def runParallelSims(simnumber):
# Define seed
seed = int(simnumber)
random.seed(seed)
# Create unbound MSMlist (CTMSMs)
# MSM for particle type0
MSMtype = 0
markovModel0 = ctmsm(MSMtype, -1 * seed) # random variable seed
D0list = np.array([1.0])
Drot0list = np.array([1.0])
markovModel0.setD(D0list)
markovModel0.setDrot(Drot0list)
# MSM for particle type1
MSMtype = 1
ratematrix = np.array([[-0.5, 0.5], [6.0, -6.0]])
markovModel1 = ctmsm(MSMtype, ratematrix, -2 * seed)
D1list = np.array([0.5, 1.0])
Drot1list = np.array([0.5, 1.0])
markovModel1.setD(D1list)
markovModel1.setDrot(Drot1list)
unboundMSMlist = [markovModel0, markovModel1]
# Define boundary
boxBoundary = msmrd2.box(boxsize, boxsize, boxsize, boundaryType)
# Define particle list
particleList = particleTools.randomParticleMSList(Nparticles, boxsize,
separationDistance,
particleTypes,
unboundMSMlist, seed)
# Defines patchy protein potential
potentialPatchyProteinMS = patchyProteinMarkovSwitch(
sigma, strength, angularStrength, patchesCoordinates1,
patchesCoordinates2)
# Integrator definition
seed = int(
-1 * simnumber
) # random seed (negative and different for every simulation, good for parallelization)
integrator = odLangevinMS(unboundMSMlist, dt, seed, bodytype)
integrator.setBoundary(boxBoundary)
integrator.setPairPotential(potentialPatchyProteinMS)
# Creates simulation
sim = msmrd2.simulation(integrator)
# Output filename definition
filename = basefilename + "_{:04d}".format(simnumber)
# Runs simulation
sim.run(particleList, timesteps, stride, bufferSize, filename, outTxt,
outH5, outChunked, trajtype)
print("Simulation " + str(simnumber) + ", done.")
def simulationFPT(trajectorynum):
'''
Calculates first passage time of a trajectory with random initial
conditions and final state a bound state
:param trajectorynum: number of trajectories on which to calculate the FPT
:return: state, first passage time
'''
# Define simulation boundaries (choose either spherical or box)
boxBoundary = msmrd2.box(boxsize, boxsize, boxsize, 'periodic')
# Define dummy trajectory to extract bound states from python (needed to use getState function)
radialLowerBound = 1.25
radialUpperBound = 2.25
dummyTraj = msmrd2.trajectories.patchyProtein(numparticles, 1024,
radialLowerBound,
radialUpperBound)
dummyTraj.setBoundary(boxBoundary)
# Define base seed
seed = int(-1 * trajectorynum) # Negative seed, uses random device as seed
# Create unbound MSMlist (CTMSMs)
# MSM for particle type0
MSMtype = 0
markovModel0 = ctmsm(MSMtype, -1 * seed) # random variable seed
D0list = np.array([1.0])
Drot0list = np.array([1.0])
markovModel0.setD(D0list)
markovModel0.setDrot(Drot0list)
# MSM for particle type1
MSMtype = 1
ratematrix = np.array([[-0.5, 0.5], [6.0, -6.0]])
markovModel1 = ctmsm(MSMtype, ratematrix, -2 * seed)
D1list = np.array([0.5, 1.0])
Drot1list = np.array([0.5, 1.0])
markovModel1.setD(D1list)
markovModel1.setDrot(Drot1list)
unboundMSMlist = [markovModel0, markovModel1]
# Define potential
potentialPatchyProtein = patchyProteinMarkovSwitch(sigma, strength,
angularStrength,
patchesCoordinates1,
patchesCoordinates2)
# Define integrator and boundary (over-damped Langevin)
integrator = odLangevinMS(unboundMSMlist, dt, seed, bodytype)
integrator.setBoundary(boxBoundary)
integrator.setPairPotential(potentialPatchyProtein)
# Creates random particle list
seed = int(trajectorynum)
partlist = particleTools.randomParticleMSList(numparticles, boxsize,
minimumUnboundRadius,
particleTypes,
unboundMSMlist, seed)
