#pl.semilogy()
pl.xlabel("energy evaluations")
pl.ylabel("energy")
pl.show()
if __name__ == "__main__":
import pygmin.potentials.lj as lj
import scipy.optimize
from pygmin.optimize import _quench as quench
print "Running benchmark with lennard jones potential"
pot = lj.LJ()
natoms = 36
coords = np.random.random(3*natoms)*10.0
coords, E, tmp, tmp=quench.lbfgs_scipy(coords, pot.getEnergyGradient, tol=1e-3)
coords = coords + np.random.random(coords.shape)*0.1
tmp, Emin, tmp, tmp = quench.lbfgs_scipy(coords, pot.getEnergyGradient, tol=1e-3)
bench = QuenchBenchmark(pot)
bench.addMinimizer("lbfgs", quench.lbfgs_scipy)
bench.addMinimizer("mylbfgs", quench.mylbfgs)
bench.addMinimizer("lbfgs_py", quench.lbfgs_py)
bench.addMinimizer("lbfgs_ase", quench.lbfgs_ase)
bench.addMinimizer("cg", quench.cg)
bench.addMinimizer("fire", quench.fire)
bench.addMinimizer("bfgs", quench.bfgs)
#bench.addMinimizer("fmin", quench.fmin)
#bench.addMinimizer("steep", quench.steepest_descent)
pl.xlabel("energy evaluations")
pl.ylabel("energy")
pl.show()
if __name__ == "__main__":
import pygmin.potentials.lj as lj
import scipy.optimize
from pygmin.optimize import _quench as quench
print "Running benchmark with lennard jones potential"
pot = lj.LJ()
natoms = 36
coords = np.random.random(3 * natoms) * 10.0
res = quench.lbfgs_scipy(coords, pot, tol=1e-3)
coords = res.coords
coords = coords + np.random.random(coords.shape) * 0.1
res = quench.lbfgs_scipy(coords, pot, tol=1e-3)
Emin = res.energy
bench = QuenchBenchmark(pot)
bench.addMinimizer("lbfgs", quench.lbfgs_scipy)
bench.addMinimizer("mylbfgs", quench.mylbfgs)
bench.addMinimizer("lbfgs_py", quench.lbfgs_py)
#bench.addMinimizer("lbfgs_ase", quench.lbfgs_ase)
bench.addMinimizer("cg", quench.cg)
bench.addMinimizer("fire", quench.fire)
bench.addMinimizer("bfgs_scipy", quench.bfgs_scipy)
#bench.addMinimizer("fmin", quench.fmin)
#bench.addMinimizer("steep", quench.steepest_descent)
pl.ylabel("energy")
pl.show()
if __name__ == "__main__":
import pygmin.potentials.lj as lj
import scipy.optimize
from pygmin.optimize import _quench as quench
print "Running benchmark with lennard jones potential"
pot = lj.LJ()
natoms = 36
coords = np.random.random(3 * natoms) * 10.0
res = quench.lbfgs_scipy(coords, pot, tol=1e-3)
coords = res.coords
coords = coords + np.random.random(coords.shape) * 0.1
res = quench.lbfgs_scipy(coords, pot, tol=1e-3)
Emin = res.energy
bench = QuenchBenchmark(pot)
bench.addMinimizer("lbfgs", quench.lbfgs_scipy)
bench.addMinimizer("mylbfgs", quench.mylbfgs)
bench.addMinimizer("lbfgs_py", quench.lbfgs_py)
# bench.addMinimizer("lbfgs_ase", quench.lbfgs_ase)
bench.addMinimizer("cg", quench.cg)
bench.addMinimizer("fire", quench.fire)
bench.addMinimizer("bfgs_scipy", quench.bfgs_scipy)
# bench.addMinimizer("fmin", quench.fmin)
# bench.addMinimizer("steep", quench.steepest_descent)
