def postpick(runinfo):
seldata = runinfo.seldata
# hack to put parent info as a silent column
if os.path.exists('gen.out') and not os.path.exists('gen.retag.out'):
add_parents('gen.out','gen.retag.out')
os.system('rm gen.out')
if not os.path.exists('sel.out'):
seedstr = ' '.join(['%d'%seldata.poolids[seed] for seed in seldata.seeds])
simlimit = runinfo.simlimit()
class EmptyClass:
def __init__(self):
pass
local_opt = EmptyClass()
local_opt.refpdb = '%s/init.pdb'%(runinfo.opt.curr)
local_opt.silent_ref = 'ref.out'
local_opt.silent_gen = 'gen.retag.out'
local_opt.silent_out = 'sel.out'
local_opt.seeds = ['%d'%seldata.poolids[seed] for seed in seldata.seeds]
local_opt.simlimit = simlimit
local_opt.dcut = runinfo.dcut
local_opt.outprefix = "iter%d"%(runinfo.it+1)
local_opt.mode = runinfo.opt.pool_update #TODO
local_opt.iha_cut = runinfo.opt.iha
if runinfo.opt.iha > 1: local_opt.iha_cut *= 0.01
local_opt.add_init_penalty = True
local_opt.iha_penalty_slope = 10.0
local_opt.preserve_nuse_sim = True
local_opt.min_reset_unused = 3
local_opt.filterscore = "score"
local_opt.verbose = False
sellog=open("sel.log",'w')
#sellog=sys.stdout
print("Call Qpool...")
Qpool.main(local_opt,out=sellog)
sellog.close()
# Reset nuse
reset = False
if runinfo.phase == 2:
reset = True
else:
cont = utils.scparse('sel.out',['nuse'])
nuses = [int(float(l[:-1].split()[1])) for l in cont[1:]]
n0 = nuses.count(0)
reset = runinfo.is_reset(n0)
if reset:
runinfo.phase += 1
cont = utils.reset_score('sel.out','nuse','0.000')
out = open('sel.out','w')
out.writelines(cont)
out.close()
runinfo.phase_update_it = runinfo.it
os.system('echo "%d %d"> PHASE'%(runinfo.phase,runinfo.phase_update_it))
os.system('touch DONE')
def run_iter(runinfo):
ngen = runinfo.ngen(runinfo.phase)
combs = make_combination(runinfo)
report_combination('combination.log', runinfo.seldata, combs)
if os.path.exists('gen.out'): #in case when terminated
ndone = len(utils.scparse('gen.out', []))
if ndone > runinfo.ngen(runinfo.phase):
return
elif os.path.exists('gen.retag.out'): #in case when terminated
ndone = len(utils.scparse('gen.retag.out', []))
if ndone > runinfo.ngen(runinfo.phase):
return
launch_job(runinfo, combs, reconstruct=runinfo.opt.reconstruct_every_iter)
os.system('rm *log')
def launch_job(runinfo, combs, reconstruct=False, mode=''):
out = open('alljobs', 'w')
itstr = 'iter_%d' % runinfo.it
ngen = runinfo.get_ngen_per_job(runinfo.phase)
cmds = []
for icomb, comb in enumerate(combs):
iseed = runinfo.seldata.poolids[comb[0]]
for k in range(ngen):
script_vars_add = ''
for i, strct in enumerate(comb):
if i == 0 and k > 0 and reconstruct: # take partial of seed if k>0
script_vars_add += ' template%d=partial.%s.cons.pdb' % (
i + 1, strct)
else:
script_vars_add += ' template%d=%s.pdb' % (i + 1, strct)
if len(comb) > 1: # cross
cmd = runinfo.get_script('cross',
runinfo.phase,
itstr,
iseed,
script_vars_add,
cstprefix=comb[0],
autocst=(runinfo.opt.cross2_autocst
and k % 2 == 1))
else: #mut
cmd = runinfo.get_script('mut',
runinfo.phase,
itstr,
iseed,
script_vars_add,
cstprefix=comb[0])
cmds.append(cmd)
out.write(cmd + '\n')
out.close()
n = 0
t0 = time.time()
while True:
dt = (time.time() - t0) / 60.0
if dt > runinfo.opt.max_min_terminate:
sys.exit(
'ERROR: jobs at iter_%d did not finish within %.1f minutes -- terminate!'
