def getEnergy(self, coords):
E = GMINPotential.getEnergy(self, coords)
ca = CoordsAdapter(nrigid=coords.size / 6, coords=coords)
RMX = [rmdrvt(p, True) for p in ca.rotRigid]
xback = np.array([x - 0.4 * np.dot(r[0], np.array([1.0, 0.0, 0.0])) for x, r in zip(ca.posRigid, RMX)])
xbase = np.array([x + 0.4 * np.dot(r[0], np.array([1.0, 0.0, 0.0])) for x, r in zip(ca.posRigid, RMX)])
Eangle = 0
v2 = xback[1] - xback[0]
v2 /= np.linalg.norm(v2)
for i in xrange(1, ca.nrigid - 1):
v1 = -v2.copy()
v2 = xback[i + 1] - xback[i]
v2 /= np.linalg.norm(v2)
theta = np.arccos(np.dot(v1, v2))
Eangle += 0.5 * self.k * (theta - self.theta0) ** 2
# add the torsion angle
Etorsion = 0
if self.use_torsion:
for i in xrange(ca.nrigid - 3):
theta = dihedral_angle(xback[i : i + 4])
Etorsion += U_torsion_back(theta)
return E + Eangle + Etorsion
def getEnergy(self, coords):
E = GMINPotential.getEnergy(self, coords)
ca = CoordsAdapter(nrigid=old_div(coords.size, 6), coords=coords)
RMX = [rotMatDeriv(p, True) for p in ca.rotRigid]
xback = np.array([
x - 0.4 * np.dot(r[0], np.array([1., 0., 0.]))
for x, r in zip(ca.posRigid, RMX)
])
xbase = np.array([
x + 0.4 * np.dot(r[0], np.array([1., 0., 0.]))
for x, r in zip(ca.posRigid, RMX)
])
Eangle = 0
v2 = xback[1] - xback[0]
v2 /= np.linalg.norm(v2)
for i in range(1, ca.nrigid - 1):
v1 = -v2.copy()
v2 = xback[i + 1] - xback[i]
v2 /= np.linalg.norm(v2)
theta = np.arccos(np.dot(v1, v2))
Eangle += 0.5 * self.k * (theta - self.theta0)**2
# add the torsion angle
Etorsion = 0
if self.use_torsion:
for i in range(ca.nrigid - 3):
theta = dihedral_angle(xback[i:i + 4])
Etorsion += U_torsion_back(theta)
return E + Eangle + Etorsion
def getEnergyGradient(self, coords):
#return self.getEnergy(coords), self.NumericalDerivative(coords)
E, grad = GMINPotential.getEnergyGradient(self, coords)
ca = CoordsAdapter(nrigid=old_div(coords.size, 6), coords=coords)
RMX = [rotMatDeriv(p, True) for p in ca.rotRigid]
xback = [
x - 0.4 * np.dot(r[0], np.array([1., 0., 0.]))
for x, r in zip(ca.posRigid, RMX)
]
xbase = [
x - 0.4 * np.dot(r[0], np.array([1., 0., 0.]))
for x, r in zip(ca.posRigid, RMX)
]
gback = np.zeros_like(xback)
Eangle = 0.
v2 = xback[1] - xback[0]
absv2 = np.linalg.norm(v2)
v2 /= absv2
for i in range(1, ca.nrigid - 1):
v1 = -v2
absv1 = absv2
v2 = xback[i + 1] - xback[i]
absv2 = np.linalg.norm(v2)
v2 /= absv2
v1v2 = np.dot(v1, v2)
theta = np.arccos(v1v2)
Eangle += 0.5 * self.k * (theta - self.theta0)**2
acos_prime = 1. / np.sqrt(1. - v1v2**2)
s = self.k * (theta - self.theta0) * acos_prime
gback[i -
1] += s * (old_div(-v2, absv1) + old_div(v1v2 * v1, absv1))
gback[i] += s * (old_div(v1, absv2) + old_div(v2, absv1) - old_div(
v1v2 * v1, absv1) - old_div(v1v2 * v2, absv2))
gback[i +
1] += s * (old_div(-v1, absv2) + old_div(v1v2 * v2, absv2))
Etorsion = 0
if self.use_torsion:
for i in range(ca.nrigid - 3):
r = xback[i:i + 4]
theta = dihedral_angle(r)
e_theta, g_theta = U_torsion_back_grad(theta)
Etorsion += e_theta
gback[i:i + 4] += g_theta * dihedral_gradient(r)
cg = CoordsAdapter(nrigid=ca.nrigid, coords=grad)
cg.posRigid += gback
for i in range(ca.nrigid):
x = -0.4 * np.array([1., 0., 0.])
R = RMX[i]
cg.rotRigid[i][0] += np.dot(gback[i], np.dot(R[1], x))
cg.rotRigid[i][1] += np.dot(gback[i], np.dot(R[2], x))
cg.rotRigid[i][2] += np.dot(gback[i], np.dot(R[3], x))
return E + Eangle + Etorsion, grad
def getEnergyGradient(self, coords):
#return self.getEnergy(coords), self.NumericalDerivative(coords)
E, grad = GMINPotential.getEnergyGradient(self, coords)
ca = CoordsAdapter(nrigid=coords.size/6, coords=coords)
RMX = [rmdrvt(p, True) for p in ca.rotRigid]
xback = [x - 0.4*np.dot(r[0], np.array([1., 0., 0.])) for x, r in zip(ca.posRigid, RMX)]
xbase = [x - 0.4*np.dot(r[0], np.array([1., 0., 0.])) for x, r in zip(ca.posRigid, RMX)]
gback = np.zeros_like(xback)
Eangle = 0.
v2 = xback[1] - xback[0]
absv2 = np.linalg.norm(v2)
v2 /= absv2
for i in xrange(1,ca.nrigid-1):
v1 = -v2
absv1 = absv2
v2 = xback[i+1] - xback[i]
absv2 = np.linalg.norm(v2)
v2 /= absv2
v1v2 = np.dot(v1,v2)
theta = np.arccos(v1v2)
Eangle += 0.5*self.k*(theta - self.theta0)**2
acos_prime = 1. / np.sqrt(1. - v1v2**2);
s = self.k*(theta - self.theta0)*acos_prime
gback[i-1] += s * (- v2 / absv1 + v1v2 * v1 / absv1 )
gback[i] += s * ( v1/absv2 + v2/absv1
- v1v2 * v1 / absv1
- v1v2 * v2 / absv2)
gback[i+1] += s * (- v1 / absv2 + v1v2 * v2 / absv2 )
Etorsion = 0
if self.use_torsion:
for i in xrange(ca.nrigid-3):
r = xback[i:i+4]
theta = dihedral_angle(r)
e_theta, g_theta = U_torsion_back_grad(theta)
Etorsion += e_theta
gback[i:i+4] += g_theta * dihedral_gradient(r)
cg = CoordsAdapter(nrigid=ca.nrigid, coords=grad)
cg.posRigid += gback
for i in xrange(ca.nrigid):
x = -0.4*np.array([1., 0., 0.])
R = RMX[i]
cg.rotRigid[i][0] += np.dot(gback[i], np.dot(R[1], x))
cg.rotRigid[i][1] += np.dot(gback[i], np.dot(R[2], x))
cg.rotRigid[i][2] += np.dot(gback[i], np.dot(R[3], x))
return E + Eangle + Etorsion, grad
