def benchmark_number_of_minima(): import time, sys import numpy as np db = Database("test.large.db") if True: istart = np.random.randint(0, sys.maxint) for i in xrange(istart, istart + 10000): e = float(i) db.addMinimum(e, [e], commit=False) db.session.commit() else: i = 1 t1 = time.clock() print db.number_of_minima() print "time", t1 - time.clock() t1 = time.clock() print db.number_of_minima() print "time", t1 - time.clock() t1 = time.clock() print db.number_of_minima() print "time", t1 - time.clock() t1 = time.clock() e = float(i + 1) db.addMinimum(e, [e], commit=False) t1 = time.clock() print db.number_of_minima() print "time", t1 - time.clock() t1 = time.clock() print len(db.minima()) print "time", t1 - time.clock() t1 = time.clock()
def benchmark_number_of_minima(): import time, sys import numpy as np db = Database("test.large.db") if True: istart = np.random.randint(0, sys.maxint) for i in xrange(istart,istart+10000): e = float(i) db.addMinimum(e, [e], commit=False) db.session.commit() else: i=1 t1 = time.clock() print db.number_of_minima() print "time", t1 - time.clock(); t1 = time.clock() print db.number_of_minima() print "time", t1 - time.clock(); t1 = time.clock() print db.number_of_minima() print "time", t1 - time.clock(); t1 = time.clock() e = float(i+1) db.addMinimum(e, [e], commit=False) t1 = time.clock() print db.number_of_minima() print "time", t1 - time.clock(); t1 = time.clock() print len(db.minima()) print "time", t1 - time.clock(); t1 = time.clock()
coords1 = np.genfromtxt("coords.A") coords2 = np.genfromtxt("coords.B") res1 = lbfgs_py(coords1.reshape(-1), pot) res2 = lbfgs_py(coords2.reshape(-1), pot) coords1 = res1.coords coords2 = res2.coords E1 = res1.energy E2 = res2.energy natoms = len(coords1)/3 #add the minima to a database dbfile = "database.sqlite" database = Database(dbfile) database.addMinimum(E1, coords1) database.addMinimum(E2, coords2) min1 = database.minima()[0] min2 = database.minima()[1] #set up the structural alignment routine. #we have to deal with global translational, global rotational, #and permutational symmetry. permlist = [range(natoms)] mindist = MinPermDistAtomicCluster(permlist=permlist, niter=10) #The transition state search needs to know what the eigenvector corresponding #to the lowest nonzero eigenvector is. For this we need to know what the #eivenvector corresponding to the zero eigenvalues are. These are related #to global symmetries. for this system we have 3 zero eigenvalues for translational
class TestDB(unittest.TestCase): def setUp(self): self.db = Database() self.nminima = 10 for i in range(self.nminima): e = float(i) self.db.addMinimum(e, [e]) self.nts = 3 self.db.addTransitionState(0., [0.], self.db.minima()[0], self.db.minima()[1], eigenval=0., eigenvec=[0.]) self.db.addTransitionState(0., [0.], self.db.minima()[1], self.db.minima()[2], eigenval=0., eigenvec=[0.]) self.db.addTransitionState(0., [0.], self.db.minima()[0], self.db.minima()[2], eigenval=0., eigenvec=[0.]) def test_size(self): self.assertEqual(len(self.db.minima()), self.nminima) def test_energy(self): m = self.db.minima()[0] self.assertEqual(m.energy, 0.) def test_coords(self): m = self.db.minima()[0] self.assertEqual(m.coords, [0.]) def test_sizets(self): self.assertEqual(len(self.db.transition_states()), self.nts) def test_energyts(self): ts = self.db.transition_states()[0] self.assertEqual(ts.energy, 0.) def test_coordsts(self): ts = self.db.transition_states()[0] self.assertEqual(ts.coords, [0.]) def test_remove_minimum(self): m = self.db.minima()[0] self.db.removeMinimum(m) self.assertEqual(len(self.db.minima()), self.nminima - 1) self.assertNotIn(m, self.db.minima()) # m should have 2 minima. both of those should be gone self.assertEqual(len(self.db.transition_states()), self.nts - 2) def test_remove_ts(self): ts = self.db.transition_states()[0] self.db.remove_transition_state(ts) self.assertEqual(self.db.number_of_transition_states(), self.nts - 1) self.assertNotIn(ts, self.db.transition_states()) # m should have 2 minima. both of those should be gone self.assertEqual(self.db.number_of_minima(), self.nminima) def test_getTransitionState(self): m1 = self.db.minima()[0] m2 = self.db.minima()[1] m3 = self.db.minima()[-1] self.assertIsNotNone(self.db.getTransitionState(m1, m2)) self.assertIsNone(self.db.getTransitionState(m1, m3)) def test_getMinimum(self): m = self.db.minima()[0] self.assertEqual(m, self.db.getMinimum(m._id)) def test_minimum_adder(self): ma = self.db.minimum_adder() ma(101., [101.]) self.assertEqual(len(self.db.minima()), self.nminima + 1) def test_merge_minima(self): m1 = self.db.minima()[0] m2 = self.db.minima()[1] self.db.mergeMinima(m1, m2) self.assertEqual(len(self.db.minima()), self.nminima - 1) # transition states shouldn't be deleted self.assertEqual(len(self.db.transition_states()), self.nts) def test_number_of_minima(self): self.assertEqual(self.nminima, self.db.number_of_minima()) def test_number_of_transition_states(self): self.assertEqual(self.nts, self.db.number_of_transition_states()) def test_highest_energy_minimum(self): m1 = self.db._highest_energy_minimum() m2 = self.db.minima()[-1] self.assertEqual(m1, m2) def test_maximum_number_of_minima(self): m = self.db.addMinimum(-1., [-1.], max_n_minima=self.nminima) self.assertEqual(self.nminima, self.db.number_of_minima()) self.assertIn(m, self.db.minima()) def test_maximum_number_of_minima_largestE(self): e = float(self.nminima + 1) m = self.db.addMinimum(e, [e], max_n_minima=self.nminima) self.assertEqual(self.nminima, self.db.number_of_minima()) self.assertIsNone(m) #ensure the highest energy minimum is still in the database mmax = self.db._highest_energy_minimum() self.assertEqual(mmax.energy, float(self.nminima - 1)) def test_maximum_number_of_minima_minima_adder(self): ma = self.db.minimum_adder(max_n_minima=self.nminima) m = ma(-1., [-1.]) self.assertEqual(self.nminima, self.db.number_of_minima()) self.assertIn(m, self.db.minima())
self.setCentralWidget(self.dgraph_widget) def rebuild_disconnectivity_graph(self): self.dgraph_widget.rebuild_disconnectivity_graph() def reduced_db2graph(db, Emax): ''' make a networkx graph from a database including only transition states with energy < Emax ''' g = nx.Graph() ts = db.session.query(TransitionState).filter( TransitionState.energy <= Emax).all() for t in ts: g.add_edge(t.minimum1, t.minimum2, ts=t) return g if __name__ == "__main__": db = Database("lj31.db") if len(db.minima()) < 2: raise Exception("database has no minima") app = QApplication(sys.argv) md = DGraphDialog(db) md.show() md.rebuild_disconnectivity_graph() sys.exit(app.exec_())
print "length of path:", len(path_xyz) path = [ map_to_aa(xyz) for xyz in path_xyz] #p#ath = [ x for x in IntterpolatedPath(db.minima[19], )] #path = [ x for x in InterpolatedPath(path[0].copy(), path[-1].copy(), 34) ] traj = open("traj.xyz", "w") #for x in path: # #export_xyz(traj, x) # #ret = quench.mylbfgs(x, pot.getEnergyGradient) # #print i,pot.getEnergy(x), ret[1] # # # export_xyz(traj, ret[0]) db=Database(db="oxdna.sqlite") path[0]=db.minima()[19].coords path[-1]=db.minima()[0].coords e1 = [] e2 = [] e1.append(pot.getEnergy(path[0])) e2.append(pot.getEnergy(path[0])) for i in xrange(1): for i in xrange(len(path)-1): e1.append(pot.getEnergy(path[i+1])) c1 = CoordsAdapter(nrigid=13, coords = path[i]) c2 = CoordsAdapter(nrigid=13, coords = path[i+1]) com1 = np.sum(c1.posRigid,axis=0) / float(13) com2 = np.sum(c1.posRigid,axis=0) / float(13)
from pygmin.utils.disconnectivity_graph import DisconnectivityGraph from pygmin.storage import Database from pygmin.landscape import TSGraph import pylab as pl import numpy as np kbT = 0.75 db = Database(db="tip4p_8.sqlite", createdb=False) graph = TSGraph(db) dg = DisconnectivityGraph(graph.graph, db.minima(), subgraph_size=20) dg.calculate() dg.plot() for m in db.minima(): if m.pgorder != 2: print m.pgorder m.free_energy = m.energy + kbT * 0.5*m.fvib + kbT*np.log(m.pgorder) for ts in db.transition_states(): # if ts.pgorder != 2: print ts.pgorder #assert ts.pgorder == 2 ts.free_energy = ts.energy + kbT * 0.5*ts.fvib + kbT*np.log(ts.pgorder) + kbT*np.log(kbT) if ts.free_energy > ts.minimum1.free_energy or ts.free_energy > ts.minimum2.free_energy: print "warning, free energy of transition state lower than minimum" print ts.free_energy, ts.minimum1.free_energy, ts.minimum2.free_energy
parser.add_argument("--Tcount", type=int, help="Number of temperature points for the calculation.", default=300) parser.add_argument("--OPTIM", action="store_true", help="read data from a min.data file instead." "fname should be the filename of the min.data file") args = parser.parse_args() print args.fname print args k = args.k # get the list of minima if args.OPTIM: # fname is a min.data file minima = read_min_data(args.fname) else: dbfname = args.fname db = Database(dbfname, createdb=False) minima = [m for m in db.minima() if m.fvib is not None and m.pgorder is not None] if len(minima) == 0: print "There are not minima with the necessary thermodynamic information in the database. Have you computed the normal mode"\ " frequencies and point group order for all the minima? See pygmin.thermodynamics "\ " for more information" exit(1) print "computing heat capacity from", len(minima), "minima" Tmin = args.Tmin Tmax = args.Tmax nT = args.Tcount dT = (Tmax-Tmin) / nT T = np.array([Tmin + dT*i for i in range(nT)]) Z, U, U2, Cv = minima_to_cv(minima, T, k)
from pygmin.utils.disconnectivity_graph import DisconnectivityGraph from pygmin.storage import Database from pygmin.landscape import TSGraph import pylab as pl import numpy as np kbT = 0.75 db = Database(db="tip4p_8.sqlite", createdb=False) graph = TSGraph(db) dg = DisconnectivityGraph(graph.graph, db.minima(), subgraph_size=20) dg.calculate() dg.plot() for m in db.minima(): if m.pgorder != 2: print m.pgorder m.free_energy = m.energy + kbT * 0.5 * m.fvib + kbT * np.log(m.pgorder) for ts in db.transition_states(): # if ts.pgorder != 2: print ts.pgorder #assert ts.pgorder == 2 ts.free_energy = ts.energy + kbT * 0.5 * ts.fvib + kbT * np.log( ts.pgorder) + kbT * np.log(kbT) if ts.free_energy > ts.minimum1.free_energy or ts.free_energy > ts.minimum2.free_energy: print "warning, free energy of transition state lower than minimum" print ts.free_energy, ts.minimum1.free_energy, ts.minimum2.free_energy
self.setCentralWidget(self.dgraph_widget) def rebuild_disconnectivity_graph(self): self.dgraph_widget.rebuild_disconnectivity_graph() def reduced_db2graph(db, Emax): ''' make a networkx graph from a database including only transition states with energy < Emax ''' g = nx.Graph() ts = db.session.query(TransitionState).filter(TransitionState.energy <= Emax).all() for t in ts: g.add_edge(t.minimum1, t.minimum2, ts=t) return g if __name__ == "__main__": db = Database("lj31.db") if len(db.minima()) < 2: raise Exception("database has no minima") app = QApplication(sys.argv) md = DGraphDialog(db) md.show() md.rebuild_disconnectivity_graph() sys.exit(app.exec_())
#path = [ x for x in InterpolatedPath(path[0].copy(), path[-1].copy(), 34) ] traj = open("traj.xyz", "w") #for x in path: # #export_xyz(traj, x) # #ret = quench.mylbfgs(x, pot.getEnergyGradient) # #print i,pot.getEnergy(x), ret[1] # # # export_xyz(traj, ret[0]) for x in path: export_xyz(traj, x) import pickle pickle.dump(path, open("interpolate.pickle", "w")) exit() db = Database(db="oxdna.sqlite") path[0] = db.minima()[19].coords path[-1] = db.minima()[0].coords e1 = [] e2 = [] e1.append(pot.getEnergy(path[0])) e2.append(pot.getEnergy(path[0])) for i in xrange(1): for i in xrange(len(path) - 1): e1.append(pot.getEnergy(path[i + 1])) c1 = CoordsAdapter(nrigid=13, coords=path[i]) c2 = CoordsAdapter(nrigid=13, coords=path[i + 1]) com1 = np.sum(c1.posRigid, axis=0) / float(13) com2 = np.sum(c1.posRigid, axis=0) / float(13)
