yupeng_dyp
发表于 2024-8-12 21:37:41
你有种再说一遍 发表于 2024-8-12 15:35
只能说你没有继续想下去,令人失望,
60ms就觉得很好?那你一次链选2ms,我也觉得不好呢,
如果是10w图元都 ...
惊佬说的对,像我这种业余用大都是解决了现有问题后就不想抽时间再去深入了,主要是没有多少精力去深入学习,除非现有方案必需要优化或是有闲暇时间才再去深入{:1_1:}
你有种再说一遍
发表于 2024-8-12 21:39:59
yupeng_dyp 发表于 2024-8-12 21:37
惊佬说的对,像我这种业余用大都是解决了现有问题后就不想抽时间再去深入了,主要是没有多少精力去深入学 ...
看下面的帖子,我有说优化方向的.
起码体会体会,感受感受...我之后再发个帖子说说具体怎么写
yupeng_dyp
发表于 2024-8-12 23:28:31
橡皮 发表于 2024-8-12 14:24
以他这个插件来说一次查询的时间和选择的线连接串连得线得数量正相关(基本就是线性关系),我推测就是简 ...
你电脑配置高不,怎么你的那么快,我自己笔记本电脑 AMD R7 5800H 16G,用你那个图查寻,那个长点的要80ms左右,速度比你慢差不多4倍
yupeng_dyp
发表于 2024-8-12 23:55:15
dcl1214 发表于 2024-8-12 15:10
既然你提到了高频查询,这就是数据库的优势了,数据库支持索引法,以及树结构查询,你要查询一根直线的关 ...
用的发的 vlx 查寻 25 楼发的那个文件,查寻他视频中那个大点的用时 380s 左右……,用四叉树他自己电脑22ms左右,我自己 80ms 左右
橡皮
发表于 2024-8-13 00:14:06
本帖最后由 橡皮 于 2024-8-13 00:16 编辑
yupeng_dyp 发表于 2024-8-12 23:28
你电脑配置高不,怎么你的那么快,我自己笔记本电脑 AMD R7 5800H 16G,用你那个图查寻,那个长点的要80m ...
可能是语言上和细节上有的差别吧,这个是C++写的,还有就是可能和CAD版本也有关系
橡皮
发表于 2024-8-13 00:40:03
本帖最后由 橡皮 于 2024-8-14 12:34 编辑
yupeng_dyp 发表于 2024-8-12 23:55
用的发的 vlx 查寻 25 楼发的那个文件,查寻他视频中那个大点的用时 380s 左右……,用四叉树他自己电脑2 ...
把插件上传一下,大伙自行测试比对一下吧。
更新一下:
1. 之前把搜索和图形颜色设置放在一块了,现在分开统计。
2. 添加了一个误差(1e-5~1)设置交互过程。
说句题外话,25的比24效率上确实高一点。
演示:
data:image/png;base64,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
说明:
1. 里边包含 2024(应该适用于ACAD 2021-2024)和2025两个版本;
2. SSG SSGet 的方式 -- 单次选择计算
3. SSG2 SSGet 方式 -- 可多次连续选择
4. TTF 四叉树 -- 可多次连续选择
yupeng_dyp
发表于 2024-8-13 11:40:11
橡皮 发表于 2024-8-13 00:40
把插件上传一下,大伙自行测试比对一下吧。
用你发的测试了一下,在我电脑上是28ms左右,我写的在80ms多点
gzxl
发表于 2024-8-13 12:21:08
本帖最后由 gzxl 于 2024-8-13 12:26 编辑
何必争论?佩服 lisp 语言敢来 c#版块争艳。
都学过 lisp,各自语言有什么长处非常清楚。
你有种再说一遍
发表于 2024-8-13 16:24:09
yupeng_dyp 发表于 2024-8-12 21:37
惊佬说的对,像我这种业余用大都是解决了现有问题后就不想抽时间再去深入了,主要是没有多少精力去深入学 ...
http://bbs.mjtd.com/thread-190913-1-1.html
优化方向放这里了
wang2006zhi
发表于 2024-8-13 19:42:49
本帖最后由 wang2006zhi 于 2024-8-13 21:11 编辑
yupeng_dyp 发表于 2024-8-11 15:34
我采用四叉树的方式19W线图元,其中构建四叉树300多毫秒,执行选择在2毫秒左右,高频查寻用四叉树还是不 ...
四叉树消耗大部分在构造上,,查找是很快的,一般采用CAD自带的SSGET(低版本视口外无视,另外SSGET无法后台处理数据)是比较快的,因为在CAD数据库中已经存在了这么一个八叉树,不需要重新构建了。。故一般高版本前台用SSGET,后台构造四叉树。。。。