code: def decomposition(self, image, x, y, n_max, beta, deltaPix, center_x=0, center_y=0):
          
          num_param = int((n_max+1)*(n_max+2)/2)
          param_list = np.zeros(num_param)
          amp_norm = 1./beta**2*deltaPix**2
          n1 = 0
          n2 = 0
          H_x, H_y = self.shapelets.pre_calc(x, y, beta, n_max, center_x, center_y)
          for i in range(num_param):
              kwargs_source_shapelet = {'center_x': center_x, 'center_y': center_y, 'n1': n1, 'n2': n2, 'beta': beta, 'amp': amp_norm}
              base = self.shapelets.function(H_x, H_y, **kwargs_source_shapelet)
              param = np.sum(image*base)
              param_list[i] = param
              if n1 == 0:
                  n1 = n2 + 1
                  n2 = 0
              else:
                  n1 -= 1
                  n2 += 1
          return param_list
docs: decomposes an image into the shapelet coefficients in same order as for the function call
          :param image:
          :param x:
          :param y:
          :param n_max:
          :param beta:
          :param center_x:
          :param center_y:
          :return: