def coulomb_energy(r, switchd, nbcutoff):
'''
given a distance, calculate the coulomb energy
'''
Uel_kCpM1 = np.zeros(len(r))
Uel1 = np.zeros(len(r))
coor = np.zeros((4, 3))
charge = np.zeros(4)
charge[0] = charge[-1] = 2
e = 1
for (i, ri) in enumerate(r):
coor[-1, 0] = ri
# (Uel_kCpM1[i], Uel1[i]) = coulomb.coulomb(coor, charge, e, ARGS.temperature, switchd, nbcutoff)
(Uel_kCpM1[i], Uel1[i]) = coulomb.screen_coulomb(
coor, charge, e, ARGS.temperature, 9.61, switchd, nbcutoff) # screened
return (Uel_kCpM1, Uel1)
def coulomb_energy(r, switchd, nbcutoff):
'''
given a distance, calculate the coulomb energy
'''
Uel_kCpM1 = np.zeros(len(r))
Uel1 = np.zeros(len(r))
coor = np.zeros((4, 3))
charge = np.zeros(4)
charge[0] = charge[-1] = 2
e = 1
for (i, ri) in enumerate(r):
coor[-1, 0] = ri
# (Uel_kCpM1[i], Uel1[i]) = coulomb.coulomb(coor, charge, e, ARGS.temperature, switchd, nbcutoff)
(Uel_kCpM1[i],
Uel1[i]) = coulomb.screen_coulomb(coor, charge, e, ARGS.temperature,
9.61, switchd, nbcutoff) # screened
return (Uel_kCpM1, Uel1)
def dna_mc_save_info(ARGS, cg_dna, aa_dna, cg_pro, aa_pro, vecXYZ, lp,
trialbeads, beadgroups, group_masks, all_beads,
dna_bead_masks, aa_pgroup_masks, cg_pgroup_masks,
all_proteins, aa_all, aa_pro_mask, aa_dna_mask,
bp_per_bead, dna_type='b'):
'''
this function perform nsteps Monte-Carlo moves on the cg_dna
'''
timestr = time.strftime("_%y%m%d_%H%M%S") # prefix for output files
all_dcd_name = ARGS.pdb[:-4] + timestr + '.dcd'
aa_all_dcd_out = aa_all.open_dcd_write(all_dcd_name)
if False:
aa_all.send_coordinates_to_vmd(2222, 0)
# create the coarse-grained DNA and protein dcd and pdb files
cg_dna_dcd_name = 'cg_dna' + timestr + '.dcd'
cg_pro_dcd_name = 'cg_pro' + timestr + '.dcd'
cg_dna_dcd_out = cg_dna.open_dcd_write(cg_dna_dcd_name)
cg_pro_dcd_out = cg_pro.open_dcd_write(cg_pro_dcd_name)
cg_dna.write_dcd_step(cg_dna_dcd_out, 0, 1)
cg_pro.write_dcd_step(cg_pro_dcd_out, 0, 1)
cg_dna_pdb_name = 'cg_dna' + timestr + '.pdb'
cg_pro_pdb_name = 'cg_pro' + timestr + '.pdb'
cg_dna.write_pdb(cg_dna_pdb_name, 0, 'w')
cg_pro.write_pdb(cg_pro_pdb_name, 0, 'w')
# create a dummy sasmol object for the 3 orientation vectors for each bead
# will write these out to dcd files to store the coordinates along the way
vecX_mol = sasmol.SasMol(0)
vecY_mol = sasmol.SasMol(0)
vecZ_mol = sasmol.SasMol(0)
error, mask = cg_dna.get_subset_mask('(all)')
error = cg_dna.copy_molecule_using_mask(vecX_mol, mask, 0)
error = cg_dna.copy_molecule_using_mask(vecY_mol, mask, 0)
error = cg_dna.copy_molecule_using_mask(vecZ_mol, mask, 0)
# the np.array recast these so they
vecX_mol.setCoor(np.array([vecXYZ[0]]))
vecY_mol.setCoor(np.array([vecXYZ[1]])) # do not update with vecXYZ
vecZ_mol.setCoor(np.array([vecXYZ[2]]))
vecX_dcd_name = 'vecX' + timestr + '.dcd'
vecY_dcd_name = 'vecY' + timestr + '.dcd'
vecZ_dcd_name = 'vecZ' + timestr + '.dcd'
