def test(natoms=40, boxl=4.0):
import pele.potentials.ljpshiftfast as ljpshift
from pele.optimize import mylbfgs
from pele.utils.neighbor_list import makeBLJNeighborListPot
ntypeA = int(natoms * 0.8)
ntypeB = natoms - ntypeA
rcut = 2.5
freezelist = range(ntypeA / 2) + range(ntypeA, ntypeA + ntypeB / 2)
nfrozen = len(freezelist)
print "nfrozen", nfrozen
coords = np.random.uniform(-1, 1, natoms * 3) * (natoms) ** (1.0 / 3) / 2
NLblj = ljpshift.LJpshift(natoms, ntypeA, rcut=rcut, boxl=boxl)
blj = FreezePot(NLblj, freezelist, natoms)
pot = makeBLJNeighborListPotFreeze(natoms, freezelist, ntypeA=ntypeA, rcut=rcut, boxl=boxl)
# pot = FreezePot(NLpot, freezelist)
eblj = blj.getEnergy(coords)
print "blj energy", eblj
epot = pot.getEnergy(coords)
print "mcpot energy", epot
print "difference", (epot - eblj) / eblj
pot.test_potential(coords)
print "\n"
ret1 = mylbfgs(coords, blj, iprint=-11)
np.savetxt("out.coords", ret1.coords)
print "energy from quench1", ret1.energy
ret2 = mylbfgs(coords, pot, iprint=-1)
print "energy from quench2", ret2.energy
print "ret1 evaluated in both potentials", pot.getEnergy(ret1.coords), blj.getEnergy(ret1.coords)
print "ret2 evaluated in both potentials", pot.getEnergy(ret2.coords), blj.getEnergy(ret2.coords)
coords = ret1.coords
e1, g1 = blj.getEnergyGradient(coords)
e2, g2 = pot.getEnergyGradient(coords)
print "energy difference from getEnergyGradient", (e2 - e1)
print "largest gradient difference", np.max(np.abs(g2 - g1))
print "rms gradients", np.linalg.norm(g1) / np.sqrt(len(g1)), np.linalg.norm(g2) / np.sqrt(len(g1))
if True:
for subpot in pot.pot.potentials:
nl = subpot
print "number of times neighbor list was remade:", nl.buildcount, "out of", nl.count
if False:
try:
import pele.utils.pymolwrapper as pym
pym.start()
pym.draw_spheres(np.reshape(coords, [-1, 3]), "A", 1)
pym.draw_spheres(np.reshape(ret1.coords, [-1, 3]), "A", 2)
pym.draw_spheres(np.reshape(ret2.coords, [-1, 3]), "A", 3)
except ImportError:
print "Could not draw using pymol, skipping this step"
def test_align_improvement(self, verbose = True):
np.random.seed(6)
max_step = 10000
fail_counter = 0
ave = 0
ave_inc = 0
for i in range(max_step):
if (i%100 == 0):
print(i)
self.x1 = self.get_random_configuration()
self.x2diff = self.get_random_configuration()
dist = self.measure.get_dist(self.x1, self.x2diff)
dist2, x1, x2 = self.mindist(self.x1, self.x2diff)
if(dist2 > dist):
# if(i==10):
fail_counter += 1
ave_inc += dist2 - dist
if(verbose):
print("x1", x1)
print("old x2", self.x2diff)
print("new x2", x2)
# print "atomistic x1", self.topology.to_atomistic(x1).flatten()
# print "atomistic x2", self.topology.to_atomistic(self.x2diff)
# print "new atomistic x2", self.topology.to_atomistic(x2)
print("dist", dist)
print("dist2", dist2)
print("i", i)
try:
import pele.utils.pymolwrapper as pym
pym.start()
x1 = self.topology.to_atomistic(x1)
x2 = self.topology.to_atomistic(x2)
self.x2diff = self.topology.to_atomistic(self.x2diff)
pym.draw_rigid(x1, "A", 0.1, (1,0,0), self.system.draw_bonds)
pym.draw_rigid(self.x2diff, "B", 0.1, (0,1,0), self.system.draw_bonds)
pym.draw_rigid(x2, "C", 0.1, (0,0,1), self.system.draw_bonds)
pym.draw_box(self.boxl, "D", 0.1)
# pym.draw_rigid(x1[:self.nrigid*3], "A", 0.1, (1,0,0))
# pym.draw_rigid(self.x2diff[:self.nrigid*3], "B", 0.1, (0,1,0))
# pym.draw_rigid(x2[:self.nrigid*3], "C", 0.1, (0,0,1))
# pym.draw_box(self.boxl, "D", 0.1)
except:
print("Could not draw using pymol, skipping this step")
else:
ave += dist - dist2
ave = old_div(ave,max_step)
if (fail_counter>0): ave_inc = old_div(ave_inc, fail_counter)
print("average decrease in distance", ave)
print("average increase in distance", ave_inc)
self.assertFalse(fail_counter, "alignment failed %d times" % fail_counter)
def test_align_improvement(self, verbose = True):
np.random.seed(6)
max_step = 10000
fail_counter = 0
ave = 0
ave_inc = 0
for i in range(max_step):
if (i%100 == 0):
print(i)
self.x1 = self.get_random_configuration()
self.x2diff = self.get_random_configuration()
dist = self.measure.get_dist(self.x1, self.x2diff)
dist2, x1, x2 = self.mindist(self.x1, self.x2diff)
if(dist2 > dist):
# if(i==10):
fail_counter += 1
ave_inc += dist2 - dist
if(verbose):
print("x1", x1)
print("old x2", self.x2diff)
print("new x2", x2)
# print "atomistic x1", self.topology.to_atomistic(x1).flatten()
# print "atomistic x2", self.topology.to_atomistic(self.x2diff)
# print "new atomistic x2", self.topology.to_atomistic(x2)
print("dist", dist)
print("dist2", dist2)
print("i", i)
try:
import pele.utils.pymolwrapper as pym
pym.start()
x1 = self.topology.to_atomistic(x1)
x2 = self.topology.to_atomistic(x2)
self.x2diff = self.topology.to_atomistic(self.x2diff)
pym.draw_rigid(x1, "A", 0.1, (1,0,0), self.system.draw_bonds)
pym.draw_rigid(self.x2diff, "B", 0.1, (0,1,0), self.system.draw_bonds)
pym.draw_rigid(x2, "C", 0.1, (0,0,1), self.system.draw_bonds)
pym.draw_box(self.boxl, "D", 0.1)
# pym.draw_rigid(x1[:self.nrigid*3], "A", 0.1, (1,0,0))
# pym.draw_rigid(self.x2diff[:self.nrigid*3], "B", 0.1, (0,1,0))
# pym.draw_rigid(x2[:self.nrigid*3], "C", 0.1, (0,0,1))
# pym.draw_box(self.boxl, "D", 0.1)
except:
print("Could not draw using pymol, skipping this step")
else:
ave += dist - dist2
ave = ave/max_step
if (fail_counter>0): ave_inc = ave_inc / fail_counter
print("average decrease in distance", ave)
print("average increase in distance", ave_inc)
self.assertFalse(fail_counter, "alignment failed %d times" % fail_counter)
def runtest(X, pot, natoms = 100, iprint=-1):
from _lbfgs_py import PrintEvent
tol = 1e-5
maxstep = 0.005
Xinit = np.copy(X)
e, g = pot.getEnergyGradient(X)
print "energy", e
lbfgs = LBFGS(X, pot, maxstep = 0.1, nsteps=10000, tol=tol,
iprint=iprint, H0=2.)
printevent = PrintEvent( "debugout.xyz")
lbfgs.attachEvent(printevent)
ret = lbfgs.run()
print ret
print ""
print "now do the same with scipy lbfgs"
from pele.optimize import lbfgs_scipy as quench
ret = quench(Xinit, pot, tol = tol)
print ret
#print ret[1], ret[2], ret[3]
if False:
print "now do the same with scipy bfgs"
from pele.optimize import bfgs as oldbfgs
ret = oldbfgs(Xinit, pot, tol = tol)
print ret
if False:
print "now do the same with gradient + linesearch"
import _bfgs
gpl = _bfgs.GradientPlusLinesearch(Xinit, pot, maxstep = 0.1)
ret = gpl.run(1000, tol = 1e-6)
print ret
if False:
print "calling from wrapper function"
from pele.optimize import lbfgs_py
ret = lbfgs_py(Xinit, pot, tol = tol)
print ret
if True:
print ""
print "now do the same with lbfgs_py"
from pele.optimize import lbfgs_py
ret = lbfgs_py(Xinit, pot, tol = tol)
print ret
try:
import pele.utils.pymolwrapper as pym
pym.start()
for n, coords in enumerate(printevent.coordslist):
coords=coords.reshape(natoms, 3)
pym.draw_spheres(coords, "A", n)
except ImportError:
print "error loading pymol"
def test(natoms=40, boxl=4.): # pragma: no cover
import pele.potentials.ljpshiftfast as ljpshift