% (runinfo.it, dt))
if os.path.exists('gen.out'):
n = len(utils.scparse('gen.out', ['nuse'])) - 1
if n >= runinfo.ngen(runinfo.phase): break
os.system('echo "%s -j %d --workdir . :::: alljobs" > run.cmd' %
(PARALLEL, runinfo.opt.nproc))
os.system('%s -j %d --workdir . :::: alljobs > run.log 2> err' %
(PARALLEL, runinfo.opt.nproc))
time.sleep(5)
def run_iter_recomb(runinfo):
print("Running DL predictions for all...")
#direct call
pdbs = glob.glob('iter*.?.pdb') + glob.glob('iter*.??.pdb')
npzs = [
pdb[:-4] + '.npz' for pdb in pdbs
if os.path.exists('%s.npz' % pdb[:-4])
]
n = len(pdbs)
if len(pdbs) != len(npzs):
nproc = runinfo.opt.nproc
os.system('python %s/DeepAccNet.py -p %d ./ 1> DANmsa.log' %
(DANPATH, nproc))
all_idx = list(range(n))
logout = open('combination.log', 'w')
cross_from_DAN = recomb.find_partners.main(infolder='./',
out=open('recomb1D.txt', 'w'),
seeds=all_idx,
logout=logout)
logout.close()
# make all-to-all recomb
pdbs = ['iter%d.%d.pdb' % (runinfo.it, k) for k in range(n)]
extraargs = ' -2D sub -relax dual' # opt.recomb is for recomb suggestion for hybrid; use 2D always
if runinfo.opt.native != '':
extraargs += ' -native %s' % runinfo.opt.native
cmd = 'python %s/recomb/modeling.py %s %s -out gen.retag.out %s > recomb.log\n'
jobs = open('alljobs', 'w')
for seed in cross_from_DAN:
for partner in cross_from_DAN[seed]:
jobs.write(cmd %
(MYPATH, seed + ".pdb", partner + ".pdb", extraargs))
jobs.close()
ngen = len(pdbs) * 4
t0 = time.time()
while True:
dt = (time.time() - t0) / 60.0
if dt > runinfo.opt.max_min_terminate:
sys.exit(
'ERROR: jobs at iter_%d did not finish within %.1f minutes -- terminate!'
% (runinfo.it, dt))
if os.path.exists('gen.retag.out'):
n = len(utils.scparse('gen.retag.out', ['nuse'])) - 1
if n >= ngen: break
os.system('echo "%s -j %d --workdir . :::: alljobs" > run.cmd' %
(PARALLEL, runinfo.opt.nproc))
os.system('%s -j %d --workdir . :::: alljobs > run.log 2> err' %
(PARALLEL, runinfo.opt.nproc))
time.sleep(5)
def main(ihyb_path):
os.chdir(ihyb_path)
its = [int(l.split('/')[0].split('_')[-1]) for l in glob.glob('iter_*/ref.out')]
its.sort()
fit = its[-1]
print("Working on %s, final iteration iter_%d detected"%(ihyb_path,fit))
l = utils.scparse('iter_%d/ref.out'%fit,['Q'])[1]
maxQ = float(l.split()[-1])
# Get representative model -- since Qpool been used, model0 always has the best Q
if not os.path.exists('Qsel.pdb'):
os.system('ln -s iter_%d/iter%d.%d.pdb ./Qsel.pdb'%(fit,fit,0))
print("%s Qsel: iter%d.%d.pdb, Q=%.3f"%(ihyb_path,fit,0,maxQ))
# Average trajectory around the representative model followed by relaxation
avrg_trj()
os.chdir(CURR)
