def find_bounding_sphere(mrc, L):
v = AIF.read_mrc(mrc)
points = []
density_max = v.max()
contour_level = L * density_max
for ijk in np.ndindex(v.shape):
if v[ijk] >= contour_level:
points.append([float(ijk[0]), float(ijk[1]), float(ijk[2])])
points = np.asarray(points)
# return boundingSphere.find_min_bounding_sphere(points)
return miniball.Miniball(points)
def find_min_bounding_sphere(path, L):
v = AIF.read_mrc(path)
points = []
density_max = v.max()
contour_level = L * density_max
for ijk in np.ndindex(v.shape):
if v[ijk] >= contour_level:
points.append([float(ijk[0]), float(ijk[1]), float(ijk[2])])
R, C, Xb = exact_min_bound_sphere_3D(points)
#print(R)
#print(C)
#print(Xb)
#print(R, C, Xb)
return R, C
M = N.zeros(Rsq.shape)
M[ind] = Rsq[ind] / dif_ms[ind]
return M
else:
return Rsq
if __name__ == '__main__':
import json
import aitom.io.file as IF
import aitom.filter.gaussian as FG
with open('surface_feature__op.json') as f:
op = json.load(f)
im = IF.read_mrc(op['vol_file'])
# voxel spacing in nm unit
voxel_spacing = (im['header']['MRC']['xlen'] /
im['header']['MRC']['nx']) * 0.1
print('voxel_spacing', voxel_spacing)
v = im['value']
if 'debug' in op:
se = N.array(op['debug']['start_end'])
v = v[se[0, 0]:se[0, 1], se[1, 0]:se[1, 1], se[2, 0]:se[2, 1]]
v = v.astype(N.float)
v -= v.mean()
IF.put_mrc(v, '/tmp/v.mrc', overwrite=True)