TYpe ERROR

[Wangmmstar]

When I optimize the tpd file, it keeps throwing error. ANy advice?

python scripts/optimise.py /mnt/study/mengjun/end-effector/passive-gripper/build/test1

================================================================================
ToPy problem definition (TPD) file successfully parsed.
TPD file name: /mnt/study/mengjun/end-effector/passive-gripper/build/test1 (v2007)

Domain discretisation (NUM_ELEM_X x NUM_ELEM_Y x NUM_ELEM_Z) = 60 x 77 x 66
Element type (ELEM_K) = H8
Filter radius (FILT_RAD) = 1.8
Number of iterations (NUM_ITER) = 50
Problem type (PROB_TYPE) = comp
Problem name (PROB_NAME) = test1
Damping factor (ETA) = 0.40
Passive elements (PASV_ELEM) specified
No active elements (ACTV_ELEM) specified

Iter | Obj. func. | Vol. | Change | P_FAC | Q_FAC | Ave ETA | S-V frac.

ToPy: Solution for FEA converged after 537 iterations.
Traceback (most recent call last):
File "scripts/optimise.py", line 20, in
optimise(argv[1])
File "scripts/optimise.py", line 16, in optimise
topy.optimise(t)
File "/home/niux/anaconda3/envs/topy/lib/python2.7/site-packages/topy/optimisation.py", line 67, in optimise
_optimise(topology)
File "/home/niux/anaconda3/envs/topy/lib/python2.7/site-packages/topy/optimisation.py", line 23, in _optimise
t.update_desvars_oc()
File "/home/niux/anaconda3/envs/topy/lib/python2.7/site-packages/topy/topology.py", line 535, in update_desvars_oc
pasv = np.take(idx, self.pasv) # new indices
File "/home/niux/anaconda3/envs/topy/lib/python2.7/site-packages/numpy/core/fromnumeric.py", line 189, in take
return _wrapfunc(a, 'take', indices, axis=axis, out=out, mode=mode)
File "/home/niux/anaconda3/envs/topy/lib/python2.7/site-packages/numpy/core/fromnumeric.py", line 66, in _wrapfunc
return _wrapit(obj, method, *args, **kwds)
File "/home/niux/anaconda3/envs/topy/lib/python2.7/site-packages/numpy/core/fromnumeric.py", line 46, in _wrapit
result = getattr(asarray(obj), method)(*args, **kwds)
TypeError: Cannot cast array data from dtype('float64') to dtype('int64') according to the rule 'safe'