还是求助 是程序有问题还是CAD本身问题
我写的逻辑是循环在 线段两端做ssget “C ”上下扩400 去找灰色字体①的后面高度 最后用于出表格计算高度② ，但在使用过程中发现太多线条时候会经常判断为空（如果为空我设置了默认值），我不太清楚具体是为什么。小白，这种情况一般是不是代码有问题。谢谢大家。①data:image/png;base64,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
(if (= ss1 nil) 这是判断灰字的部分感觉这里可能有问题吧
(setq lg lbh)
(progn
(setq enr (ssname ss1 0))
(setq enr_data (entget enr))
(setq lst (mapcar 'cdr (vl-remove-if-not ''((x)(= (car x) 1)) (entget enr))));从图元名中提取对应结果
(mapcar 'set '(lg ) lst)(setq nnn 1 )
(repeat (strlen lg) ;循环找x
(setq yy (substr lgnnn 1))
(if (or(= "x" yy)(= "X" yy)(= "*" yy))
(setq yyy (substr lg (1+ nnn)))
)
(setq nnn (1+ nnn)) )
(setq lg (atoi yyy))
))
有区别吗 发表于 2023-8-3 19:47
1.没错是ACAD的问题,
2.严格来说是所有需要和可视化的图形前端有人机交互操作的计算机图形软件系统的问题, ...
原来如此 感谢建议 本帖最后由 有区别吗 于 2023-8-3 19:56 编辑
1.没错是ACAD的问题,
2.严格来说是所有需要和可视化的图形前端有人机交互操作的计算机图形软件系统的问题,
3.用X选,如果速度能接受的话.
4.换高分屏.
5.用其他方式比如扩展数据来存储和读取文本
大概这样 用栏选试试 ssget之前是否 zoom 了？ 调整判断顺序，textbox求出文本的外框，判断该外框是否与线段相交，且相交符合要求。缺点是循环次数增加了。 飞雪神光 发表于 2023-8-3 19:43
ssget之前是否 zoom 了？
没有，zoom 会提高精度吗 marcoyuwen 发表于 2023-8-4 08:28
调整判断顺序，textbox求出文本的外框，判断该外框是否与线段相交，且相交符合要求。缺点是循环次数增加了 ...
这个函数还没用过 我是试试 感谢建议
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