blocks|key|4667348|text|为此，您可以使用逗号初始值设定项语法。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4667349|水平方向：|4667350|MatrixXd+C(A.rows(),+A.cols()%2BB.cols());
C+<<+A,+B;|code-block|syntax|javascript|4667351|纵向：|4667352|//+eigen+uses+provided+dimensions+in+declaration+to+determine
//+concatenation+direction
MatrixXd+D(A.rows()%2BB.rows(),+A.cols());+//+<--+D(A.rows()+%2B+B.rows(),+...)
D+<<+A,+B;+//+<--+syntax+is+the+same+for+vertical+and+horizontal+concatenation|4667353|为了提高可读性，可以使用空格设置垂直连接的格式：|4667354|D+<<+A,
+++++B;+//+<--+But+this+is+for+readability+only.+|4667355|entityMap^0|0|0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|S|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|T|8|@]|9|@]|A|$]]|$1|D|3|E|5|F|7|U|8|@]|9|@]|A|$G|H]]|$1|I|3|J|5|6|7|V|8|@]|9|@]|A|$]]|$1|K|3|L|5|F|7|W|8|@]|9|@]|A|$G|H]]|$1|M|3|N|5|6|7|X|8|@]|9|@]|A|$]]|$1|O|3|P|5|F|7|Y|8|@]|9|@]|A|$G|H]]|$1|Q|3|-4|5|6|7|Z|8|@]|9|@]|A|$]]]|R|$]]

You can use the comma initializer syntax for that.

Horizontally:

<pre><code>MatrixXd C(A.rows(), A.cols()+B.cols());
C &lt;&lt; A, B;
</code></pre>

Vertically:

<pre><code>// eigen uses provided dimensions in declaration to determine
// concatenation direction
MatrixXd D(A.rows()+B.rows(), A.cols()); // &lt;-- D(A.rows() + B.rows(), ...)
D &lt;&lt; A, B; // &lt;-- syntax is the same for vertical and horizontal concatenation
</code></pre>

For readability, one might format vertical concatenations with whitespace: 

<pre><code>D &lt;&lt; A,
 B; // &lt;-- But this is for readability only. 
</code></pre>

blocks|key|4667398|text|我有一个稍微不同的用例:垂直堆叠特征矩阵的std：：向量。下面是我如何实现一个更通用的函数。如果可以进一步改进，请让我知道：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4667399|//+matrix_eig+=+Eigen::MatrixXf+in+RowMajor+format
matrix_eig+VStack(const+std::vector<matrix_eig>+&mat_vec)+{
++assert(!mat_vec.empty());
++long+num_cols+=+mat_vec[0].cols();
++size_t+num_rows+=+0;
++for+(size_t+mat_idx+=+0;+mat_idx+<+mat_vec.size();+%2B%2Bmat_idx)+{
++++assert(mat_vec[mat_idx].cols()+==+num_cols);
++++num_rows+%2B=+mat_vec[mat_idx].rows();
++}
++matrix_eig+vstacked_mat(num_rows,+num_cols);
++size_t+row_offset+=+0;
++for+(size_t+mat_idx+=+0;+mat_idx+<+mat_vec.size();+%2B%2Bmat_idx)+{
++++long+cur_rows+=+mat_vec[mat_idx].rows();
++++vstacked_mat.middleRows(row_offset,+cur_rows)+=+mat_vec[mat_idx];
++++row_offset+%2B=++cur_rows;
++}
++return+vstacked_mat;
}|code-block|syntax|javascript|4667400|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|J|8|@]|9|@]|A|$E|F]]|$1|G|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|H|$]]

I had a slightly different use case: To vertically stack a std::vector of Eigen matrices. Here is how I implemented a function which is more general purpose. Let me know if this can be further improved:

<pre><code>// matrix_eig = Eigen::MatrixXf in RowMajor format
matrix_eig VStack(const std::vector&lt;matrix_eig&gt; &amp;mat_vec) {
 assert(!mat_vec.empty());
 long num_cols = mat_vec[0].cols();
 size_t num_rows = 0;
 for (size_t mat_idx = 0; mat_idx &lt; mat_vec.size(); ++mat_idx) {
 assert(mat_vec[mat_idx].cols() == num_cols);
 num_rows += mat_vec[mat_idx].rows();
 }
 matrix_eig vstacked_mat(num_rows, num_cols);
 size_t row_offset = 0;
 for (size_t mat_idx = 0; mat_idx &lt; mat_vec.size(); ++mat_idx) {
 long cur_rows = mat_vec[mat_idx].rows();
 vstacked_mat.middleRows(row_offset, cur_rows) = mat_vec[mat_idx];
 row_offset += cur_rows;
 }
 return vstacked_mat;
}
</code></pre>

blocks|key|161327|text|我将以类似于this+post+(连接到现有矩阵)的方式使用Eigen's+block+indexing。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|161328|块索引避免了公认方法中的方向歧义，并且语法非常紧凑。下面的代码相当于MATLAB中的C+=+cat(2,+A,+B)：|style|CODE|161329|MatrixXd+C(A.rows(),+A.cols()%2BB.cols());
C.leftCols(A.cols())+=+A;
C.rightCols(B.cols())+=+B;|code-block|syntax|javascript|161330|entityMap|0|LINK|mutability|MUTABLE|url|https://stackoverflow.com/questions/27404811/append-column-to-matrix-using-eigen-library|1|https://eigen.tuxfamily.org/dox/group__TutorialBlockOperations.html^0|6|9|0|U|M|1|0|16|G|0|0^^$0|@$1|2|3|4|5|6|7|W|8|@]|9|@$A|X|B|Y|1|Z]|$A|10|B|11|1|12]]|C|$]]|$1|D|3|E|5|6|7|13|8|@$A|14|B|15|F|G]]|9|@]|C|$]]|$1|H|3|I|5|J|7|16|8|@]|9|@]|C|$K|L]]|$1|M|3|-4|5|6|7|17|8|@]|9|@]|C|$]]]|N|$O|$5|P|Q|R|C|$S|T]]|U|$5|P|Q|R|C|$S|V]]]]

I'd use <a href="https://eigen.tuxfamily.org/dox/group__TutorialBlockOperations.html" rel="noreferrer">Eigen's block indexing</a> in a way similar to <a href="https://stackoverflow.com/questions/27404811/append-column-to-matrix-using-eigen-library">this post</a> (which concatenates to an existing matrix).

The block indexing avoids the direction ambiguity in the accepted approach, and is pretty compact syntax. The following is equivalent to <code>C = cat(2, A, B)</code> in MATLAB:

<pre><code>MatrixXd C(A.rows(), A.cols()+B.cols());
C.leftCols(A.cols()) = A;
C.rightCols(B.cols()) = B;
</code></pre>

I have two eigen matrices and I would like to concatenate them, like in matlab <code>cat(0, A, B)</code>

Is there anything equivalent in eigen?

Thanks.

Eigen how to concatenate matrix along a specific dimension?

我有两个特征矩阵，我想把它们连接起来，就像matlab中的cat(0, A, B)一样。在eigen中有没有类似的东西？谢谢。

问特征:如何沿特定维度连接矩阵？
EN

社区

活动

资源

关于

腾讯云开发者

热门产品

热门推荐

更多推荐

问特征:如何沿特定维度连接矩阵？EN

社区

活动

资源

关于

腾讯云开发者

热门产品

热门推荐

更多推荐

问特征:如何沿特定维度连接矩阵？
EN