def run(self):
self.br=BGrate.calcBGrate(self.dbname,20,400,T0=600.0)
self.burst=BurstSearch.findBurst(self.br,self.dbname,["All"])
self.burstSeff, self.burstFRET,self.wei,self.H,self.xedges, \
self.yedges=fretAndS.FretAndS(self.dbname,self.burst,(27,27),self.br)
#self.timer.stop()
self.viewbox.canvas.drawHist(self.H,self.xedges,self.yedges)
if self.mainui is not None:
print ("copy burst")
self.mainui.burst=copy.deepcopy(self.burst)
print(self.mainui.burst["SyncResolution"])
def main(comm, dbname, n_states, Sth):
rank = comm.Get_rank()
clsize = comm.Get_size()
#print("============size=====",clsize)
if rank == 0:
br = BGrate.calcBGrate(dbname, 20, 400)
burst = BurstSearch.findBurst(br, dbname, ["All"])
burstSeff, burstFRET, wei, H, xedges, yedges = fretAndS.FretAndS(
dbname, burst, (27, 27), br)
n_burst = len(burst["All"]['chl'])
if n_burst < clsize:
clsize = n_burst
chunkLists = list(chunks(range(n_burst), clsize))
#gsml=GS_MLE(burst,0.891)
#gsml.n_states=2
#gsml.MaxLikehood([0.3,0.7,0.2, 3,3,3, 3,3,3])
#endtime = datetime.datetime.now()
#print (endtime - starttime)
else:
burst = dict()
chunkLists = list()
clsize = comm.bcast(clsize, root=0)
burst = comm.bcast(burst, root=0)
burstIdxRange = comm.scatter(chunkLists, root=0)
#print(burstIdxRange,rank)
gsml = GS_MLE(burst, comm, burstIdxRange, Sth)
gsml.n_states = n_states
params = [0.38, 0.6, 675.0, 325.0, 3, 3, 3, 3, 3]
params = params[:n_states * n_states]
#print(params)
stop = [0]
if rank == 0:
gsml.MaxLikehood(params)
#gsml.lnLikelihood(params,stop)
else:
while stop[0] == 0:
gsml.lnLikelihood(params, stop)
return None
matP = np.empty([n, 1])
ap = 0
for i in range(n):
ap += matK[i, i]
for i in range(n):
matP[i, 0] = matK[i, i] / ap
return matP
if __name__ == '__main__':
import matplotlib
import datetime
starttime = datetime.datetime.now()
dbname = '/home/liuk/sf/oc/data/38.sqlite'
dbname = 'E:/liuk/proj/ptu/data/55.sqlite'
#dbname='E:/sf/oc/data/38.sqlite'
dbname = "E:/dbox/sf/oc/data/1min.sqlite"
br = BGrate.calcBGrate(dbname, 20, 400)
burst = BurstSearch.findBurst(br, dbname, ["All"])
burstSeff, burstFRET, wei, H, xedges, yedges = fretAndS.FretAndS(
dbname, burst, (27, 27), br)
#matplotlib.pyplot.plot(burst["All"].s)
gsml = GS_MLE(burst, 0.891)
gsml.n_states = 3
gsml.MaxLikehood([0.3, 0.7, 0.2, 3, 3, 3, 3, 3, 3])
endtime = datetime.datetime.now()
print(endtime - starttime)