vecX_dcd_out = vecX_mol.open_dcd_write(vecX_dcd_name)
vecY_dcd_out = vecY_mol.open_dcd_write(vecY_dcd_name)
vecZ_dcd_out = vecZ_mol.open_dcd_write(vecZ_dcd_name)
vecX_mol.write_dcd_step(vecX_dcd_out, 0, 1)
vecY_mol.write_dcd_step(vecY_dcd_out, 0, 1)
vecZ_mol.write_dcd_step(vecZ_dcd_out, 0, 1)
# initialize variables for each run
steps_from_0 = np.zeros(ARGS.nsteps, dtype='int64')
xyz = np.copy(vecXYZ)
d_coor = np.copy(cg_dna.coor()[0]) # unique memory for each
p_coor = np.copy(cg_pro.coor()[0]) # unique memory for each
# vectors between beads u, and average distance l
(u, l) = dna_move.checkU(d_coor)
# s print "(u, l) =", (u, l) # debug info
lpl = lp / l # setup the presistence length paramater
# yet to use a, and z type dna
dna_energy_width = {'a': 0, 'b': 46., 'z': 0}
w = dna_energy_width[dna_type.lower()]
if w > l:
w = np.floor(l)
# print '~~~ %.2f > %.2f ~~~~~~~~~~~~~~~~~~~~~~~~' % (w, l)
print ('>>> setting chain width (w) to %d (chain width < distance' % w,
' btwn beads)')
dna_diam = {'a': 25.5, 'b': 23.7, 'z': 18.4}
dna_bead_radius = 4.5
pro_bead_radius = 1.0 # 2A min seperation of CA atoms in database
pro_pro_test = pro_bead_radius + pro_bead_radius
dna_pro_test = dna_bead_radius + pro_bead_radius
# calculate the energy of the starting positions
wca0 = np.zeros((cg_dna.natoms(), cg_dna.natoms()))
Ub0 = dna_move.energyBend(lpl, u, l)
(Uwca0, wca0) = dna_move.f_energy_wca(w, d_coor, wca0, 0)
U_T0 = Ub0 + Uwca0
# print '(Ub0, Uwca0, Ub0/U_T0, Uwca0/U_T0) = ', (Ub0, Uwca0, Ub0/U_T0,
# Uwca0/U_T0)
n_accept = 0 # total times configuration was accepted
n_reject = 0 # total times configuration was rejected
n_written = 0 # total times dcd write has been called
fail_tally = 0 # number of times failed for particular iteration
n_from_reload = 0 # number of stps since last reload
n_reload = [0] # listt containing the i_goback values
# this should not actually be >=, come back to this
assert np.size(ARGS.theta_max) - 1 >= np.max(beadgroups), (
'each group needs its own theta_max: %d < %d'
% (np.size(ARGS.theta_max) - 1, np.max(beadgroups)))
rg_old = cg_dna.calcrg(0)
rg = np.zeros(ARGS.nsteps)
Uel_kCpM = np.zeros(ARGS.nsteps)
Uel = np.zeros(ARGS.nsteps)
Uwca = np.zeros(ARGS.nsteps)
Ub = np.zeros(ARGS.nsteps)
# Main MC loop #
while n_accept < ARGS.nsteps:
# Choose a bead to rotate
trial_bead = trialbeads[int((trialbeads.size) * np.random.random())]
# Determine rotation to perform
theta_max = ARGS.theta_max[beadgroups[trial_bead]]
# option to scale thetaZ separatly
thetaZ_max = 0 * np.float(theta_max)
# thetaZ_max = np.float(theta_max) # option to scale thetaZ separatly
thetaZ = 2 * thetaZ_max * np.random.random() - thetaZ_max
thetaX = 2 * theta_max * np.random.random() - theta_max
thetaY = 2 * theta_max * np.random.random() - theta_max
thetaXYZ = [
thetaX / ARGS.n_soft, thetaY / ARGS.n_soft, thetaZ / ARGS.n_soft]