# Calculates the first passage times for a given bound state. Each trajectory is integrated until
# a bound state is reached. The output in the files is the elapsed time.
unbound = True
while (unbound):
integrator.integrate(partlist)
boundState = dummyTraj.getState(partlist[0], partlist[1])
if boundState in boundStates:
unbound = False
return boundState, integrator.clock
elif integrator.clock >= 15000.0:
unbound = False
return 'Failed at:', integrator.clock
def MSMRDsimulationFPT(trajectorynum):
'''
Calculates first passage time of a trajectory with random initial
conditions and final state a bound state
:param trajectorynum: trajectory number (index on parallel computation) on which to calculate the FPT
:return: state, first passage time
'''
# Define discretization
discretization = msmrd2.discretizations.positionOrientationPartition(
radialBounds[1], numSphericalSectionsPos, numRadialSectionsQuat,
numSphericalSectionsQuat)
discretization.setThetasOffset(np.pi / 4.0)
# Define boundary
boxBoundary = msmrd2.box(boxsize, boxsize, boxsize, 'periodic')
# Define isotropic potential (no patches)
potentialPatchyProtein = patchyProteinMarkovSwitch(sigma, strength,
angularStrength,
patchesCoordinates1,
patchesCoordinates2)
# Define base seed
seed = int(-1 * trajectorynum) # Negative seed, uses random device as seed
# Load rate dicitionary
pickle_in = open(
MSMdirectory + "MSM_patchyProtein_t6.00E+06_s25_lagt" + str(lagtime) +
".pickle", "rb")
mainMSM = pickle.load(pickle_in)
tmatrix = mainMSM['transition_matrix']
activeSet = mainMSM['active_set']
# Create unbound MSMlist (CTMSMs)
# MSM for particle type0
MSMtype = 0
markovModel0 = ctmsm(MSMtype, -1 * seed) # random variable seed
D0list = np.array([1.0])
Drot0list = np.array([1.0])
markovModel0.setD(D0list)
markovModel0.setDrot(Drot0list)
# MSM for particle type1
MSMtype = 1
ratematrix = np.array([[-0.5, 0.5], [6.0, -6.0]])
markovModel1 = ctmsm(MSMtype, ratematrix, -2 * seed)
D1list = np.array([0.5, 1.0])
Drot1list = np.array([0.5, 1.0])
markovModel1.setD(D1list)
markovModel1.setDrot(Drot1list)
unboundMSMlist = [markovModel0, markovModel1]
# Set coupling MSM for MSM/RD
seed = int(-3 * trajectorynum) # Negative seed, uses random device as seed
couplingMSM = msmrdMSM(numBoundStates, maxNumBoundStates, tmatrix,
activeSet, realLagtime, seed)
couplingMSM.setDbound(Dbound, DboundRot)
# Define integrator, boundary and discretization
seed = -int(1 * trajectorynum) # Negative seed, uses random device as seed
integrator = msmrdPatchyProtein(dt, seed, bodytype, numParticleTypes,
radialBounds, unboundMSMlist, couplingMSM)
integrator.setBoundary(boxBoundary)
integrator.setDiscretization(discretization)
integrator.setPairPotential(potentialPatchyProtein)
# Creates random particle list
seed = int(trajectorynum)
partlist = particleTools.randomParticleMSList(numparticles, boxsize,
minimumUnboundRadius,
particleTypes,
unboundMSMlist, seed)
# Calculates the first passage times for a given bound state. Each trajectory is integrated until
# a bound state is reached. The output in the files is the elapsed time.
unbound = True
while (unbound):
integrator.integrate(partlist)
currentState = partlist[0].boundState
if currentState in boundStates:
unbound = False
#filenameLog = filename = "../../data/patchyProtein/eventLog_" + str(trajectorynum)
#integrator.printEventLog(filenameLog)
return currentState, integrator.clock
elif integrator.clock >= 15000.0:
unbound = False
return 'Failed at:', integrator.clock
def MSMRDsimulationFPT(trajectorynum):
'''
Calculates first passage time of a trajectory with random initial
conditions and final state a bound state
:param trajectorynum: trajectory number (index on parallel computation) on which to calculate the FPT
:return: state, first passage time
'''
# Define discretization
discretization = msmrd2.discretizations.positionOrientationPartition(
radialBounds[1], numSphericalSectionsPos, numRadialSectionsQuat,
numSphericalSectionsQuat)
# Define boundary
boxBoundary = msmrd2.box(boxsize, boxsize, boxsize, 'periodic')
# Load rate dicitionary
pickle_in = open(
MSMdirectory + "MSM_patchyDimer_t3.00E+06_s25_lagt" + str(lagtime) +
".pickle", "rb")
mainMSM = pickle.load(pickle_in)
tmatrix = mainMSM['transition_matrix']
activeSet = mainMSM['active_set']
# Set unbound MSM
seed = int(-2 * trajectorynum) # Negative seed, uses random device as seed
unboundMSM = ctmsm(MSMtype, ratematrix, seed)
unboundMSM.setD(Dlist)
unboundMSM.setDrot(Drotlist)
# Set coupling MSM
seed = int(-3 * trajectorynum) # Negative seed, uses random device as seed
couplingMSM = msmrdMSM(numBoundStates, maxNumBoundStates, tmatrix,
activeSet, realLagtime, seed)
couplingMSM.setDbound(Dbound, DboundRot)
# Define integrator, boundary and discretization
seed = -int(1 * trajectorynum) # Negative seed, uses random device as seed
integrator = msmrdIntegrator(dt, seed, bodytype, numParticleTypes,
radialBounds, unboundMSM, couplingMSM)
integrator.setBoundary(boxBoundary)
integrator.setDiscretization(discretization)
# Generate random position and orientation particle list with two particles
seed = int(trajectorynum)
partlist = particleTools.randomParticleMSList(numParticles, boxsize,
minimumUnboundRadius,
partTypes, [unboundMSM],
seed)
