def setup_aatopology(self):
GMIN.initialize()
pot = GMINPotential(GMIN)
coords = pot.getCoords()
nrigid = old_div(coords.size, 6)
print("I have %d water molecules in the system"%nrigid)
print("The initial energy is", pot.getEnergy(coords))
water = create_base()
system = RBTopology()
system.add_sites([deepcopy(water) for i in range(nrigid)])
self.potential = pot
self.nrigid = nrigid
self.render_scale = 0.15
self.atom_types = system.get_atomtypes()
self.draw_bonds = []
for i in range(nrigid-1):
self.draw_bonds.append((2*i, 2*i+1))
self.draw_bonds.append((2*i, 2*i+2))
return system
def setup_aatopology(self):
GMIN.initialize()
pot = GMINPotential(GMIN)
coords = pot.getCoords()
nrigid = coords.size / 6
print "I have %d PAP molecules in the system" % nrigid
print "The initial energy is", pot.getEnergy(coords)
water = create_pap()
system = RBTopology()
system.add_sites([deepcopy(water) for i in xrange(nrigid)])
self.potential = pot
self.nrigid = nrigid
self.render_scale = 0.1
self.atom_types = system.get_atomtypes()
self.draw_bonds = []
for i in xrange(nrigid):
self.draw_bonds.append((3 * i, 3 * i + 1))
self.draw_bonds.append((3 * i, 3 * i + 2))
return system
def setup_aatopology(self):
GMIN.initialize()
pot = GMINPotential(GMIN)
coords = pot.getCoords()
nrigid = coords.size / 6
print "I have %d water molecules in the system"%nrigid
print "The initial energy is", pot.getEnergy(coords)
water = tip4p.water()
system = RBTopology()
system.add_sites([deepcopy(water) for i in xrange(nrigid)])
self.potential = pot
self.nrigid = nrigid
self.render_scale = 0.3
self.atom_types = system.get_atomtypes()
self.draw_bonds = []
for i in xrange(nrigid):
self.draw_bonds.append((3*i, 3*i+1))
self.draw_bonds.append((3*i, 3*i+2))
return system
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 __init__(self, *args, **kwargs):
AppBasinHopping.__init__(self, *args, **kwargs)
self.quenchRoutine = mylbfgs
self.potential = GMINPotential(GMIN)
self.quenchParameters["tol"] = 1e-4
self.quenchParameters["M"] = 80
self.quenchParameters["maxErise"] = 0.1
self.quenchRoutine = mylbfgs
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, 0.0, 0.0])) for x, r in zip(ca.posRigid, RMX)]
xbase = [x - 0.4 * np.dot(r[0], np.array([1.0, 0.0, 0.0])) for x, r in zip(ca.posRigid, RMX)]
gback = np.zeros_like(xback)
Eangle = 0.0
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 = 1.0 / np.sqrt(1.0 - 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, 0.0, 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 setup_aatopology(self):
self.write_coords_data()
GMIN.initialize()
self.pot = GMINPotential(GMIN)
coords = self.pot.getCoords()
self.nrigid = coords.size/6
assert(self.nrigid == self.nmol)
#self.nrigid = self.nmol
otp = self.make_otp()
topology = RBTopology()
topology.add_sites([deepcopy(otp) for i in xrange(self.nrigid)])
self.render_scale = 0.2
self.atom_types = topology.get_atomtypes()
self.draw_bonds = []
for i in xrange(self.nrigid):
self.draw_bonds.append((3*i, 3*i+1))
self.draw_bonds.append((3*i, 3*i+2))
self.params.double_ended_connect.local_connect_params.tsSearchParams.iprint = 10
return topology
def check_converged(E, coords):
if (E < (parameters.TARGET + parameters.EDIFF)):
fl = open("stat.dat", "a")
print("#found minimum")
t1 = time.clock()
timespent = t1 - t0
fl.write("#quenches, functioncalls, time\n")
fl.write("%d %d %f\n" % (opt.stepnum, potential.ncalls, timespent))
fl.close()
exit()
# initialize GMIN
GMIN.initialize()
# create a potential which calls GMIN
potential = GMINPotential(GMIN)
# get the initial coorinates
coords = potential.getCoords()
coords = np.random.random(coords.shape)
# create takestep routine
# we combine a normal step taking
group = takestep.BlockMoves()
step1 = takestep.AdaptiveStepsize(OXDNATakestep(displace=parameters.displace,
rotate=0.),
frequency=50)
step2 = takestep.AdaptiveStepsize(OXDNATakestep(displace=0.,
rotate=parameters.rotate),
frequency=50)
group.addBlock(100, step1)
def __init__(self, theta0=140.0 / 180.0 * np.pi, k=4.0, use_torsion=False):
GMINPotential.__init__(self, GMIN)
self.theta0 = theta0
self.k = k
print "theta0 is", theta0
self.use_torsion = use_torsion
def __init__(self, theta0=140. / 180. * np.pi, k=4., use_torsion=False):
GMINPotential.__init__(self, GMIN)
self.theta0 = theta0
self.k = k
print("theta0 is", theta0)
self.use_torsion = use_torsion
import numpy as np
from pele.potentials import GMINPotential
import gmin_ as GMIN
from pele.utils import rotations
from pele.takestep import buildingblocks
from pele.transition_states import NEB
import pylab as pl
from copy import deepcopy, copy
from pele.optimize import mylbfgs
from pele.angleaxis import RigidFragment, RBSystem
import tip4p
from tip4p import dump_path
# initialize GMIN and potential
GMIN.initialize()
pot = GMINPotential(GMIN)
coords = pot.getCoords()
nrigid = old_div(coords.size, 6)
print("I have %d water molecules in the system" % nrigid)
water = tip4p.water()
#water.S = np.identity(3, dtype="float64")
#water.S*=10.
