hlchirs 发表于 2024-2-3 10:29:31

求助,关于Python(VBA)批量打印时设置的坐标点

错误现象
在CAD文件中图框的坐标点是0,0和105100,59400,设置好窗口,将其应用到布局后,在通过doc.layouts['Model'].GetWindowToPlot()获取的坐标点却是((-936363.5505367576, -141903.4767118285), (-831263.5505367576, -82503.47671182864))。
这导致无法通过代码来设置坐标点。

但是将这些图形复制到一个新建的图纸中后,设置的窗口坐标点和Python获取的坐标点是一致的,即可以通过多线段获取坐标值,自动设置打印窗口的坐标,从而使用Python中的doc.layouts['Model'].SetWindowToPlot(p1,p2)实现自动批量打印。
请问各位高手,有遇到过这种情况吗?

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查看完整版本: 求助,关于Python(VBA)批量打印时设置的坐标点