code: def show_winner_matrix(self):
          
          
          if self.__ccore_som_pointer is not None:
              self._award = wrapper.som_get_awards(self.__ccore_som_pointer)
          
          (fig, ax) = plt.subplots()
          winner_matrix = [[0] * self._cols for i in range(self._rows)]
          
          for i in range(self._rows):
              for j in range(self._cols):
                  neuron_index = i * self._cols + j
                  
                  winner_matrix[i][j] = self._award[neuron_index]
                  ax.text(i, j, str(winner_matrix[i][j]), va='center', ha='center')
          
          ax.imshow(winner_matrix, cmap = plt.get_cmap('cool'), interpolation='none')
          ax.grid(True)
          
          plt.title("Winner Matrix")
          plt.show()
docs: !
          @brief Show winner matrix where each element corresponds to neuron and value represents
                 amount of won objects from input dataspace at the last training iteration.
          
          @see show_distance_matrix()