def test_superposition():
n = 4
crds1 = [v3.random_vector() for i in range(n)]
random_m = v3.random_rotation()
crds2 = [v3.transform(random_m, c) for c in crds1]
rms, m = rmsd.calc_rmsd_rot(crds1, crds2)
for crd1, crd2 in zip(crds1, crds2):
assert v3.is_similar_vector(v3.transform(m, crd1), crd2)
def test_superposition():
n = 4
crds1 = [v3.random_vector() for i in range(n)]
random_m = v3.random_rotation()
crds2 = [v3.transform(random_m, c) for c in crds1]
rms, m = rmsd.calc_rmsd_rot(crds1, crds2)
for crd1, crd2 in zip(crds1, crds2):
assert v3.is_similar_vector(v3.transform(m, crd1), crd2)
def test_rmsd():
n = 4
crds1 = [v3.random_vector() for i in range(n)]
random_m = v3.random_rotation()
crds2 = [v3.transform(random_m, c) for c in crds1]
rms, m = rmsd.calc_rmsd_rot(crds1, crds2)
assert v3.is_similar_mag(0, rms)
# test the two algorithms separately
rms, m = rmsd.pyqcprot_rmsd_rot(crds1, crds2)
assert v3.is_similar_mag(0, rms)
if rmsd.is_numpy:
rms, m = rmsd.numpy_svd_rmsd_rot(crds1, crds2)
assert v3.is_similar_mag(0, rms)
def test_rmsd():
n = 4
crds1 = [v3.random_vector() for i in range(n)]
random_m = v3.random_rotation()
crds2 = [v3.transform(random_m, c) for c in crds1]
rms, m = rmsd.calc_rmsd_rot(crds1, crds2)
assert v3.is_similar_mag(0, rms)
# test the two algorithms separately
rms, m = rmsd.pyqcprot_rmsd_rot(crds1, crds2)
assert v3.is_similar_mag(0, rms)
if rmsd.is_numpy:
rms, m = rmsd.numpy_svd_rmsd_rot(crds1, crds2)
assert v3.is_similar_mag(0, rms)
def _rmsd_rot_res(self, res1, res2):
"""
RMSD of arbitrary residue lists, may be out of order or a subset
of total.
"""
assert_eq(len(res1), len(res2))
coords1 = [r.position for r in res1]
coords2 = [r.position for r in res2]
center1, coords1 = center_vlist(coords1)
center2, coords2 = center_vlist(coords2)
score, rot_matrix = rmsd.calc_rmsd_rot(coords1, coords2)
return StructuralAlignSolution(
self, score=score, rot_matrix=rot_matrix, center1=center1, center2=center2, res1=res1, res2=res2
)