def __main__():
parser = make_parser()
args = parser.parse_args()
LENGTH_OF_SMALLEST = int(args.bp)
FNAME = str(args.plyfile)
SPACERS = int(args.spacers)
overhangs = None
overhangfilename = args.overhangfile
if overhangfilename is not None:
overhangs = read_overhang_file(overhangfilename)
#breakpoint()
segs_list = segment_maker.get_segments(FNAME,
LENGTH_OF_SMALLEST,
SPACERS,
nicks=args.nicks,
overhangs=overhangs)
#now we apply the sequence optimizer.
sequence_optimizer.optimize_sequence(segs_list)
model = mrdna.SegmentModel(
segs_list,
local_twist=True,
dimensions=(5000, 5000, 5000),
)
#model.set_sequence(m13seq(),force=False)
#NUPACK add sequence here!
prefix = "DNA"
run_args = dict(
model=model,
output_name=prefix,
job_id="job-" + prefix,
directory=args.directory,
gpu=args.gpu,
minimization_output_period=int(args.output_period),
coarse_local_twist=args.coarse_local_twist,
fix_linking_number=args.fix_linking_number,
coarse_output_period=int(args.output_period),
fine_output_period=int(args.output_period),
minimization_steps=0, # int(args.minimization_steps),
coarse_steps=int(args.coarse_steps),
fine_steps=int(args.fine_steps),
backbone_scale=args.backbone_scale,
oxdna_steps=args.oxdna_steps,
oxdna_output_period=args.oxdna_output_period)
export_sequences(model, args.seqfile)
simulate(**run_args)
def __main__():
parser = make_parser()
args = parser.parse_args()
LENGTH_OF_SMALLEST = int(args.bp)
FNAME = str(args.plyfile)
SPACERS = int(args.spacers)
segs_list = segment_maker.get_segments(FNAME, LENGTH_OF_SMALLEST, SPACERS)
model = mrdna.SegmentModel(
segs_list,
local_twist=True,
dimensions=(5000, 5000, 5000),
)
#apply sequence here
model.set_sequence(m13seq(), force=False)
prefix = "DNA"
run_args = dict(
model=model,
output_name=prefix,
job_id="job-" + prefix,
directory=args.directory,
gpu=args.gpu,
minimization_output_period=int(args.output_period),
coarse_local_twist=args.coarse_local_twist,
fix_linking_number=args.fix_linking_number,
coarse_output_period=int(args.output_period),
fine_output_period=int(args.output_period),
minimization_steps=0, # int(args.minimization_steps),
coarse_steps=int(args.coarse_steps),
fine_steps=int(args.fine_steps),
backbone_scale=args.backbone_scale,
oxdna_steps=args.oxdna_steps,
oxdna_output_period=args.oxdna_output_period)
export_sequences(model, args.seqfile)
simulate(**run_args)
if type(i).__name__ != "DoubleStrandedSegment":
if i.num_nt == 7:
i.num_nt = ss2
print("ss2 sorted")
'''
if type(ss3) == type(1):
for i in model.segments:
if i.num_nt == 7:
i.num_nt = ss3
print ("ss3 sorted")
'''
run_args = dict(
model=model,
output_name="out",
directory=args.directory,
minimization_output_period=int(args.output_period),
coarse_local_twist=args.coarse_local_twist,
fix_linking_number=args.fix_linking_number,
bond_cutoff=args.coarse_bond_cutoff,
coarse_output_period=int(args.output_period),
fine_output_period=int(args.output_period),
minimization_steps=0, # int(args.minimization_steps),
coarse_steps=int(args.coarse_steps),
fine_steps=int(args.fine_steps),
backbone_scale=args.backbone_scale,
oxdna_steps=args.oxdna_steps,
oxdna_output_period=args.oxdna_output_period,
run_enrg_md=args.run_enrg_md)
simulate(**run_args)