# Calculates the first passage times for a given bound state. Each trajectory is integrated until
# a bound state is reached. The output in the files is the elapsed time.
unbound = True
while (unbound):
integrator.integrate(partlist)
currentState = partlist[0].boundState
if currentState in boundStatesA:
unbound = False
return 'A', integrator.clock
elif currentState in boundStatesB:
unbound = False
return 'B', integrator.clock
elif integrator.clock >= 10000.0:
unbound = False
return 'Failed at:', integrator.clock
def MSMRDsimulationFPT(trajectorynum):
'''
Calculates first passage time of a trajectory with random initial
conditions and final state a bound state
:param trajectorynum: trajectory number (index on parallel computation) on which to calculate the FPT
:return: state, first passage time
'''
# Define discretization
discretization = msmrd2.discretizations.positionOrientationPartition(
radialBounds[1], numSphericalSectionsPos, numRadialSectionsQuat,
numSphericalSectionsQuat)
# Define boundary
boxBoundary = msmrd2.box(boxsize, boxsize, boxsize, 'periodic')
# Load rate dicitionary
pickle_in = open(
"../../data/pentamer/MSMs/MSM_dimerForPentamer_t3.00E+06_s25_lagt" +
str(lagtime) + ".pickle", "rb") # Same MSM as trimer
mainMSM = pickle.load(pickle_in)
tmatrix = mainMSM['transition_matrix']
activeSet = mainMSM['active_set']
# Set unbound MSM
seed = int(-2 * trajectorynum) # Negative seed, uses random device as seed
unboundMSM = ctmsm(MSMtype, ratematrix, seed)
unboundMSM.setD(Dlist)
unboundMSM.setDrot(Drotlist)
# Set coupling MSM
seed = int(-3 * trajectorynum) # Negative seed, uses random device as seed
couplingMSM = msmrdMSM(numBoundStates, maxNumBoundStates, tmatrix,
activeSet, realLagtime, seed)
couplingMSM.setDbound(Dbound, DboundRot)
# Define integrator, boundary and discretization
seed = -int(1 * trajectorynum) # Negative seed, uses random device as seed
integrator = msmrdMultiParticleIntegrator(dt, seed, bodytype,
numParticleTypes, radialBounds,
unboundMSM, couplingMSM,
DlistCompound, DrotlistCompound)
integrator.setBoundary(boxBoundary)
integrator.setDiscretization(discretization)
# Generate random position and orientation particle list with two particles
seed = int(trajectorynum)
partlist = particleTools.randomParticleMSList(numParticles, boxsize,
minimumUnboundRadius,
partTypes, [unboundMSM],
seed)
# Calculates the first passage times to a given bound state. Each trajectory is integrated until
# a bound state is reached. The output in the files is the elapsed time.
unbound = True
ii = 0
while (unbound):
ii += 1
integrator.integrate(partlist)
# Check status every 5000 timesteps (adds possible error of up to 5000*dt = 0.5), but
# speeds up simulations
if (ii % 5000 == 0):
ringFormations = integrator.findClosedBindingLoops(partlist)
if (3 in ringFormations):
unbound = False
return 'trimeric-loop', integrator.clock
elif (4 in ringFormations):
unbound = False
return 'tetrameric-loop', integrator.clock
elif (5 in ringFormations):
unbound = False
return "pentameric-loop", integrator.clock
elif integrator.clock >= 400.0:
unbound = False
return 'Failed at:', integrator.clock