Generate'):
log.dump(' Gradient: rms = %.3e max = %.3e cnstr = %.3e' %(np.sqrt((grad[:self.ndof]**2).mean()), max(grad[:self.ndof]), grad[self.ndof]))
return grad
class Strain(ForceField):
def __init__(self,
system,
cons_ic,
cons_ic_atindexes,
ics,
cart_penalty=1e-3 * angstrom):
'''
A class deriving from the Yaff ForceField class to implement the
strain of a molecular geometry associated with the term defined by
term_index.
**Arguments**
system
A Yaff System instance containing all system information.
cons_ic
An instance of Yaff Internal Coordinate representing the
constrained term in the strain.
cons_ic_atindexes
A list of the atoms involved in the constrained IC. This is
required for the implementation of the cartesian penalty. In
principle this could be extracted from the information stored
in cons_ic, but this is the lazy solution.
ics
A list of Yaff Internal Coordinate instances for which the
strain needs to be minimized.
cart_penalty
Magnitude of an extra term added to the strain that penalises
a deviation of the cartesian coordinates of each atom with
respect to the equilibrium coordinates. This penalty is equal
to norm(R-R_eq)**2/(2.0*3*Natoms*cart_penalty**2) and prevents
global translations, global rotations as well as rotations of
molecular fragments far from the IC under consideration.
'''
self.coords0 = system.pos.copy()
self.ndof = np.prod(self.coords0.shape)
self.cart_penalty = cart_penalty
self.cons_ic_atindexes = cons_ic_atindexes
part = ForcePartValence(system)
for ic in ics:
part.add_term(Harmonic(1.0, None, ic))
#set the rest values to the equilibrium values
part.dlist.forward()
part.iclist.forward()
for iterm in xrange(part.vlist.nv):
term = part.vlist.vtab[iterm]
ic = part.iclist.ictab[term['ic0']]
term['par1'] = ic['value']
ForceField.__init__(self, system, [part])
#Abuse the Chebychev1 polynomial to simply get the value of q-1 and
#implement the contraint
part = ForcePartValence(system)
part.add_term(Chebychev1(-2.0, cons_ic))
self.constraint = ForceField(system, [part])
self.constrain_target = None
self.constrain_value = None
self.value = None
def gradient(self, X):
'''
Compute the gradient of the strain wrt Cartesian coordinates of the
system. For every ic that needs to be constrained, a Lagrange multiplier
is included.
'''
#small check
#assert X.shape[0] == self.ndof + 1
#initialize return value
grad = np.zeros((len(X), ))
#compute strain gradient
gstrain = np.zeros(self.coords0.shape)
self.update_pos(self.coords0 + X[:self.ndof].reshape((-1, 3)))
self.value = self.compute(gpos=gstrain)
#compute constraint gradient
gconstraint = np.zeros(self.coords0.shape)
self.constraint.update_pos(self.coords0 +
X[:self.ndof].reshape((-1, 3)))
self.constrain_value = self.constraint.compute(gpos=gconstraint) + 1.0
#construct gradient
grad[:self.ndof] = gstrain.reshape(
(-1, )) + X[self.ndof] * gconstraint.reshape((-1, ))
grad[self.ndof] = self.constrain_value - self.constrain_target
#cartesian penalty, i.e. extra penalty for deviation w.r.t. cartesian equilibrium coords
indices = np.array([[3 * i, 3 * i + 1, 3 * i + 2]
for i in xrange(self.ndof / 3)
if i not in self.cons_ic_atindexes]).ravel()
if len(indices) > 0:
grad[indices] += X[indices] / (self.ndof * self.cart_penalty**2)
with log.section('PTGEN', 4, timer='PT Generate'):
log.dump(' Gradient: rms = %.3e max = %.3e cnstr = %.3e' %
(np.sqrt(
(grad[:self.ndof]**2).mean()), max(
grad[:self.ndof]), grad[self.ndof]))
return grad
class Strain(ForceField):
def __init__(self, system, term, other_terms, cart_penalty=1e-3*angstrom):
'''
A class deriving from the Yaff ForceField class to implement the
strain of a molecular geometry associated with the term defined by
term_index.
**Arguments**
system
A Yaff System instance containing all system information.
term
a Term instance representing the term of the perturbation
trajectory of the current strain
other_terms
a list of Term instances representing all other terms for ICs
for which a strain contribution should be added
**Keyword Arguments**
cart_penalty
Magnitude of an extra term added to the strain that penalises
a deviation of the cartesian coordinates of each atom with
respect to the equilibrium coordinates. This penalty is equal
to norm(R-R_eq)**2/(2.0*3*Natoms*cart_penalty**2) and prevents
global translations, global rotations as well as rotations of
molecular fragments far from the IC under consideration.
'''
self.coords0 = system.pos.copy()
self.ndof = np.prod(self.coords0.shape)
self.cart_penalty = cart_penalty
self.cons_ic_atindexes = term.get_atoms()
#construct main strain
strain = ForcePartValence(system)
for other in other_terms:
if other.kind == 3: continue #no cross terms
strain.add_term(Harmonic(1.0, None, other.ics[0]))
#set the rest values to the equilibrium values
strain.dlist.forward()
strain.iclist.forward()
for iterm in range(strain.vlist.nv):
vterm = strain.vlist.vtab[iterm]
ic = strain.iclist.ictab[vterm['ic0']]
vterm['par1'] = ic['value']
ForceField.__init__(self, system, [strain])
#Abuse the Chebychev1 polynomial to simply get the value of q-1 and
#implement the contraint
constraint = ForcePartValence(system)
constraint.add_term(Chebychev1(-2.0,term.ics[0]))
self.constraint = ForceField(system, [constraint])
self.constrain_target = None
self.constrain_value = None
self.value = None
def gradient(self, X):
'''
Compute the gradient of the strain w.r.t. Cartesian coordinates of
the system. For the ic that needs to be constrained, a Lagrange
multiplier is included.
'''
#initialize return value
grad = np.zeros((len(X),))
#compute strain gradient
gstrain = np.zeros(self.coords0.shape)
self.update_pos(self.coords0 + X[:self.ndof].reshape((-1,3)))
self.value = self.compute(gpos=gstrain)
#compute constraint gradient
gconstraint = np.zeros(self.coords0.shape)
self.constraint.update_pos(self.coords0 + X[:self.ndof].reshape((-1,3)))
self.constrain_value = self.constraint.compute(gpos=gconstraint) + 1.0
#construct gradient
grad[:self.ndof] = gstrain.reshape((-1,)) + X[self.ndof]*gconstraint.reshape((-1,))
grad[self.ndof] = self.constrain_value - self.constrain_target
#cartesian penalty, i.e. extra penalty for deviation w.r.t. cartesian equilibrium coords
indices = np.array([[3*i,3*i+1,3*i+2] for i in range(self.ndof//3) if i not in self.cons_ic_atindexes]).ravel()
if len(indices)>0:
grad[indices] += X[indices]/(self.ndof*self.cart_penalty**2)
with log.section('PTGEN', 4, timer='PT Generate'):
log.dump(' Gradient: rms = %.3e max = %.3e cnstr = %.3e' %(np.sqrt((grad[:self.ndof]**2).mean()), max(grad[:self.ndof]), grad[self.ndof]))
return grad
