def _overlayPoints(points1, points2):
"""Given two sets of points, determine the translation and rotation that matches them as closely as possible.
This is based on W. Kabsch, Acta Cryst., A34, pp. 828-829 (1978)."""
if len(points1) == 0:
return (Vec3(0, 0, 0), np.identity(3), Vec3(0, 0, 0))
if len(points1) == 1:
return (points1[0], np.identity(3), -1*points2[0])
# Compute centroids.
center1 = unit.sum(points1)/float(len(points1))
center2 = unit.sum(points2)/float(len(points2))
# Compute R matrix.
R = np.zeros((3, 3))
for p1, p2 in zip(points1, points2):
x = p1-center1
y = p2-center2
for i in range(3):
for j in range(3):
R[i][j] += y[i]*x[j]
# Use an SVD to compute the rotation matrix.
(u, s, v) = lin.svd(R)
return (-1*center2, np.dot(u, v).transpose(), center1)
def end_to_end_CA_distance(self, topology, positions):
residues = list(topology.residues())
# get the index of the first and last alpha carbons
i1 = [a.index for a in residues[0].atoms() if a.name == 'CA'][0]
i2 = [a.index for a in residues[-1].atoms() if a.name == 'CA'][0]
# get the current distanc be between the two alpha carbons
return i1, i2, sqrt(sum((positions[i1] - positions[i2])**2))
def _overlayPoints(points1, points2):
"""Given two sets of points, determine the translation and rotation that matches them as closely as possible.
Parameters
----------
points1 (numpy array of simtk.unit.Quantity with units compatible with distance) - reference set of coordinates
points2 (numpy array of simtk.unit.Quantity with units compatible with distance) - set of coordinates to be rotated
Returns
-------
translate2 - vector to translate points2 by in order to center it
rotate - rotation matrix to apply to centered points2 to map it on to points1
center1 - center of points1
Notes
-----
This is based on W. Kabsch, Acta Cryst., A34, pp. 828-829 (1978).
"""
if len(points1) == 0:
return (mm.Vec3(0, 0, 0), np.identity(3), mm.Vec3(0, 0, 0))
if len(points1) == 1:
return (points1[0], np.identity(3), -1*points2[0])
# Compute centroids.
center1 = unit.sum(points1)/float(len(points1))
center2 = unit.sum(points2)/float(len(points2))
# Compute R matrix.
R = np.zeros((3, 3))
for p1, p2 in zip(points1, points2):
x = p1-center1
y = p2-center2
for i in range(3):
for j in range(3):
R[i][j] += y[i]*x[j]
# Use an SVD to compute the rotation matrix.
(u, s, v) = lin.svd(R)
return (-1*center2, np.dot(u, v).transpose(), center1)
def _overlayPoints(points1, points2):
"""Given two sets of points, determine the translation and rotation that matches them as closely as possible.
Parameters
----------
points1 (numpy array of simtk.unit.Quantity with units compatible with distance) - reference set of coordinates
points2 (numpy array of simtk.unit.Quantity with units compatible with distance) - set of coordinates to be rotated
Returns
-------
translate2 - vector to translate points2 by in order to center it
rotate - rotation matrix to apply to centered points2 to map it on to points1
center1 - center of points1
Notes
-----
This is based on W. Kabsch, Acta Cryst., A34, pp. 828-829 (1978).
"""
if len(points1) == 0:
return (mm.Vec3(0, 0, 0), np.identity(3), mm.Vec3(0, 0, 0))
if len(points1) == 1:
return (points1[0], np.identity(3), -1*points2[0])
# Compute centroids.
center1 = unit.sum(points1)/float(len(points1))
center2 = unit.sum(points2)/float(len(points2))
# Compute R matrix.
R = np.zeros((3, 3))
for p1, p2 in zip(points1, points2):
x = p1-center1
y = p2-center2
for i in range(3):
for j in range(3):
R[i][j] += y[i]*x[j]
# Use an SVD to compute the rotation matrix.
(u, s, v) = lin.svd(R)
return (-1*center2, np.dot(u, v).transpose(), center1)
def __init__(self, structure):
"""Create a new PDBFixer to fix problems in a PDB file.
Parameters:
- structure (PdbStructure) the starting PDB structure containing problems to be fixed
"""
self.structure = structure
self.pdb = app.PDBFile(structure)
self.topology = self.pdb.topology
self.positions = self.pdb.positions
self.centroid = unit.sum(self.positions)/len(self.positions)
self.structureChains = list(self.structure.iter_chains())
# Load the templates.
self.templates = {}
templatesPath = os.path.join(os.path.dirname(__file__), 'templates')
for file in os.listdir(templatesPath):
templatePdb = app.PDBFile(os.path.join(templatesPath, file))
name = next(templatePdb.topology.residues()).name
self.templates[name] = templatePdb
def testUnitMathModule(self):
""" Tests the unit_math functions on Quantity objects """
self.assertEqual(u.sqrt(1.0*u.kilogram*u.joule),
1.0*u.kilogram*u.meter/u.second)
self.assertEqual(u.sqrt(1.0*u.kilogram*u.calorie),
math.sqrt(4.184)*u.kilogram*u.meter/u.second)
self.assertEqual(u.sqrt(9), 3) # Test on a scalar
self.assertEqual(u.sin(90*u.degrees), 1)
self.assertEqual(u.sin(math.pi/2*u.radians), 1)
self.assertEqual(u.sin(math.pi/2), 1)
self.assertEqual(u.cos(180*u.degrees), -1)
self.assertEqual(u.cos(math.pi*u.radians), -1)
self.assertEqual(u.cos(math.pi), -1)
self.assertAlmostEqual(u.tan(45*u.degrees), 1)
self.assertAlmostEqual(u.tan(math.pi/4*u.radians), 1)
self.assertAlmostEqual(u.tan(math.pi/4), 1)
acos = u.acos(1.0)
asin = u.asin(1.0)
atan = u.atan(1.0)
self.assertTrue(u.is_quantity(acos))
self.assertTrue(u.is_quantity(asin))
self.assertTrue(u.is_quantity(atan))
self.assertEqual(acos.unit, u.radians)
self.assertEqual(asin.unit, u.radians)
self.assertEqual(atan.unit, u.radians)
self.assertEqual(acos.value_in_unit(u.degrees), 0)
self.assertEqual(acos / u.radians, 0)
self.assertEqual(asin.value_in_unit(u.degrees), 90)
self.assertEqual(asin / u.radians, math.pi/2)
self.assertAlmostEqual(atan.value_in_unit(u.degrees), 45)
self.assertAlmostEqual(atan / u.radians, math.pi/4)
# Check some sequence maths
seq = [1, 2, 3, 4] * u.meters
self.assertEqual(u.sum(seq), 10*u.meters)
self.assertEqual(u.dot(seq, seq), (1+4+9+16)*u.meters**2)
self.assertEqual(u.norm(seq), math.sqrt(30)*u.meters)
def _computeResidueCenter(self, residue):
"""Compute the centroid of a residue."""
return unit.sum([self.pdb.positions[atom.index] for atom in residue.atoms()])/len(list(residue.atoms()))
def _computeResidueCenter(self, residue):
"""Compute the centroid of a residue."""
return unit.sum([self.pdb.positions[atom.index] for atom in residue.atoms()])/len(list(residue.atoms()))
def test_velocity_assignment(mpicomm=None, verbose=True):
"""
Test Maxwell-Boltzmann velocity assignment subtroutine produces correct distribution, raising an exception if this test fails.
"""
# Stop here if not root node.
if mpicomm and (mpicomm.rank != 0): return
if verbose: print "Testing Maxwell-Boltzmann velocity assignment: ",
# Make a list of all test system constructors.
import simtk.pyopenmm.extras.testsystems as testsystems
# Test parameters
temperature = 298.0 * units.kelvin # test temperature
kT = kB * temperature # thermal energy
ntrials = 1000 # number of test trials
systems_to_test = ['HarmonicOscillator', 'HarmonicOscillatorArray', 'AlanineDipeptideImplicit'] # systems to test
for system_name in systems_to_test:
#print '*' * 80
#print system_name
# Create system.
constructor = getattr(testsystems, system_name)
[system, coordinates] = constructor()
# Create temporary filename.
import tempfile # use a temporary file for testing
file = tempfile.NamedTemporaryFile()
