for(auto row: col[c] i&= ~row)

s the syntax for a range-based for loop in C++.

It allows you to iterate over a range of values, such as an array, vector, or other container.

In this case, the loop is iterating over the elements in the c-th column of a two-dimensional array or matrix called "col".

The "auto" keyword automatically deduces the type of the elements in the range, which in this case is likely a primitive data type like int or double.

The variable "row" is assigned each element in the range one at a time, and the loop body can then operate on that element.

The loop will continue until all elements in the range have been processed.

相关问题

def get_logic_pos(self,x,y): return (y-self.margin + self.cell_width//2)//self.cell_width, (x-self.margin + self.cell_width//2)//self.cell_width def judge_line(self,row,col,direct,chess_color): c = 1 for i in range(1,6): next_row, next_col = row + direct[0][0] * i, col + direct[0][1] * i if self.matrix[next_row][next_col] == chess_color: c +=1 else: break for i in range(1, 6): next_row, next_col = row + direct[1][0] * i, col + direct[1][1] * i if self.matrix[next_row][next_col] == chess_color: c +=1 else: break return c def judge(self,row,col,chess_color): for direct in [[(-1,0),(1,0)],[(0,-1),(0,1)],[(-1,1),(1,-1)],[(-1,-1),(1,1)]]: if self.judge_line(row,col,direct,chess_color) ==6: return chess_color if len(self.history) == self.n * self.n: return -1 return 0 def deal_with_judge(self, judge_result): if not judge_result: return if judge_result == 1: txt = 'Black Win' elif judge_result == 2: txt = 'White Win' elif judge_result == -1: txt = 'Draw Chess' self.gameboard.draw_box(txt) self.full_matrix(self.n) def put_chess(self,x,y): l = len(self.history) chess_color = (l+1) % 4 // 2+1 if chess_color == self.auto_color: row, col = self.AI.generate_next(self.history, 1 - len(self.history) % 2, chess_color) else: row,col = self.get_logic_pos(x,y) if self.matrix[row][col] == 0: self.history.append((row, col, chess_color)) self.matrix[row][col] = chess_color self.gameboard.drawchess(row, col, chess_color) self.gameboard.draw_now_chess(chess_color) self.deal_with_judge(self.judge(row,col,chess_color)) def full_matrix(self,n): for i in range(self.n): for j in range(self.n): self.matrix[i][j] = 1

这段代码是GameBoard类的一些额外方法。让我来逐个解释它们的功能：

1. get_logic_pos方法接受鼠标点击的屏幕坐标x和y，计算出逻辑位置（行、列）并返回。

2. judge_line方法用于判断指定位置的棋子在指定方向上是否连成一条线。它接受行、列、方向和棋子颜色作为参数，并返回连线的数量。

3. judge方法用于判断给定位置的棋子是否达成胜利条件。它接受行、列和棋子颜色作为参数，并根据棋子在水平、垂直和斜向上的连线数量判断胜负情况。

4. deal_with_judge方法根据judge方法返回的结果进行处理。如果有胜负或平局，它将在游戏板上显示相应的文本框。

5. put_chess方法用于在指定位置放置棋子。它接受鼠标点击的屏幕坐标x和y，并根据当前该轮是玩家还是AI下棋来决定棋子的颜色及位置。如果位置合法，它会更新历史记录、矩阵和游戏板的显示，并调用deal_with_judge方法判断胜负情况。

6. full_matrix方法用于将整个矩阵填充为1，表示所有位置都已经下满棋子。

这些方法似乎是一个与GameBoard类相关的游戏逻辑的一部分。

template <typename PointT> void fromPCLPointCloud2 (const pcl::PCLPointCloud2& msg, pcl::PointCloud<PointT>& cloud, const MsgFieldMap& field_map) { // Copy info fields cloud.header = msg.header; cloud.width = msg.width; cloud.height = msg.height; cloud.is_dense = msg.is_dense == 1; // Copy point data cloud.resize (msg.width * msg.height); std::uint8_t* cloud_data = reinterpret_cast<std::uint8_t*>(&cloud[0]); // Check if we can copy adjacent points in a single memcpy. We can do so if there // is exactly one field to copy and it is the same size as the source and destination // point types. if (field_map.size() == 1 && field_map[0].serialized_offset == 0 && field_map[0].struct_offset == 0 && field_map[0].size == msg.point_step && field_map[0].size == sizeof(PointT)) { const auto cloud_row_step = (sizeof (PointT) * cloud.width); const std::uint8_t* msg_data = &msg.data[0]; // Should usually be able to copy all rows at once if (msg.row_step == cloud_row_step) { memcpy (cloud_data, msg_data, msg.data.size ()); } else { for (uindex_t i = 0; i < msg.height; ++i, cloud_data += cloud_row_step, msg_data += msg.row_step) memcpy (cloud_data, msg_data, cloud_row_step); } } else { // If not, memcpy each group of contiguous fields separately for (uindex_t row = 0; row < msg.height; ++row) { const std::uint8_t* row_data = &msg.data[row * msg.row_step]; for (uindex_t col = 0; col < msg.width; ++col) { const std::uint8_t* msg_data = row_data + col * msg.point_step; for (const detail::FieldMapping& mapping : field_map) { memcpy (cloud_data + mapping.struct_offset, msg_data + mapping.serialized_offset, mapping.size); } cloud_data += sizeof (PointT); } } } }

这是一个模板函数，用于将PCLPointCloud2类型的数据转换为PointCloud<PointT>类型的点云数据。其中，PointT是点云中点的数据类型。该函数会将PCLPointCloud2中的点云数据复制到PointCloud<PointT>中。

在函数中，首先将PCLPointCloud2中的header、width、height、is_dense等信息复制到PointCloud<PointT>中。然后根据点云的大小调整PointCloud<PointT>的大小，并将数据复制到PointCloud<PointT>中。在复制数据时，先判断是否可以一次性复制整个点云，如果可以则使用memcpy函数将数据一次性复制到PointCloud<PointT>中。如果不能一次性复制，则需要分别复制每个点的数据。在复制每个点的数据时，需要遍历field_map中的每个字段，将每个字段的数据从PCLPointCloud2中复制到PointCloud<PointT>中。最后返回转换后的PointCloud<PointT>类型的点云数据。