Eigen
3.3.90 (git rev 4ad30a73fc8b707bf90b9ec712a12a7f63ae823a)

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 inplace 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: 

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: 10 1 4 7 8 6 9 10 5 10 2 9 1 4 0 1 Here is m.reshaped(2, 8): 10 5 1 10 4 2 7 9 8 1 6 4 9 0 10 1 
By default, the input coefficients are always interpreted in columnmajor order regardless of the storage order of the input expression. For more control on ordering, compiletime 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: 

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: 10 1 4 7 8 6 9 10 5 10 2 9 1 4 0 1 Here is m.reshaped().transpose(): 10 8 5 1 1 6 10 4 4 9 2 0 7 10 9 1 Here is m.reshaped<RowMajor>().transpose(): 10 1 4 7 8 6 9 10 5 10 2 9 1 4 0 1 
This shortcut always returns a column vector and by default input coefficients are always interpreted in columnmajor 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: 

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: 10 1 4 7 8 6 9 10 5 10 2 9 1 4 0 1 Here is m.reshaped(2, 8): 10 5 1 10 4 2 7 9 8 1 6 4 9 0 10 1 Here is the matrix m after m.resize(2,8): 10 5 1 10 4 2 7 9 8 1 6 4 9 0 10 1 
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: 10 8 5 1 1 6 10 4 4 9 2 0 7 10 9 1 Here is m.reshaped(2, 8): 10 4 8 9 5 2 1 0 1 7 6 10 10 9 4 1 Here is m.reshaped<AutoOrder>(2, 8): 10 8 5 1 1 6 10 4 4 9 2 0 7 10 9 1 Here is the matrix m after m.resize(2,8): 10 8 5 1 1 6 10 4 4 9 2 0 7 10 9 1 
Finally, assigning a reshaped matrix to itself is currently not supported and will result to undefinedbehavior because of aliasing . The following is forbidden:
This is OK: