def AddLinearConstraint ( self, constraint ):
"""Add a linear constraint."""
if len ( constraint ) != self.nvariables: raise ValueError ( "Invalid linear constraint length." )
# . Orthogonalize to existing constraints.
if self.linearVectors is not None:
constraint = Clone ( constraint )
self.linearVectors.ProjectOutOfArray ( constraint )
# . Check to see if the constraint is valid.
cnorm2 = constraint.Norm2 ( )
if cnorm2 > 1.0e-10:
constraint.Scale ( 1.0 / cnorm2 )
# . Allocate space for new constraints.
ncolumns = 1
if self.linearVectors is not None: ncolumns += self.linearVectors.columns
newconstraints = Real2DArray.WithExtents ( len ( constraint ), ncolumns )
# . Copy over constraints.
if self.linearVectors is not None:
for r in range ( self.linearVectors.rows ):
for c in range ( self.linearVectors.columns ):
newconstraints[r,c] = self.linearVectors[r,c]
for r in range ( len ( constraint ) ): newconstraints[r,ncolumns-1] = constraint[r]
self.linearVectors = newconstraints
# . Determine the linear scalars.
self.linearScalars = Real1DArray.WithExtent ( self.linearVectors.columns )
reference = Real1DArray.WithExtent ( self.linearVectors.rows )
if self.rtReference is None: self.system.coordinates3.CopyToArray ( reference )
else: self.rtReference.CopyToArray ( reference )
self.linearVectors.VectorMultiply ( reference, self.linearScalars, 1.0, 0.0, transpose = True )
# . Reset the number of degrees of freedom.
self.degreesOfFreedom = self.nvariables - len ( self.linearScalars )
def Initialize ( self ):
"""Initialization."""
( self.objectiveFunction, options ) = self.pipe.bcast ( None, root = 0 )
self.__dict__.update ( options )
self.g = Real1DArray ( self.objectiveFunction.NumberOfVariables ( ) ) ; self.g.Set ( 0.0 )
if self.useBP:
self.x = Real1DArray ( self.objectiveFunction.NumberOfVariables ( ) ) ; self.x.Set ( 0.0 )
def FromSystem(selfClass,
system,
electronicState1,
electronicState2,
method="GP"):
"""Constructor given a system."""
# . Basic setup.
system.electronicState = electronicState1
self = super(SEAMObjectiveFunction, selfClass).FromSystem(system)
self.method = method
# . Define the first system.
self.system1 = self.system
# . Define the second system without coordinates.
coordinates3 = self.system1.coordinates3
symmetryParameters = self.system1.symmetryParameters
self.system1.coordinates3 = None
self.system1.symmetryParameters = None
self.system2 = Clone(self.system1)
self.system2.electronicState = electronicState2
# . Reset the coordinates for both systems so that they are the same.
self.system1.coordinates3 = coordinates3
self.system2.coordinates3 = coordinates3
if symmetryParameters is not None:
self.system1.symmetryParameters = symmetryParameters
self.system2.symmetryParameters = symmetryParameters
# . Allocate space.
self.g1 = Real1DArray.WithExtent(len(self))
self.g2 = Real1DArray.WithExtent(len(self))
# . Finish up.
return self
def WHAM_Bootstrapping(paths, **keywordArguments):
"""Solve the WHAM equations and estimate errors using bootstrapping."""
# . Get specific options.
options = dict(keywordArguments)
log = options.get("log", logFile)
minimizer = options.pop("minimizerFunction",
WHAM_ConjugateGradientMinimize)
resamples = options.pop("resamples", _Default_Resamples)
# . Initial minimization - it must succeed to proceed.
results = minimizer(paths, **dict(options))
if results["Converged"]:
# . Reset options for resampling.
options["handler"] = results.pop("Handler")
options["histogram"] = Clone(results.pop("Unreduced Histogram"))
options["log"] = None
# . Resampling minimizations.
pmfs = []
for r in range(resamples):
localResults = minimizer(paths, **dict(options))
if localResults["Converged"]: pmfs.append(localResults.pop("PMF"))
# . Process results.
numberOfResamples = len(pmfs)
results.update({
"Number Of Resamples": numberOfResamples,
"PMFs": pmfs
})
if numberOfResamples > 1:
# . Gather some counters.
lowerIndex = int(math.ceil(
0.5 * _Alpha * float(numberOfResamples))) - 1
upperIndex = int(
math.floor(
(1.0 - 0.5 * _Alpha) * float(numberOfResamples))) - 1
# . Do statistics.
originalPMF = results["PMF"]
lowerLimit = Real1DArray.WithExtent(len(originalPMF))
standardError = Real1DArray.WithExtent(len(originalPMF))
upperLimit = Real1DArray.WithExtent(len(originalPMF))
work = Real1DArray.WithExtent(numberOfResamples)
for b in range(len(originalPMF)):
for (r, pmf) in enumerate(pmfs):
work[r] = pmf[b]
work.Sort()
m = originalPMF[b]
lowerLimit[b] = 2.0 * m - work[upperIndex]
upperLimit[b] = 2.0 * m - work[lowerIndex]
standardError[b] = Statistics(work).standardDeviation
# . Printing.
data = (("Standard Error", standardError),
("Lower 95% Confidence Interval", lowerLimit),
("Upper 95% Confidence Interval", upperLimit))
_BootstrappingSummary(results["Histogram"], log, numberOfResamples,
originalPMF, standardError, lowerLimit,
upperLimit)
# . Finish up.
for (key, value) in data:
results[key] = value
return results
def Initialize(self,
pressure=_Default_Pressure,
temperature=_Default_Temperature):
"""Create the arrays needed for the WHAM equations."""
# . Initialization.
handler = self.handler
histogram = self.histogram
if (handler is not None) and (histogram is not None):
p0 = pressure * UNITS_PRESSURE_ATMOSPHERES_TO_KILOJOULES_PER_MOLE
t0 = temperature * CONSTANT_MOLAR_GAS * 1.0e-3
# . Gather pressures and temperatures.
pressures = []
temperatures = []
for (p, t) in zip(handler.pressures, handler.temperatures):
if p is None: p = pressure
if t is None: t = temperature
pressures.append(
p * UNITS_PRESSURE_ATMOSPHERES_TO_KILOJOULES_PER_MOLE)
temperatures.append(t * CONSTANT_MOLAR_GAS * 1.0e-3)
# . Create c which in the most general case is Exp ( - ( (Bj - B0) * U_i + (Bj*Pj - B0*P0) * V_i + Bj * SC_ji ) ).
c = Real2DArray.WithExtents(handler.numberOfWindows,
histogram.bins)
c.Set(0.0)
for (i, midPoint) in enumerate(histogram.BinMidPointIterator()):
# . Energy.
if handler.hasEnergy:
e = midPoint.pop(0)
for (j, tj) in enumerate(temperatures):
c[j, i] += e * (1.0 / tj - 1.0 / t0)
# . Volume.
if handler.hasVolume:
v = midPoint.pop(0)
for (j, pj) in enumerate(pressures):
c[j, i] += v * (pj / tj - p0 / t0)
# . Soft constraints.
for (j, tj) in enumerate(temperatures):
for (s, model) in zip(midPoint, handler.energyModels[j]):
c[j, i] += model.Energy(s)[0] / tj
c.Scale(-1.0)
c.Exp()
# . Create the points arrays.
m = Real1DArray.WithExtent(histogram.bins)
m.Set(0.0)
n = Real1DArray.WithExtent(handler.numberOfWindows)
n.Set(0.0)
for (i, v) in enumerate(histogram.counts):
m[i] = float(v)
for (i, v) in enumerate(handler.windowPoints):
n[i] = float(v)
# . Save all.
self.pointsPerBin = m
self.pointsPerWindow = n
self.pressure = pressure
self.temperature = temperature
self.temperatureFactor = t0
self.weightMatrix = c
def Allocate(self):
"""Allocate arrays."""
if (self.handler is not None) and (self.histogram is not None):
self.energies = Real1DArray.WithExtent(
self.handler.numberOfWindows)
self.energies.Set(1.0)
self.probabilities = Real1DArray.WithExtent(self.histogram.bins)
self.probabilities.Set(1.0)
self.workE = Real1DArray.WithExtent(self.handler.numberOfWindows)
self.workE.Set(0.0)
self.workP = Real1DArray.WithExtent(self.histogram.bins)
self.workP.Set(0.0)
self.histogram.Normalize(self.probabilities)
def AtomicCharges(self,
qcChargeModel=None,
qcAtomsOnly=False,
spinDensities=False):
"""Calculate the partial charges for the atoms."""
charges = None
if self.energyModel is not None:
em = self.energyModel
if (em.mmModel is not None) and (not qcAtomsOnly):
if spinDensities:
charges = Real1DArray.WithExtent(em.mmAtoms.size)
charges.Set(0.0e+00)
else:
charges = em.mmAtoms.AtomicCharges()
if em.qcModel is not None:
qccharges = em.qcModel.AtomicCharges(
self.configuration,
chargeModel=qcChargeModel,
spinDensities=spinDensities)
if charges is None:
charges = qccharges
else:
for (index, q) in zip(em.qcAtoms, qccharges):
charges[index] += q
return charges
def ParseAtomSection(self):
"""Parse the ATOM section."""
if hasattr(self, "natoms"):
atomicCharges = Real1DArray.WithExtent(self.natoms)
atomicCharges.Set(0.0)
atomicNumbers = []
atomNames = []
xyz = Coordinates3.WithExtent(self.natoms)
xyz.Set(0.0)
for i in range(self.natoms):
items = self.GetTokens(converters=[
int, None, float, float, float, None, None, None, float
])
if len(items) < 6:
self.Warning("Invalid ATOM line.", True)
else:
atomicNumber = PeriodicTable.AtomicNumber(items[1])
if atomicNumber <= 0:
atomicNumber = self.AtomicNumberFromAtomType(items[5])
atomicNumbers.append(atomicNumber)
atomNames.append(items[1])
xyz[i, 0] = items[2]
xyz[i, 1] = items[3]
xyz[i, 2] = items[4]
if len(items) >= 9: atomicCharges[i] = items[8]
self.atomicCharges = atomicCharges
self.atomicNumbers = atomicNumbers
self.atomNames = atomNames
self.xyz = xyz
else:
self.Warning("Unknown number of atoms in molecule.", True)
def FromObjectiveFunction(selfClass,
objectiveFunction,
fixedTerminalImages=True):
"""Constructor given an objective function."""
# . Create the object.
self = selfClass()
# . Set the objective function and associated data.
if not isinstance(objectiveFunction,
self.__class__.objectiveFunctionClass):
raise TypeError("Invalid objective function.")
self.numberOfImages = objectiveFunction.NumberOfImages()
self.numberOfImageVariables = objectiveFunction.NumberOfVariables()
if fixedTerminalImages:
self.numberOfVariables = (self.numberOfImages -
2) * self.numberOfImageVariables
else:
self.numberOfVariables = self.numberOfImages * self.numberOfImageVariables
self.objectiveFunction = objectiveFunction
# . Read the trajectory into the path.
self.path = ChainOfStatesPath(self.numberOfImages,
self.numberOfImageVariables)
self.path.Load(objectiveFunction)
# . Allocate remaining space.
self.tangent = Real1DArray(self.numberOfImageVariables)
self.tangent.Set(0.0)
# . Finish up.
return self
def PathSummary ( self, log = logFile ):
"""Output a path summary."""
if LogFileActive ( log ):
# . Calculate all data for the current path.
variables = Real1DArray.WithExtent ( self.NumberOfVariables ( ) )
self.VariablesGet ( variables )
self.Function ( variables )
# . Get the energies of the first and last structures.
self.energies[0:0] = [ self.objectiveFunction.Function ( self.x0 ) ]
self.energies.append ( self.objectiveFunction.Function ( self.xn ) )
# . Modify the distance lists.
self.distances1.append ( None )
self.distances2.extend ( [ None, None ] )
# . Output.
table = log.GetTable ( columns = [ 10, 20, 20, 20 ] )
table.Start ( )
table.Title ( "Path Summary" )
table.Heading ( "Structure" )
table.Heading ( "Energy" )
table.Heading ( "Dist(i,i+1)" )
table.Heading ( "Dist(i,i+2)" )
for ( i, ( e, d1, d2 ) ) in enumerate ( zip ( self.energies, self.distances1, self.distances2 ) ):
table.Entry ( "{:d}" .format ( i ) )
table.Entry ( "{:.3f}".format ( e ) )
if d1 is None: table.Entry ( "" )
else: table.Entry ( "{:.3f}".format ( d1 ) )
if d2 is None: table.Entry ( "" )
else: table.Entry ( "{:.3f}".format ( d2 ) )
table.Stop ( )
def VelocitiesAssign ( self, temperature, normalDeviateGenerator = None ):
"""Set up the velocities for the system at a particular temperature.
If |temperature| is None the velocities must already exist.
"""
# . Check for an existing set of velocities of the correct size.
velocities = self.system.configuration.__dict__.get ( "velocities", None )
QASSIGN = ( velocities is None ) or ( ( velocities is not None ) and ( len ( velocities ) != self.nvariables ) )
# . Assign velocities.
if QASSIGN:
if temperature is None:
raise ValueError ( "Velocities need to be assigned for the system but a temperature has not been specified." )
else:
# . Get the generator.
if normalDeviateGenerator is None:
normalDeviateGenerator = NormalDeviateGenerator.WithRandomNumberGenerator ( RandomNumberGenerator.WithRandomSeed ( ) )
# . Get the velocities.
sigma = _MS_TO_APS * math.sqrt ( CONSTANT_BOLTZMANN * temperature / CONSTANT_ATOMIC_MASS )
velocities = Real1DArray.WithExtent ( self.NumberOfVariables ( ) )
normalDeviateGenerator.NextStandardDeviates ( velocities )
velocities.Scale ( ( sigma ) )
self.system.configuration.velocities = velocities
# . Project out linear constraints.
if self.linearVectors is not None: self.linearVectors.ProjectOutOfArray ( velocities )
# . Scale velocities if necessary (even for assigned velocities).
if temperature is not None:
( ke, tactual ) = self.Temperature ( velocities )
velocities.Scale ( math.sqrt ( temperature / tactual ) )
def VariablesAllocate ( self ):
"""Return a variables object of the correct size."""
if self.NumberOfVariables ( ) > 0:
variables = Real1DArray.WithExtent ( self.NumberOfVariables ( ) )
variables.Set ( 0.0 )
return variables
else:
return None
def VariablesAllocate ( self ):
"""Return an object to hold the variables."""
if self.NumberOfVariables ( ) > 0:
variables = Real1DArray.WithExtent ( self.NumberOfVariables ( ) )
variables.Set ( 0.0 )
return variables
else:
return None
def Setup ( selfClass, qcAtoms, electronicState, nbState, job, scratch, deleteJobFiles = False, useRandomJob = False, useRandomScratch = False ):
"""Set up a state given the relevant data."""
self = selfClass ( )
# . QC atoms.
# . Basic attributes.
self.charge = electronicState.charge
self.multiplicity = electronicState.multiplicity
self.numberOfQCAtoms = len ( qcAtoms )
# . File paths.
if useRandomJob: job = RandomString ( )
if useRandomScratch:
self.scratchPath = os.path.join ( scratch, RandomString ( ) )
if not os.path.exists ( self.scratchPath ): os.mkdir ( self.scratchPath )
self.jobPath = os.path.join ( self.scratchPath, job )
else:
self.scratchPath = None
self.jobPath = os.path.join ( scratch, job )
self.engradPath = self.jobPath + ".engrad"
self.inputPath = self.jobPath + ".inp"
self.outputPath = self.jobPath + ".log"
self.pcgradPath = self.jobPath + ".pcgrad"
self.pcPath = self.jobPath + ".pc"
# . Options.
self.deleteJobFiles = deleteJobFiles
# . Symbols.
atomicNumbers = qcAtoms.GetAtomicNumbers ( )
self.symbols = []
for i in atomicNumbers:
self.symbols.append ( PeriodicTable.Symbol ( i ) )
# . Array attributes.
self.qcCoordinates3 = Coordinates3.WithExtent ( self.numberOfQCAtoms ) ; self.qcCoordinates3.Set ( 0.0 )
self.dipole = Vector3.Null ( )
self.qcGradients3 = Coordinates3.WithExtent ( self.numberOfQCAtoms ) ; self.qcGradients3.Set ( 0.0 )
self.chelpgCharges = Real1DArray.WithExtent ( self.numberOfQCAtoms ) ; self.chelpgCharges.Set ( 0.0 )
self.lowdinCharges = Real1DArray.WithExtent ( self.numberOfQCAtoms ) ; self.lowdinCharges.Set ( 0.0 )
self.lowdinSpins = Real1DArray.WithExtent ( self.numberOfQCAtoms ) ; self.lowdinSpins.Set ( 0.0 )
self.mullikenCharges = Real1DArray.WithExtent ( self.numberOfQCAtoms ) ; self.mullikenCharges.Set ( 0.0 )
self.mullikenSpins = Real1DArray.WithExtent ( self.numberOfQCAtoms ) ; self.mullikenSpins.Set ( 0.0 )
# . Orbital data.
self.H**O = -1
self.LUMO = -1
self.orbitalEnergies = []
# . NB state.
self.nbState = nbState
return self
def Eigenvalues ( extent, cpuTimer, ndg ):
s = SymmetricMatrix ( extent ) ; s.Set ( 0.0 )
e = Real1DArray ( extent ) ; e.Set ( 0.0 )
v = Real2DArray ( extent, extent ) ; v.Set ( 0.0 )
for i in range ( extent ):
for j in range ( i+1 ): s[i,j] = ndg.NextDeviate ( )
s[i,i] *= 2.0
tStart = cpuTimer.Current ( )
s. Diagonalize ( e, eigenVectors = v )
return ( cpuTimer.Current ( ) - tStart )
def CovarianceMatrix(*arguments, **keywordArguments):
"""Calculate the covariance matrix for selected particles."""
# . Initialization.
covariance = None
# . Get the trajectory and associated system data.
(system, trajectories) = _GetSystemAndTrajectoriesFromArguments(*arguments)
# . Get the selection and the size of the problem.
selection = keywordArguments.pop("selection", None)
if selection is None:
selection = Selection.FromIterable(range(len(system.atoms)))
n = 3 * len(selection)
# . Get the average positions.
averagePositions = keywordArguments.pop("averagePositions", None)
if averagePositions is None:
averagePositions = AveragePositions(trajectories, selection=selection)
_CheckForUnknownOptions(keywordArguments)
# . Continue processing.
if (n > 0) and (averagePositions is not None):
# . Allocate space.
covariance = SymmetricMatrix.WithExtent(n)
covariance.Set(0.0)
displacement = Real1DArray.WithExtent(n)
displacement.Set(0.0)
# . Loop over trajectory frames.
numberFrames = 0
for trajectory in trajectories:
trajectory.ReadHeader()
while trajectory.RestoreOwnerData():
frame = system.coordinates3
for (p, i) in enumerate(selection):
displacement[3 * p] = frame[i, 0] - averagePositions[p, 0]
displacement[3 * p +
1] = frame[i, 1] - averagePositions[p, 1]
displacement[3 * p +
2] = frame[i, 2] - averagePositions[p, 2]
for i in range(n):
dI = displacement[i]
for j in range(i + 1):
covariance[i, j] += (dI * displacement[j])
trajectory.ReadFooter()
trajectory.Close()
numberFrames += len(trajectory)
# . Scale.
if numberFrames > 0: covariance.Scale(1.0 / float(numberFrames))
return covariance
def FromOptions(selfClass,
alphas,
gradientsAlpha,
hessianAlpha,
minimumCoefficient,
numberOfSets=1):
"""Constructor from options."""
self = selfClass()
self.alphas = alphas
self.gradientsAlpha = gradientsAlpha
self.hessianAlpha = hessianAlpha
self.minimumCoefficient = minimumCoefficient
self.numberOfSets = numberOfSets
self.numberOfVariables = len(self.alphas)
self.numberOfVariablesPerSet = self.numberOfVariables // self.numberOfSets
self.work = Real1DArray.WithExtent(self.numberOfVariables)
self.workA = Real1DArray.WithExtent(self.numberOfVariables)
self.workS = Real1DArray.WithExtent(self.numberOfVariables)
self.workT = Real1DArray.WithExtent(self.numberOfVariables)
return self
def GetPMF(self):
"""Calculate the PMF."""
if (self.reducedHistogram is not None) and (self.reducedProbabilities
is not None):
pmf = Real1DArray.WithExtent(self.reducedHistogram.bins)
pmf.Set(0.0)
self.reducedProbabilities.CopyTo(pmf)
pmf.Ln()
pmf.Scale(-self.temperatureFactor)
v = min(pmf)
pmf.AddScalar(-v)
self.pmf = pmf
def _GetHardSphereRadii(atoms):
"""Get the hard-sphere radii for the atoms."""
hsradii = Real1DArray.WithExtent(len(atoms))
hsradii.Set(0.0)
atomicNumbers = atoms.GetItemAttributes("atomicNumber")
for (i, atomicNumber) in enumerate(atomicNumbers):
try:
hsradii[i] = _HSRADII[atomicNumber]
except:
raise KeyError("Hard-sphere radius for element " +
PeriodicTable.Symbol(atomicNumber) + " unknown.")
return hsradii
def DefineGrid ( self, gridspacing = _DEFAULT_GRIDSPACING, radiusfactor = _DEFAULT_RADIUSFACTOR ):
"""Define the grid."""
if ( self.system is not None ) and ( self.system.coordinates3 is not None ) and ( self.system.energyModel is not None ) and ( self.system.energyModel.qcModel is not None ):
self.qcCoordinates3 = self.system.energyModel.qcAtoms.GetCoordinates3 ( self.system.coordinates3, toBohrs = True )
allRadii = self.system.atoms.GetItemAttributes ( "vdwRadius" )
if len ( self.qcSelection ) == len ( self.system.atoms ):
radii = allRadii
else:
radii = Real1DArray ( len ( self.qcSelection ) )
for ( i, s ) in enumerate ( self.qcSelection ):
radii[i] = allRadii[s]
radii.Scale ( radiusfactor / UNITS_LENGTH_BOHRS_TO_ANGSTROMS )
self.grid = RegularCubicGrid3 ( gridspacing, self.qcCoordinates3, radii )
def DefineWeights ( self ):
"""Define atom weights - use masses by default."""
self.atomWeights = self.system.atoms.GetItemAttributes ( "mass" )
if self.nvariables > 0:
self.variableWeights = Real1DArray.WithExtent ( self.nvariables )
self.variableWeights.Set ( 0.0 )
if self.freeAtoms is None: indices = range ( len ( self.system.atoms ) )
else: indices = self.freeAtoms
n = 0
for iatom in indices:
w = math.sqrt ( self.atomWeights[iatom] )
for j in range ( 3 ):
self.variableWeights[n] = w
n += 1
def FindMaxima(self, computeStructures=False):
"""Find maxima along the path."""
if self.imageSpline is not None:
if self.functionSplineA is None: self.BuildFunctionSplines()
self.maximaA = self.functionSplineA.FindMaxima()
self.maximaI = self.functionSplineI.FindMaxima()
if computeStructures:
structures = []
for (s, fs) in self.maximaI:
v = Real1DArray.WithExtent(
self.imageSpline.NumberOfSplines())
v.Set(0.0)
self.imageSpline.Evaluate(s, f=v)
structures.append((s, fs, v))
self.maximaIStructures = structures
def WriteBlock(self):
"""Write a block of data."""
if self.current > 0:
# . The following is a fudge until slicing is handled properly.
if self.current == self.blockSize: outdata = self.data
else:
outdata = Real1DArray.WithExtent(self.current * self.rank)
for i in range(len(outdata)):
outdata[i] = self.data[i]
Pickle(
os.path.join(
self.path,
_BlockPrefix + "{:d}".format(self.blocks) + _BlockPostfix),
outdata)
# . This is what it should be.
# Pickle ( os.path.join ( self.path, _BlockPrefix + "{:d}".format ( self.blocks ) + _BlockPostfix, self.data[0:self.current*self.rank] )
self.blocks += 1
self.current = 0
def WriteHeader(self, pressure=None, temperature=None):
"""Write the trajectory header."""
# . Check for soft constraints.
self.hasSoftConstraints = hasattr(
self.owner.energyModel, "softConstraints") and (len(
self.owner.energyModel.softConstraints) > 0)
# . Check the volume option.
self.hasVolume = self.hasVolume and hasattr(self.owner, "symmetry")
# . Check that there will be data on the trajectory.
if not (self.hasPotentialEnergy or self.hasSoftConstraints
or self.hasVolume):
raise ValueError("A soft-constraint trajectory contains no data.")
# . Initialization.
labels = []
models = []
# . Potential energy and volume.
if self.hasPotentialEnergy: labels.append("Potential Energy")
if self.hasVolume: labels.append("Volume")
# . Soft constraints.
if self.hasSoftConstraints:
self.softConstraintLabels = sorted(
self.owner.energyModel.softConstraints)
for label in self.softConstraintLabels:
models.append(
self.owner.energyModel.softConstraints[label].energyModel)
labels.extend(self.softConstraintLabels)
# . Set up the header.
header = {
"labels": labels,
"hasPotentialEnergy": self.hasPotentialEnergy,
"hasVolume": self.hasVolume,
"softConstraintEnergyModels": models
}
# . Optional information.
if pressure is not None: header["pressure"] = pressure
if temperature is not None: header["temperature"] = temperature
# . Write out.
Pickle(os.path.join(self.path, _HeaderName + _BlockPostfix), header)
# . Setup the block for output.
self.rank = len(labels)
self.data = Real1DArray.WithExtent(self.rank * self.blockSize)
def SGOFProcessMultiprocessingScript(objectiveFunction, receiver, sender):
"""Multiprocessing script."""
# . Initialization.
g = Real1DArray(objectiveFunction.NumberOfVariables())
g.Set(0.0)
# . Poll for tasks.
while True:
if receiver.poll():
(task, arguments) = receiver.recv()
if task == ProcessTaskCode_Exit:
break
elif task == ProcessTaskCode_FunctionGradients:
try:
x = arguments[0]
f = objectiveFunction.FunctionGradients(x, g)
sender.send((ProcessExitCode_Success, f, g))
except Exception as error:
sender.send((ProcessExitCode_Failure, error[0]))
else:
sender.send(
(ProcessExitCode_Failure, "Unrecognized task."))
def ParseCharges(self):
"""Parse charges from a charge analysis."""
if (self.natoms > 0):
nall = self.natoms + len(self.dummies)
q = Real1DArray.WithExtent(self.natoms)
q.Set(0.0)
i = -1
n = -1
for iblock in range((nall + 4) // 5):
self.GetLine() # Blank line.
self.GetLine() # Atom heading.
line = self.GetLine()
tokens = line[7:].split()
for token in tokens:
n += 1
if n not in self.dummies:
i += 1
q[i] = float(token)
return q
else:
return None
def GetItemAttributes(self,
attributeLabel,
asDictionary=False,
selection=None):
"""Return a sequence of item attributes."""
# . Initialization.
data = None
if (attributeLabel
in Atom.defaultAttributes) or (attributeLabel
in Element.defaultAttributes):
if selection is None: indices = range(len(self))
else: indices = selection
if indices is not None:
# . Use a dictionary for non-default values only.
if asDictionary:
data = {}
if attributeLabel in Atom.defaultAttributes:
defaultValue = Atom.defaultAttributes[attributeLabel]
else:
defaultValue = Element.defaultAttributes[
attributeLabel]
for i in indices:
value = getattr(self[i], attributeLabel)
if value != defaultValue: data[i] = value
# . Use a sequence for all values.
else:
attribute = getattr(self[0], attributeLabel)
# . Float attribute.
if isinstance(attribute, (float)):
data = Real1DArray.WithExtent(len(indices))
for (i, index) in enumerate(indices):
data[i] = getattr(self[index], attributeLabel)
# . Other attribute.
else:
data = []
for i in indices:
data.append(getattr(self[i], attributeLabel))
return data
def __init__ ( self, system, trajectory, **keywordArguments ):
"""Constructor."""
# . Set defaults for all options.
for ( key, value ) in self.__class__.attributes.iteritems ( ): setattr ( self, key, value )
# . Set values of keyword arguments.
for ( key, value ) in keywordArguments.iteritems ( ): setattr ( self, key, value )
# . Define the system geometry object function.
self.objectiveFunction = SystemGeometryObjectiveFunction.FromSystem ( system )
# . Define the trajectory - a check should be made here to ensure that the trajectory is a direct access one with coordinates!
# . Reading and writing the header/footer is not required but maybe should be included for completeness?
self.trajectory = trajectory
# . Get some scratch space.
self.g = Real1DArray.WithExtent ( self.objectiveFunction.NumberOfVariables ( ) )
self.gd = Real1DArray.WithExtent ( self.objectiveFunction.NumberOfVariables ( ) + self.NumberOfVariables ( ) )
self.x = Real1DArray.WithExtent ( self.objectiveFunction.NumberOfVariables ( ) )
self.x0 = Real1DArray.WithExtent ( self.objectiveFunction.NumberOfVariables ( ) )
self.xn = Real1DArray.WithExtent ( self.objectiveFunction.NumberOfVariables ( ) )
self.y = Real1DArray.WithExtent ( self.objectiveFunction.NumberOfVariables ( ) )
self.g.Set ( 0.0 )
self.gd.Set ( 0.0 )
self.x.Set ( 0.0 )
self.x0.Set ( 0.0 )
self.xn.Set ( 0.0 )
self.y.Set ( 0.0 )
# . Get the first structure on the trajectory.
self.trajectory.RestoreOwnerData ( index = 0 )
self.objectiveFunction.VariablesGet ( self.x0 )
# . Make the first structure the reference structure.
# . It is assumed that the remaining structures on the trajectory are already
# . orientated with respect to this one. This is the case for trajectories
# . from linear-interpolation or expansion or previous SAW calculations but
# . may not be otherwise.
if self.removeRotationTranslation: self.objectiveFunction.RemoveRotationTranslation ( reference = self.objectiveFunction.system.coordinates3 )
# . Get the last structure on the trajectory.
self.trajectory.RestoreOwnerData ( index = self.trajectory.frames - 1 )
self.objectiveFunction.VariablesGet ( self.xn )
self.trajectories = []
def CoordinateFluctuations(*arguments, **keywordArguments):
"""Calculate the coordinate fluctuations for selected particles."""
# . Initialization.
fluctuations = None
# . Get the trajectory and associated system data.
(system, trajectories) = _GetSystemAndTrajectoriesFromArguments(*arguments)
# . Get the selection and the size of the problem.
selection = keywordArguments.pop("selection", None)
if selection is None:
selection = Selection.FromIterable(range(len(system.atoms)))
n = len(selection)
# . Get the average positions.
averagePositions = keywordArguments.pop("averagePositions", None)
if averagePositions is None:
averagePositions = AveragePositions(trajectories, selection=selection)
# . Various other options.
anisotropic = keywordArguments.pop("anisotropic", False)
asBFactors = keywordArguments.pop("asBFactors", False)
_CheckForUnknownOptions(keywordArguments)
# . Continue processing.
if (n > 0) and (averagePositions is not None):
# . Allocate space.
displacement = Coordinates3.WithExtent(n)
if anisotropic: fluctuations = Real2DArray.WithExtents(n, 6)
else: fluctuations = Real1DArray.WithExtent(n)
displacement.Set(0.0)
fluctuations.Set(0.0)
# . Loop over trajectory frames.
numberFrames = 0
for trajectory in trajectories:
trajectory.ReadHeader()
while trajectory.RestoreOwnerData():
frame = system.coordinates3
if anisotropic:
for (p, i) in enumerate(selection):
dx = frame[i, 0] - averagePositions[p, 0]
dy = frame[i, 1] - averagePositions[p, 1]
dz = frame[i, 2] - averagePositions[p, 2]
fluctuations[p, 0] += dx * dx
fluctuations[p, 1] += dy * dx
fluctuations[p, 2] += dy * dy
fluctuations[p, 3] += dz * dx
fluctuations[p, 4] += dz * dy
fluctuations[p, 5] += dz * dz
else:
for (p, i) in enumerate(selection):
fluctuations[p] += ( ( frame[i,0] - averagePositions[p,0] )**2 + \
( frame[i,1] - averagePositions[p,1] )**2 + \
( frame[i,2] - averagePositions[p,2] )**2 )
trajectory.ReadFooter()
trajectory.Close()
numberFrames += len(trajectory)
# . Scale.
if numberFrames > 0: fluctuations.Scale(1.0 / float(numberFrames))
# . Convert to B-factors if necessary.
if asBFactors:
conversionFactor = 8.0 * math.pi**2
if not anisotropic: conversionFactor /= 3.0
fluctuations.Scale(conversionFactor)
# . Finish up.
return fluctuations
def JaguarBondOrders(infile,
outfile,
bondOrdertolerance=_DEFAULTBONDORDERTOLERANCE,
chargetolerance=_DEFAULTCHARGETOLERANCE,
log=logFile,
QCROSS=False):
"""Calculate bond orders given Jaguar input and output files."""
# . Parse the input file.
infile = JaguarInputFileReader(infile)
infile.Parse()
infile.Summary(log=logFile)
# . Parse the output file.
outfile = JaguarOutputFileReader(outfile)
outfile.Parse()
outfile.Summary(log=logFile)
# . Get data from the files.
# . Input.
atomicNumbersi = getattr(infile, "atomicNumbers", None)
coordinates3 = getattr(infile, "coordinates3", None)
orbitalsets = getattr(infile, "orbitalsets", None)
# . Output.
atomicNumberso = getattr(outfile, "atomicNumbers", None)
nfunctions = getattr(outfile, "nfunctions", None)
overlap = getattr(outfile, "overlap", None)
# . Check for coordinates.
if coordinates3 is None:
raise ValueError("The coordinate data is missing from the input file.")
# . Check the orbital data.
QOK = (orbitalsets is not None) and (len(orbitalsets) > 0)
if QOK:
if (len(orbitalsets) == 1) and ("" in orbitalsets):
spinDensitiesRESTRICTED = True
elif (len(orbitalsets)
== 2) and ("alpha" in orbitalsets) and ("beta" in orbitalsets):
spinDensitiesRESTRICTED = False
else:
QOK = False
if not QOK: raise ValueError("Invalid orbital data on input file.")
if spinDensitiesRESTRICTED: nbasisi = infile.orbitalsets[""][1]
else: nbasisi = infile.orbitalsets["alpha"][1]
# . Check the overlap.
if (overlap is None):
raise ValueError("The overlap matrix is missing from the output file.")
nbasiso = overlap.Dimension()
# . Check the array giving the number of functions per atom.
# print nfunctions, len ( nfunctions ), len ( atomicNumberso ), sum ( nfunctions ), nbasiso
if (nfunctions is None) or (len(nfunctions) != len(atomicNumberso) or
(sum(nfunctions) != nbasiso)):
raise ValueError(
"Basis function data on the output file is missing or invalid.")
# . Create the function index array.
findices = []
first = 0
last = 0
for f in nfunctions:
last += f
findices.append((first, last))
first += f
# . Check for compatibility between the data.
QOK = (atomicNumbersi is not None) and (atomicNumberso is not None) and (
len(atomicNumbersi) == len(atomicNumberso)) and (nbasisi == nbasiso)
if QOK:
for (i, j) in zip(atomicNumbersi, atomicNumberso):
if i != j:
QOK = False
break
if not QOK:
raise ValueError(
"The systems on the input and output files are incompatible.")
# . Set the keys for the calculation.
if spinDensitiesRESTRICTED: keys = [""]
else: keys = ["alpha", "beta"]
# . Get the densities multiplied by the overlap.
ps = {}
for key in keys:
p = _MakeDensity(orbitalsets[key])
# p.Print ( title = "**1**" )
result = Real2DArray.WithExtents(nbasisi, nbasisi)
result.Set(999.0)
p.PostMultiply(overlap, result)
# overlap.Print ( title = "**2**" )
# result.Print ( title = "**3**" )
ps[key] = result
# f = STOP
# . Scale ps correctly for the spin-restricted case.
if spinDensitiesRESTRICTED: ps[""].Scale(2.0)
# . If cross terms are not required condense the ps matrices.
if (not QCROSS) and (not spinDensitiesRESTRICTED):
tps = ps.pop(keys[0])
for key in keys[1:]:
tps.AddScaledMatrix(1.0, ps[key])
ps = {"": tps}
keys = [""]
# . Get the bond-orders.
bondOrders = {}
for key1 in keys:
for key2 in keys:
bondOrders[(key1, key2)] = _MakeBondOrders(ps[key1], ps[key2],
findices)
# . Make the total bond-order if necessary.
bokeys = bondOrders.keys()
if len(bokeys) > 1:
bokeys.sort()
tbo = Clone(bondOrders[bokeys[0]])
for key in bokeys[1:]:
tbo.AddScaledMatrix(1.0, bondOrders[key])
tkey = ("", "")
bokeys.append(tkey)
bondOrders[tkey] = tbo
# . Compute the electronic contribution to the Mulliken charges.
qmulliken = Real1DArray.WithExtent(len(atomicNumbersi))
qmulliken.Set(0.0)
for key in keys:
_MakeElectronicMullikenCharges(ps[key], findices, qmulliken)
# . Determine atom valencies.
free = Real1DArray.WithExtent(len(atomicNumbersi))
free.Set(0.0)
valencies = Real1DArray.WithExtent(len(atomicNumbersi))
valencies.Set(0.0)
tbo = bondOrders[("", "")]
for i in range(len(atomicNumbersi)):
valencies[i] = (-2.0 * qmulliken[i]) - tbo[i, i]
totalbo = 0.0
for j in range(len(atomicNumbersi)):
totalbo += tbo[i, j]
free[i] = (-2.0 * qmulliken[i]) - totalbo
# . Add in the core contributions to the Mulliken charges.
for (i, q) in enumerate(atomicNumbersi):
qmulliken[i] += float(q)
if outfile.QECP:
for (i, q) in enumerate(outfile.ecpelectrons):
qmulliken[i] -= float(q)
# . Output the results.
if LogFileActive(log):
# . Get the spin label.
if spinDensitiesRESTRICTED: spinlabel = "Spin Restricted"
else: spinlabel = "Spin Unrestricted"
# . Create the atom names.
atomnames = []
for (i, n) in enumerate(atomicNumbersi):
atomnames.append(PeriodicTable.Symbol(n, index=i + 1))
# . Atom data.
columns = [10, 20, 20, 20]
if not spinDensitiesRESTRICTED: columns.append(20)
table = log.GetTable(columns=columns)
table.Start()
table.Title("Atom Data (" + spinlabel + ")")
table.Heading("Atom")
table.Heading("Charge")
table.Heading("Self Bond Order")
table.Heading("Valence")
if not spinDensitiesRESTRICTED: table.Heading("Free Valence")
for (i, ni) in enumerate(atomnames):
table.Entry(ni)
table.Entry("{:.3f}".format(qmulliken[i]))
table.Entry("{:.3f}".format(tbo[i, i]))
table.Entry("{:.3f}".format(valencies[i]))
if not spinDensitiesRESTRICTED:
table.Entry("{:.3f}".format(free[i]))
table.Stop()
# . Bond orders.
for key in bokeys:
orders = bondOrders[key]
table = log.GetTable(columns=[10, 10, 20, 20])
table.Start()
if key == ("", ""): table.Title("Total Bond Orders")
else:
table.Title(key[0].title() + "/" + key[1].title() +
" Bond Orders")
table.Heading("Atom 1")
table.Heading("Atom 2")
table.Heading("Order")
table.Heading("Distance")
for (i, ni) in enumerate(atomnames):
for (j, nj) in enumerate(atomnames[0:i]):
b = orders[i, j]
if math.fabs(b) > bondOrdertolerance:
table.Entry(ni)
table.Entry(nj)
table.Entry("{:.3f}".format(b))
table.Entry("{:.3f}".format(coordinates3.Distance(
i, j)))
table.Stop()
# . Checks on the calculation.
# . Free valence.
if spinDensitiesRESTRICTED:
deviation = free.AbsoluteMaximum()
if deviation > chargetolerance:
log.Paragraph(
"Warning: the largest deviation between the free valence values and zero is {:.3f}."
.format(deviation))
# . Total charge.
deviation = math.fabs(qmulliken.Sum() - float(infile.charge))
if deviation > chargetolerance:
log.Paragraph(
"Warning: the total charge deviates from the formal charge by {:.3f}."
.format(deviation))
# . Check for a valid reference set of Mulliken charges.
qreference = getattr(outfile, "qmulliken", None)
if (qreference is not None) and (len(qreference)
== len(atomicNumbersi)):
qmulliken.AddScaledArray(-1.0, qreference)
deviation = qmulliken.AbsoluteMaximum()
if deviation > chargetolerance:
log.Paragraph(
"Warning: the largest deviation between calculated and read Mulliken charges is {:.3f}."
.format(deviation))
# . Finish up.
return bondOrders
