# PRINT INITIAL STRING I0
print "\nI0: ",
print z
#io.plotVector(prop[0][0],stringgraph,z, rangex=[-numpy.pi, numpy.pi], rangey=[-numpy.pi, numpy.pi])
dt = 1.0
for iter in range(0, numsteps): # NUMBER OF FTSM ITERATIONS
for p in range(0, numpoints): # LOOPING OVER POINTS
if (iter >= 10000 and iter <= 100000):
kappa += (100. - 40.) / 90000.
if (p != 0 or iter != 0):
FTSM.setConstraint(PHI,
PSI,
phi=z[p][0],
psi=z[p][1],
kappa=kappa,
forcefield=ff)
# UPDATE FREE SPACE
# USE FIRST SYSTEM TO GET M
# USE SECOND SYSTEM TO OBTAIN PHI AND PSI DIFFERENCES
# FROM TARGETS
zp0 = z[p][0]
z[p][0] -= (kappa / gamma) * dt * (FTSM.M(x[p], PHI, PHI) *
(z[p][0] - y[p].dihedral(PHI)) +
FTSM.M(x[p], PHI, PSI) *
(z[p][1] - y[p].dihedral(PSI)))
z[p][1] -= (kappa / gamma) * dt * (FTSM.M(x[p], PSI, PHI) *
(zp0 - y[p].dihedral(PHI)) +
FTSM.M(x[p], PSI, PSI) *
'switching': 'C2'
}
ff.params['CoulombDiElec'] = {
'algorithm': 'Cutoff',
'switching': 'Cn',
'switchon': 10,
'cutoff': 12,
'order': 2
}
for ii in range(0, numgridsquares):
for jj in range(0, numgridsquares):
print "BOX: ", ii, jj
if (ii != 0):
FTSM.setConstraint(PHI, PSI, midpts[ii][jj][0], midpts[ii][jj][1],
kappa, ff)
elif (jj != 0):
FTSM.setConstraint(PHI, PSI, midpts[ii][jj][0], midpts[ii][jj][1],
kappa, ff)
pts = ii * numgridsquares + jj
for i in range(0, 20):
myProp.propagate(scheme="LangevinImpulse",
steps=100,
dt=1.0,
forcefield=ff,
params={
'temp': 300,
'gamma': 91
})
#stringgraph=io.newGraph('Phi', 'Psi')
# PRINT INITIAL STRING I0
print "\nI0: ",
print z
#io.plotVector(prop[0][0],stringgraph,z, rangex=[-numpy.pi, numpy.pi], rangey=[-numpy.pi, numpy.pi])
dt = 1.0
for iter in range(0, numsteps): # NUMBER OF FTSM ITERATIONS
for p in range(0, numpoints): # LOOPING OVER POINTS
if (iter >= 10000 and iter <= 100000):
kappa += (100.-40.)/90000.
if (p != 0 or iter != 0):
FTSM.setConstraint(PHI, PSI, phi=z[p][0], psi=z[p][1], kappa=kappa, forcefield=ff)
# UPDATE FREE SPACE
# USE FIRST SYSTEM TO GET M
# USE SECOND SYSTEM TO OBTAIN PHI AND PSI DIFFERENCES
# FROM TARGETS
zp0 = z[p][0]
z[p][0] -= (kappa/gamma)*dt*(FTSM.M(x[p], PHI, PHI)*(z[p][0]-y[p].dihedral(PHI)) + FTSM.M(x[p], PHI, PSI)*(z[p][1] - y[p].dihedral(PSI)))
z[p][1] -= (kappa/gamma)*dt*(FTSM.M(x[p], PSI, PHI)*(zp0-y[p].dihedral(PHI)) + FTSM.M(x[p], PSI, PSI)*(z[p][1] - y[p].dihedral(PSI)))
# UPDATE CARTESIAN
prop[p][0].propagate(scheme="velocityscale", steps=1, dt=dt, forcefield=ff, params={'T0':300})
prop[p][1].propagate(scheme="velocityscale", steps=1, dt=dt, forcefield=ff, params={'T0':300})
sys.exit(0)
ff.params['HarmonicDihedral'] = {'kbias':[kappa, kappa],
'dihedralnum':[PHI-1, PSI-1],
'angle':[z_p[0], z_p[1]]}
dt = 1.0
kappaincr = (1000.-40.)/100000.
