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Clarify documentation on the restrictions of writable sparse block expressions.

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Gael Guennebaud
2016-02-03 16:08:43 +01:00
parent 64ce78c2ec
commit c85fbfd0b7
2 changed files with 58 additions and 28 deletions
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62
doc/SparseQuickReference.dox
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@@ -21,7 +21,7 @@ i.e either row major or column major. The default is column major. Most arithmet
<td> Resize/Reserve</td>
<td>
\code
sm1.resize(m,n); //Change sm1 to a m x n matrix.
sm1.resize(m,n); // Change sm1 to a m x n matrix.
sm1.reserve(nnz); // Allocate room for nnz nonzeros elements.
\endcode
</td>
@@ -151,10 +151,10 @@ It is easy to perform arithmetic operations on sparse matrices provided that the
<td> Permutation </td>
<td>
\code
perm.indices(); // Reference to the vector of indices
perm.indices(); // Reference to the vector of indices
sm1.twistedBy(perm); // Permute rows and columns
sm2 = sm1 * perm; //Permute the columns
sm2 = perm * sm1; // Permute the columns
sm2 = sm1 * perm; // Permute the columns
sm2 = perm * sm1; // Permute the columns
\endcode
</td>
<td>
@@ -181,9 +181,9 @@ sm2 = perm * sm1; // Permute the columns
\section sparseotherops Other supported operations
<table class="manual">
<tr><th>Operations</th> <th> Code </th> <th> Notes</th> </tr>
<tr><th style="min-width:initial"> Code </th> <th> Notes</th> </tr>
<tr><td colspan="2">Sub-matrices</td></tr>
<tr>
<td>Sub-matrices</td>
<td>
\code
sm1.block(startRow, startCol, rows, cols);
@@ -193,25 +193,31 @@ sm2 = perm * sm1; // Permute the columns
sm1.bottomLeftCorner( rows, cols);
sm1.bottomRightCorner( rows, cols);
\endcode
</td> <td> </td>
</td><td>
Contrary to dense matrices, here <strong>all these methods are read-only</strong>.\n
See \ref TutorialSparse_SubMatrices and below for read-write sub-matrices.
</td>
</tr>
<tr>
<td> Range </td>
<tr class="alt"><td colspan="2"> Range </td></tr>
<tr class="alt">
<td>
\code
sm1.innerVector(outer);
sm1.innerVectors(start, size);
sm1.leftCols(size);
sm2.rightCols(size);
sm1.middleRows(start, numRows);
sm1.middleCols(start, numCols);
sm1.col(j);
sm1.innerVector(outer); // RW
sm1.innerVectors(start, size); // RW
sm1.leftCols(size); // RW
sm2.rightCols(size); // RO because sm2 is row-major
sm1.middleRows(start, numRows); // RO becasue sm1 is column-major
sm1.middleCols(start, numCols); // RW
sm1.col(j); // RW
\endcode
</td>
<td>A inner vector is either a row (for row-major) or a column (for column-major). As stated earlier, the evaluation can be done in a matrix with different storage order </td>
<td>
A inner vector is either a row (for row-major) or a column (for column-major).\n
As stated earlier, for a read-write sub-matrix (RW), the evaluation can be done in a matrix with different storage order.
</td>
</tr>
<tr><td colspan="2"> Triangular and selfadjoint views</td></tr>
<tr>
<td> Triangular and selfadjoint views</td>
<td>
\code
sm2 = sm1.triangularview<Lower>();
@@ -222,26 +228,30 @@ sm2 = perm * sm1; // Permute the columns
\code
\endcode </td>
</tr>
<tr>
<td>Triangular solve </td>
<tr class="alt"><td colspan="2">Triangular solve </td></tr>
<tr class="alt">
<td>
\code
dv2 = sm1.triangularView<Upper>().solve(dv1);
dv2 = sm1.topLeftCorner(size, size).triangularView<Lower>().solve(dv1);
dv2 = sm1.topLeftCorner(size, size)
.triangularView<Lower>().solve(dv1);
\endcode
</td>
<td> For general sparse solve, Use any suitable module described at \ref TopicSparseSystems </td>
</tr>
<tr><td colspan="2"> Low-level API</td></tr>
<tr>
<td> Low-level API</td>
<td>
\code
sm1.valuePtr(); // Pointer to the values
sm1.innerIndextr(); // Pointer to the indices.
sm1.outerIndexPtr(); //Pointer to the beginning of each inner vector
sm1.valuePtr(); // Pointer to the values
sm1.innerIndextr(); // Pointer to the indices.
sm1.outerIndexPtr(); // Pointer to the beginning of each inner vector
\endcode
</td>
<td> If the matrix is not in compressed form, makeCompressed() should be called before. Note that these functions are mostly provided for interoperability purposes with external libraries. A better access to the values of the matrix is done by using the InnerIterator class as described in \link TutorialSparse the Tutorial Sparse \endlink section</td>
<td>
If the matrix is not in compressed form, makeCompressed() should be called before.\n
Note that these functions are mostly provided for interoperability purposes with external libraries.\n
A better access to the values of the matrix is done by using the InnerIterator class as described in \link TutorialSparse the Tutorial Sparse \endlink section</td>
</tr>
</table>
*/