glm::vec2 Projection_PointC = Point_A + glm::dot(Normal_AB, turn_Circle_Vertex.Center_Position - Point_A) * Normal_AB; 这行代码什么意思
时间: 2024-04-18 08:34:02 浏览: 25
这行代码的意思是通过点 `Point_A` 和法线向量 `Normal_AB` 来计算投影点 `Projection_PointC`。投影点是位于线段 AB 上的一个点,它到圆心位置 `turn_Circle_Vertex.Center_Position` 的向量与法线向量 `Normal_AB` 的点积乘以法线向量,然后加上点 `Point_A` 的位置。这样可以得到线段 AB 上离圆心位置最近的点。
相关问题
exp(confint(Muti_uni)) :glm.fit: fitted probabilities numerically 0 or 1 occurred
This error message is indicating that the logistic regression model is having difficulty fitting the data, resulting in probabilities that are either 0 or 1. This can occur when the model is overfitting the data, which means that it is too complex and is fitting the noise in the data rather than the underlying patterns.
One solution is to simplify the model by reducing the number of predictor variables, or by using regularization techniques such as ridge or lasso regression. It may also be helpful to examine the data and ensure that there are no outliers or other issues that could be causing the model to struggle.
glm::dvec3 头文件
根据提供的引用内容,glm::dvec3 头文件应该是 glm/glm.hpp。\[2\]在使用 glm::dvec3 类型之前,需要包含 glm/glm.hpp 头文件。
#### 引用[.reference_title]
- *1* *3* [关于 C/C++ 引入头文件的一点理解](https://blog.csdn.net/Wonz5130/article/details/83099566)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v91^control_2,239^v3^insert_chatgpt"}} ] [.reference_item]
- *2* [总结GLM库中glm::transform(位移), glm:scale(缩放), glm::rotate(旋转)](https://blog.csdn.net/sinat_36301420/article/details/89372482)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v91^control_2,239^v3^insert_chatgpt"}} ] [.reference_item]
[ .reference_list ]