def main_user_coordinates(filename,delta_t,arguments):
#arguments will be a nested list with the desired coordinates.
workfile = tools.readfile(filename)
geoms = tools.trajectory_extractor(filename)
internals = [ check_internal(geoms,argument) for argument in arguments ]
coordinates = zip(*internals)
times_all = tools.times(workfile ,delta_t)[0]
times_hop = tools.times(workfile ,delta_t)[1]
time_internals = zip(times_all,coordinates)
inds = [times_all.index(i) for i in times_hop]
time_internals_hop = [time_internals[j] for j in inds]
return (time_internals , time_internals_hop)
def Enepop_data(filename,time_step):
workfile = tools.readfile(filename)
ener_states = tools.just_energies(workfile)[0]
ener_hops = tools.just_energies(workfile)[1]
current_eners = tools.just_energies(workfile)[2]
populations = tools.populations(workfile)
first2pops = [[0,1.0],[0,1.0]]
allpops = [ map(str,i) for i in first2pops + populations]
times = tools.times(workfile ,time_step)[0]
timeshop = tools.times(workfile ,time_step)[1]
# Same name as the molcas .out but different extension.
fileout = os.path.splitext(filename)[0] + '.EnePop'
with open(fileout,'w') as fo:
for i ,j, k, l in zip(map(str,times),allpops,ener_states,current_eners):
fo.write("{tim} {pop} {eners} {currE} \n".format(tim=i,pop=' '.join(j) ,eners=' '.join(k), currE= l))
return