# print theta_max, thetaXYZ
if len(group_masks) == 0 or beadgroups[trial_bead] == len(group_masks):
# Only DNA will be moving, create place-holder dummy coordinates
p_coor_rot = np.zeros((0, 3))
else:
p_mask = group_masks[beadgroups[trial_bead]]
p_ind_rot = mask2ind(p_mask)
p_ind_fix = mask2ind(-(p_mask - 1))
p_coor_rot = p_coor[p_ind_rot]
p_coor_fix = p_coor[p_ind_fix]
# generate a newly rotated model
(d_coor[trial_bead:], xyz[:, trial_bead:], p_coor_rot
) = dna_move.beadRotate(d_coor[trial_bead - 1:], xyz[:, trial_bead - 1:],
thetaXYZ, ARGS.n_soft, p_coor_rot)
# store the rotated protein coordinates
if beadgroups[trial_bead] < len(group_masks):
p_coor[p_ind_rot] = p_coor_rot
# verify the Rg_new < Rg_old * 1.01
d_coor_old = np.copy(cg_dna.coor()[0])
cg_dna.setCoor(np.array([(d_coor)])) # update dna coordinates
rg_new = cg_dna.calcrg(0)
rg_pass = True
if rg_pass:
# calculate the change in energy (dU) and the boltzman factor (p)
(u, l) = dna_move.checkU(d_coor)
Ub1 = dna_move.energyBend(lpl, u, l)
# ~~~~ DNA interaction energy ~~~~~~#
(Uwca1, wca1) = dna_move.f_energy_wca(w, d_coor, wca0, trial_bead)
U_T1 = Ub1 + Uwca1
dU = U_T1 - U_T0
with warnings.catch_warnings():
warnings.filterwarnings('error') # need this for np warnings
try:
p = np.exp(-dU)
except Warning:
if dU > 99:
p = 0
# s print 'energy was large, setting probability to 0'
elif dU < 0:
p = 1
# s print 'energy was negative, setting probability to
# 1'
else:
print 'Warning: ~~> unclear OverflowError <~~ dU = ', dU
print 'not sure where the error originated from'
test = np.random.random()
if p <= test:
dna_pass = False
# print 'step failed because of DNA energy'
else:
dna_pass = True
# now check for collisions protein involved collisions
if len(p_coor_rot) > 0: # only if proteins were rotated
# ~~~~ Check for overlap, DNA-protein or protein-protein ~~~~~~#
d_coor_fix = d_coor[trial_bead:]
d_coor_rot = d_coor[:trial_bead]
# check for protein-protein overlap
if 1 == f_overlap2(p_coor_rot, p_coor_fix, pro_pro_test):
print 'Protein-Protein'
# print 'collision, set p=0'
collisionless = False
# print 'currently ignoring DNA-protein overlap'
# check for DNA-protein overlap
elif 1 == f_overlap2(p_coor_rot, d_coor_fix, dna_pro_test):
print 'Potein-DNA (rot-fix)'
# print 'collision, set p=0'
collisionless = False
print 'ignoring this for now'
elif 1 == f_overlap2(p_coor_fix, d_coor_rot, dna_pro_test):
print 'Potein-DNA (fix-rot)'
# print 'collision, set p=0'
collisionless = False
else: # passed all collision tests
collisionless = True
if not collisionless:
print 'failed because of collision'
# there are no proteins rotated -> no possible collisions
else:
collisionless = True
if rg_pass and dna_pass and collisionless:
rg_old = rg_new
n_from_reload += 1
steps_from_0[n_accept] = n_from_reload + n_reload[-1]
# calculate the electrostatic energy of this configuration
charge = bp_per_bead * 2 # in units of C (2C per bp)
