pyclustering/nnet/sync.py
def _phase_kuramoto(self, teta, t, argv):
        """!
        @brief Returns result of phase calculation for specified oscillator in the network.
        
        @param[in] teta (double): Phase of the oscillator that is differentiated.
        @param[in] t (double): Current time of simulation.
        @param[in] argv (tuple): Index of the oscillator in the list.
        
        @return (double) New phase for specified oscillator (don't assign here).
        
        """
        
        index = argv;
        phase = 0;
        for k in range(0, self._num_osc):
            if (self.has_connection(index, k) == True):
                phase += math.sin(self._phases[k] - teta);
            
        return ( self._freq[index] + (phase * self._weight / self._num_osc) );
def _phase_kuramoto(self, teta, t, argv):
        """!
        @brief Returns result of phase calculation for specified oscillator in the network.
        
        @param[in] teta (double): Phase of the oscillator that is differentiated.
        @param[in] t (double): Current time of simulation.
        @param[in] argv (tuple): Index of the oscillator in the list.
        
        @return (double) New phase for specified oscillator (don't assign here).
        
        """
        
        index = argv;
        phase = 0;
        for k in range(0, self._num_osc):
            if (self.has_connection(index, k) == True):
                phase += math.sin(self._phases[k] - teta);
            
        return ( self._freq[index] + (phase * self._weight / self._num_osc) );
!
        @brief Returns result of phase calculation for specified oscillator in the network.
        
        @param[in] teta (double): Phase of the oscillator that is differentiated.
        @param[in] t (double): Current time of simulation.
        @param[in] argv (tuple): Index of the oscillator in the list.
        
        @return (double) New phase for specified oscillator (don't assign here).