回忆倒转 发表于 2023-3-3 09:52:16

想请教大佬们关于参照绑定和图层修改

想请教论坛里各位大佬们两个问题。

第一个是参照绑定。想快速的绑定所有参照,现在用的是命令   -xrB *data:image/png;base64,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
我想放到lsp做成拖进图里就能执行的。我用了(command "-xr" "b" "*"),这里提示-xr   b   *都是未知命令,应该怎么修改,或者是还有其他更好的方式么?

第二个问题是图层修改问题。出图的时候会需要吧一些修改指定的图层颜色,关闭指定的图层。在特性过滤器里已经建好过滤了,也有特定的图层筛选的词条,应该怎么实现这个功能。

kucha007 发表于 2023-3-3 10:31:13

lisp命令用全称xref。图层颜色特性等等可以用standard命令来检查修改(需要先准备一个标准文件)

d1742647821 发表于 2023-3-3 12:01:32

不是 b和*是未知命令,而是你的-xr是未知命令,改成-xref就好了,command里的命令要用全称

vladimir 发表于 2023-3-4 09:46:37

使用外部参照的图纸处理起来就是麻烦无比。

回忆倒转 发表于 2023-3-4 10:52:17

d1742647821 发表于 2023-3-3 12:01
不是 b和*是未知命令,而是你的-xr是未知命令,改成-xref就好了,command里的命令要用全称

感谢大佬~!

回忆倒转 发表于 2023-3-4 10:54:15

kucha007 发表于 2023-3-3 10:31
lisp命令用全称xref。图层颜色特性等等可以用standard命令来检查修改(需要先准备一个标准文件)

感谢大佬~!
页: [1]
查看完整版本: 想请教大佬们关于参照绑定和图层修改