store_filename = file.name
# Create repex instance.
states = [ ThermodynamicState(system, temperature=temperature) ]
simulation = repex.ReplicaExchange(states=states, coordinates=coordinates, store_filename=store_filename)
# Create integrator and context.
natoms = system.getNumParticles()
velocity_trials = numpy.zeros([ntrials, natoms, 3])
kinetic_energy_trials = numpy.zeros([ntrials])
for trial in range(ntrials):
velocities = simulation._assign_Maxwell_Boltzmann_velocities(system, temperature)
kinetic_energy = 0.5 * units.sum(units.sum(system.masses * velocities**2))
velocity_trials[trial,:,:] = velocities / (units.nanometers / units.picosecond)
kinetic_energy_trials[trial] = kinetic_energy / units.kilocalories_per_mole
velocity_mean = velocity_trials.mean(0)
velocity_stderr = velocity_trials.std(0) / numpy.sqrt(ntrials)
kinetic_analytical = (3.0/2.0) * natoms * kT / units.kilocalories_per_mole
kinetic_mean = kinetic_energy_trials.mean()
kinetic_error = kinetic_mean - kinetic_analytical
kinetic_stderr = kinetic_energy_trials.std() / numpy.sqrt(ntrials)
# Test if violations exceed tolerance.
MAX_SIGMA = 6.0 # maximum number of standard errors allowed
if numpy.any(numpy.abs(kinetic_error / kinetic_stderr) > MAX_SIGMA):
print "analytical kinetic energy"
print kinetic_analytical
print "mean kinetic energy (kcal/mol)"
print kinetic_mean
print "difference (kcal/mol)"
print kinetic_mean - kinetic_analytical
print "stderr (kcal/mol)"
print kinetic_stderr
print "nsigma"
print (kinetic_mean - kinetic_analytical) / kinetic_stderr
raise Exception("Mean kinetic energy exceeds error tolerance of %.1f standard errors." % MAX_SIGMA)
if numpy.any(numpy.abs(velocity_mean / velocity_stderr) > MAX_SIGMA):
print "mean velocity (nm/ps)"
print velocity_mean
print "stderr (nm/ps)"
print velocity_stderr
print "nsigma"
print velocity_mean / velocity_stderr
raise Exception("Mean velocity exceeds error tolerance of %.1f standard errors." % MAX_SIGMA)
if verbose: print "PASSED"
return
def _calculateElongation(self, state):
positions = state.getPositions(asNumpy=True)
displacement = positions[self._index1] - positions[self._index2]
distance = unit.sqrt(unit.sum(displacement**2))
return distance.value_in_unit(unit.nanometers)
def __init__(self, filename=None, file=None, url=None, pdbid=None):
"""Create a new PDBFixer instance to fix problems in a PDB file.
Parameters
----------
filename : str, optional, default=None
A filename specifying the file from which the PDB file is to be read.
file : file, optional, default=None
A file-like object from which the PDB file is to be read.
The file is not closed after reading.
url : str, optional, default=None
A URL specifying the internet location from which the PDB file contents should be retrieved.
pdbid : str, optional, default=None
A four-letter PDB code specifying the structure to be retrieved from the RCSB.
Notes
-----
Only one of structure, filename, file, url, or pdbid may be specified or an exception will be thrown.
Examples
--------
Start from a file object.
>>> pdbid = '1VII'
>>> url = 'http://www.rcsb.org/pdb/files/%s.pdb' % pdbid
>>> file = urlopen(url)
>>> fixer = PDBFixer(file=file)
Start from a filename.
>>> filename = 'test.pdb'
>>> file = urlopen(url)
>>> outfile = open(filename, 'w')
>>> outfile.write(file.read())
>>> outfile.close()
>>> fixer = PDBFixer(filename=filename)
Start from a URL.
>>> fixer = PDBFixer(url=url)
Start from a PDB code.
