def changeLoop(filename, loopname):
posted=request.get_json(force=True)
if posted["action"]=="change" and posted["method"]=="random":
sm=get_sm(filename)
sm.load_sampled_elems()
if loopname not in sm.bg.coords:
abort(404)
original_cg=copy.deepcopy(sm.bg)
new_filename=get_new_filename()
smCache.renameSM(filename, new_filename)
change_elem(sm, loopname)
cg=sm.bg
centroid0 = ftuv.get_vector_centroid(ftug.bg_virtual_residues(original_cg))
centroid1 = ftuv.get_vector_centroid(ftug.bg_virtual_residues(cg))
crds0 = ftuv.center_on_centroid(ftug.bg_virtual_residues(original_cg))
crds1 = ftuv.center_on_centroid(ftug.bg_virtual_residues(cg))
rot_mat = ftur.optimal_superposition(crds0, crds1)
for k in cg.coords.keys():
cg.coords[k] = (np.dot(rot_mat, cg.coords[k][0] - centroid1),
np.dot(rot_mat, cg.coords[k][1] - centroid1))
if k[0] == 's':
cg.twists[k] = (np.dot(rot_mat, cg.twists[k][0]),
np.dot(rot_mat, cg.twists[k][1]))
filename=get_new_filename()
cg.to_cg_file("user_files/"+filename)
return jsonify({"url": url_for("structure_main", filename=filename)})
else:
abort(403)
def changeLoop(filename, loopname):
posted = request.get_json(force=True)
if posted["action"] == "change" and posted["method"] == "random":
sm = get_sm(filename)
sm.load_sampled_elems()
if loopname not in sm.bg.coords:
abort(404)
original_cg = copy.deepcopy(sm.bg)
new_filename = get_new_filename()
smCache.renameSM(filename, new_filename)
change_elem(sm, loopname)
cg = sm.bg
centroid0 = ftuv.get_vector_centroid(
ftug.bg_virtual_residues(original_cg))
centroid1 = ftuv.get_vector_centroid(ftug.bg_virtual_residues(cg))
crds0 = ftuv.center_on_centroid(ftug.bg_virtual_residues(original_cg))
crds1 = ftuv.center_on_centroid(ftug.bg_virtual_residues(cg))
rot_mat = ftur.optimal_superposition(crds0, crds1)
for k in cg.coords.keys():
cg.coords[k] = (np.dot(rot_mat, cg.coords[k][0] - centroid1),
np.dot(rot_mat, cg.coords[k][1] - centroid1))
if k[0] == 's':
cg.twists[k] = (np.dot(rot_mat, cg.twists[k][0]),
np.dot(rot_mat, cg.twists[k][1]))
filename = get_new_filename()
cg.to_cg_file("user_files/" + filename)
return jsonify({"url": url_for("structure_main", filename=filename)})
else:
abort(403)
def align_cgs(cgs):
'''
Align each coarse grain RNA to the first one.
The points representing each coarse grain RNA molecule
will be the virtual residues.
@param cgs: A list of CoarseGrainRNA structures.
