Various documentation updates:

- update the tutorial
- update doc of deprecated cwise function
- update cwise doc snippets
This commit is contained in:
Gael Guennebaud 2010-01-06 17:18:38 +01:00
parent c11300dbd5
commit 7d3fe69eff
43 changed files with 320 additions and 472 deletions

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@ -30,13 +30,7 @@
***************************************************************************/
/** \returns an expression of the coefficient-wise absolute value of \c *this
*
* Example: \include Cwise_abs.cpp
* Output: \verbinclude Cwise_abs.out
*
* \sa abs2()
*/
/** \deprecated ArrayBase::abs() */
template<typename ExpressionType>
EIGEN_STRONG_INLINE const EIGEN_CWISE_UNOP_RETURN_TYPE(ei_scalar_abs_op)
Cwise<ExpressionType>::abs() const
@ -44,13 +38,7 @@ Cwise<ExpressionType>::abs() const
return _expression();
}
/** \returns an expression of the coefficient-wise squared absolute value of \c *this
*
* Example: \include Cwise_abs2.cpp
* Output: \verbinclude Cwise_abs2.out
*
* \sa abs(), square()
*/
/** \deprecated ArrayBase::abs2() */
template<typename ExpressionType>
EIGEN_STRONG_INLINE const EIGEN_CWISE_UNOP_RETURN_TYPE(ei_scalar_abs2_op)
Cwise<ExpressionType>::abs2() const
@ -58,13 +46,7 @@ Cwise<ExpressionType>::abs2() const
return _expression();
}
/** \returns an expression of the coefficient-wise exponential of *this.
*
* Example: \include Cwise_exp.cpp
* Output: \verbinclude Cwise_exp.out
*
* \sa pow(), log(), sin(), cos()
*/
/** \deprecated ArrayBase::exp() */
template<typename ExpressionType>
inline const EIGEN_CWISE_UNOP_RETURN_TYPE(ei_scalar_exp_op)
Cwise<ExpressionType>::exp() const
@ -72,13 +54,7 @@ Cwise<ExpressionType>::exp() const
return _expression();
}
/** \returns an expression of the coefficient-wise logarithm of *this.
*
* Example: \include Cwise_log.cpp
* Output: \verbinclude Cwise_log.out
*
* \sa exp()
*/
/** \deprecated ArrayBase::log() */
template<typename ExpressionType>
inline const EIGEN_CWISE_UNOP_RETURN_TYPE(ei_scalar_log_op)
Cwise<ExpressionType>::log() const
@ -86,13 +62,7 @@ Cwise<ExpressionType>::log() const
return _expression();
}
/** \returns an expression of the Schur product (coefficient wise product) of *this and \a other
*
* Example: \include Cwise_product.cpp
* Output: \verbinclude Cwise_product.out
*
* \sa class CwiseBinaryOp, operator/(), square()
*/
/** \deprecated ArrayBase::operator*() */
template<typename ExpressionType>
template<typename OtherDerived>
EIGEN_STRONG_INLINE const EIGEN_CWISE_PRODUCT_RETURN_TYPE(ExpressionType,OtherDerived)
@ -101,13 +71,7 @@ Cwise<ExpressionType>::operator*(const MatrixBase<OtherDerived> &other) const
return EIGEN_CWISE_PRODUCT_RETURN_TYPE(ExpressionType,OtherDerived)(_expression(), other.derived());
}
/** \returns an expression of the coefficient-wise quotient of *this and \a other
*
* Example: \include Cwise_quotient.cpp
* Output: \verbinclude Cwise_quotient.out
*
* \sa class CwiseBinaryOp, operator*(), inverse()
*/
/** \deprecated ArrayBase::operator/() */
template<typename ExpressionType>
template<typename OtherDerived>
EIGEN_STRONG_INLINE const EIGEN_CWISE_BINOP_RETURN_TYPE(ei_scalar_quotient_op)
@ -116,13 +80,7 @@ Cwise<ExpressionType>::operator/(const MatrixBase<OtherDerived> &other) const
return EIGEN_CWISE_BINOP_RETURN_TYPE(ei_scalar_quotient_op)(_expression(), other.derived());
}
/** Replaces this expression by its coefficient-wise product with \a other.
*
* Example: \include Cwise_times_equal.cpp
* Output: \verbinclude Cwise_times_equal.out
*
* \sa operator*(), operator/=()
*/
/** \deprecated ArrayBase::operator*=() */
template<typename ExpressionType>
template<typename OtherDerived>
inline ExpressionType& Cwise<ExpressionType>::operator*=(const MatrixBase<OtherDerived> &other)
@ -130,13 +88,7 @@ inline ExpressionType& Cwise<ExpressionType>::operator*=(const MatrixBase<OtherD
return m_matrix.const_cast_derived() = *this * other;
}
/** Replaces this expression by its coefficient-wise quotient by \a other.
*
* Example: \include Cwise_slash_equal.cpp
* Output: \verbinclude Cwise_slash_equal.out
*
* \sa operator/(), operator*=()
*/
/** \deprecated ArrayBase::operator/=() */
template<typename ExpressionType>
template<typename OtherDerived>
inline ExpressionType& Cwise<ExpressionType>::operator/=(const MatrixBase<OtherDerived> &other)
@ -144,13 +96,7 @@ inline ExpressionType& Cwise<ExpressionType>::operator/=(const MatrixBase<OtherD
return m_matrix.const_cast_derived() = *this / other;
}
/** \returns an expression of the coefficient-wise min of *this and \a other
*
* Example: \include Cwise_min.cpp
* Output: \verbinclude Cwise_min.out
*
* \sa class CwiseBinaryOp
*/
/** \deprecated ArrayBase::min() */
template<typename ExpressionType>
template<typename OtherDerived>
EIGEN_STRONG_INLINE const EIGEN_CWISE_BINOP_RETURN_TYPE(ei_scalar_min_op)
@ -159,13 +105,7 @@ Cwise<ExpressionType>::min(const MatrixBase<OtherDerived> &other) const
return EIGEN_CWISE_BINOP_RETURN_TYPE(ei_scalar_min_op)(_expression(), other.derived());
}
/** \returns an expression of the coefficient-wise max of *this and \a other
*
* Example: \include Cwise_max.cpp
* Output: \verbinclude Cwise_max.out
*
* \sa class CwiseBinaryOp
*/
/** \deprecated ArrayBase::max() */
template<typename ExpressionType>
template<typename OtherDerived>
EIGEN_STRONG_INLINE const EIGEN_CWISE_BINOP_RETURN_TYPE(ei_scalar_max_op)
@ -180,15 +120,7 @@ Cwise<ExpressionType>::max(const MatrixBase<OtherDerived> &other) const
// -- unary operators --
/** \array_module
*
* \returns an expression of the coefficient-wise square root of *this.
*
* Example: \include Cwise_sqrt.cpp
* Output: \verbinclude Cwise_sqrt.out
*
* \sa pow(), square()
*/
/** \deprecated ArrayBase::sqrt() */
template<typename ExpressionType>
inline const EIGEN_CWISE_UNOP_RETURN_TYPE(ei_scalar_sqrt_op)
Cwise<ExpressionType>::sqrt() const
@ -196,15 +128,7 @@ Cwise<ExpressionType>::sqrt() const
return _expression();
}
/** \array_module
*
* \returns an expression of the coefficient-wise cosine of *this.
*
* Example: \include Cwise_cos.cpp
* Output: \verbinclude Cwise_cos.out
*
* \sa sin(), exp(), EIGEN_FAST_MATH
*/
/** \deprecated ArrayBase::cos() */
template<typename ExpressionType>
inline const EIGEN_CWISE_UNOP_RETURN_TYPE(ei_scalar_cos_op)
Cwise<ExpressionType>::cos() const
@ -213,15 +137,7 @@ Cwise<ExpressionType>::cos() const
}
/** \array_module
*
* \returns an expression of the coefficient-wise sine of *this.
*
* Example: \include Cwise_sin.cpp
* Output: \verbinclude Cwise_sin.out
*
* \sa cos(), exp(), EIGEN_FAST_MATH
*/
/** \deprecated ArrayBase::sin() */
template<typename ExpressionType>
inline const EIGEN_CWISE_UNOP_RETURN_TYPE(ei_scalar_sin_op)
Cwise<ExpressionType>::sin() const
@ -230,15 +146,7 @@ Cwise<ExpressionType>::sin() const
}
/** \array_module
*
* \returns an expression of the coefficient-wise power of *this to the given exponent.
*
* Example: \include Cwise_pow.cpp
* Output: \verbinclude Cwise_pow.out
*
* \sa exp(), log()
*/
/** \deprecated ArrayBase::log() */
template<typename ExpressionType>
inline const EIGEN_CWISE_UNOP_RETURN_TYPE(ei_scalar_pow_op)
Cwise<ExpressionType>::pow(const Scalar& exponent) const
@ -247,15 +155,7 @@ Cwise<ExpressionType>::pow(const Scalar& exponent) const
}
/** \array_module
*
* \returns an expression of the coefficient-wise inverse of *this.
*
* Example: \include Cwise_inverse.cpp
* Output: \verbinclude Cwise_inverse.out
*
* \sa operator/(), operator*()
*/
/** \deprecated ArrayBase::inverse() */
template<typename ExpressionType>
inline const EIGEN_CWISE_UNOP_RETURN_TYPE(ei_scalar_inverse_op)
Cwise<ExpressionType>::inverse() const
@ -263,15 +163,7 @@ Cwise<ExpressionType>::inverse() const
return _expression();
}
/** \array_module
*
* \returns an expression of the coefficient-wise square of *this.
*
* Example: \include Cwise_square.cpp
* Output: \verbinclude Cwise_square.out
*
* \sa operator/(), operator*(), abs2()
*/
/** \deprecated ArrayBase::square() */
template<typename ExpressionType>
inline const EIGEN_CWISE_UNOP_RETURN_TYPE(ei_scalar_square_op)
Cwise<ExpressionType>::square() const
@ -279,15 +171,7 @@ Cwise<ExpressionType>::square() const
return _expression();
}
/** \array_module
*
* \returns an expression of the coefficient-wise cube of *this.
*
* Example: \include Cwise_cube.cpp
* Output: \verbinclude Cwise_cube.out
*
* \sa square(), pow()
*/
/** \deprecated ArrayBase::cube() */
template<typename ExpressionType>
inline const EIGEN_CWISE_UNOP_RETURN_TYPE(ei_scalar_cube_op)
Cwise<ExpressionType>::cube() const
@ -298,15 +182,7 @@ Cwise<ExpressionType>::cube() const
// -- binary operators --
/** \array_module
*
* \returns an expression of the coefficient-wise \< operator of *this and \a other
*
* Example: \include Cwise_less.cpp
* Output: \verbinclude Cwise_less.out
*
* \sa MatrixBase::all(), MatrixBase::any(), operator>(), operator<=()
*/
/** \deprecated ArrayBase::operator<() */
template<typename ExpressionType>
template<typename OtherDerived>
inline const EIGEN_CWISE_BINOP_RETURN_TYPE(std::less)
@ -315,15 +191,7 @@ Cwise<ExpressionType>::operator<(const MatrixBase<OtherDerived> &other) const
return EIGEN_CWISE_BINOP_RETURN_TYPE(std::less)(_expression(), other.derived());
}
/** \array_module
*
* \returns an expression of the coefficient-wise \<= operator of *this and \a other
*
* Example: \include Cwise_less_equal.cpp
* Output: \verbinclude Cwise_less_equal.out
*
* \sa MatrixBase::all(), MatrixBase::any(), operator>=(), operator<()
*/
/** \deprecated ArrayBase::<=() */
template<typename ExpressionType>
template<typename OtherDerived>
inline const EIGEN_CWISE_BINOP_RETURN_TYPE(std::less_equal)
@ -332,15 +200,7 @@ Cwise<ExpressionType>::operator<=(const MatrixBase<OtherDerived> &other) const
return EIGEN_CWISE_BINOP_RETURN_TYPE(std::less_equal)(_expression(), other.derived());
}
/** \array_module
*
* \returns an expression of the coefficient-wise \> operator of *this and \a other
*
* Example: \include Cwise_greater.cpp
* Output: \verbinclude Cwise_greater.out
*
* \sa MatrixBase::all(), MatrixBase::any(), operator>=(), operator<()
*/
/** \deprecated ArrayBase::operator>() */
template<typename ExpressionType>
template<typename OtherDerived>
inline const EIGEN_CWISE_BINOP_RETURN_TYPE(std::greater)
@ -349,15 +209,7 @@ Cwise<ExpressionType>::operator>(const MatrixBase<OtherDerived> &other) const
return EIGEN_CWISE_BINOP_RETURN_TYPE(std::greater)(_expression(), other.derived());
}
/** \array_module
*
* \returns an expression of the coefficient-wise \>= operator of *this and \a other
*
* Example: \include Cwise_greater_equal.cpp
* Output: \verbinclude Cwise_greater_equal.out
*
* \sa MatrixBase::all(), MatrixBase::any(), operator>(), operator<=()
*/
/** \deprecated ArrayBase::operator>=() */
template<typename ExpressionType>
template<typename OtherDerived>
inline const EIGEN_CWISE_BINOP_RETURN_TYPE(std::greater_equal)
@ -366,20 +218,7 @@ Cwise<ExpressionType>::operator>=(const MatrixBase<OtherDerived> &other) const
return EIGEN_CWISE_BINOP_RETURN_TYPE(std::greater_equal)(_expression(), other.derived());
}
/** \array_module
*
* \returns an expression of the coefficient-wise == operator of *this and \a other
*
* \warning this performs an exact comparison, which is generally a bad idea with floating-point types.
* In order to check for equality between two vectors or matrices with floating-point coefficients, it is
* generally a far better idea to use a fuzzy comparison as provided by MatrixBase::isApprox() and
* MatrixBase::isMuchSmallerThan().