>>> fixer = PDBFixer(pdbid=pdbid)
"""
# Check to make sure only one option has been specified.
if bool(filename) + bool(file) + bool(url) + bool(pdbid) != 1:
raise Exception("Exactly one option [filename, file, url, pdbid] must be specified.")
if filename:
# A local file has been specified.
file = open(filename, 'r')
structure = PdbStructure(file)
file.close()
elif file:
# A file-like object has been specified.
structure = PdbStructure(file)
elif url:
# A URL has been specified.
file = urlopen(url)
structure = PdbStructure(file)
file.close()
elif pdbid:
# A PDB id has been specified.
url = 'http://www.rcsb.org/pdb/files/%s.pdb' % pdbid
file = urlopen(url)
# Read contents all at once and split into lines, since urlopen doesn't like it when we read one line at a time over the network.
contents = file.read()
lines = contents.split('\n')
file.close()
structure = PdbStructure(lines)
# Check the structure has some atoms in it.
atoms = list(structure.iter_atoms())
if len(atoms)==0:
raise Exception("Structure contains no atoms.")
self.structure = structure
self.pdb = app.PDBFile(structure)
self.topology = self.pdb.topology
self.positions = self.pdb.positions
self.centroid = unit.sum(self.positions)/len(self.positions)
self.structureChains = list(self.structure.iter_chains())
# Load the templates.
self.templates = {}
templatesPath = os.path.join(os.path.dirname(__file__), 'templates')
for file in os.listdir(templatesPath):
templatePdb = app.PDBFile(os.path.join(templatesPath, file))
name = next(templatePdb.topology.residues()).name
self.templates[name] = templatePdb
return
def __init__(self, filename=None, file=None, url=None, pdbid=None):
"""Create a new PDBFixer instance to fix problems in a PDB file.
Parameters
----------
filename : str, optional, default=None
A filename specifying the file from which the PDB file is to be read.
file : file, optional, default=None
A file-like object from which the PDB file is to be read.
The file is not closed after reading.
url : str, optional, default=None
A URL specifying the internet location from which the PDB file contents should be retrieved.
pdbid : str, optional, default=None
A four-letter PDB code specifying the structure to be retrieved from the RCSB.
Notes
-----
Only one of structure, filename, file, url, or pdbid may be specified or an exception will be thrown.
Examples
--------
Start from a file object.
>>> pdbid = '1VII'
>>> url = 'http://www.rcsb.org/pdb/files/%s.pdb' % pdbid
>>> file = urlopen(url)
>>> fixer = PDBFixer(file=file)
Start from a filename.
>>> filename = 'test.pdb'
>>> file = urlopen(url)
>>> outfile = open(filename, 'w')
>>> outfile.write(file.read())
>>> outfile.close()
>>> fixer = PDBFixer(filename=filename)
Start from a URL.
>>> fixer = PDBFixer(url=url)
Start from a PDB code.
>>> fixer = PDBFixer(pdbid=pdbid)
"""
# Check to make sure only one option has been specified.
if bool(filename) + bool(file) + bool(url) + bool(pdbid) != 1:
raise Exception("Exactly one option [filename, file, url, pdbid] must be specified.")
self.source = None
if filename:
self.source = filename
# A local file has been specified.
file = open(filename, 'r')
structure = PdbStructure(file)
file.close()
elif file:
# A file-like object has been specified.
structure = PdbStructure(file)
elif url:
self.source = url
# A URL has been specified.
file = urlopen(url)
structure = PdbStructure(file)
file.close()
elif pdbid:
# A PDB id has been specified.
url = 'http://www.rcsb.org/pdb/files/%s.pdb' % pdbid
self.source = url
file = urlopen(url)
# Read contents all at once and split into lines, since urlopen doesn't like it when we read one line at a time over the network.
contents = file.read()
lines = contents.split('\n')
file.close()
structure = PdbStructure(lines)
# Check the structure has some atoms in it.
atoms = list(structure.iter_atoms())
if len(atoms)==0:
raise Exception("Structure contains no atoms.")
self.structure = structure
self.pdb = app.PDBFile(structure)
self.topology = self.pdb.topology
self.positions = self.pdb.positions
self.centroid = unit.sum(self.positions)/len(self.positions)
self.structureChains = list(self.structure.iter_chains())
# Load the templates.
self.templates = {}
templatesPath = os.path.join(os.path.dirname(__file__), 'templates')
for file in os.listdir(templatesPath):
templatePdb = app.PDBFile(os.path.join(templatesPath, file))
name = next(templatePdb.topology.residues()).name
self.templates[name] = templatePdb
return
def createRigidBodies(system, positions, bodies):
"""Modify a System to turn specified sets of particles into rigid bodies.