for iter in range(0, 2000): # NUMBER OF FTSM ITERATIONS
#for workpt in range(0, numpoints): # LOOPING OVER POINTS
if (iter >= 10001 and iter <= 110000):
kappa += kappaincr
if (iter != 0):
FTSM.setConstraint(PHI, PSI, phi=z_p[0], psi=z_p[1], kappa=kappa, forcefield=ff)
# UPDATE FREE SPACE
# USE FIRST SYSTEM TO GET M
# USE SECOND SYSTEM TO OBTAIN PHI AND PSI DIFFERENCES
# FROM TARGETS
zp0 = z_p[0]
z_p[0] -= (kappa/gamma)*dt*(FTSM.M(x, PHI, PHI)*(z_p[0]-y.angle(PHI)) + FTSM.M(x, PHI, PSI)*(z_p[1] - y.angle(PSI)))
z_p[1] -= (kappa/gamma)*dt*(FTSM.M(x, PSI, PHI)*(zp0-y.angle(PHI)) + FTSM.M(x, PSI, PSI)*(z_p[1] - y.angle(PSI)))
# UPDATE CARTESIAN
# Dr. Izaguirre: I have checked and this constraint
# is correct. The energy is harmonic, but the force (the gradient)
# is not harmonic. In fact it is exactly what is in the paper.
prop[0].propagate(scheme="velocityscale", steps=1, dt=dt, forcefield=ff, params={'T0':300})
prop[1].propagate(scheme="velocityscale", steps=1, dt=dt, forcefield=ff, params={'T0':300})
'cutoff':12,
'switchon':10,
'switching':'C2'}
ff.params['CoulombDiElec'] = {'algorithm':'Cutoff',
'switching':'Cn',
'switchon':10,
'cutoff':12,
'order':2}
for ii in range(0,numgridsquares):
for jj in range(0,numgridsquares):
print "BOX: ", ii, jj
if (ii !=0):
FTSM.setConstraint(PHI, PSI, midpts[ii][jj][0],midpts[ii][jj][1],kappa,ff)
elif (jj != 0) :
FTSM.setConstraint(PHI, PSI, midpts[ii][jj][0],midpts[ii][jj][1],kappa,ff)
pts = ii*numgridsquares + jj
for i in range(0,20):
myProp.propagate(scheme="LangevinImpulse",steps=100,dt=1.0,forcefield=ff,params={'temp':300,'gamma':91})
FTSM.setConstraint(PHI, PSI, midpts[ii][jj][0],midpts[ii][jj][1],kappa1,ff)
#Equilibrate at this point for a bit
myProp.propagate(scheme="LangevinImpulse",steps=50,dt=1.0,forcefield=ff,params={'temp':300,'gamma':91})
ef = outdir+'/sampleatrc.energies.'+str(ii)+'.'+str(jj)
df = outdir+'/sampleatrc.'+str(ii)+'.'+str(jj)+'.dcd'
#converged = False
#d = 40000
#initial = copy(z)
convergedPhis = []
convergedPsis = []
matlabfile = open("formatlab.txt", "w")
for iter in range(0, numsteps): # NUMBER OF FTSM ITERATIONS
for p in range(0, numpoints): # LOOPING OVER POINTS
if (iter >= 15000):# and iter <= 100000):
kappa += (100.-40.)/90000.
