W3cubDocs

/Eigen3

Reshape

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.

Reshaped 2D views

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:
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: 7 9 -5 -3 -2 -6 1 0 6 -3 0 9 6 6 3 9 Here is m.reshaped(2, 8): 7 6 9 -3 -5 0 -3 9 -2 6 -6 6 1 3 0 9

Example:

Output:

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:
 7  9 -5 -3
-2 -6  1  0
 6 -3  0  9
 6  6  3  9
Here is m.reshaped(2, 8):
 7  6  9 -3 -5  0 -3  9
-2  6 -6  6  1  3  0  9

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.

1D linear views

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:
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;
Output:
Here is the matrix m: 7 9 -5 -3 -2 -6 1 0 6 -3 0 9 6 6 3 9 Here is m.reshaped().transpose(): 7 -2 6 6 9 -6 -3 6 -5 1 0 3 -3 0 9 9 Here is m.reshaped<RowMajor>().transpose(): 7 9 -5 -3 -2 -6 1 0 6 -3 0 9 6 6 3 9

Example:

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;

Output:

Here is the matrix m:
 7  9 -5 -3
-2 -6  1  0
 6 -3  0  9
 6  6  3  9
Here is m.reshaped().transpose():
 7 -2  6  6  9 -6 -3  6 -5  1  0  3 -3  0  9  9
Here is m.reshaped<RowMajor>().transpose():  
 7  9 -5 -3 -2 -6  1  0  6 -3  0  9  6  6  3  9

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.

TutorialReshapeInPlace

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:
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;
Output:
Here is the matrix m: 7 9 -5 -3 -2 -6 1 0 6 -3 0 9 6 6 3 9 Here is m.reshaped(2, 8): 7 6 9 -3 -5 0 -3 9 -2 6 -6 6 1 3 0 9 Here is the matrix m after m.resize(2,8): 7 6 9 -3 -5 0 -3 9 -2 6 -6 6 1 3 0 9

Example:

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;

Output:

Here is the matrix m:
 7  9 -5 -3
-2 -6  1  0
 6 -3  0  9
 6  6  3  9
Here is m.reshaped(2, 8):
 7  6  9 -3 -5  0 -3  9
-2  6 -6  6  1  3  0  9
Here is the matrix m after m.resize(2,8):
 7  6  9 -3 -5  0 -3  9
-2  6 -6  6  1  3  0  9

However beware that unlike reshaped, the result of resize depends on the input storage order. It thus behaves similarly to reshaped<AutoOrder>:

Example:
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;
Output:
Here is the matrix m: 7 -2 6 6 9 -6 -3 6 -5 1 0 3 -3 0 9 9 Here is m.reshaped(2, 8): 7 -5 -2 1 6 0 6 3 9 -3 -6 0 -3 9 6 9 Here is m.reshaped<AutoOrder>(2, 8): 7 -2 6 6 9 -6 -3 6 -5 1 0 3 -3 0 9 9 Here is the matrix m after m.resize(2,8): 7 -2 6 6 9 -6 -3 6 -5 1 0 3 -3 0 9 9

Example:

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;

Output:

Here is the matrix m:
 7 -2  6  6
 9 -6 -3  6
-5  1  0  3
-3  0  9  9
Here is m.reshaped(2, 8):
 7 -5 -2  1  6  0  6  3
 9 -3 -6  0 -3  9  6  9
Here is m.reshaped<AutoOrder>(2, 8):
 7 -2  6  6  9 -6 -3  6
-5  1  0  3 -3  0  9  9
Here is the matrix m after m.resize(2,8):
 7 -2  6  6  9 -6 -3  6
-5  1  0  3 -3  0  9  9

Finally, assigning a reshaped matrix to itself is currently not supported and will result to undefined-behavior because of aliasing . The following is forbidden:

A = A.reshaped(2,8);

This is OK:

A = A.reshaped(2,8).eval();