Eigen  3.4.90 (git rev a4098ac676528a83cfb73d4d26ce1b42ec05f47c)

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:
cout << "Here is the matrix m:" << endl << m << endl;
cout << "Here is m.reshaped(2, 8):" << endl << m.reshaped(2, 8) << endl;
static const RandomReturnType Random()
Definition: Random.h:115
The matrix class, also used for vectors and row-vectors.
Definition: Matrix.h:182
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 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:
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;
TransposeReturnType transpose()
Definition: Transpose.h:184
@ RowMajor
Definition: Constants.h:323
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 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:
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;
void resize(Index rows, Index cols)
Definition: PlainObjectBase.h:283
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:
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 undefined-behavior because of aliasing . The following is forbidden:

A = A.reshaped(2,8);

This is OK:

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