def replace_tail(sasmol, basis_to_python):
# mv_A_to_E()
mono_file = '../../1KX5_tailfold/1KX5tailfold_167bp.pdb'
ncp = sasmol.SasMol(0)
ncp.read_pdb(mono_file)
replace_basis = basis_to_python.parse_basis('chain E and resid < 40')
error, replace_mask = ncp.get_subset_mask(replace_basis)
print sum(replace_mask)
histone_file = '1KX5tailfold_A2E_2.pdb'
new_histone = sasmol.SasMol(0)
new_histone.read_pdb(histone_file)
print new_histone.coor().shape
part_histone = sasmol.SasMol(0)
part_basis = basis_to_python.parse_basis('resid < 40')
error, part_mask = new_histone.get_subset_mask(part_basis)
new_histone.copy_molecule_using_mask(part_histone, part_mask, 0)
ncp.set_coor_using_mask(part_histone, 0, replace_mask)
ncp.write_pdb('1KX5tailfold_fxd2.pdb', 0, 'w')
def replace_tail(sasmol, basis_to_python):
# mv_A_to_E()
mono_file = '../../1KX5_tailfold/1KX5tailfold_167bp.pdb'
ncp = sasmol.SasMol(0)
ncp.read_pdb(mono_file)
replace_basis = basis_to_python.parse_basis('chain E and resid < 40')
error, replace_mask = ncp.get_subset_mask(replace_basis)
print sum(replace_mask)
histone_file = '1KX5tailfold_A2E_2.pdb'
new_histone = sasmol.SasMol(0)
new_histone.read_pdb(histone_file)
print new_histone.coor().shape
part_histone = sasmol.SasMol(0)
part_basis = basis_to_python.parse_basis('resid < 40')
error, part_mask = new_histone.get_subset_mask(part_basis)
new_histone.copy_molecule_using_mask(part_histone, part_mask, 0)
ncp.set_coor_using_mask(part_histone, 0, replace_mask)
ncp.write_pdb('1KX5tailfold_fxd2.pdb', 0, 'w')
def get_tetramer_axes(pdb, ncp_dna_resids, dna_ids, ncp_dyad_resids,
ncp_ref_atom_resids, array=None):
pkl_file = pdb[:-3] + 'pkl'
try:
pkl_in = open(pkl_file, 'rb')
load_masks = True
all_ncp_bases = pickle.load(pkl_in)
all_ncp_masks = pickle.load(pkl_in)
all_dyad_bases = pickle.load(pkl_in)
all_dyad_masks = pickle.load(pkl_in)
all_ref_atom_masks = pickle.load(pkl_in)
all_ncp_origins = pickle.load(pkl_in)
all_ncp_axes = pickle.load(pkl_in)
all_ncp_opt_params = pickle.load(pkl_in)
all_ncp_dyad_mol = pickle.load(pkl_in)
all_ncp_plot_vars = pickle.load(pkl_in)
pkl_in.close()
print 'using masks from: %s' % pkl_file
except:
if 'load_masks' in locals():
pkl_in.close()
load_masks = False
n_ncps = len(ncp_dna_resids)
all_ncp_bases = [None] * n_ncps
all_ncp_masks = [None] * n_ncps
all_dyad_bases = [None] * n_ncps
all_dyad_masks = [None] * n_ncps
all_ref_atom_masks = [None] * n_ncps
all_ncp_origins = [None] * n_ncps
all_ncp_axes = [None] * n_ncps
all_ncp_opt_params = [None] * n_ncps
all_ncp_dyad_mol = [None] * n_ncps
all_ncp_plot_vars = [None] * n_ncps
print 'creating masks from input variables'
# check if pdb is a filename or a sasmol object
if not array:
array = sasmol.SasMol(0)
array.read_pdb(pdb)
# # re-orient the array
# coor = array.coor()
# coor[0] = geometry.transform_coor(coor[0], np.array([1, 0, 0]),
# np.array([0, 0, 0]))
# array.setCoor(coor)
# array.write_pdb('gH5c11_r.pdb', 0, 'w')
for (i, resids) in enumerate(ncp_dna_resids):
print 'fitting NCP %d' % (i + 1)
if load_masks:
ncp_mask = all_ncp_masks[i]
dyad_mask = all_dyad_masks[i]
ncp_opt_params = all_ncp_opt_params[i]
ref_atom_mask = all_ref_atom_masks[i]
else:
ncp_basis_vmd = ("((segname %s and resid >= %d and resid <= %d) or"
" (segname %s and resid <= %d and resid >= %d) ) "
"and name C1' "
% (dna_ids[i][0], resids[0, 0], resids[1, 0],
dna_ids[i][1], resids[0, 1], resids[1, 1]))
ncp_basis = basis_to_python.parse_basis(ncp_basis_vmd)
error, ncp_mask = array.get_subset_mask(ncp_basis)
assert not error, error
dyad_basis = ('( segname[i] == "%s" and resid[i] == %d ) or'
'( segname[i] == "%s" and resid[i] == %d )'
% (dna_ids[i][0], ncp_dyad_resids[i][0],
dna_ids[i][1], ncp_dyad_resids[i][1]))
error, dyad_mask = array.get_subset_mask(dyad_basis)
assert not error, error
ref_atom_basis_vmd = ("(segname %s and resid %d and name C1\')" %
(dna_ids[i][0], ncp_ref_atom_resids[i]))
ref_atom_basis = basis_to_python.parse_basis(ref_atom_basis_vmd)
error, ref_atom_mask = array.get_subset_mask(ref_atom_basis)
assert not error, error
ncp_opt_params = None
all_ncp_bases[i] = ncp_basis
all_ncp_masks[i] = ncp_mask
all_dyad_bases[i] = dyad_basis
all_dyad_masks[i] = dyad_mask
all_ref_atom_masks[i] = ref_atom_mask
debug = not load_masks
(ncp_origin, ncp_axes, ncp_opt_params, ncp_dyad_mol, ncp_plot_vars
) = geometry.get_ncp_origin_and_axes(ncp_mask, dyad_mask, dna_ids[i],
array, ref_atom_mask, debug=debug,
prev_opt_params=ncp_opt_params)
# store all the variables for debug purposes
all_ncp_origins[i] = ncp_origin
all_ncp_axes[i] = ncp_axes
all_ncp_opt_params[i] = ncp_opt_params
all_ncp_dyad_mol[i] = ncp_dyad_mol
all_ncp_plot_vars[i] = ncp_plot_vars
if not load_masks:
print 'saving masks and other results to: %s' % pkl_file
pkl_out = open(pkl_file, 'wb')
pickle.dump(all_ncp_bases, pkl_out, -1)
pickle.dump(all_ncp_masks, pkl_out, -1)
pickle.dump(all_dyad_bases, pkl_out, -1)
pickle.dump(all_dyad_masks, pkl_out, -1)
pickle.dump(all_ref_atom_masks, pkl_out, -1)
pickle.dump(all_ncp_origins, pkl_out, -1)
pickle.dump(all_ncp_axes, pkl_out, -1)
pickle.dump(all_ncp_opt_params, pkl_out, -1)
pickle.dump(all_ncp_dyad_mol, pkl_out, -1)
pickle.dump(all_ncp_plot_vars, pkl_out, -1)
pkl_out.close()
return all_ncp_plot_vars, all_ncp_axes, all_ncp_origins
def main(inputs):
run_name = inputs.run_name
dcd_name = inputs.dcd_name
dcd_path = inputs.dcd_path
pdb_name = inputs.pdb_name
pdb_path = inputs.pdb_path
foxs_exe = inputs.foxs_exe
try:
max_q = inputs.max_q
except:
max_q = 0.2
try:
num_points = inputs.num_points
except:
num_points = 50
try:
basis = inputs.basis
except:
basis = 'all'
# n_cpus = inputs.n_cpus # not fully implemented for parallel
n_cpus = 1
pdb_full_name = inputs.pdb_full_name = op.join(pdb_path, pdb_name)
dcd_full_name = inputs.dcd_full_name = op.join(dcd_path, dcd_name)
# check the input
assert op.exists(dcd_full_name), 'ERROR: no such file "%s"' % dcd_full_name
