def __init__(self,S,atomindices=None,permuteindices=None):
super(LPTraj,self).__init__(S)
aidx = list(atomindices) if atomindices != None else []
pidx = list(itertools.chain(*permuteindices)) if permuteindices != None else []
if atomindices == None:
self.TD = RMSD.TheoData(S['XYZList'])
else:
self.TD = RMSD.TheoData(S['XYZList'][:,np.array(aidx)])
target = c_xyzlist[which, :, :]
progressive = False
for i in range(1, len(xyzlist)):
if progressive:
target = c_xyzlist[i - i]
rmsd, operator = kabsch(c_xyzlist[i], target, operator=True)
c_xyzlist[i] = operator(c_xyzlist[i])
return c_xyzlist
if __name__ == '__main__':
"Some test code"
N = 40
query = np.arange(N)[:, np.newaxis] * np.random.randn(N, 3)
target = np.arange(N)[:, np.newaxis] * np.random.randn(N, 3)
dist, op = kabsch(query, target)
print('my rmsd ', dist)
from msmbuilder.metrics import RMSD
_rmsdcalc = RMSD()
t0 = RMSD.TheoData(query[np.newaxis, :, :])
t1 = RMSD.TheoData(target[np.newaxis, :, :])
print('msmbuilder rmsd', _rmsdcalc.one_to_all(t0, t1, 0)[0])
print(np.sqrt(np.sum(np.square(target - op(query))) / N))