# These are kinda random...
switchd = 200
nbcutoff = 350
e = 78.54 # dielectric constant for pure water
# e = 1 # dielectric constant for vacuum
# (Uel_kCpM1, Uel1) = coulomb.coulomb(cg_dna.coor(),
# charge, e, ARGS.temperature, switchd, nbcutoff)
ld = 9.61 # debye screening constant in Angstroms
(Uel_kCpM1, Uel1) = coulomb.screen_coulomb(cg_dna.coor(),
charge, e, ARGS.temperature, ld, switchd, nbcutoff)
# store the energies for analysis
rg[n_accept] = rg_new
Uel_kCpM[n_accept] = Uel_kCpM1
Uel[n_accept] = Uel1
Uwca[n_accept] = Uwca1
Ub[n_accept] = Ub1
n_accept += 1 # increment accept counter
# cg_dna.setCoor(d_coor) # <-- DO NOT use setCoor, want uniuqe mem
# cg_pro.setCoor(p_coor) # <-- DO NOT use setCoor, want uniuqe mem
cg_pro.setCoor(np.array([(p_coor)])) # update protein coordinates
vecXYZ = np.copy(xyz) # update dna orientations
vecX_mol.setCoor(np.array([vecXYZ[0]])) # independent of vecXYZ[0]
vecY_mol.setCoor(np.array([vecXYZ[1]])) # independent of vecXYZ[1]
vecZ_mol.setCoor(np.array([vecXYZ[2]])) # independent of vecXYZ[2]
wca0 = np.copy(wca1) # update DNA WCA energy
U_T0 = U_T1 # update total energy
# print output regarding trial
print "trial_bead(%3d) = %2d\t failed attempts = %2d" % (n_accept,
trial_bead, fail_tally)
fail_tally = 0 # reset fail_tally
# print out the Rg
print 'Rg = ', cg_dna.calcrg(0)
# write out the accepted configuration for go-back use
if ARGS.goback > 0:
# these are incremented by one because the original coordinates
# are saved (that is not the case for aa_all)
cg_dna.write_dcd_step(cg_dna_dcd_out, 0, n_written + 1)
cg_pro.write_dcd_step(cg_pro_dcd_out, 0, n_written + 1)
vecX_mol.write_dcd_step(vecX_dcd_out, 0, n_written + 1)
vecY_mol.write_dcd_step(vecY_dcd_out, 0, n_written + 1)
vecZ_mol.write_dcd_step(vecZ_dcd_out, 0, n_written + 1)
# recover an all atom representation and save coordinates to a dcd
# this requires re-inserting the aa-coordinates which takes added
# time so only do when designated
if 0 == n_accept % ARGS.n_dcd_write:
# ~~recover aa-DNA~~
error = dna_move.recover_aaDNA_model(cg_dna, aa_dna, vecXYZ,
all_beads, dna_bead_masks)
# ~~recover aa-Protein~~
dna_move.recover_aaPro_model(aa_pgroup_masks, cg_pgroup_masks,
cg_pro, all_proteins, aa_pro)
# ~~Combine aa Complete Structure~~
aa_all.set_coor_using_mask(aa_pro, 0, aa_pro_mask)
aa_all.set_coor_using_mask(aa_dna, 0, aa_dna_mask)
# ~~Write DCD step~~
n_written += 1
aa_all.write_dcd_step(aa_all_dcd_out, 0, n_written)
else:
# default ARGS.goback is -1 so this returns FALSE without user
# input
if fail_tally == ARGS.goback:
i_goback = rewind(ARGS, n_accept, cg_dna_dcd_name,
cg_dna, cg_pro_dcd_name, cg_pro, vecX_dcd_name,
vecX_mol, vecY_mol, vecY_dcd_name, vecZ_mol,
vecZ_dcd_name, vecXYZ)
# revert dna coordinates
cg_dna.setCoor(np.array([(d_coor_old)]))
d_coor = np.copy(cg_dna.coor()[0]) # reset the dna coordinates
# reset the reference energy
(u, l) = checkU(d_coor)
(Uwca0, wca0) = f_energy_wca(w, d_coor, wca0, 0)
Ub0 = energyBend(lpl, u, l)
U_T0 = Ub0 + Uwca0
n_from_reload = 0
n_reload.append(steps_from_0[i_goback - 1])
fail_tally = 0 # reset the fail counter
else:
fail_tally += 1 # increment bead reject counter
# increment total reject counter
n_reject += 1
