def pdb2map_save(op):
ms = pdb2map(op)
import iomap as IM
for n in ms:
v = ms[n]
IM.map2mrc(v, op['savepath'] + '{}.mrc'.format(n))
data = {}
i = 0
for n in ms:
data[i] = {n: ms[n]}
i = i + 1
import numpy as np
np.save(op['savepath'] + 'data.npy', data)
y = packing_result['optimal_result']['y'] / 10
z = packing_result['optimal_result']['z'] / 10
print('initialization', packing_result['optimal_result']['initialization'])
x0 = np.array(packing_result['optimal_result']['initialization'][0]) / 10
y0 = np.array(packing_result['optimal_result']['initialization'][1]) / 10
z0 = np.array(packing_result['optimal_result']['initialization'][2]) / 10
box_size = packing_result['general_info']['box_size'] / 10
# merge map to hugemap, save random angle in packing_result
import map_tomo.merge_map as MM
initmap, init_angle_list = MM.merge_map(v, protein_name, x0, y0, z0,
box_size)
packmap, pack_angle_list = MM.merge_map(v, protein_name, x, y, z, box_size)
packing_result['optimal_result']['initmap_rotate_angle'] = init_angle_list
packing_result['optimal_result']['packmap_rotate_angle'] = pack_angle_list
IM.map2mrc(initmap, output['initmap']['mrc'])
IM.map2mrc(packmap, output['packmap']['mrc'])
# save packing info
with open(output['json']['pack'], 'w') as f:
json.dump(packing_result, f, cls=MM.NumpyEncoder)
# trim hugemap
trim_initmap = trim_margin(initmap)
trim_packmap = trim_margin(packmap)
print('initmap shape', initmap.shape)
print('trimmed shape', trim_initmap.shape)
print('packmap shape', packmap.shape)
print('trimmed shape', trim_packmap.shape)
IM.map2mrc(trim_initmap, output['initmap']['trim'])
IM.map2mrc(trim_packmap, output['packmap']['trim'])
op = {
'model': {
'missing_wedge_angle': 30,
'SNR': 0.4
},
'ctf': {
'pix_size': 1.0,
'Dz': -5.0,
'voltage': 300,
'Cs': 2.0,
'sigma': 0.4
}
}
def map2tomo(map1, op):
vb = TSRSC.do_reconstruction(map1, op, verbose=True)
# vb = td(map1, op, verbose=True)
print('vb', 'mean', vb.mean(), 'std', vb.std(), 'var', vb.var())
return vb
if __name__ == '__main__':
import iomap as IM
packmap = IM.readMrcMap('../IOfile/packmap/mrc/packmap1.mrc')
vb = map2tomo(packmap, op)
IM.map2mrc(vb, '../IOfile/tomo/mrc/tomo_SNR04.mrc')
IM.map2png(vb, '../IOfile/tomo/png/tomo_SNR04.png')
import aitom.structure.pdb.situs_pdb2vol__batch as TSPS
ms = TSPS.batch_processing(op)
# use resize_center_batch_dict() to change maps into same size
ms = {_: ms[_][10.0][10.0]['map'] for _ in ms}
import numpy as np
for n in ms:
print(n, np.shape(ms[n]))
import tomominer.image.vol.util as TIVU
ms = TIVU.resize_center_batch_dict(vs=ms, cval=0.0)
print('#resize#')
for n in ms:
print(n, np.shape(ms[n]))
return ms
if __name__ == '__main__':
ms = pdb2map(op)
import iomap as IM
for n in ms:
v = ms[n]
IM.map2mrc(v, '../IOfile/map_single/{}.mrc'.format(n))
data = {}
i = 0
for n in ms:
data[i] = {n:ms[n]}
i = i + 1
import numpy as np
np.save('../IOfile/map_single/data.npy', data)