假设我使用 std::vector
表示一个矩阵 foo
的值:
Suppose I'm representing a matrix foo
of values using std::vector
:
int rows = 5;
int cols = 10;
auto foo = vector<vector<double>>(rows, vector<double>(cols));
是否有一种巧妙简单的方法可以让我获得一个 vector
大小的 rows
包含 foo 的第一个列":
Is there a cleverly simple way for me to get a vector<int>
of size rows
that contains the first "column" of foo:
{foo[0][0], foo[0][1], foo[0][2], foo[0][3], foo[0][4] }
换句话说,我可以转置"foo 以使以下三件事为真:
Put another way, can I "transpose" foo so that the following three things are true:
foo_transpose.size() == cols
foo_transpose[0].size() == rows
foo_transpose[0] == {foo[0][0], foo[0][1], foo[0][2], foo[0][3], foo[0][4] }
对于表示矩阵"的替代方法,有一些很好的建议.当我使用术语矩阵"时,我只是意味着每个第二级 vector
的大小都相同.我并不是要建议我将这个数据结构用于线性代数类型的运算.我实际上确实需要一个向量向量,或者一个可以从中拉出"一维向量的数据结构,因为我有对向量进行操作的函数,例如:
There are a few good suggestions for alternative ways to represent a "matrix". When I use the term "matrix" I simply mean that each of the second level vector
's will be the same size. I don't mean to suggest that I will be using this data structure for linear algebra type operation. I actually DO need a vector of vectors, or a data structure from which you can "pull out" 1D vectors, because I have functions that operate on vectors like:
double sum(vector<double> const & v);
我打电话给:
sum(foo[0]);
只是在特殊情况下我遇到了需要做的情况:
It's just in a special case I came up to a situation that need to do:
sum({foo[0][0], foo[0][1], foo[0][2], foo[0][3], foo[0][4] };
有一个明显的 for 循环解决方案,但我一直在寻找更健壮和高效的方法.
There is an obvious for loop solution, but I was looking for something more robust and efficient.
正如我在评论中提到的,由于以下几个原因,使用 vector-of-vector 表示矩阵是不切实际的:
As I mentioned in the comments, it's not practical to represent matrices using vector-of-vector for a few reasons:
这是我创建的一个非常简单的类,它将在单个向量中保存一个 2D 矩阵.这几乎就是 MATLAB 之类的软件的工作方式……尽管进行了极大的简化.
Here is a very simple class I have created that will hold a 2D matrix in a single vector. This is pretty much how software like MATLAB does it... albeit a huge simplification.
template <class T>
class SimpleMatrix
{
public:
SimpleMatrix( int rows, int cols, const T& initVal = T() );
// Size and structure
int NumRows() const { return m_rows; }
int NumColumns() const { return m_cols; }
int NumElements() const { return m_data.size(); }
// Direct vector access and indexing
operator const vector<T>& () const { return m_data; }
int Index( int row, int col ) const { return row * m_cols + col; }
// Get a single value
T & Value( int row, int col ) { return m_data[Index(row,col)]; }
const T & Value( int row, int col ) const { return m_data[Index(row,col)]; }
T & operator[]( size_t idx ) { return m_data[idx]; }
const T & operator[]( size_t idx ) const { return m_data[idx]; }
// Simple row or column slices
vector<T> Row( int row, int colBegin = 0, int colEnd = -1 ) const;
vector<T> Column( int row, int colBegin = 0, int colEnd = -1 ) const;
private:
vector<T> StridedSlice( int start, int length, int stride ) const;
int m_rows;
int m_cols;
vector<T> m_data;
};
这个类基本上是围绕一个单一的函数——StridedSlice
.其实现是:
This class is basically sugar-coating around a single function -- StridedSlice
. The implementation of that is:
template <class T>
vector<T> SimpleMatrix<T>::StridedSlice( int start, int length, int stride ) const
{
vector<T> result;
result.reserve( length );
const T *pos = &m_data[start];
for( int i = 0; i < length; i++ ) {
result.push_back(*pos);
pos += stride;
}
return result;
}
剩下的就很简单了:
template <class T>
SimpleMatrix<T>::SimpleMatrix( int rows, int cols, const T& initVal )
: m_data( rows * cols, initVal )
, m_rows( rows )
, m_cols( cols )
{
}
template <class T>
vector<T> SimpleMatrix<T>::Row( int row, int colBegin, int colEnd ) const
{
if( colEnd < 0 ) colEnd = m_cols-1;
if( colBegin <= colEnd )
return StridedSlice( Index(row,colBegin), colEnd-colBegin+1, 1 );
else
return StridedSlice( Index(row,colBegin), colBegin-colEnd+1, -1 );
}
template <class T>
vector<T> SimpleMatrix<T>::Column( int col, int rowBegin, int rowEnd ) const
{
if( rowEnd < 0 ) rowEnd = m_rows-1;
if( rowBegin <= rowEnd )
return StridedSlice( Index(rowBegin,col), rowEnd-rowBegin+1, m_cols );
else
return StridedSlice( Index(rowBegin,col), rowBegin-rowEnd+1, -m_cols );
}
请注意,Row
和 Column
函数的设置方式使您可以轻松请求整行或整列,但功能更强大一些,因为您可以通过传递一个或两个以上的参数来分割一个范围.是的,您可以通过使起始值大于结束值来反向返回行/列.
Note that the Row
and Column
functions are set up in such a way that you can easily request an entire row or column, but are a little more powerful because you can slice a range by passing one or two more parameters. And yes, you can return the row/column in reverse by making your start value larger than your end value.
这些函数没有内置边界检查,但您可以轻松添加.
There is no bounds-checking built into these functions, but you can easily add that.
您还可以添加一些内容以将区域切片作为另一个 SimpleMatrix
返回.
You could also add something to return an area slice as another SimpleMatrix<T>
.
玩得开心.
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