def _add_times(self, ptfile):
"""Make ptfile time series data an observable"""
data = numpy.array(ptfile.time_steps())
label = Label("t", "DLM steps", "time steps")
tobs = Observable(data, label)
self.add_observable(tobs, independent_variable=True)
def _add_mols_yaml(self, ptfile):
"""Make observable"""
nmoltypes, moldata = ptfile.nmol()
for mol in range(nmoltypes):
data = numpy.array(moldata[mol])
lmol = self.field.moltypes[mol].name
label = Label("nmol" + lmol, "No. molecules " + lmol, None)
self.add_observable(Observable(data, label))
def _add_energies(self, ptfile):
"""Look at energy data and move to obsevable"""
energies = dict(dlptfile.ENERGY)
eunits = self.field.units
for key in energies:
data = numpy.array(ptfile.time_series(key))
if numpy.any(data):
label = Label(key, dlptfile.KEYS[key], eunits)
eobs = Observable(data, label)
self.add_observable(eobs)
def _add_atoms(self, ptfile):
"""Make observable from number of atoms"""
# Units are really "None"
natomtypes, atomdata = ptfile.natom()
for natom in range(natomtypes):
data = numpy.array(atomdata[natom])
_, nau1 = numpy.unique(data, return_counts=True)
if nau1.size > 1:
latom = self.field.atomtypes[natom].name
label = Label("natom" + latom, "No. atoms " + latom, None)
self.add_observable(Observable(data, label))
def _add_lattice(self, ptfile):
"""If lattice vectors fixed, ignore. Or treat together"""
data1 = numpy.array(ptfile.time_series("L1"))
_, nlv1 = numpy.unique(data1, return_counts=True)
data2 = numpy.array(ptfile.time_series("L2"))
_, nlv2 = numpy.unique(data2, return_counts=True)
data3 = numpy.array(ptfile.time_series("L3"))
_, nlv3 = numpy.unique(data3, return_counts=True)
if nlv1.size > 1 or nlv2.size > 1 or nlv3.size > 1:
label = Label("la", "Lat. vector 1", "Angstrom")
self.add_observable(Observable(data1, label))
label = Label("lb", "Lat. vector 2", "Angstrom")
self.add_observable(Observable(data2, label))
label = Label("lc", "Lat. vector 3", "Angstrom")
self.add_observable(Observable(data3, label))
data1 = numpy.array(ptfile.time_series("Lcos1"))
_, nlcos1 = numpy.unique(data1, return_counts=True)
data2 = numpy.array(ptfile.time_series("Lcos2"))
_, nlcos2 = numpy.unique(data2, return_counts=True)
data3 = numpy.array(ptfile.time_series("Lcos3"))
_, nlcos3 = numpy.unique(data3, return_counts=True)
if nlcos1.size > 1 or nlcos2.size > 1 or nlcos3.size > 1:
label = Label("lcos1", "Angle 1", "TBC")
self.add_observable(Observable(data1, label))
label = Label("lcos2", "Angle 2", "TBC")
self.add_observable(Observable(data2, label))
label = Label("lcos3", "Angle 3", "TBC")
self.add_observable(Observable(data3, label))
def load(self, filename=None):
"""Load data from file"""
# Parameters
f = open(filename, "r")
with f:
line = f.readline()
line = f.readline()
match = re.search(r" (\d+)$", line)
n = int(match.group(0))
v = 1.0 * n * n
line = f.readline()
match = re.search(r" (\w+.\w+)$", line)
j = float(match.group(0))
line = f.readline()
match = re.search(r" (\w+.\w+)$", line)
h = float(match.group(0))
line = f.readline()
match = re.search(r" (\w+.\w+)$", line)
kT = float(match.group(0))
# Load the parameters
self.add_parameter(n * n, Label("N", "Number of spins", None))
self.add_parameter(kT, Label("kT", "Temperature", "k_bT"))
self.add_parameter(v, Label("V", "Volume", "sites"))
self.add_parameter(j, Label("J", "Coupling constant", "k_bT"))
self.add_parameter(h, Label("H", "External field", "k_bT"))
self.data_source = filename
self.data_type = "Ising Model (2d) " + str(n) + "x" + str(n)
# Load the observable data
data = numpy.loadtxt(filename, skiprows=9)
tdata = data[:, 0]
sdata = data[:, 1]
mdata = data[:, 2]
# Form the total energy (per site)
edata = sdata.copy()
edata[:] = -j * sdata[:] - h * mdata[:]
tobs = Observable(tdata, Label("t", "Time", "MC Sweeps"))
sobs = Observable(sdata, Label("S", "Interaction Energy", "k_bT/site"))
mobs = Observable(mdata, Label("M", "Magnetisation", "k_bT/site"))
eobs = Observable(edata, Label("E", "Total Energy", "k_bT/site"))
self.add_observable(tobs, independent_variable=True)
self.add_observable(sobs)
self.add_observable(mobs)
self.add_observable(eobs)
# Reweighters
# Reweighting always takes place via the total energy
# (system, not per site), so introduce a factor of the
# volume
vparam = self.parameter("v")
tparam = self.parameter("kt")
hparam = self.parameter("h")
beta = Parameter(1.0 / kT, Label("beta", "Inverse Energy", "1/k_bT"))
rbeta = BetaReweighter("beta", beta, vparam, eobs)
rkt = KTReweighter("kt", tparam, vparam, eobs)
# To reweight wrt external field, a factor of v/kT is
# required as we have magnetistation per site
alpha = Parameter(v / kT, Label("a", "Volume/k_bT", "sites/k_bT"))
rh = Reweighter("h", hparam, alpha, mobs)
self.add_reweighter(rbeta)
self.add_reweighter(rkt)
self.add_reweighter(rh)
def _add_energy_observable(self, data):
"""Add energy as observable time series"""
label = Label("energy", "Energy", self.field.units)
self.add_observable(Observable(data, label))
def _add_volume_observable(self, vdata):
"""Add volume as observable time series"""
label = Label("volume", "Volume", "Angstrom^3")
self.add_observable(Observable(vdata, label))