if (p != 0 or iter != 0):
FTSM.setConstraint(PHI, PSI, phi=z[p][0], psi=z[p][1], kappa=kappa, forcefield=ff)
# UPDATE FREE SPACE
# USE FIRST SYSTEM TO GET M
# USE SECOND SYSTEM TO OBTAIN PHI AND PSI DIFFERENCES
# FROM TARGETS
zp0 = z[p][0]
z[p][0] -= (kappa/gamma)*dt*(FTSM.M(x[p], PHI, PHI)*(z[p][0]-y[p].dihedral(PHI)) + FTSM.M(x[p], PHI, PSI)*(z[p][1] - y[p].dihedral(PSI)))
z[p][1] -= (kappa/gamma)*dt*(FTSM.M(x[p], PSI, PHI)*(zp0-y[p].dihedral(PHI)) + FTSM.M(x[p], PSI, PSI)*(z[p][1] - y[p].dihedral(PSI)))
# My own function which sets phi and psi for individual force objects
# Saves performance since I only change 'angle', I don't want to define
# all new force objects by changing params.
#if (iter != 0 or p != 0):
# FTSM.setConstraint(phi=z[p][0], psi=z[p][1], kappa=kappa, forcefield=ff)
# UPDATE CARTESIAN
io.plotVector(proparray[0][0],stringgraph,S, rangex=[-numpy.pi, 0], rangey=[-100*numpy.pi/180, numpy.pi])
# SET THE STATE BACK TO THE ORIGINAL PDB
#io.readPDBPos(physarray[0][0], "examples/alanSolStates/alanC7axial_wb5_min_eq.pdb")
dt = 1.0
for iter in range(0, 100000): # NUMBER OF FTSM ITERATIONS
for workpt in range(0, numpoints): # LOOPING OVER POINTS
if (iter >= 10000 and iter <= 100000):
kappa += (100.-40.)/90000.
# UPDATE FREE SPACE
# USE FIRST SYSTEM TO GET M
# USE SECOND SYSTEM TO OBTAIN PHI AND PSI DIFFERENCES
# FROM TARGETS
M = FTSM.M(physarray[workpt][0], PHI_DIHEDRAL, PSI_DIHEDRAL)
#print "DIFFERENCE: ", S[workpt][0]-physarray[workpt][1].phi(PHI_DIHEDRAL), " " , S[workpt][1]-physarray[workpt][1].phi(PSI_DIHEDRAL)
S[workpt][0] -= (kappa/gamma)*M*dt*(S[workpt][0]-physarray[workpt][1].phi(PHI_DIHEDRAL))
S[workpt][1] -= (kappa/gamma)*M*dt*(S[workpt][1]-physarray[workpt][1].phi(PSI_DIHEDRAL))
# UPDATE CARTESIAN
# Dr. Izaguirre: I have checked and this constraint
# is correct. The energy is harmonic, but the force (the gradient)
# is not harmonic. In fact it is exactly what is in the paper.
proparray[workpt][0].propagate(scheme="LangevinImpulse", steps=1, dt=dt, forcefield=ff)
proparray[workpt][1].propagate(scheme="LangevinImpulse", steps=1, dt=dt, forcefield=ff)
# My own function which sets phi and psi for individual force objects
# Saves performance since I only change 'angle', I don't want to define
# all new force objects by changing params.
'kbias': [kappa, kappa],
'dihedralnum': [PHI - 1, PSI - 1],
'angle': [z_p[0], z_p[1]]
}
dt = 1.0
kappaincr = (1000. - 40.) / 100000.
for iter in range(0, 2000): # NUMBER OF FTSM ITERATIONS
#for workpt in range(0, numpoints): # LOOPING OVER POINTS
if (iter >= 10001 and iter <= 110000):
kappa += kappaincr
if (iter != 0):
FTSM.setConstraint(PHI,
PSI,
phi=z_p[0],
psi=z_p[1],
kappa=kappa,
forcefield=ff)
# UPDATE FREE SPACE
# USE FIRST SYSTEM TO GET M
# USE SECOND SYSTEM TO OBTAIN PHI AND PSI DIFFERENCES
# FROM TARGETS
zp0 = z_p[0]
z_p[0] -= (kappa /
gamma) * dt * (FTSM.M(x, PHI, PHI) *
(z_p[0] - y.angle(PHI)) + FTSM.M(x, PHI, PSI) *
(z_p[1] - y.angle(PSI)))
z_p[1] -= (kappa /
gamma) * dt * (FTSM.M(x, PSI, PHI) *
(zp0 - y.angle(PHI)) + FTSM.M(x, PSI, PSI) *
(z_p[1] - y.angle(PSI)))
