class img_correlator:
    def __init__ (self,path):
        self.path = path
        self.notzero = 1
        self.results = {}
        #self.LLD = 20 # it was 200 in the past
 

    def submit_correlator_jobs(self):
        filenames = os.listdir(self.path)          
        for filename in filenames: 

                  self.correlator_2D(filename)


    def correlator_2D(self, fina):
 
        f_id = open(os.path.join(self.path, fina), 'r')
        data = np.zeros((self.ncols, self.nrows, self.nframes)) # (130,134,500)

        for i in range(self.nframes):
            data[:,:,i] = np.load(f_id)
            data[:,:,i] = data[:,:,i]/ self.monitor[i]
            self.log('Frame ' + str(i) + ' was normalized by ' + str(self.monitor[i]))  
            data[:,:,i][data[:,:,i]<(self.LLD)] = self.notzero
    
        f_id.close()
        s = data.shape
        self.tau = ... tau = [1,2,3,4,5,6,7,8,9,10,12,14,16,20]
       ...

        IP = np.zeros(s,np.float64)
        IF = np.zeros_like(IP)
        G2 = np.zeros_like(IP)
        counter = np.zeros_like(self.tau)

        for t in range(len(self.tau)):
            delta = self.tau[t]
            for i in range(data.shape[2]-delta):

                if (self.monitor[i] >= self.treshold) and (self.monitor[i + delta] >= self.treshold) and (self.monitor[i] <= self.treshold_up) and (self.monitor[i + delta] <= self.treshold_up):                                                                   

                    np.add(G2[:,:,t],np.multiply(data[:,:,i], data[:,:,i+delta]),G2[:,:,t])
                    np.add(IP[:,:,t],data[:,:,i],IP[:,:,t])
                    np.add(IF[:,:,t],data[:,:,i+delta],IF[:,:,t])
                    counter[t] += 1
       ...

        to_be_deleted = []
        for i in range(0,len(self.tau)):
            if counter[i] == 0:
                to_be_deleted.append(i)
        self.tau = np.delete(self.tau,to_be_deleted)
        print "tbd = ", to_be_deleted
        counter = np.delete(counter, to_be_deleted) 
        G2 = np.delete(G2,to_be_deleted, axis = 2)
        IP = np.delete(IP,to_be_deleted, axis = 2)
        IF = np.delete(IF,to_be_deleted, axis = 2)
        for i in range(0,len(self.tau)):
            G2[:,:,i] = G2[:,:,i]/counter[i]
            IP[:,:,i] = IP[:,:,i]/counter[i]
            IF[:,:,i] = IF[:,:,i]/counter[i]
            IP[:,:,i][IP[:,:,i] < self.notzero]  = self.notzero
            IF[:,:,i][IF[:,:,i] < self.notzero]  = self.notzero
       ...

        f_id = open(path_G2, 'w')  
        for i in range(G2.shape[2]):   
            np.save(f_id, G2[:,:,i])
        f_id.close()

        f_id = open(path_IP, 'w') 
        for i in range(IP.shape[2]):   
            np.save(f_id, IP[:,:,i])
        f_id.close()

        f_id = open(path_IF, 'w') 
        for i in range(IF.shape[2]):   
            np.save(f_id, IF[:,:,i])
        f_id.close()