def main():
parser = argparse.ArgumentParser(
description=desc, formatter_class=argparse.RawDescriptionHelpFormatter)
parser.add_argument(
'--ndof',
help=
'Number of total degrees of freedom (e.g. 3*number of atoms). This is simply the length of a coordinates vector.',
type=int,
default=1)
# parser.add_argument('--Database','-d', help = 'Name of database to write into', type = str, default="optimdb.sqlite")
# parser.add_argument('--Mindata','-m', help = 'Name of min.data file', type = str, default="min.data")
# parser.add_argument('--Tsdata','-t', help = 'Name of ts.data file', type = str, default="ts.data")
# parser.add_argument('--Pointsmin','-p', help = 'Name of points.min file', type = str, default="points.min")
# parser.add_argument('--Pointsts','-q', help = 'Name of points.ts file', type = str, default="points.ts")
# parser.add_argument('--endianness', help = 'set the endianness of the binary data. Can be "<" for little-endian or ">" for big-endian', type = str, default="=")
args = parser.parse_args()
system = BaseSystem()
db = system.create_database()
converter = OptimDBConverter(db,
mindata="min.data",
tsdata="ts.data",
pointsmin="points.min",
pointsts="points.ts",
endianness="=",
assert_coords=False)
converter.convert_no_coords()
system.get_ndof = lambda: args.ndof
run_gui(system, db=db)
print(db.number_of_minima())
def test1(self):
current_dir = os.path.dirname(__file__)
db = Database()
converter = OptimDBConverter(
db,
mindata=os.path.join(current_dir, "min.data"),
tsdata=os.path.join(current_dir, "ts.data"),
pointsmin=os.path.join(current_dir, "points.min"),
pointsts=os.path.join(current_dir, "points.ts"),
endianness="<")
converter.convert()
self.assertEqual(db.number_of_minima(), 2)
self.assertEqual(db.number_of_transition_states(), 1)
ts = db.transition_states()[0]
self.assertAlmostEqual(ts.coords[0], 1.548324, 5)
self.assertAlmostEqual(ts.coords[2], 0.18178001, 5)
self.assertAlmostEqual(ts.coords[-1], -0.50953229, 5)
self.assertEqual((180, ), ts.coords.shape)
m = db.minima()[0]
print repr(m.coords)
self.assertAlmostEqual(m.coords[0], 1.53700142, 5)
self.assertAlmostEqual(m.coords[2], 0.87783657, 5)
self.assertAlmostEqual(m.coords[-1], -0.50953229, 5)
self.assertEqual((180, ), m.coords.shape)
def setUp(self):
from pele.utils.optim_compatibility import OptimDBConverter
from pele.storage import Database
ndof = 10 # wrong, but who cares.
self.db = Database()
current_dir = os.path.dirname(__file__)
converter = OptimDBConverter(self.db, ndof=ndof, mindata=current_dir+"/collagen.min.data",
tsdata=current_dir+"/collagen.ts.data", assert_coords=False)
converter.convert_no_coords()
def test_nocoords(self):
current_dir = os.path.dirname(__file__)
db = Database()
converter = OptimDBConverter(
db,
mindata=os.path.join(current_dir, "min.data"),
tsdata=os.path.join(current_dir, "ts.data"),
pointsmin="poo",
pointsts="poo",
assert_coords=False,
endianness="<")
converter.convert()
def test_nocoords_Fails(self):
current_dir = os.path.dirname(__file__)
db = Database()
converter = OptimDBConverter(
db,
mindata=os.path.join(current_dir, "min.data"),
tsdata=os.path.join(current_dir, "ts.data"),
pointsmin="poo",
pointsts="poo",
assert_coords=True,
endianness="<")
with self.assertRaises(IOError):
converter.convert()
def test1(self):
current_dir = os.path.dirname(__file__)
db = Database()
converter = OptimDBConverter(
db,
mindata=os.path.join(current_dir, "min.data"),
tsdata=os.path.join(current_dir, "ts.data"),
pointsmin=os.path.join(current_dir, "points.min"),
