#loading data points ('N' points for each one of the 'DIM' CVs)
N=file_lines(args.INPUT)
DIM=file_cols(args.INPUT)
P1=load_data(args.INPUT,N,DIM)
dK1=[]
dK2=[]
conv_all=[]
# estimate the initial string (P2) of size Min
P2 = string_ini(P1,DIM,args.K)
Pini=string_ini(P1,DIM,args.K)
PiniT=zip(*Pini)
# maximun distances of the data to the images of the string
maxdistances=maxvec(P1,P2)
# Estimate the mean of the voronoid cells
P3, fail, free_energy, allpoints, closeP, closeI = voroid_mean(P1,P2,DIM,maxdistances,0)
#############################
if (len(args.CV2plot)==3):
converg=[]
for i in range(args.Niter):
print 'Iteration ', (i+1), 'out of ', args.Niter
# get voronoid centers
maxdistances=maxvec(P1,P3)
Pm, fail, free_energy, allpoints, closeP, closeI = voroid_mean(P1,P3,DIM,maxdistances,0)
d=np.linalg.norm(np.asarray(Pm)-np.asarray(P3))
converg.append(d)
P3=Pm
##########################
####### MAIN PROGRAM #####
##########################
sys.stdout.write("\a")
#loading the input file ('N' rows 'M' columns or colective variables...CVs)
N=file_lines(args.INPUT)
M=file_cols(args.INPUT)
P1=load_data(args.INPUT,N,M)
# estimate the initial string (P2) of size Min
P2 = string_ini(P1,M,args.Min)
Pini=string_ini(P1,M,args.Min)
PiniT=zip(*Pini)
# maximun distances of the data to the images of the string
maxdistances=maxvec(P1,P2)
# Estimate the mean of the voronoid cells
P3, fail, free_energy, allpoints, closeP, closeI = voroid_mean(P1,P2,M,maxdistances, 0)
# Reparametrization and smoothing of the centers of the voronoid cells
dist_to_X2, totalD = dm_vec(P3,args.Min)
Pin=np.asarray(P3)
Plist=reparam(Pin,M,args.Min,dist_to_X2)
#smooth
Ps = smooth_DIM(Plist,args.smooth,M)
Prep=zip(*Plist)
PinT=zip(*Pin)
PsT=zip(*Ps)