For every rigid body, four particles are selected as "real" particles whose positions are integrated.
Constraints are added between them to make them move as a rigid body. All other particles in the body
are then turned into virtual sites whose positions are computed based on the "real" particles.
Because virtual sites are massless, the mass properties of the rigid bodies will be slightly different
from the corresponding sets of particles in the original system. The masses of the non-virtual particles
are chosen to guarantee that the total mass and center of mass of each rigid body exactly match those of
the original particles. The moment of inertia will be similar to that of the original particles, but
not identical.
Care is needed when using constraints, since virtual particles cannot participate in constraints. If the
input system includes any constraints, this function will automatically remove ones that connect two
particles in the same rigid body. But if there is a constraint beween a particle in a rigid body and
another particle not in that body, it will likely lead to an exception when you try to create a context.
Parameters:
- system (System) the System to modify
- positions (list) the positions of all particles in the system
- bodies (list) each element of this list defines one rigid body. Each element should itself be a list
of the indices of all particles that make up that rigid body.
"""
# Remove any constraints involving particles in rigid bodies.
for i in range(system.getNumConstraints() - 1, -1, -1):
p1, p2, distance = system.getConstraintParameters(i)
if (any(p1 in body and p2 in body for body in bodies)):
system.removeConstraint(i)
# Loop over rigid bodies and process them.
for particles in bodies:
if len(particles) < 5:
# All the particles will be "real" particles.
realParticles = particles
realParticleMasses = [system.getParticleMass(i) for i in particles]
else:
# Select four particles to use as the "real" particles. All others will be virtual sites.
pos = [positions[i] for i in particles]
mass = [system.getParticleMass(i) for i in particles]
cm = unit.sum([p * m for p, m in zip(pos, mass)]) / unit.sum(mass)
r = [p - cm for p in pos]
avgR = unit.sqrt(
unit.sum([unit.dot(x, x) for x in r]) / len(particles))
rank = sorted(range(len(particles)),
key=lambda i: abs(unit.norm(r[i]) - avgR))
for p in combinations(rank, 4):
# Select masses for the "real" particles. If any is negative, reject this set of particles
# and keep going.
matrix = np.zeros((4, 4))
for i in range(4):
particleR = r[p[i]].value_in_unit(unit.nanometers)
matrix[0][i] = particleR[0]
matrix[1][i] = particleR[1]
matrix[2][i] = particleR[2]
matrix[3][i] = 1.0
rhs = np.array(
[0.0, 0.0, 0.0,
unit.sum(mass).value_in_unit(unit.amu)])
weights = lin.solve(matrix, rhs)
if all(w > 0.0 for w in weights):
# We have a good set of particles.
realParticles = [particles[i] for i in p]
realParticleMasses = [float(w) for w in weights] * unit.amu
break
# Set particle masses.
for i, m in zip(realParticles, realParticleMasses):
system.setParticleMass(i, m)
# Add constraints between the real particles.
for p1, p2 in combinations(realParticles, 2):
distance = unit.norm(positions[p1] - positions[p2])
key = (min(p1, p2), max(p1, p2))
system.addConstraint(p1, p2, distance)
# Select which three particles to use for defining virtual sites.
bestNorm = 0
for p1, p2, p3 in combinations(realParticles, 3):
d12 = (positions[p2] - positions[p1]).value_in_unit(unit.nanometer)
d13 = (positions[p3] - positions[p1]).value_in_unit(unit.nanometer)
crossNorm = unit.norm((d12[1] * d13[2] - d12[2] * d13[1],
d12[2] * d13[0] - d12[0] * d13[2],
d12[0] * d13[1] - d12[1] * d13[0]))
if crossNorm > bestNorm:
bestNorm = crossNorm
vsiteParticles = (p1, p2, p3)
