Hi Pawel-
As discussed on Friday, when I tried to account for delay in injection, I got a funny output in which all of the frames were essentially identical. This does not happen when I just include the data before injection (which produces blank frames=0 until a reliable reconstruction can be generated).
This was when using the following code:
#obtain histogram dictionary:
hst = nipet.mmrhist(datain, mMRparams)
#From histogram, obtain offset in seconds:
time_offset = nipet.lm.get_time_offset(hst)
print('Time offset for start is' + str(time_offset))
#Adjust the frames getting a new frame dictionary:
fdic = nipet.mmraux.timings_from_list(dframes, offset=time_offset)
print(fdic)
#Create customised frames:
dframes_c = fdic['timings']
#not sure its needed, but insert a flag for customised dynamic reconstruction:
dframes_c[0]='fluid'
where dframes_c was passed into mmrchain instead of dframes, which was originally set to:
dframes = ['def',[4, 15], [8, 30], [9, 60], [2, 180], [8, 300]]
This was my fault. The variable hst that is the output of nipet.mmrhist seems to not be the appropriate input to mmrchain, which is what i was doing. So I have just let mmrchain generate its own histogram.
Hi Pawel- As discussed on Friday, when I tried to account for delay in injection, I got a funny output in which all of the frames were essentially identical. This does not happen when I just include the data before injection (which produces blank frames=0 until a reliable reconstruction can be generated). This was when using the following code:
where dframes_c was passed into mmrchain instead of dframes, which was originally set to:
dframes = ['def',[4, 15], [8, 30], [9, 60], [2, 180], [8, 300]]