# revert dna coordinates
cg_dna.setCoor(np.array([(d_coor_old)]))
d_coor = np.copy(cg_dna.coor()[0]) # reset the dna coordinates
p_coor = np.copy(cg_pro.coor()[0]) # reset the protein coordinates
xyz = np.copy(vecXYZ) # reset the dna orientations
# save previous coordinates again
if not ARGS.keep_unique:
# ~~Write DCD step~~
n_written += 1
aa_all.write_dcd_step(aa_all_dcd_out, 0, n_written)
cg_dna.write_dcd_step(cg_dna_all_dcd_out, 0, n_written + 1)
cg_pro.write_dcd_step(cg_pro_all_dcd_out, 0, n_written + 1)
aa_all.close_dcd_write(aa_all_dcd_out)
os.remove(vecX_dcd_name)
os.remove(vecY_dcd_name)
os.remove(vecZ_dcd_name)
if ARGS.keep_cg_files:
cg_dna.close_dcd_write(cg_dna_dcd_out)
cg_pro.close_dcd_write(cg_pro_dcd_out)
else:
os.remove(cg_dna_pdb_name)
os.remove(cg_pro_pdb_name)
os.remove(cg_dna_dcd_name)
os.remove(cg_pro_dcd_name)
if ARGS.goback > 0:
np.savetxt(timestr + 'n_from_0.txt', steps_from_0, fmt='%d')
print "accepted %d moves" % n_accept
print "rejected %d moves" % n_reject
# print n_reload
# print steps_from_0
return (rg, Uel_kCpM, Uel, Uwca, Ub)
def dna_mc_save_info(ARGS,
cg_dna,
aa_dna,
cg_pro,
aa_pro,
vecXYZ,
lp,
trialbeads,
beadgroups,
group_masks,
all_beads,
dna_bead_masks,
aa_pgroup_masks,
cg_pgroup_masks,
all_proteins,
aa_all,
aa_pro_mask,
aa_dna_mask,
bp_per_bead,
dna_type='b'):
'''
this function perform nsteps Monte-Carlo moves on the cg_dna
'''
timestr = time.strftime("_%y%m%d_%H%M%S") # prefix for output files
all_dcd_name = ARGS.pdb[:-4] + timestr + '.dcd'
aa_all_dcd_out = aa_all.open_dcd_write(all_dcd_name)
if False:
aa_all.send_coordinates_to_vmd(2222, 0)
# create the coarse-grained DNA and protein dcd and pdb files
cg_dna_dcd_name = 'cg_dna' + timestr + '.dcd'
cg_pro_dcd_name = 'cg_pro' + timestr + '.dcd'
cg_dna_dcd_out = cg_dna.open_dcd_write(cg_dna_dcd_name)
cg_pro_dcd_out = cg_pro.open_dcd_write(cg_pro_dcd_name)
cg_dna.write_dcd_step(cg_dna_dcd_out, 0, 1)
cg_pro.write_dcd_step(cg_pro_dcd_out, 0, 1)
cg_dna_pdb_name = 'cg_dna' + timestr + '.pdb'
cg_pro_pdb_name = 'cg_pro' + timestr + '.pdb'
cg_dna.write_pdb(cg_dna_pdb_name, 0, 'w')
cg_pro.write_pdb(cg_pro_pdb_name, 0, 'w')
# create a dummy sasmol object for the 3 orientation vectors for each bead
# will write these out to dcd files to store the coordinates along the way
vecX_mol = sasmol.SasMol(0)
vecY_mol = sasmol.SasMol(0)
vecZ_mol = sasmol.SasMol(0)
error, mask = cg_dna.get_subset_mask('(all)')
error = cg_dna.copy_molecule_using_mask(vecX_mol, mask, 0)
error = cg_dna.copy_molecule_using_mask(vecY_mol, mask, 0)
error = cg_dna.copy_molecule_using_mask(vecZ_mol, mask, 0)
# the np.array recast these so they
vecX_mol.setCoor(np.array([vecXYZ[0]]))
vecY_mol.setCoor(np.array([vecXYZ[1]])) # do not update with vecXYZ
vecZ_mol.setCoor(np.array([vecXYZ[2]]))
vecX_dcd_name = 'vecX' + timestr + '.dcd'
vecY_dcd_name = 'vecY' + timestr + '.dcd'
vecZ_dcd_name = 'vecZ' + timestr + '.dcd'
vecX_dcd_out = vecX_mol.open_dcd_write(vecX_dcd_name)
vecY_dcd_out = vecY_mol.open_dcd_write(vecY_dcd_name)
vecZ_dcd_out = vecZ_mol.open_dcd_write(vecZ_dcd_name)
vecX_mol.write_dcd_step(vecX_dcd_out, 0, 1)
vecY_mol.write_dcd_step(vecY_dcd_out, 0, 1)
vecZ_mol.write_dcd_step(vecZ_dcd_out, 0, 1)
# initialize variables for each run
steps_from_0 = np.zeros(ARGS.nsteps, dtype='int64')