# Create virtual sites.
d12 = (positions[vsiteParticles[1]] -
positions[vsiteParticles[0]]).value_in_unit(unit.nanometer)
d13 = (positions[vsiteParticles[2]] -
positions[vsiteParticles[0]]).value_in_unit(unit.nanometer)
cross = mm.Vec3(d12[1] * d13[2] - d12[2] * d13[1],
d12[2] * d13[0] - d12[0] * d13[2],
d12[0] * d13[1] - d12[1] * d13[0])
matrix = np.zeros((3, 3))
for i in range(3):
matrix[i][0] = d12[i]
matrix[i][1] = d13[i]
matrix[i][2] = cross[i]
for i in particles:
if i not in realParticles:
system.setParticleMass(i, 0)
rhs = np.array((positions[i] -
positions[vsiteParticles[0]]).value_in_unit(
unit.nanometer))
weights = lin.solve(matrix, rhs)
system.setVirtualSite(
i,
mm.OutOfPlaneSite(vsiteParticles[0], vsiteParticles[1],
vsiteParticles[2], weights[0],
weights[1], weights[2]))
def test_velocity_assignment(mpicomm=None, verbose=True):
"""
Test Maxwell-Boltzmann velocity assignment subtroutine produces correct distribution, raising an exception if this test fails.
"""
# Stop here if not root node.
if mpicomm and (mpicomm.rank != 0): return
if verbose: print "Testing Maxwell-Boltzmann velocity assignment: ",
# Make a list of all test system constructors.
import simtk.pyopenmm.extras.testsystems as testsystems
# Test parameters
temperature = 298.0 * units.kelvin # test temperature
kT = kB * temperature # thermal energy
ntrials = 1000 # number of test trials
systems_to_test = [
'HarmonicOscillator', 'HarmonicOscillatorArray',
'AlanineDipeptideImplicit'
] # systems to test
for system_name in systems_to_test:
#print '*' * 80
#print system_name
# Create system.
constructor = getattr(testsystems, system_name)
[system, coordinates] = constructor()
# Create temporary filename.
import tempfile # use a temporary file for testing
file = tempfile.NamedTemporaryFile()
store_filename = file.name
# Create repex instance.
states = [ThermodynamicState(system, temperature=temperature)]
simulation = repex.ReplicaExchange(states=states,
coordinates=coordinates,
store_filename=store_filename)
# Create integrator and context.
natoms = system.getNumParticles()
velocity_trials = numpy.zeros([ntrials, natoms, 3])
kinetic_energy_trials = numpy.zeros([ntrials])
for trial in range(ntrials):
velocities = simulation._assign_Maxwell_Boltzmann_velocities(
system, temperature)
kinetic_energy = 0.5 * units.sum(
units.sum(system.masses * velocities**2))
velocity_trials[trial, :, :] = velocities / (units.nanometers /
units.picosecond)
kinetic_energy_trials[
trial] = kinetic_energy / units.kilocalories_per_mole
velocity_mean = velocity_trials.mean(0)
velocity_stderr = velocity_trials.std(0) / numpy.sqrt(ntrials)
kinetic_analytical = (3.0 /
2.0) * natoms * kT / units.kilocalories_per_mole
kinetic_mean = kinetic_energy_trials.mean()
kinetic_error = kinetic_mean - kinetic_analytical
kinetic_stderr = kinetic_energy_trials.std() / numpy.sqrt(ntrials)
# Test if violations exceed tolerance.
MAX_SIGMA = 6.0 # maximum number of standard errors allowed
if numpy.any(numpy.abs(kinetic_error / kinetic_stderr) > MAX_SIGMA):
print "analytical kinetic energy"
print kinetic_analytical
print "mean kinetic energy (kcal/mol)"
print kinetic_mean
print "difference (kcal/mol)"
print kinetic_mean - kinetic_analytical
print "stderr (kcal/mol)"
print kinetic_stderr
print "nsigma"
print(kinetic_mean - kinetic_analytical) / kinetic_stderr
raise Exception(
"Mean kinetic energy exceeds error tolerance of %.1f standard errors."
% MAX_SIGMA)
if numpy.any(numpy.abs(velocity_mean / velocity_stderr) > MAX_SIGMA):
print "mean velocity (nm/ps)"
print velocity_mean
print "stderr (nm/ps)"
print velocity_stderr
print "nsigma"
print velocity_mean / velocity_stderr
raise Exception(
"Mean velocity exceeds error tolerance of %.1f standard errors."
% MAX_SIGMA)
if verbose: print "PASSED"
return
