def test_lprmsd_5(get_fn):
t = md.load(get_fn('frame0.h5'))
t1 = md.load(get_fn('frame0.h5'))
r = md.rmsd(t, t1, 0)
a = md.lprmsd(t, t1, 0, permute_groups=[[]], superpose=True)
eq(a, r, decimal=3)
def test_lprmsd_3(get_fn):
# resolve rotation and permutation togetehr
t1 = md.load(get_fn('alanine-dipeptide-explicit.pdb'))[0]
t2 = md.load(get_fn('alanine-dipeptide-explicit.pdb'))[0]
h2o_o_indices = [a.index for a in t1.topology.atoms if a.residue.name == 'HOH' and a.element.symbol == 'O'][0:20]
h2o_h_indices = [a.index for a in t1.topology.atoms if a.residue.name == 'HOH' and a.element.symbol == 'H'][0:20]
backbone_indices = [a.index for a in t1.topology.atoms if a.element.symbol in ['C', 'N']][:5]
# scramble two groups of indices
t2.xyz[:, random.permutation(h2o_o_indices)] = t2.xyz[:, h2o_o_indices]
t2.xyz[:, random.permutation(h2o_h_indices)] = t2.xyz[:, h2o_h_indices]
# offset the backbone indices slightly
t2.xyz[:, backbone_indices] += 0.001 * random.randn(len(backbone_indices), 3)
# rotate everything
rot = rotation_matrix_from_quaternion(uniform_quaternion())
t2.xyz[0].dot(rot)
print('raw distinguishable indices', backbone_indices)
atom_indices = np.concatenate((h2o_o_indices, backbone_indices))
value = md.lprmsd(t2, t1, atom_indices=atom_indices, permute_groups=[h2o_o_indices])
t1.xyz[:, h2o_o_indices] += random.randn(len(h2o_o_indices), 3)
print('final value', value)
assert value[0] < 1e-2
def test_lprmsd_1():
# resolve a random rotation with no permutation
ref = random.randn(1, 50, 3).astype(np.float32)
mapping = np.arange(50)
rot = rotation_matrix_from_quaternion(uniform_quaternion())
new = ref[:, mapping].dot(rot)
value = lprmsd(Trajectory(xyz=new, topology=None), Trajectory(xyz=ref, topology=None), permute_groups=[[]])
assert value[0] < 1e-2
def test_lprmsd_0():
# remap a permutation of all the atoms with no rotation
ref = random.randn(1, 10, 3).astype(np.float32)
mapping = random.permutation(10)
print('true mapping', mapping)
new = ref[:, mapping]
value = lprmsd(Trajectory(xyz=new, topology=None), Trajectory(xyz=ref, topology=None))
eq(value, np.array([0.0], dtype=np.float32), decimal=3)
def test_lprmsd_2():
# resolve a random rotation with some permutation
ref = random.randn(1, 50, 3).astype(np.float32)
# first half of the atoms can permute, last 10 are fixed permutation
mapping = np.concatenate((random.permutation(10), 10 + np.arange(40)))
rot = rotation_matrix_from_quaternion(uniform_quaternion())
new = ref[:, mapping].dot(rot)
value = lprmsd(Trajectory(xyz=new, topology=None), Trajectory(xyz=ref, topology=None), permute_groups=[np.arange(10)])
assert value[0] < 1e-2
def main():
rstr = args.ref
ref = mdtraj.load(rstr)
fn = args.zf
pth = '/'.join(fn.split('/')[:-1])
# extract zip file
xtract(fn)
# easier to move into working dir
os.chdir(pth)
# set some final params
od = './relevant/'
try:
os.mkdir(od)
except OSError:
pass
rf = 'receptor.pdb'
ligf = 'lig.pdb'
og_pdbs = [f for f in os.listdir('.') if '.pdb' in f]
# pull clc config from lig 0
call_write('grep -v LIG ' + og_pdbs[0], rf)
# rewrite to dock dir in consistent format
recptr = mdtraj.load(rf)
recptr.save_pdb(od + rf)
# parse ligs out of dock pdbs
for p, pdb in enumerate(og_pdbs):
call_write('grep LIG ' + pdb, 'lig_' + str(p) + '.pdb')
# get updated list of lig pdbs
lig_pdbs = [f for f in os.listdir('.') if 'lig_' in f]
lig_pdbs.sort()
# join lig pdbs into one trj
lig_trj = mdtraj.load(lig_pdbs[0])
for lig in lig_pdbs[1:]:
l = mdtraj.load(lig)
lig_trj += l
# compare distances of ligand pdbs to reference
dists = mdtraj.lprmsd(lig_trj, ref)
# get closest 3
winnars = np.argsort(dists)[:3]
# move receptor and closest lig to dock dir
for w in winnars:
lig_trj[w].save_pdb(od + str(w) + '_' + ligf)
# write some reference info
results = open('results.dat', 'w+')
results.write('path: ' + pth + '\n')
results.write('ref: ' + rstr + '\n')
results.write('w1nn4r: ' + str(winnars) + '\n')
def test_lprmsd_4(get_fn):
t1 = md.load(get_fn('1bpi.pdb'))
t1.xyz += 0.05 * random.randn(t1.n_frames, t1.n_atoms, 3)
t2 = md.load(get_fn('1bpi.pdb'))
# some random indices
indices = random.permutation(t1.n_atoms)[:t1.n_atoms - 5]
got = md.lprmsd(t2, t1, atom_indices=indices, permute_groups=[[]])
ref = md.rmsd(t2, t1, atom_indices=indices)
eq(got, ref, decimal=3)
def test_lprmsd_null():
ref = random.randn(1, 10, 3).astype(np.float32)
new = np.copy(ref)
value = lprmsd(Trajectory(xyz=new, topology=None), Trajectory(xyz=ref, topology=None))
eq(value, np.array([0.0], dtype=np.float32), decimal=3)