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Eigen
3.4.0
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Since the version 3.4, Eigen exposes convenient methods to reshape a matrix to another matrix of different sizes or vector. All cases are handled via the DenseBase::reshaped(NRowsType,NColsType) and DenseBase::reshaped() functions. Those functions do not perform in-place reshaping, but instead return a view on the input expression.
The more general reshaping transformation is handled via: reshaped(nrows,ncols)
. Here is an example reshaping a 4x4 matrix to a 2x8 one:
Example: | Output: |
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Matrix4i m = Matrix4i::Random();
cout << "Here is the matrix m:" << endl << m << endl;
cout << "Here is m.reshaped(2, 8):" << endl << m.reshaped(2, 8) << endl;
| Here is the matrix m: 0 9 0 -5 -7 -7 -8 -3 -4 4 -9 10 1 -6 -2 1 Here is m.reshaped(2, 8): 0 -4 9 4 0 -9 -5 10 -7 1 -7 -6 -8 -2 -3 1 |
By default, the input coefficients are always interpreted in column-major order regardless of the storage order of the input expression. For more control on ordering, compile-time sizes, and automatic size deduction, please see de documentation of DenseBase::reshaped(NRowsType,NColsType) that contains all the details with many examples.
A very common usage of reshaping is to create a 1D linear view over a given 2D matrix or expression. In this case, sizes can be deduced and thus omitted as in the following example:
Example: |
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Matrix4i m = Matrix4i::Random();
cout << "Here is the matrix m:" << endl << m << endl;
cout << "Here is m.reshaped().transpose():" << endl << m.reshaped().transpose() << endl;
cout << "Here is m.reshaped<RowMajor>().transpose(): " << endl << m.reshaped<RowMajor>().transpose() << endl;
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Output: |
Here is the matrix m: 0 9 0 -5 -7 -7 -8 -3 -4 4 -9 10 1 -6 -2 1 Here is m.reshaped().transpose(): 0 -7 -4 1 9 -7 4 -6 0 -8 -9 -2 -5 -3 10 1 Here is m.reshaped<RowMajor>().transpose(): 0 9 0 -5 -7 -7 -8 -3 -4 4 -9 10 1 -6 -2 1 |
This shortcut always returns a column vector and by default input coefficients are always interpreted in column-major order. Again, see the documentation of DenseBase::reshaped() for more control on the ordering.
The above examples create reshaped views, but what about reshaping inplace a given matrix? Of course this task in only conceivable for matrix and arrays having runtime dimensions. In many cases, this can be accomplished via PlainObjectBase::resize(Index,Index):
Example: |
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MatrixXi m = Matrix4i::Random();
cout << "Here is the matrix m:" << endl << m << endl;
cout << "Here is m.reshaped(2, 8):" << endl << m.reshaped(2, 8) << endl;
m.resize(2,8);
cout << "Here is the matrix m after m.resize(2,8):" << endl << m << endl;
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Output: |
Here is the matrix m: 0 9 0 -5 -7 -7 -8 -3 -4 4 -9 10 1 -6 -2 1 Here is m.reshaped(2, 8): 0 -4 9 4 0 -9 -5 10 -7 1 -7 -6 -8 -2 -3 1 Here is the matrix m after m.resize(2,8): 0 -4 9 4 0 -9 -5 10 -7 1 -7 -6 -8 -2 -3 1 |
However beware that unlike reshaped
, the result of resize
depends on the input storage order. It thus behaves similarly to reshaped<AutoOrder>
:
Example: |
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Matrix<int,Dynamic,Dynamic,RowMajor> m = Matrix4i::Random();
cout << "Here is the matrix m:" << endl << m << endl;
cout << "Here is m.reshaped(2, 8):" << endl << m.reshaped(2, 8) << endl;
cout << "Here is m.reshaped<AutoOrder>(2, 8):" << endl << m.reshaped<AutoOrder>(2, 8) << endl;
m.resize(2,8);
cout << "Here is the matrix m after m.resize(2,8):" << endl << m << endl;
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Output: |
Here is the matrix m: 0 -7 -4 1 9 -7 4 -6 0 -8 -9 -2 -5 -3 10 1 Here is m.reshaped(2, 8): 0 0 -7 -8 -4 -9 1 -2 9 -5 -7 -3 4 10 -6 1 Here is m.reshaped<AutoOrder>(2, 8): 0 -7 -4 1 9 -7 4 -6 0 -8 -9 -2 -5 -3 10 1 Here is the matrix m after m.resize(2,8): 0 -7 -4 1 9 -7 4 -6 0 -8 -9 -2 -5 -3 10 1 |
Finally, assigning a reshaped matrix to itself is currently not supported and will result to undefined-behavior because of aliasing . The following is forbidden:
This is OK: