def runTest(self):
"""The test."""
# . Paths.
dataPath = os.path.join(os.getenv("PDYNAMO_PMOLECULE"), "data", "mol")
log = self.GetLog()
# . Get the system.
molecule = MOLFile_ToSystem(
os.path.join(dataPath, "tyrosineDipeptide.mol"))
molecule.DefineMMModel(MMModelOPLS("protein"))
molecule.DefineNBModel(NBModelFull())
molecule.Summary(log=log)
molecule.Energy(log=log, doGradients=True)
# . Save initial coordinates.
reference3 = Clone(molecule.coordinates3)
# . Do some dynamics.
normalDeviateGenerator = NormalDeviateGenerator.WithRandomNumberGenerator(
RandomNumberGenerator.WithSeed(247171))
LangevinDynamics_SystemGeometry(
molecule,
collisionFrequency=25.0,
log=log,
logFrequency=1000,
normalDeviateGenerator=normalDeviateGenerator,
steps=_NSteps,
temperature=300.0,
timeStep=0.001)
# . Check RMSs which should be the same as rotation and translation are removed.
masses = molecule.atoms.GetItemAttributes("mass")
rms0 = molecule.coordinates3.RMSDeviation(reference3, weights=masses)
molecule.coordinates3.Superimpose(reference3, weights=masses)
rms1 = molecule.coordinates3.RMSDeviation(reference3, weights=masses)
# . Get the observed and reference data.
observed = {"RMS Deviation": rms1}
referenceData = TestDataSet("Rotation/Translation Removal")
referenceData.AddDatum(
TestReal("RMS Deviation",
rms0,
referenceData,
absoluteErrorTolerance=_RMSAbsoluteErrorTolerance,
toleranceFormat="{:.3f}",
valueFormat="{:.3f}"))
# . Check for success/failure.
if len(observed) > 0:
results = referenceData.VerifyAgainst(observed)
results.Summary(log=log, fullSummary=self.fullVerificationSummary)
isOK = results.WasSuccessful()
else:
isOK = True
self.assertTrue(isOK)
def runTest ( self ):
"""The test."""
# . Paths.
dataPath = os.path.join ( os.getenv ( "PDYNAMO_ROOT" ), "molecularStructures", "aminoAcids", "mol" )
log = self.GetLog ( )
# . Models.
mmModel = MMModelOPLS ( "protein" )
nbModel = NBModelFull ( )
# . Get all files.
molFiles = glob.glob ( os.path.join ( dataPath, "*.mol" ) )
molFiles.sort ( )
# . Read all mol files.
numberFailed = 0
for molFile in molFiles:
if log is not None: log.Text ( "\nProcessing " + molFile + ":\n" )
molecule = MOLFile_ToSystem ( molFile )
try:
molecule.DefineMMModel ( mmModel, log = log )
molecule.DefineNBModel ( nbModel )
molecule.Summary ( log = log )
molecule.Energy ( log = log, doGradients = True )
except Exception as e:
numberFailed += 1
if log is not None: log.Text ( "\nError occurred> " + e.args[0] + "\n" )
# . Summary of results.
if log is not None:
summary = log.GetSummary ( )
summary.Start ( "OPLS Protein Parameter Tests" )
summary.Entry ( "Successes", "{:d}".format ( len ( molFiles ) - numberFailed ) )
summary.Entry ( "Failures" , "{:d}".format ( numberFailed ) )
summary.Stop ( )
# . Success/failure.
self.assertTrue ( ( numberFailed == 0 ) )
def runTest ( self ):
"""The test."""
# . Paths.
dataPath = os.path.join ( os.getenv ( "PDYNAMO_PMOLECULE" ), "data", "mol" )
if self.resultPath is None: outPath = os.path.join ( os.getenv ( "PDYNAMO_SCRATCH" ), _Destination )
else: outPath = os.path.join ( self.resultPath , _Destination )
if not os.path.exists ( outPath ): os.mkdir ( outPath )
log = self.GetLog ( )
# . Energy models.
mmModel = MMModelOPLS ( "protein" )
nbModel = NBModelFull ( )
qcModel = QCModelMNDO ( converger = DIISSCFConverger ( densityTolerance = 1.0e-10 ) )
# . Initialization.
numberFailures = 0
# . Loop over molecules.
for moleculeLabel in _MoleculeLabels:
# . Get the system.
system = MOLFile_ToSystem ( os.path.join ( dataPath, moleculeLabel + ".mol" ) )
if moleculeLabel in _QCModels:
system.DefineQCModel ( qcModel )
else:
system.DefineMMModel ( mmModel, log = log )
system.DefineNBModel ( nbModel )
system.Summary ( log = log )
system.Energy ( log = log )
# . Minimize well.
LBFGSMinimize_SystemGeometry ( system,
log = log ,
logFrequency = _LogFrequency ,
maximumIterations = _Iterations ,
rmsGradientTolerance = _Tolerance )
# . Normal mode analysis.
nmState = NormalModes_SystemGeometry ( system, log = log )
# . Do a dynamics simulation: equilibration and then data collection.
normalDeviateGenerator = NormalDeviateGenerator.WithRandomNumberGenerator ( RandomNumberGenerator.WithSeed ( _Seed ) )
LangevinDynamics_SystemGeometry ( system ,
collisionFrequency = _CollisionFrequency ,
log = log ,
logFrequency = _LogFrequency ,
normalDeviateGenerator = normalDeviateGenerator ,
steps = _NSteps0 ,
temperature = _Temperature ,
timeStep = 0.001 )
reference3 = Clone ( system.coordinates3 )
trajectory = AmberTrajectoryFileWriter ( os.path.join ( outPath, moleculeLabel + ".crd" ), system )
LangevinDynamics_SystemGeometry ( system ,
collisionFrequency = _CollisionFrequency ,
log = log ,
logFrequency = _LogFrequency ,
normalDeviateGenerator = normalDeviateGenerator ,
steps = _NSteps1 ,
temperature = _Temperature ,
timeStep = 0.001 ,
trajectories = [ ( trajectory, _SaveFrequency ) ] )
# . Check RMSs.
masses = system.atoms.GetItemAttributes ( "mass" )
rms0 = system.coordinates3.RMSDeviation ( reference3, weights = masses )
system.coordinates3.Superimpose ( reference3, weights = masses )
rms1 = system.coordinates3.RMSDeviation ( reference3, weights = masses )
if ( math.fabs ( rms1 - rms0 ) >= _RMSAbsoluteErrorTolerance ): numberFailures += 1
# . Do a quasi-harmonic analysis.
trajectory = AmberTrajectoryFileReader ( os.path.join ( outPath, moleculeLabel + ".crd" ), system )
qhState = QuasiHarmonic_SystemGeometry ( system, log = log, temperature = _Temperature, trajectories = [ trajectory ] )
# . Success/failure.
self.assertTrue ( ( numberFailures == 0 ) )
def runTest(self):
"""The test."""
# . Paths.
dataPath = os.path.join(os.getenv("PDYNAMO_PMOLECULE"), "data", "mol")
log = self.GetLog()
# . Energy models.
mmModel = MMModelOPLS("protein")
nbModel = NBModelFull()
# . Get the files.
molFiles = glob.glob(os.path.join(dataPath, "*.mol"))
# . Initialization.
numberErrors = 0
numberFailures = 0
# . Loop over the files.
for molFile in molFiles:
try:
# . Get the system.
try:
system = MOLFile_ToSystem(molFile)
system.DefineMMModel(mmModel, log=log)
system.DefineNBModel(nbModel)
system.Summary(log=log)
except:
continue
# . Calculate an energy.
eBefore = system.Energy(log=log, doGradients=True)
# . Define all hydrogen positions as undefined.
for (i, atom) in enumerate(system.atoms):
if atom.atomicNumber == 1:
system.coordinates3.FlagCoordinateAsUndefined(i)
# . Build as many undefined coordinates as possible.
randomNumberGenerator = RandomNumberGenerator.WithSeed(957197)
BuildHydrogenCoordinates3FromConnectivity(
system,
log=log,
randomNumberGenerator=randomNumberGenerator)
# . Calculate an energy if all coordinates have been defined.
if system.coordinates3.numberUndefined > 0:
numberFailures += 1
if log is not None:
log.Paragraph("Not all hydrogens have been rebuilt.")
else:
eAfter = system.Energy(log=log, doGradients=True)
if log is not None:
log.Paragraph(
"Energy difference after rebuilding = {:.1f}.".
format(eAfter - eBefore))
except Exception as e:
numberErrors += 1
if log is not None:
log.Text("\nError occurred> " + e.args[0] + "\n")
# . Success/failure.
self.assertTrue(((numberErrors == 0) and (numberFailures == 0)))
def runTest(self):
"""The test."""
# . Output setup.
dataPath = os.path.join(os.getenv("PDYNAMO_PMOLECULE"), "data", "mol")
log = self.GetLog()
# . Define the MM, NB and QC models.
mmModel = MMModelOPLS("bookSmallExamples")
nbModel = NBModelFull()
qcModel = QCModelMNDO()
# . Define the dimer with an MM model.
dimer = MOLFile_ToSystem(os.path.join(dataPath, "waterDimer_cs.mol"))
dimer.DefineMMModel(mmModel)
dimer.Summary(log=log)
# . Define the monomer selections.
selection1 = Selection.FromIterable(range(0, 3))
selection2 = Selection.FromIterable(range(3, 6))
# . Get the monomer energies.
e1 = self.MonomerEnergies(dimer, selection1, nbModel, qcModel, log=log)
e2 = self.MonomerEnergies(dimer, selection2, nbModel, qcModel, log=log)
# . Get the binding energies.
e12 = {}
for model1 in _Models:
for model2 in _Models:
key = model1 + " " + model2
if log is not None:
log.Heading(model1 + "/" + model2 + " Dimer Calculation",
QBLANKLINE=True)
# . Define the energy model.
if key == "QC QC": dimer.DefineQCModel(qcModel)
elif key == "QC MM":
dimer.DefineQCModel(qcModel, qcSelection=selection1)
elif key == "MM QC":
dimer.DefineQCModel(qcModel, qcSelection=selection2)
else:
dimer.energyModel.ClearQCModel(dimer.configuration)
if "MM" in key: dimer.DefineNBModel(nbModel)
dimer.Summary(log=log)
# . Store the results.
e12[key] = dimer.Energy(log=log) - e1[model1] - e2[model2]
# . Output the results.
if log is not None:
keys = e12.keys()
keys.sort()
table = log.GetTable(columns=[20, 20, 20])
table.Start()
table.Title("Water Dimer Binding Energies")
table.Heading("Monomer 1")
table.Heading("Monomer 2")
table.Heading("Binding Energy")
for key in keys:
(model1, model2) = key.split()
table.Entry(model1)
table.Entry(model2)
table.Entry("{:.1f}".format(e12[key]))
table.Stop()
# . Success/failure.
isOK = True
for e in e12.values():
if (e < _LowerBound) or (e > _UpperBound):
isOK = False
break
self.assertTrue(isOK)