pointsts=os.path.join(current_dir, "points.ts"),
endianness="<")
converter.convert()
mdata = tempfile.NamedTemporaryFile(delete=True)
tsdata = tempfile.NamedTemporaryFile(delete=True)
pm = tempfile.NamedTemporaryFile(delete=True)
pts = tempfile.NamedTemporaryFile(delete=True)
print mdata.name, tsdata.name
writer = WritePathsampleDB(db,
mindata=mdata.name,
tsdata=tsdata.name,
pointsmin=pm.name,
pointsts=pts.name,
endianness="<")
writer.write_db()
d1 = np.genfromtxt(os.path.join(current_dir, "min.data"))[:, :3]
d2 = np.genfromtxt(mdata.name)[:, :3]
_base_test.assert_arrays_almost_equal(self, d1, d2)
d1 = np.genfromtxt(os.path.join(current_dir,
"ts.data")).reshape(-1, 8)[:, :5]
d2 = np.genfromtxt(tsdata.name).reshape(-1, 8)[:, :5]
print d1, d2
_base_test.assert_arrays_almost_equal(self, d1, d2)
self.assertEqual(sha1_of_file(os.path.join(current_dir, "points.min")),
sha1_of_file(pm.name))
self.assertEqual(sha1_of_file(os.path.join(current_dir, "points.ts")),
sha1_of_file(pts.name))
def test2(self):
from pele.utils.tests.test_disconnectivity_graph import create_random_database
db = create_random_database(nmin=20, nts=15)
delete = False
mdata = tempfile.NamedTemporaryFile(delete=delete, suffix=".min.data")
tsdata = tempfile.NamedTemporaryFile(delete=delete, suffix=".ts.data")
pm = tempfile.NamedTemporaryFile(delete=delete)
pts = tempfile.NamedTemporaryFile(delete=delete)
print mdata.name, tsdata.name
writer = WritePathsampleDB(db,
mindata=mdata.name,
tsdata=tsdata.name,
pointsmin=pm.name,
pointsts=pts.name,
endianness="<")
writer.write_db()
newdb = Database()
reader = OptimDBConverter(newdb,
mindata=mdata.name,
tsdata=tsdata.name,
pointsmin=pm.name,
pointsts=pts.name,
endianness="<")
reader.convert()
for m1, m2 in izip(db.minima(), newdb.minima()):
self.assertAlmostEqual(m1.energy, m2.energy)
_base_test.assert_arrays_almost_equal(self, m1.coords, m2.coords)
for ts1, ts2 in izip(db.transition_states(),
newdb.transition_states()):
self.assertAlmostEqual(ts1.energy, ts2.energy)
_base_test.assert_arrays_almost_equal(self, ts1.coords, ts2.coords)
self.assertAlmostEqual(ts1.minimum1.energy, ts2.minimum1.energy)
self.assertAlmostEqual(ts1.minimum2.energy, ts2.minimum2.energy)
help="output file name. The heat capacity will be written to output and output.pdf", default="Cv")
parser.add_argument("--Tmin", type=float, help="Minimum temperature for the calculation.", default=0.02)
parser.add_argument("--Tmax", type=float, help="Minimum temperature for the calculation.", default=1.0)
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
db = Database()
converter = OptimDBConverter(db, mindata=args.fname)
converter.convert_no_coords()
minima = db.minima()
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 pele.thermodynamics "\
" for more information"
exit(1)
print "computing heat capacity from", len(minima), "minima"
Tmin = args.Tmin
Tmax = args.Tmax
def main():
parser = argparse.ArgumentParser(
description="""
convert an OPTIM database to a pele sqlite database. Four files are needed. Normally they are called:
points.min : the coordinates of the minima in binary format
min.data : additional information about the minima (like the energy)
points.ts : the coordinates of the transition states
min.ts : additional information about transition states (like which minima they connect)
Other file names can optionally be passed. Some fortran compilers use non-standard endianness to save the
binary data. If your coordinates are garbage, try changing the endianness.