xyz = np.copy(vecXYZ)
d_coor = np.copy(cg_dna.coor()[0]) # unique memory for each
p_coor = np.copy(cg_pro.coor()[0]) # unique memory for each
# vectors between beads u, and average distance l
(u, l) = dna_move.checkU(d_coor)
# s print "(u, l) =", (u, l) # debug info
lpl = lp / l # setup the presistence length paramater
# yet to use a, and z type dna
dna_energy_width = {'a': 0, 'b': 46., 'z': 0}
w = dna_energy_width[dna_type.lower()]
if w > l:
w = np.floor(l)
# print '~~~ %.2f > %.2f ~~~~~~~~~~~~~~~~~~~~~~~~' % (w, l)
print('>>> setting chain width (w) to %d (chain width < distance' % w,
' btwn beads)')
dna_diam = {'a': 25.5, 'b': 23.7, 'z': 18.4}
dna_bead_radius = 4.5
pro_bead_radius = 1.0 # 2A min seperation of CA atoms in database
pro_pro_test = pro_bead_radius + pro_bead_radius
dna_pro_test = dna_bead_radius + pro_bead_radius
# calculate the energy of the starting positions
wca0 = np.zeros((cg_dna.natoms(), cg_dna.natoms()))
Ub0 = dna_move.energyBend(lpl, u, l)
(Uwca0, wca0) = dna_move.f_energy_wca(w, d_coor, wca0, 0)
U_T0 = Ub0 + Uwca0
# print '(Ub0, Uwca0, Ub0/U_T0, Uwca0/U_T0) = ', (Ub0, Uwca0, Ub0/U_T0,
# Uwca0/U_T0)
n_accept = 0 # total times configuration was accepted
n_reject = 0 # total times configuration was rejected
n_written = 0 # total times dcd write has been called
fail_tally = 0 # number of times failed for particular iteration
n_from_reload = 0 # number of stps since last reload
n_reload = [0] # listt containing the i_goback values
# this should not actually be >=, come back to this
assert np.size(ARGS.theta_max) - 1 >= np.max(beadgroups), (
'each group needs its own theta_max: %d < %d' %
(np.size(ARGS.theta_max) - 1, np.max(beadgroups)))
rg_old = cg_dna.calcrg(0)
rg = np.zeros(ARGS.nsteps)
Uel_kCpM = np.zeros(ARGS.nsteps)
Uel = np.zeros(ARGS.nsteps)
Uwca = np.zeros(ARGS.nsteps)
Ub = np.zeros(ARGS.nsteps)
# Main MC loop #
while n_accept < ARGS.nsteps:
# Choose a bead to rotate
trial_bead = trialbeads[int((trialbeads.size) * np.random.random())]
# Determine rotation to perform
theta_max = ARGS.theta_max[beadgroups[trial_bead]]
# option to scale thetaZ separatly
thetaZ_max = 0 * np.float(theta_max)
# thetaZ_max = np.float(theta_max) # option to scale thetaZ separatly
thetaZ = 2 * thetaZ_max * np.random.random() - thetaZ_max
thetaX = 2 * theta_max * np.random.random() - theta_max
thetaY = 2 * theta_max * np.random.random() - theta_max
thetaXYZ = [
thetaX / ARGS.n_soft, thetaY / ARGS.n_soft, thetaZ / ARGS.n_soft
]
# print theta_max, thetaXYZ
if len(group_masks) == 0 or beadgroups[trial_bead] == len(group_masks):
# Only DNA will be moving, create place-holder dummy coordinates
p_coor_rot = np.zeros((0, 3))
else:
p_mask = group_masks[beadgroups[trial_bead]]
p_ind_rot = mask2ind(p_mask)
p_ind_fix = mask2ind(-(p_mask - 1))
p_coor_rot = p_coor[p_ind_rot]
p_coor_fix = p_coor[p_ind_fix]
# generate a newly rotated model
(d_coor[trial_bead:], xyz[:, trial_bead:],
p_coor_rot) = dna_move.beadRotate(d_coor[trial_bead - 1:],
xyz[:, trial_bead - 1:], thetaXYZ,
ARGS.n_soft, p_coor_rot)
# store the rotated protein coordinates
if beadgroups[trial_bead] < len(group_masks):
p_coor[p_ind_rot] = p_coor_rot
# verify the Rg_new < Rg_old * 1.01
d_coor_old = np.copy(cg_dna.coor()[0])
cg_dna.setCoor(np.array([(d_coor)])) # update dna coordinates
rg_new = cg_dna.calcrg(0)
rg_pass = True
if rg_pass:
# calculate the change in energy (dU) and the boltzman factor (p)
(u, l) = dna_move.checkU(d_coor)
Ub1 = dna_move.energyBend(lpl, u, l)
# ~~~~ DNA interaction energy ~~~~~~#
(Uwca1, wca1) = dna_move.f_energy_wca(w, d_coor, wca0, trial_bead)
U_T1 = Ub1 + Uwca1
dU = U_T1 - U_T0
with warnings.catch_warnings():
warnings.filterwarnings('error') # need this for np warnings
try:
p = np.exp(-dU)
except Warning:
if dU > 99:
p = 0
# s print 'energy was large, setting probability to 0'
elif dU < 0:
p = 1
# s print 'energy was negative, setting probability to
# 1'
else:
print 'Warning: ~~> unclear OverflowError <~~ dU = ', dU
print 'not sure where the error originated from'
test = np.random.random()
if p <= test:
dna_pass = False
# print 'step failed because of DNA energy'
else:
dna_pass = True
# now check for collisions protein involved collisions
if len(p_coor_rot) > 0: # only if proteins were rotated
# ~~~~ Check for overlap, DNA-protein or protein-protein ~~~~~~#
d_coor_fix = d_coor[trial_bead:]
d_coor_rot = d_coor[:trial_bead]
# check for protein-protein overlap
if 1 == f_overlap2(p_coor_rot, p_coor_fix, pro_pro_test):
print 'Protein-Protein'
# print 'collision, set p=0'
collisionless = False
# print 'currently ignoring DNA-protein overlap'
# check for DNA-protein overlap
elif 1 == f_overlap2(p_coor_rot, d_coor_fix, dna_pro_test):
print 'Potein-DNA (rot-fix)'
# print 'collision, set p=0'
collisionless = False
print 'ignoring this for now'
elif 1 == f_overlap2(p_coor_fix, d_coor_rot, dna_pro_test):
print 'Potein-DNA (fix-rot)'
# print 'collision, set p=0'
collisionless = False
else: # passed all collision tests
collisionless = True
if not collisionless:
print 'failed because of collision'
# there are no proteins rotated -> no possible collisions
else:
collisionless = True
if rg_pass and dna_pass and collisionless:
rg_old = rg_new
n_from_reload += 1
steps_from_0[n_accept] = n_from_reload + n_reload[-1]
# calculate the electrostatic energy of this configuration
charge = bp_per_bead * 2 # in units of C (2C per bp)
# These are kinda random...
switchd = 200
nbcutoff = 350
e = 78.54 # dielectric constant for pure water
# e = 1 # dielectric constant for vacuum
# (Uel_kCpM1, Uel1) = coulomb.coulomb(cg_dna.coor(),
# charge, e, ARGS.temperature, switchd, nbcutoff)
ld = 9.61 # debye screening constant in Angstroms
(Uel_kCpM1, Uel1) = coulomb.screen_coulomb(cg_dna.coor(), charge,
e, ARGS.temperature, ld,
switchd, nbcutoff)
# store the energies for analysis
rg[n_accept] = rg_new
Uel_kCpM[n_accept] = Uel_kCpM1
Uel[n_accept] = Uel1
Uwca[n_accept] = Uwca1
Ub[n_accept] = Ub1
n_accept += 1 # increment accept counter
# cg_dna.setCoor(d_coor) # <-- DO NOT use setCoor, want uniuqe mem
# cg_pro.setCoor(p_coor) # <-- DO NOT use setCoor, want uniuqe mem
cg_pro.setCoor(np.array([(p_coor)])) # update protein coordinates
vecXYZ = np.copy(xyz) # update dna orientations
vecX_mol.setCoor(np.array([vecXYZ[0]])) # independent of vecXYZ[0]
vecY_mol.setCoor(np.array([vecXYZ[1]])) # independent of vecXYZ[1]
vecZ_mol.setCoor(np.array([vecXYZ[2]])) # independent of vecXYZ[2]
wca0 = np.copy(wca1) # update DNA WCA energy
U_T0 = U_T1 # update total energy
# print output regarding trial
print "trial_bead(%3d) = %2d\t failed attempts = %2d" % (
n_accept, trial_bead, fail_tally)
fail_tally = 0 # reset fail_tally
# print out the Rg
print 'Rg = ', cg_dna.calcrg(0)
# write out the accepted configuration for go-back use
if ARGS.goback > 0:
# these are incremented by one because the original coordinates
# are saved (that is not the case for aa_all)
cg_dna.write_dcd_step(cg_dna_dcd_out, 0, n_written + 1)
cg_pro.write_dcd_step(cg_pro_dcd_out, 0, n_written + 1)
vecX_mol.write_dcd_step(vecX_dcd_out, 0, n_written + 1)
vecY_mol.write_dcd_step(vecY_dcd_out, 0, n_written + 1)
vecZ_mol.write_dcd_step(vecZ_dcd_out, 0, n_written + 1)
# recover an all atom representation and save coordinates to a dcd
# this requires re-inserting the aa-coordinates which takes added
# time so only do when designated
if 0 == n_accept % ARGS.n_dcd_write:
# ~~recover aa-DNA~~
error = dna_move.recover_aaDNA_model(cg_dna, aa_dna, vecXYZ,
all_beads, dna_bead_masks)
# ~~recover aa-Protein~~
dna_move.recover_aaPro_model(aa_pgroup_masks, cg_pgroup_masks,
cg_pro, all_proteins, aa_pro)
# ~~Combine aa Complete Structure~~
aa_all.set_coor_using_mask(aa_pro, 0, aa_pro_mask)
aa_all.set_coor_using_mask(aa_dna, 0, aa_dna_mask)
# ~~Write DCD step~~
n_written += 1
aa_all.write_dcd_step(aa_all_dcd_out, 0, n_written)
else:
# default ARGS.goback is -1 so this returns FALSE without user
# input
if fail_tally == ARGS.goback:
i_goback = rewind(ARGS, n_accept, cg_dna_dcd_name, cg_dna,
cg_pro_dcd_name, cg_pro, vecX_dcd_name,
vecX_mol, vecY_mol, vecY_dcd_name, vecZ_mol,
vecZ_dcd_name, vecXYZ)
# revert dna coordinates
cg_dna.setCoor(np.array([(d_coor_old)]))
d_coor = np.copy(cg_dna.coor()[0]) # reset the dna coordinates
# reset the reference energy
(u, l) = checkU(d_coor)
(Uwca0, wca0) = f_energy_wca(w, d_coor, wca0, 0)
Ub0 = energyBend(lpl, u, l)
U_T0 = Ub0 + Uwca0
n_from_reload = 0
n_reload.append(steps_from_0[i_goback - 1])
fail_tally = 0 # reset the fail counter
else:
fail_tally += 1 # increment bead reject counter
# increment total reject counter
n_reject += 1
# revert dna coordinates
cg_dna.setCoor(np.array([(d_coor_old)]))
d_coor = np.copy(cg_dna.coor()[0]) # reset the dna coordinates
p_coor = np.copy(cg_pro.coor()[0]) # reset the protein coordinates
xyz = np.copy(vecXYZ) # reset the dna orientations
# save previous coordinates again
if not ARGS.keep_unique:
# ~~Write DCD step~~
n_written += 1
aa_all.write_dcd_step(aa_all_dcd_out, 0, n_written)
cg_dna.write_dcd_step(cg_dna_all_dcd_out, 0, n_written + 1)
cg_pro.write_dcd_step(cg_pro_all_dcd_out, 0, n_written + 1)
aa_all.close_dcd_write(aa_all_dcd_out)
os.remove(vecX_dcd_name)
os.remove(vecY_dcd_name)
os.remove(vecZ_dcd_name)
if ARGS.keep_cg_files:
cg_dna.close_dcd_write(cg_dna_dcd_out)
cg_pro.close_dcd_write(cg_pro_dcd_out)
else:
os.remove(cg_dna_pdb_name)
os.remove(cg_pro_pdb_name)
os.remove(cg_dna_dcd_name)
os.remove(cg_pro_dcd_name)
if ARGS.goback > 0:
np.savetxt(timestr + 'n_from_0.txt', steps_from_0, fmt='%d')
print "accepted %d moves" % n_accept
print "rejected %d moves" % n_reject
# print n_reload
# print steps_from_0
return (rg, Uel_kCpM, Uel, Uwca, Ub)