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README
Apache-2.0

进度

多边形选多边形(blend polygons)

select_polygons_demo_0 select_polygons_demo_1

支持初始化、写入、直读 Canvas

select_points_canvas_demo

输入点、凸多边形,并显示它们

select_points_demo

额外依赖项

  1. Boost: GIL 用于读写 PNG 格式图片(已弃用)
  2. Eigen: 用于高性能线性代数计算

疑难

几何变换的实现

注意到几何变换的目的坐标是通过 $\gamma$ 函数计算出来的。除非 $\gamma$ 函数拥有反函数,否则我们无法提前预知 $C'(x, y)$ 的数据来源。又由于可以根据值变换,$\gamma$ 函数几乎不可能拥有反函数。

所以,对于坐标 $(x, y)$,我们需要具有写入任意坐标 $C'(x', y')$ 的能力,这与传统 OpenGL 的渲染管线的理念相悖。传统 OpenGL 约定,每个像素(准确地说是片元)运行着一个片元着色器(fragment shader),无论如何,数据一定被写入当前的像素中,而不能写入其他像素,故不具备“写入任意坐标”的能力。

好在现代 OpenGL 为了 GPGPU 添加了新的工具:Image。Image 就像 CUDA 中位于全局内存的数组,可以任意地读取和写入,但是操作顺序、同步、原子性等问题须由程序员负责。

目前暂定所有数据存储都使用 Image 来抽象。暂不知传统 Texture 和 Image 的性能差异(官方 Wiki 并无说明)。

注:涉及几何变换的运算还有映射聚合

切分 (Dissect) 的实现

原文称切分是针对每个非空像素点,单独挑出,形成 Canvas。我认为纯粹依照原文的概念,极难实现这一操作。首先,原文声称用 OpenGL Texture 来实现 Canvas,然而 OpenGL 支持的最大 Texture 数量十分有限(在我的机器上最多 80 个),难道切分操作不支持超过 80 个非空像素点吗?其次,一张 Canvas 的空间消耗极大。假设原文中 $S$ 的每个元素为 4 字节,则一个像素 $S^3$ 至少需要 36 字节(原文已指明还需额外的标记位,故空间消耗应更多)。假设 Canvas 的分辨率为 1024x1024,那么一张 Canvas 的空间消耗至少为 36 MB。80张这样的 Canvas 就需要 2880 MB 显存,若每张 Canvas 只有一个非空像素点,太过奢侈。第三,据我所知,OpenGL 的输出空间是不能在着色器运行时修改的,问题是我怎么知道切分操作会生成多少张 Canvas 呢,除非我两次遍历?

综上所述,切分的实现不可能是朴素的,不能照搬论文中的概念进行操作。

我目前的想法是,将切分定义为一种特殊的中间运算,定义特殊的储存格式与其运算结果对应,而不是 Canvas。副作用是,这会产生切分与后续运算的耦合性。


以下内容(除实现外)皆来自 arXiv:2004.03630 [cs]

运算符

基本运算符

几何变换

$$ C'=\mathscr{G}\gamma $$

  1. 根据坐标变换:$C'(\gamma(x, y))=C(x, y)$
  2. 根据值变换:$C'(\gamma(C(x, y)))=C(x, y)$

值变换

$$ C'=\mathscr{V}f \\ f: \mathbb{R}^{2} \times S^{3} \rightarrow S^{3} $$

根据值和坐标变换:$C'(x, y)=f(x, y, C(x, y))$

遮罩

$$ C'=\mathscr{M}M $$

若值不符合要求,则抛弃之:

$C'(x, y)=\left{\begin{array}{ll}C(x, y), & \text { if } C(x, y) \in M \\ \emptyset & \text { otherwise }\end{array}\right.$

混合

$$ C'=\mathscr{B}[\odot]\left(C_{1}, C_{2}\right)\\ \odot: S^{3} \times S^{3} \rightarrow S^{3} $$

根据两旧值产生新值:

$C'(x, y)= C_{1}(x, y) \odot C_{2}(x, y)$

切分 (Dissect)

$$ \left{C_{1}, C_{2}, \ldots, C_{n}\right}=\mathscr{D}(C) $$

每个非空像素点产生一张新 canvas:

$C_{i}\left(x', y'\right)=\left{\begin{array}{ll}C(x, y), & \text { if }\left(x', y'\right)=(x, y) \\ \emptyset & \text { otherwise }\end{array}\right.$

派生运算符

多重混合

$$ \begin{aligned} C' = & \mathscr{B}^{*}[\odot]\left(C_{1}, C_{2}, \ldots, C_{n}\right)\\ = & \mathscr{B}[\odot]\left(C_{1}, \mathscr{B}[\odot]\left(C_{2}, \mathscr{B}[\odot]\left(C_{3}, \ldots\right)\right)\right) \end{aligned} $$

映射

$$ \begin{aligned} \left{C_{1}, C_{2}, \ldots, C_{n}\right}=&\mathscr{D}^{*}\gamma\ =& \mathscr{G}\gamma

\end{aligned} $$

表达

选择查询

选点

select_points

$C_{i}(x, y)[0]=\left{\begin{array}{ll}(i d, 1,0) & \text { if }(x, y)=\left(x_{i}, y_{i}\right) \\ \emptyset & \text { otherwise }\end{array}\right.$

$C_{i}(x, y)[1]=C_{i}(x, y)[2]=\emptyset$

$\begin{aligned} C_{Q}(x, y)[0] &=C_{Q}(x, y)[1]=\emptyset \\ C_{Q}(x, y)[2] &=\left{\begin{array}{ll}(1,1,0) & \text { if }(x, y) \text { falls inside } Q \\ \emptyset & \text { otherwise }\end{array}\right.\end{aligned}$

$\mathbb{C}{\text {result }} \leftarrow \mathscr{M}\left[M{p}\right]\left(\mathscr{B}[\odot]\left(\mathbb{C}{P}, C{Q}\right)\right)$

$s_{1} \odot s_{2}=\left[\begin{array}{ccc}s_{1}[0][0] & s_{1}[0][1] & s_{1}[0][2] \\ - & \emptyset & - \\ s_{2}[2][0] & s_{2}[2][1] & s_{2}[2][2]\end{array}\right]$

$M_{p}=\left{s \in S^{3} \mid s[0] \neq \emptyset\right.$ and $\left.s[2][0]=1\right}$

选多边形

select_polygons

$\begin{aligned} C_{i}(x, y)[0] &=C_{i}(x, y)[1]=\emptyset \\ C_{i}(x, y)[2] &=\left{\begin{array}{ll}(i d, 1,0) & \text { if }(x, y) \text { falls inside } Y_{i} \\ \emptyset & \text { otherwise }\end{array}\right.\end{aligned}$

$\mathbb{C}{\text {result }} \leftarrow \mathscr{M}\left[M{y}\right]\left(\mathscr{B}[\oplus]\left(\mathbb{C}{Y}, C{Q}\right)\right)$

$s_{1} \oplus s_{2}=\left[\begin{array}{ccc}- & \emptyset & - \\ - & \emptyset & - \\ s_{1}[2][0] & s_{1}[2][1]+s_{2}[2][1] & s_{1}[2][2]\end{array}\right]$

$M_{y}=\left{s \in S^{3} \mid s[2][1]=2\right}$

连接 (Join) 查询

[TODO]

聚合 (Aggregate) 查询

SELECT COUNT (*) FROM $D_P$ WHERE Location INSIDE $Q$

$C_{\text {count }} \leftarrow \mathscr{B}^{*}[+]\left(\mathscr{G}\left[\gamma_{c}\right]\left(\mathbb{C}_{\text {result }}\right)\right)$

$\gamma_{c}: S^{3} \rightarrow \mathbb{R}^{2}: \gamma_{c}(s)=(s[2][0], 0), \forall s \in S^{3} ;$

$+: S^{3} \times S^{3} \rightarrow S^{3}$ : $$ s_{1}+s_{2}=\left[\begin{array}{ccc} 0 & s_{1}[0][1]+s_{2}[0][1] & 0 \

  • & \emptyset & - \ s_{2}[2][0] & s_{2}[2][1] & s_{2}[2][2] \end{array}\right] $$ $\mathbb{C}{\text {result }} \leftarrow \mathscr{M}\left[M{p}\right]\left(\mathscr{B}[\odot]\left(\mathbb{C}{P}, C{Q}\right)\right)$ 是选点查询的结果。是多张 canvas。

第k近邻居查询

做法:给定一个半径画圆,求出点的数量,据此二分答案。

实现注意点

  1. 对于点,需要记住精确的 location
  2. 对于多边形,需要标记像素是否在边界上
  3. 使用扩展:conservative rasterization
  4. 维护一个map,将位于边界的像素映射到原多边形(矢量形式)
  5. 用 (r,g,b,a) 来储存 canvas function
  6. 对于有洞的多边形,先绘制无洞版本,再单独绘制洞,做减法
  7. 混合 通过直接 alpha blending 两张 textures 实现
  8. 遮罩 并行地测试每个像素点。此时边界信息用于精确测试每个像素是否位于多边形边界。
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简介

Graphically Spatial Queries arXiv:2004.03630 [cs] 复现 展开 收起
C++ 等 4 种语言
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