# takes no (interesting) arguments.
#
# . Note on scratch names:
#
# It has been noticed that ORCA itself can give an error when the name of the scratch directory is too long.
# This occurs in the "%pcname" line of the ORCA input file. To cure this use a shorter name - either by resetting
# the environment variable PDYNAMO_SCRATCH or by explicitly passing a name to the model with the "scratch" option.
#
# . Define the MM, NB and QC models.
mmModel = MMModelOPLS("bookSmallExamples")
nbModel = NBModelORCA()
qcModel = QCModelORCA("MP2:6-31G*", "EXTREMESCF", "SCFCONV10")
# . Define the molecule.
molecule = MOLFile_ToSystem(
os.path.join(os.getenv("PDYNAMO_PMOLECULE"), "data", "mol",
"waterDimer_cs.mol"))
# . Define the selection for the first molecule.
firstWater = Selection.FromIterable([0, 1, 2])
# . Define the energy model.
molecule.DefineMMModel(mmModel)
molecule.DefineQCModel(qcModel, qcSelection=firstWater)
molecule.DefineNBModel(nbModel)
molecule.Summary()
# . Calculate an energy.
molecule.Energy(doGradients=True)
def runTest(self):
"""The test."""
# . Initialization.
dataPath = os.path.join(os.getenv("PDYNAMO_PMOLECULE"), "data", "mol")
log = self.GetLog()
translation = Vector3.Uninitialized()
# . Get the individual systems.
energies = []
molecules = []
for (i, label) in enumerate(_Molecules):
molecule = MOLFile_ToSystem(os.path.join(dataPath, label + ".mol"))
molecule.label = label
molecule.DefineMMModel(_mmModel)
molecule.DefineNBModel(_nbModel)
molecule.Summary(log=log)
molecule.coordinates3.TranslateToCenter()
molecule.configuration.Clear()
energies.append(molecule.Energy(log=log, doGradients=True))
molecules.append(molecule)
# . Data initialization.
observed = {}
referenceData = TestDataSet("Merge/Prune Energies")
# . Loop over the tests.
for (testIndex, (moleculeFrequencies,
moleculePruneIndices)) in enumerate(_Tests):
# . Heading.
if log is not None:
log.Heading("Merge/Prune Test {:d}".format(testIndex),
QBLANKLINE=True)
# . Initialization.
mergedEnergy = 0.0
prunedEnergy = 0.0
translation.Set(0.0)
# . Gather items.
index = 0
numberAtoms = 0
pruneIndices = []
toMerge = []
for (i, frequency) in enumerate(moleculeFrequencies):
molecule = molecules[i]
mergedEnergy += energies[i] * frequency
for f in range(frequency):
cloned = Clone(molecule)
translation[0] += _Displacement
cloned.coordinates3.Translate(translation)
toMerge.append(cloned)
if index in moleculePruneIndices:
pruneIndices.extend(
range(numberAtoms,
numberAtoms + len(cloned.atoms)))
prunedEnergy += energies[i]
index += 1
numberAtoms += len(cloned.atoms)
# . Merging.
merged = toMerge[0].Merge(toMerge[1:])
merged.Summary(log=log)
eMerged = merged.Energy(log=log)
# . Pruning.
pruned = merged.Prune(Selection.FromIterable(pruneIndices))
pruned.Summary(log=log)
ePruned = pruned.Energy(log=log)
# . Get the observed and reference data.
for (tag, eObserved,
eReference) in (("Merged Energy {:d}".format(testIndex),
eMerged, mergedEnergy),
("Pruned Energy {:d}".format(testIndex),
ePruned, prunedEnergy)):
observed[tag] = eObserved
referenceData.AddDatum(
TestReal(
tag,
eReference,
referenceData,
absoluteErrorTolerance=_EnergyAbsoluteErrorTolerance,
toleranceFormat="{:.3f}",
valueFormat="{:.3f}"))
# . Finish up.
if log is not None: log.Separator()
# . Check for success/failure.
if len(observed) > 0:
results = referenceData.VerifyAgainst(observed)
results.Summary(log=log, fullSummary=self.fullVerificationSummary)
isOK = results.WasSuccessful()
else:
isOK = True
# . Success/failure.
self.assertTrue(isOK)