Dot Product
These are vectors:

They can be multiplied using the "Dot Product" (also see Cross Product).
Calculating
You can calculate the Dot Product of two vectors this way:

a · b = |a| × |b| × cos(θ)
Where:
|a| is the magnitude (length) of vector a
|b| is the magnitude (length) of vector b
θ is the angle between a and b
So we multiply the length of a times the length of b, then multiply by the cosine of the angle between a and b
OR you can calculate it this way:

a · b = ax × bx + ay × by
So we multiply the x's, multiply the y's, then add.
Both methods work!
Example: Calculate the dot product of vectors a and b:

a · b = |a| × |b| × cos(θ)
a · b = 10 × 13 × cos(59.5°)
a · b = 10 × 13 × 0.5075...
a · b = 65.98... = 66 (rounded)
a · b = ax × bx + ay × by
a · b = -6 × 5 + 8 × 12
a · b = -30 + 96
a · b = 66
Both methods came up with the same result (after rounding)
Also note that we used minus 6 for ax (it is heading in the negative x-direction)
Note: you can use the Vector Calculator to help you.
Why cos(θ) ?
OK, to multiply two vectors it makes sense to multiply their lengths together but only when they point in the same direction.
So we make one "point in the same direction" as the other by multiplying by cos(θ):


We take the component of a
that lies alongside b
Like shining a light to see
where the shadow lies
THEN we multiply !
It works exactly the same if we "projected" b alongside a then multiplied:
Because it doesn't matter which order we do the multiplication:
|a| × |b| × cos(θ) = |a| × cos(θ) × |b|

Right Angles
When two vectors are at right angles to each other the dot product is zero.
Example: calculate the Dot Product for:

a · b = |a| × |b| × cos(θ)
a · b = | a| × | b| × cos(90°)
a · b = | a| × | b| × 0
a · b = 0
a · b = ax × bx + ay × by
a · b = -12 × 12 + 16 × 9
a · b = -144 + 144
a · b = 0
This can be a handy way to find out if two vectors are at right angles.
Three or More Dimensions
This all works fine in 3 (or more) dimensions, too.
And can actually be very useful!
Example: Sam has measured the end-points of two poles, and wants to know the angle between them:

We have 3 dimensions, so don't forget the z-components:
a · b = ax × bx + ay × by + az × bz
a · b = 9 × 4 + 2 × 8 + 7 × 10
a · b = 36 + 16 + 70
a · b = 122
Now for the other formula:
a · b = |a| × |b| × cos(θ)
But what is |a| ? It is the magnitude, or length, of the vector a. We can use Pythagoras:
- |a| = √(42 + 82 + 102)
- |a| = √(16 + 64 + 100)
- |a| = √180
Likewise for |b|:
- |b| = √(92 + 22 + 72)
- |b| = √(81 + 4 + 49)
- |b| = √134
And we know from the calculation above that a · b = 122, so:
a · b = |a| × |b| × cos(θ)
122 = √180 × √134 × cos(θ)
cos(θ) = 122 / (√180 × √134)
cos(θ) = 0.7855...
θ = cos -1(0.7855...) = 38.2...°
Done!
I tried a calculation like that once, but worked all in angles and distances ... it was very hard, involved lots of trigonometry, and my brain hurt. The method above is much easier.
Cross Product
The Dot Product gives a scalar (ordinary number) answer, and is sometimes called the scalar product.
But there is also the Cross Product which gives a vector as an answer, and is sometimes called the vector product.
Dot Product的更多相关文章
- [UCSD白板题] Minimum Dot Product
Problem Introduction The dot product of two sequences \(a_1,a_2,\cdots,a_n\) and \(b_1,b_2,\cdots,b_ ...
- FB面经Prepare: Dot Product
Conduct Dot Product of two large Vectors 1. two pointers 2. hashmap 3. 如果没有额外空间,如果一个很大,一个很小,适合scan小的 ...
- CUDA Samples: dot product(使用零拷贝内存)
以下CUDA sample是分别用C++和CUDA实现的点积运算code,CUDA包括普通实现和采用零拷贝内存实现两种,并对其中使用到的CUDA函数进行了解说,code参考了<GPU高性能编程C ...
- 向量点积(Dot Product),向量叉积(Cross Product)
参考的是<游戏和图形学的3D数学入门教程>,非常不错的书,推荐阅读,老外很喜欢把一个东西解释的很详细. 1.向量点积(Dot Product) 向量点积的结果有什么意义?事实上,向量的点积 ...
- CUDA Samples: Dot Product
以下CUDA sample是分别用C++和CUDA实现的两个非常大的向量实现点积操作,并对其中使用到的CUDA函数进行了解说,各个文件内容如下: common.hpp: #ifndef FBC_CUD ...
- vector - vector product
the inner product Givens two vectors \(x,y\in \mathbb{R}^n\), the quantity \(x^\top y\), sometimes c ...
- CF 405C Unusual Product(想法题)
题目链接: 传送门 Domino Effect time limit per test:1 second memory limit per test:256 megabytes Descrip ...
- Cross Product
Cross Product These are two vectors: They can be multiplied using the "Cross Product" (als ...
- 对NumPy中dot()函数的理解
今天学习到numpy基本的运算方法,遇到了一个让我比较难理解的问题.就是dot函数是如何对矩阵进行运算的. 一.dot()的使用 参考文档:https://docs.scipy.org/doc/num ...
随机推荐
- Spring in Action --- 第二章 装配Bean
Spirng配置的可选方案 在XML中进行显示配置 在Java中进行显示配置 隐式的bean发现机制和自动装配 bean装配 1. 在希望被扫描到的类上加注解 @Component 2. 基于不同的配 ...
- 何为PostgreSQL?
PostgreSQL 是以加州大学伯克利分校计算机系开发的 POSTGRES, Version 4.2 为基础的对象关系型数据库管理系统(ORDBMS).POSTGRES 领先的许多概念只是在非常迟的 ...
- linux driver module
本文将对Linux系统中的sysfs进行简单的分析,要分析sysfs就必须分析内核的driver-model(驱动模型),两者是紧密联系的.在分析过程中,本文将以platform总线和spi主控制器的 ...
- TreeSet与TreeMap的源码分析 JDK7
TreeSet存储原则是:不可重复,有序的. public TreeSet() { this(new TreeMap<E,Object>()); } public TreeSet(Comp ...
- laravel sum 多个字段
laravel中怎么实现下面的SQL select sum('profit'),sum('order_count') from pro where......; 参考 self::where('id' ...
- 服务管理--systemctl命令
摘要: systemctl 是系统服务管理器命令,它实际上将 service 和 chkconfig 这两个命令组合到一起. 任务 旧指令 新指令 使某服务自动启动 chkconfig --level ...
- Linux Yum仓库介绍及服务端及客户端配置
YUM服务器 适合在于内网使用,因为很多包需要国外的网站下载应用包,这样网络很不稳定 下载慢,所有为何不尝试搭建 自己内部的YUM服务器呢 YUM服务器搭建 一 创建yum仓库目录 #mkdir -p ...
- iOS开发之视差滚动视图
首先声明一点,由于自己iOS开发经验有限,这里给下面将要实现的效果起名叫视差滚动视图,自己也不知道是否严谨,等以后有经验了,再来更新吧. 一.需求 有的时候我们可能会有这样一种需求,在一个UITabl ...
- yii2.0 面包屑的使用
yii2中面包屑是yii2自带的小部件,类似本网站的导航栏应该就是采用面包屑来完成的 例子如下,需要引入 yii\widgets\Breadcrumbs echo Breadcrumbs::widge ...
- php,cgi,nginx关系
nginx是服务器 什么是服务器? 例如:IIS,Apache,Nginx......主要是提供网上浏览网页的服务,应用层使用HTTP协议. CGI,FastCGI CGI全称是"公共网关接 ...