print('z effective:', ze)
# Do Stuff
##########
# set masked pixels to negative 1
mask = params['mask'].astype(np.bool)
params['frames'] = params['frames'][params['good_frames']].astype(
np.float64)
for i in range(len(params['frames'])):
params['frames'][i][~mask] = -1
if len(params['whitefield'].shape) == 3:
for i in range(len(params['whitefield'])):
params['whitefield'][i][~mask] = -1
else:
params['whitefield'][~mask] = -1
atlas, uss, ufs = fit(params['frames'], params['whitefield'],
params['R_ss_fs'], params['o_roi'], params)
# write the result
##################
out = {'O': atlas, 'pixel_shifts': np.array([uss, ufs])}
cmdline_config_cxi_reader.write_all(params, args.filename, out)
import time
for i in range(3):
print('display: ' + params['h5_group'] + '/O')
sys.stdout.flush()
time.sleep(1)
def callback(u):
if rank == 0:
out = {'pixel_shifts': u}
cmdline_config_cxi_reader.write_all(params, args.filename, out)
print('display: ' + params['h5_group'] + '/pixel_shifts')
sys.stdout.flush()
'estimate the whitefield by taking the median value of every pixel')
params = params['make_whitefield']
return args, params
if __name__ == '__main__':
args, params = get_input()
W = np.median(params['frames'], axis=0)
st = params['sigma_t']
Ws = np.empty(params['frames'].shape, dtype=np.float)
if st is not None and st is not 0 :
for i in range(Ws.shape[0]):
i_min = max(i-st, 0)
i_max = min(i+st, Ws.shape[0])
Ws[i] = np.median(params['frames'][i_min:i_max], axis=0)
if i % 10 == 0 :
out = {'whitefield' : Ws[i]}
cmdline_config_cxi_reader.write_all(params, args.filename, out, apply_roi=False)
print('display: '+params['h5_group']+'/whitefield') ; sys.stdout.flush()
else :
Ws[:] = W
# real-time output
if rank == 0 :
out = {'whitefield' : W, 'whitefields' : Ws}
cmdline_config_cxi_reader.write_all(params, args.filename, out, apply_roi=False)
print('display: '+params['h5_group']+'/whitefield') ; sys.stdout.flush()