assert op.exists(pdb_full_name), 'ERROR: no such file "%s"' % pdb_full_name
assert op.exists(foxs_exe), 'ERROR: no such file "%s"' % foxs_exe
foxs_path = inputs.foxs_path = op.join(run_name, 'foxs')
if op.exists(foxs_path):
print 'WARNING: run folder exists (%s), moving it\n' % foxs_path
append_bk(foxs_path)
else:
print 'created foxs output folder: %s' % foxs_path
mkdir_p(foxs_path)
# run foxs instance on each folder
py_basis = b2p.parse_basis(basis)
# split the dcd into subfolders
sub_dirs, sub_dcd_names, first_last = split_dcd(pdb_full_name,
dcd_full_name, n_cpus,
foxs_path)
processes = []
if n_cpus > 1:
for cpu in xrange(n_cpus): # setup the processes
foxs_args = (sub_dirs[cpu], sub_dcd_names[cpu], first_last[cpu],
pdb_full_name, foxs_exe, py_basis, max_q, num_points)
processes.append(mp.Process(target=foxs, args=foxs_args))
for p in processes: # start the processes
p.start()
for p in processes: # exit the completed processes
p.join()
else:
foxs(sub_dirs[0], sub_dcd_names[0], first_last[0], pdb_full_name,
foxs_exe, py_basis, max_q, num_points)
print 'finished %d foxs calculations\n' % first_last[-1][1]
def main(inputs):
run_name = inputs.run_name
dcd_name = inputs.dcd_name
dcd_path = inputs.dcd_path
pdb_name = inputs.pdb_name
pdb_path = inputs.pdb_path
foxs_exe = inputs.foxs_exe
try:
max_q = inputs.max_q
except:
max_q = 0.2
try:
num_points = inputs.num_points
except:
num_points = 50
try:
basis = inputs.basis
except:
basis = 'all'
# n_cpus = inputs.n_cpus # not fully implemented for parallel
n_cpus = 1
pdb_full_name = inputs.pdb_full_name = op.join(pdb_path, pdb_name)
dcd_full_name = inputs.dcd_full_name = op.join(dcd_path, dcd_name)
# check the input
assert op.exists(dcd_full_name), 'ERROR: no such file "%s"' % dcd_full_name
assert op.exists(pdb_full_name), 'ERROR: no such file "%s"' % pdb_full_name
assert op.exists(foxs_exe), 'ERROR: no such file "%s"' % foxs_exe
foxs_path = inputs.foxs_path = op.join(run_name, 'foxs')
if op.exists(foxs_path):
print 'WARNING: run folder exists (%s), moving it\n' % foxs_path
append_bk(foxs_path)
else:
print 'created foxs output folder: %s' % foxs_path
mkdir_p(foxs_path)
# run foxs instance on each folder
py_basis = b2p.parse_basis(basis)
# split the dcd into subfolders
sub_dirs, sub_dcd_names, first_last = split_dcd(
pdb_full_name, dcd_full_name, n_cpus, foxs_path)
processes = []
if n_cpus > 1:
for cpu in xrange(n_cpus): # setup the processes
foxs_args = (sub_dirs[cpu], sub_dcd_names[cpu], first_last[cpu],
pdb_full_name, foxs_exe, py_basis, max_q, num_points)
processes.append(mp.Process(target=foxs, args=foxs_args))
for p in processes: # start the processes
p.start()
for p in processes: # exit the completed processes
p.join()
else:
foxs(sub_dirs[0], sub_dcd_names[0], first_last[0], pdb_full_name,
foxs_exe, py_basis, max_q, num_points)
print 'finished %d foxs calculations\n' % first_last[-1][1]