from pele.optimize import mylbfgs
from pele.utils.neighbor_list import makeBLJNeighborListPot
ntypeA = int(natoms * 0.8)
ntypeB = natoms - ntypeA
rcut = 2.5
freezelist = list(range(old_div(ntypeA, 2))) + list(range(ntypeA, ntypeA + old_div(ntypeB, 2)))
nfrozen = len(freezelist)
print("nfrozen", nfrozen)
coords = old_div(np.random.uniform(-1, 1, natoms * 3) * natoms ** (1. / 3), 2)
NLblj = ljpshift.LJpshift(natoms, ntypeA, rcut=rcut, boxl=boxl)
blj = FreezePot(NLblj, freezelist, natoms)
pot = makeBLJNeighborListPotFreeze(natoms, freezelist, ntypeA=ntypeA, rcut=rcut, boxl=boxl)
eblj = blj.getEnergy(coords)
print("blj energy", eblj)
epot = pot.getEnergy(coords)
print("mcpot energy", epot)
print("difference", old_div((epot - eblj), eblj))
pot.test_potential(coords)
print("\n")
ret1 = mylbfgs(coords, blj, iprint=-11)
np.savetxt("out.coords", ret1.coords)
print("energy from quench1", ret1.energy)
ret2 = mylbfgs(coords, pot, iprint=-1)
print("energy from quench2", ret2.energy)
print("ret1 evaluated in both potentials", pot.getEnergy(ret1.coords), blj.getEnergy(ret1.coords))
print("ret2 evaluated in both potentials", pot.getEnergy(ret2.coords), blj.getEnergy(ret2.coords))
coords = ret1.coords
e1, g1 = blj.getEnergyGradient(coords)
e2, g2 = pot.getEnergyGradient(coords)
print("energy difference from getEnergyGradient", (e2 - e1))
print("largest gradient difference", np.max(np.abs(g2 - g1)))
print("rms gradients", old_div(np.linalg.norm(g1), np.sqrt(len(g1))), old_div(np.linalg.norm(g2), np.sqrt(len(g1))))
if True:
for subpot in pot.pot.potentials:
nl = subpot
print("number of times neighbor list was remade:", nl.buildcount, "out of", nl.count)
if False:
try:
import pele.utils.pymolwrapper as pym
pym.start()
pym.draw_spheres(np.reshape(coords, [-1, 3]), "A", 1)
pym.draw_spheres(np.reshape(ret1.coords, [-1, 3]), "A", 2)
pym.draw_spheres(np.reshape(ret2.coords, [-1, 3]), "A", 3)
except ImportError:
print("Could not draw using pymol, skipping this step")
def takeStep(self, coords, **kwargs):
# make a new monte carlo class
mc = MonteCarlo(coords, self.potential, self.mcstep,
temperature=self.T, outstream=None)
mc.run(self.nsteps)
coords[:] = mc.coords[:]
def updateStep(self, acc, **kwargs):
pass
natoms = 12
# random initial coordinates
coords = np.random.random(3 * natoms)
potential = lj.LJ()
step = TakeStepMonteCarlo(potential)
opt = bh.BasinHopping(coords, potential, takeStep=step)
opt.run(100)
# some visualization
try:
import pele.utils.pymolwrapper as pym
pym.start()
pym.draw_spheres(opt.coords, "A", 1)
except:
print("Could not draw using pymol, skipping this step")
def takeStep(self, coords, **kwargs):
# make a new monte carlo class
mc = MonteCarlo(coords, self.potential, self.mcstep,
temperature=self.T, outstream=None)
mc.run(self.nsteps)
coords[:] = mc.coords[:]
def updateStep(self, acc, **kwargs):
pass
natoms = 12
# random initial coordinates
coords = np.random.random(3 * natoms)
potential = lj.LJ()
step = TakeStepMonteCarlo(potential)
opt = bh.BasinHopping(coords, potential, takeStep=step)
opt.run(100)
# some visualization
try:
import pele.utils.pymolwrapper as pym
pym.start()
pym.draw_spheres(opt.coords, "A", 1)
except:
print "Could not draw using pymol, skipping this step"
def draw_pymol(coords):
import pele.utils.pymolwrapper as pym
pym.start()
pym.draw_spheres(coords, "A", 1)
def draw_pymol(coords):
import pele.utils.pymolwrapper as pym
pym.start()
pym.draw_spheres(coords, "A", 1)