""",
formatter_class=argparse.RawDescriptionHelpFormatter)
parser.add_argument(
'--ndof',
help=
'Number of total degrees of freedom (e.g. 3*number of atoms). This is simply the length of a coordinates vector.',
type=int,
default=None)
parser.add_argument('--Database',
'-d',
help='Name of database to write into',
type=str,
default="optimdb.sqlite")
parser.add_argument('--Mindata',
'-m',
help='Name of min.data file',
type=str,
default="min.data")
parser.add_argument('--Tsdata',
'-t',
help='Name of ts.data file',
type=str,
default="ts.data")
parser.add_argument('--Pointsmin',
'-p',
help='Name of points.min file',
type=str,
default="points.min")
parser.add_argument('--Pointsts',
'-q',
help='Name of points.ts file',
type=str,
default="points.ts")
parser.add_argument(
'--endianness',
help=
'set the endianness of the binary data. Can be "<" for little-endian or ">" for big-endian',
type=str,
default="=")
args = parser.parse_args()
db = Database(args.Database)
cv = OptimDBConverter(database=db,
ndof=args.ndof,
mindata=args.Mindata,
tsdata=args.Tsdata,
pointsmin=args.Pointsmin,
pointsts=args.Pointsts,
endianness=args.endianness)
cv.setAccuracy()
cv.convert()
cv.db.session.commit()
def main():
if len(sys.argv) < 2:
usage()
exit(1)
kwargs = {}
outfile = None
OPTIM = False
opts, args = getopt.gnu_getopt(sys.argv[1:], "ho:",
["help", "nlevels=", "subgraph_size=", "OPTIM",
"order_by_basin_size", "order_by_energy",
"include_gmin",
"center_gmin",
"Emax=",
])
for o, a in opts:
if o == "-h" or o == "--help":
usage()
exit(1)
if o == "-o":
outfile = a
elif o == "--nlevels":
kwargs["nlevels"] = int(a)
elif o == "--Emax":
kwargs["Emax"] = float(a)
elif o == "--subgraph_size":
kwargs["subgraph_size"] = int(a)
elif o == "--order_by_basin_size":
kwargs["order_by_basin_size"] = True
elif o == "--order_by_energy":
kwargs["order_by_energy"] = True
elif o == "--includer_gmin":
kwargs["includer_gmin"] = True
elif o == "--center_gmin":
kwargs["center_gmin"] = True
elif o == "--OPTIM":
OPTIM = True
else:
print "don't understand", o, a
print ""
usage()
exit(1)
groups = None
if OPTIM:
#make database from min.data ts.data
db = Database()
converter = OptimDBConverter(db)
converter.convert_no_coords()
groups = read_AB(db)
else:
if len(args) == 0:
print "you must specify database file"
print ""
usage()
exit()
dbfile = args[0]
if not os.path.exists(dbfile):
print "database file doesn't exist", dbfile
exit()
db = Database(dbfile)
if outfile is None and use_gui:
app = QApplication(sys.argv)
kwargs["show_minima"] = False
md = DGraphDialog(db, params=kwargs)
md.rebuild_disconnectivity_graph()
if groups is not None:
md.dgraph_widget.dg.color_by_group(groups)
md.dgraph_widget.redraw_disconnectivity_graph()
md.show()
sys.exit(app.exec_())
# make graph from database
t0 = time.time()
if "Emax" in kwargs and use_gui:
graph = reduced_db2graph(db, kwargs['Emax'])
else:
graph = dg.database2graph(db)
t1 = time.time()
print "loading the data into a transition state graph took", t1-t0, "seconds"
# do the disconnectivity graph analysis
mydg = dg.DisconnectivityGraph(graph, **kwargs)
print "doing disconnectivity graph analysis"
sys.stdout.flush()
t1 = time.time()
mydg.calculate()
t2 = time.time()
print "d-graph analysis finished in", t2-t1, "seconds"
print "number of minima:", mydg.tree_graph.number_of_leaves()
print "plotting disconnectivigy graph"
sys.stdout.flush()
# make the figure and save it
mydg.plot()
if outfile is None:
plt.show()
else:
plt.savefig(outfile)
t3 = time.time()
print "plotting finished in", t3-t2, "seconds"