# define the whole water system
system = RBSystem()
system.add_sites([deepcopy(water) for i in range(nrigid)])
# this is an easy access wrapper for coordinates array
ca = system.coords_adapter(coords)
def check_converged(E, coords):
if(E<(parameters.TARGET+parameters.EDIFF)):
fl = open("stat.dat", "a")
print "#found minimum"
t1= time.clock()
timespent= t1 - t0
fl.write("#quenches, functioncalls, time\n")
fl.write("%d %d %f\n"%(opt.stepnum , potential.ncalls , timespent))
fl.close()
exit()
# initialize GMIN
GMIN.initialize()
# create a potential which calls GMIN
potential = GMINPotential(GMIN)
# get the initial coorinates
coords=potential.getCoords()
coords=np.random.random(coords.shape)
# create takestep routine
# we combine a normal step taking
group = takestep.BlockMoves()
step1 = takestep.AdaptiveStepsize(OXDNATakestep(displace=parameters.displace, rotate=0.), frequency=50)
step2 = takestep.AdaptiveStepsize(OXDNATakestep(displace=0., rotate=parameters.rotate), frequency=50)
group.addBlock(100, step1)
group.addBlock(100, step2)
# with a generate random configuration
genrandom = OXDNAReseed()
# in a reseeding takestep procedure
class OTPSystem(RBSystem):
def __init__(self, nmol, boxl=None):
# super(OTPSystem, self)
self.nmol = nmol
if boxl is None:
self.periodic = False
self.boxl = 1e100
else:
self.periodic = True
self.boxl = boxl
super(OTPSystem, self).__init__()
self.setup_params(self.params)
def get_rigid_fragment(self):
return RigidFragment()
def make_otp(self):
otp = self.get_rigid_fragment()
otp.add_atom("O", np.array([0.0, -2./3 * np.sin( 7.*pi/24.), 0.0]), 1.)
otp.add_atom("O", np.array([cos( 7.*pi/24.), 1./3. * sin( 7.* pi/24.), 0.0]), 1.)
otp.add_atom("O", np.array([-cos( 7.* pi/24.), 1./3. * sin( 7.*pi/24), 0.0]), 1.)
otp.finalize_setup()
return otp
def setup_params(self, params):
params.gui["basinhopping_nsteps"] = 1000
nebparams = params.double_ended_connect.local_connect_params.NEBparams
nebparams.max_images = 50
nebparams.image_density = 5
nebparams.iter_density = 10.
nebparams.k = 5.
nebparams.reinterpolate = 50
nebparams.NEBquenchParams["iprint"] = 10
tssearch = params.double_ended_connect.local_connect_params.tsSearchParams
tssearch.nsteps_tangent1 = 10
tssearch.nsteps_tangent2 = 30
tssearch.lowestEigenvectorQuenchParams["nsteps"] = 50
tssearch.iprint=1
tssearch.nfail_max = 100
def get_random_coordinates(self):
coords = np.zeros([self.nmol*2, 3])
coords[:self.nmol,:] = np.random.uniform(-1,1,[self.nmol,3]) * (self.nmol*3)**(-1./3) * 1.5
from pele.utils.rotations import random_aa
for i in range(self.nmol, self.nmol*2):
coords[i,:] = random_aa()
return coords.flatten()
def write_coords_data(self):
coords = self.get_random_coordinates()
coords = coords.reshape(-1,3)
with open("coords", "w") as fout:
for xyz in coords:
fout.write( "%f %f %f\n" % tuple(xyz) )
data = "LWOTP 2.614\n"
if self.periodic:
data += "periodic %f %f %f\n" % (self.boxl, self.boxl, self.boxl)
with open("data", "w") as fout:
fout.write(data)
def setup_aatopology(self):
self.write_coords_data()
GMIN.initialize()
self.pot = GMINPotential(GMIN)
coords = self.pot.getCoords()
self.nrigid = coords.size/6
assert(self.nrigid == self.nmol)
#self.nrigid = self.nmol
otp = self.make_otp()
topology = RBTopology()
topology.add_sites([deepcopy(otp) for i in xrange(self.nrigid)])
self.render_scale = 0.2
self.atom_types = topology.get_atomtypes()
self.draw_bonds = []
for i in xrange(self.nrigid):
self.draw_bonds.append((3*i, 3*i+1))
self.draw_bonds.append((3*i, 3*i+2))
self.params.double_ended_connect.local_connect_params.tsSearchParams.iprint = 10
return topology
def get_potential(self):
#return OTPPotential(self.aasystem)
return self.pot
def __call__(self):
return self
def load_coords_pymol(self, coordslist, oname, index=1):
import pymol
super(OTPSystem, self).load_coords_pymol(coordslist, oname, index=index)
pymol.cmd.set("sphere_scale", value=0.2, selection=oname)
import numpy as np from pele.potentials import GMINPotential import gmin_ as GMIN from pele.utils import rotations from pele.takestep import buildingblocks from pele.transition_states import NEB import pylab as pl from copy import deepcopy, copy from pele.optimize import mylbfgs from pele.angleaxis import RigidFragment, RBSystem import tip4p from tip4p import dump_path # initialize GMIN and potential GMIN.initialize() pot = GMINPotential(GMIN) coords = pot.getCoords() nrigid = coords.size / 6 print "I have %d water molecules in the system"%nrigid water = tip4p.water() #water.S = np.identity(3, dtype="float64") #water.S*=10. # define the whole water system system = RBSystem() system.add_sites([deepcopy(water) for i in xrange(nrigid)]) # this is an easy access wrapper for coordinates array ca = system.coords_adapter(coords)