class TestDB(unittest.TestCase): def setUp(self): self.db = Database() self.nminima = 10 for i in range(self.nminima): e = float(i) self.db.addMinimum(e, [e]) self.nts = 3 self.db.addTransitionState(0., [0.], self.db.minima()[0], self.db.minima()[1], eigenval=0., eigenvec=[0.]) self.db.addTransitionState(0., [0.], self.db.minima()[1], self.db.minima()[2], eigenval=0., eigenvec=[0.]) self.db.addTransitionState(0., [0.], self.db.minima()[0], self.db.minima()[2], eigenval=0., eigenvec=[0.]) def test_size(self): self.assertEqual(len(self.db.minima()), self.nminima) def test_energy(self): m = self.db.minima()[0] self.assertEqual(m.energy, 0.) def test_coords(self): m = self.db.minima()[0] self.assertEqual(m.coords, [0.]) def test_sizets(self): self.assertEqual(len(self.db.transition_states()), self.nts) def test_energyts(self): ts = self.db.transition_states()[0] self.assertEqual(ts.energy, 0.) def test_coordsts(self): ts = self.db.transition_states()[0] self.assertEqual(ts.coords, [0.]) def test_remove_minimum(self): m = self.db.minima()[0] self.db.removeMinimum(m) self.assertEqual(len(self.db.minima()), self.nminima-1) self.assertNotIn(m, self.db.minima()) # m should have 2 minima. both of those should be gone self.assertEqual(len(self.db.transition_states()), self.nts-2) def test_remove_ts(self): ts = self.db.transition_states()[0] self.db.remove_transition_state(ts) self.assertEqual(self.db.number_of_transition_states(), self.nts-1) self.assertNotIn(ts, self.db.transition_states()) # m should have 2 minima. both of those should be gone self.assertEqual(self.db.number_of_minima(), self.nminima) def test_getTransitionState(self): m1 = self.db.minima()[0] m2 = self.db.minima()[1] m3 = self.db.minima()[-1] self.assertIsNotNone(self.db.getTransitionState(m1, m2)) self.assertIsNone(self.db.getTransitionState(m1, m3)) def test_getMinimum(self): m = self.db.minima()[0] self.assertEqual(m, self.db.getMinimum(m._id)) def test_minimum_adder(self): ma = self.db.minimum_adder() ma(101., [101.]) self.assertEqual(len(self.db.minima()), self.nminima+1) def test_merge_minima(self): m1 = self.db.minima()[0] m2 = self.db.minima()[1] self.db.mergeMinima(m1, m2) self.assertEqual(len(self.db.minima()), self.nminima-1) # transition states shouldn't be deleted self.assertEqual(len(self.db.transition_states()), self.nts) def test_number_of_minima(self): self.assertEqual(self.nminima, self.db.number_of_minima()) def test_number_of_transition_states(self): self.assertEqual(self.nts, self.db.number_of_transition_states()) def test_highest_energy_minimum(self): m1 = self.db._highest_energy_minimum() m2 = self.db.minima()[-1] self.assertEqual(m1, m2) def test_maximum_number_of_minima(self): m = self.db.addMinimum(-1., [-1.], max_n_minima=self.nminima) self.assertEqual(self.nminima, self.db.number_of_minima()) self.assertIn(m, self.db.minima()) def test_maximum_number_of_minima_largestE(self): e = float(self.nminima + 1) m = self.db.addMinimum(e, [e], max_n_minima=self.nminima) self.assertEqual(self.nminima, self.db.number_of_minima()) self.assertIsNone(m) #ensure the highest energy minimum is still in the database mmax = self.db._highest_energy_minimum() self.assertEqual(mmax.energy, float(self.nminima-1)) def test_maximum_number_of_minima_minima_adder(self): ma = self.db.minimum_adder(max_n_minima=self.nminima) m = ma(-1., [-1.]) self.assertEqual(self.nminima, self.db.number_of_minima()) self.assertIn(m, self.db.minima())