@return: Nothing, the cgs are modified in place
'''
centroid0 = ftuv.get_vector_centroid(ftug.bg_virtual_residues(cgs[0]))
crds0 = ftuv.center_on_centroid(ftug.bg_virtual_residues(cgs[0]))
for cg in cgs:
centroid1 = ftuv.get_vector_centroid(ftug.bg_virtual_residues(cg))
crds1 = ftuv.center_on_centroid(ftug.bg_virtual_residues(cg))
rot_mat = ftur.optimal_superposition(crds0, crds1)
for k in cg.coords.keys():
cg.coords[k] = (np.dot(rot_mat, cg.coords[k][0] - centroid1),
np.dot(rot_mat, cg.coords[k][1] - centroid1))
if k[0] == 's':
cg.twists[k] = (np.dot(rot_mat, cg.twists[k][0]),
np.dot(rot_mat, cg.twists[k][1]))
def test_center_on_centroid(self):
coords = [[0., 1., 1.], [1, 1, 1], [-1, 2, 3], [3, 0, 0], [-3, 1, 0]]
nptest.assert_almost_equal(
ftuv.center_on_centroid(np.array(coords)),
[[0, 0., 0], [1, 0, 0], [-1, 1, 2], [3, -1, -1], [-3, 0, -1]])
nptest.assert_equal(
ftuv.get_vector_centroid(ftuv.center_on_centroid(coords)),
[0, 0., 0])
def _pointwise_deviation(crds1, crds2, is_centered=False):
"""
Helper function for Kabsch RMSD
"""
if not is_centered:
crds1 = ftuv.center_on_centroid(crds1)
crds2 = ftuv.center_on_centroid(crds2)
os = optimal_superposition(crds1, crds2)
crds_aligned = np.dot(crds1, os)
diff_vecs = (crds2 - crds_aligned)
return diff_vecs
def _pointwise_deviation(crds1, crds2, is_centered=False):
"""
Helper function for Kabsch RMSD
"""
if not is_centered:
crds1 = ftuv.center_on_centroid(crds1)
crds2 = ftuv.center_on_centroid(crds2)
os = optimal_superposition(crds1, crds2)
crds_aligned = np.dot(crds1, os)
diff_vecs = (crds2 - crds_aligned)
return diff_vecs
def rmsd(crds1, crds2):
'''
Center the coordinate vectors on their centroid
and then calculate the rmsd.
'''
crds1 = ftuv.center_on_centroid(crds1)
crds2 = ftuv.center_on_centroid(crds2)
os = optimal_superposition(crds1, crds2)
crds_aligned = np.dot(crds1, os)
diff_vecs = (crds2 - crds_aligned)
vec_lengths = np.sum(diff_vecs * diff_vecs, axis=1)
return math.sqrt(sum(vec_lengths) / len(vec_lengths))
def rmsd(crds1, crds2):
'''
Center the coordinate vectors on their centroid
and then calculate the rmsd.
'''
crds1 = ftuv.center_on_centroid(crds1)
crds2 = ftuv.center_on_centroid(crds2)
os = optimal_superposition(crds1, crds2)
crds_aligned = np.dot(crds1, os)
diff_vecs = (crds2 - crds_aligned)
vec_lengths = np.sum(diff_vecs * diff_vecs, axis=1)
return math.sqrt(sum(vec_lengths) / len(vec_lengths)) #rmsd(crds1, crds2)
def prepare_pca_input(cgs):
data = []
for cg in cgs:
# reshape(-1) returns a flattened view
data.append(ftuv.center_on_centroid(
cg.get_ordered_stem_poss()).reshape(-1))
return np.array(data)
def prepare_pca_input(cgs):
data = []
for cg in cgs:
# reshape(-1) returns a flattened view
data.append(
ftuv.center_on_centroid(cg.get_ordered_stem_poss()).reshape(-1))
return np.array(data)
def centered_drmsd(crds1, crds2):
'''
Center the coordinate vectors on their centroid
and then calculate the drmsd.
'''
crds1 = ftuv.center_on_centroid(crds1)
crds2 = ftuv.center_on_centroid(crds2)
os = optimal_superposition(crds1, crds2)
crds_aligned = np.dot(crds1, os)
s2 = sum(sum((crds2 - crds_aligned) * (crds2 - crds_aligned)))
diff_vecs = (crds2 - crds_aligned)
sums = np.sum(diff_vecs * diff_vecs, axis=1)
sqrts = np.sqrt(sums)
return drmsd(crds1, crds2)
def center(self):
self._coordinates = ftuv.center_on_centroid(self._coordinates)
self.is_centered = True
def test_center_on_centroid(self):
coords = [[0., 1., 1.], [1, 1, 1], [-1, 2, 3], [3, 0, 0], [-3, 1, 0]]
nptest.assert_almost_equal(ftuv.center_on_centroid(np.array(coords)),
[[0, 0., 0], [1, 0, 0], [-1, 1, 2], [3, -1, -1], [-3, 0, -1]])
nptest.assert_equal(ftuv.get_vector_centroid(
ftuv.center_on_centroid(coords)), [0, 0., 0])
def center(self):
self._coordinates = ftuv.center_on_centroid(self._coordinates)
self.is_centered = True