*
* Example: \include Cwise_equal_equal.cpp
* Output: \verbinclude Cwise_equal_equal.out
*
* \sa MatrixBase::all(), MatrixBase::any(), MatrixBase::isApprox(), MatrixBase::isMuchSmallerThan()
*/
/** \deprecated ArrayBase::operator==() */
template<typename ExpressionType>
template<typename OtherDerived>
inline const EIGEN_CWISE_BINOP_RETURN_TYPE(std::equal_to)
@ -388,20 +227,7 @@ Cwise<ExpressionType>::operator==(const MatrixBase<OtherDerived> &other) const
return EIGEN_CWISE_BINOP_RETURN_TYPE(std::equal_to)(_expression(), other.derived());
}
/** \array_module
*
* \returns an expression of the coefficient-wise != operator of *this and \a other
*
* \warning this performs an exact comparison, which is generally a bad idea with floating-point types.
* In order to check for equality between two vectors or matrices with floating-point coefficients, it is
* generally a far better idea to use a fuzzy comparison as provided by MatrixBase::isApprox() and
* MatrixBase::isMuchSmallerThan().
*
* Example: \include Cwise_not_equal.cpp
* Output: \verbinclude Cwise_not_equal.out
*
* \sa MatrixBase::all(), MatrixBase::any(), MatrixBase::isApprox(), MatrixBase::isMuchSmallerThan()
*/
/** \deprecated ArrayBase::operator!=() */
template<typename ExpressionType>
template<typename OtherDerived>
inline const EIGEN_CWISE_BINOP_RETURN_TYPE(std::not_equal_to)
@ -412,12 +238,7 @@ Cwise<ExpressionType>::operator!=(const MatrixBase<OtherDerived> &other) const
// comparisons to scalar value
/** \array_module
*
* \returns an expression of the coefficient-wise \< operator of *this and a scalar \a s
*
* \sa operator<(const MatrixBase<OtherDerived> &) const
*/
/** \deprecated ArrayBase::operator<(Scalar) */
template<typename ExpressionType>
inline const EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::less)
Cwise<ExpressionType>::operator<(Scalar s) const
@ -426,12 +247,7 @@ Cwise<ExpressionType>::operator<(Scalar s) const
typename ExpressionType::ConstantReturnType(_expression().rows(), _expression().cols(), s));
}
/** \array_module
*
* \returns an expression of the coefficient-wise \<= operator of *this and a scalar \a s
*
* \sa operator<=(const MatrixBase<OtherDerived> &) const
*/
/** \deprecated ArrayBase::operator<=(Scalar) */
template<typename ExpressionType>
inline const EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::less_equal)
Cwise<ExpressionType>::operator<=(Scalar s) const
@ -440,12 +256,7 @@ Cwise<ExpressionType>::operator<=(Scalar s) const
typename ExpressionType::ConstantReturnType(_expression().rows(), _expression().cols(), s));
}
/** \array_module
*
* \returns an expression of the coefficient-wise \> operator of *this and a scalar \a s
*
* \sa operator>(const MatrixBase<OtherDerived> &) const
*/
/** \deprecated ArrayBase::operator>(Scalar) */
template<typename ExpressionType>
inline const EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::greater)
Cwise<ExpressionType>::operator>(Scalar s) const
@ -454,12 +265,7 @@ Cwise<ExpressionType>::operator>(Scalar s) const
typename ExpressionType::ConstantReturnType(_expression().rows(), _expression().cols(), s));
}
/** \array_module
*
* \returns an expression of the coefficient-wise \>= operator of *this and a scalar \a s
*
* \sa operator>=(const MatrixBase<OtherDerived> &) const
*/
/** \deprecated ArrayBase::operator>=(Scalar) */
template<typename ExpressionType>
inline const EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::greater_equal)
Cwise<ExpressionType>::operator>=(Scalar s) const
@ -468,17 +274,7 @@ Cwise<ExpressionType>::operator>=(Scalar s) const
typename ExpressionType::ConstantReturnType(_expression().rows(), _expression().cols(), s));
}
/** \array_module
*
* \returns an expression of the coefficient-wise == operator of *this and a scalar \a s
*
* \warning this performs an exact comparison, which is generally a bad idea with floating-point types.
* In order to check for equality between two vectors or matrices with floating-point coefficients, it is
* generally a far better idea to use a fuzzy comparison as provided by MatrixBase::isApprox() and
* MatrixBase::isMuchSmallerThan().
*
* \sa operator==(const MatrixBase<OtherDerived> &) const
*/
/** \deprecated ArrayBase::operator==(Scalar) */
template<typename ExpressionType>
inline const EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::equal_to)
Cwise<ExpressionType>::operator==(Scalar s) const
@ -487,17 +283,7 @@ Cwise<ExpressionType>::operator==(Scalar s) const
typename ExpressionType::ConstantReturnType(_expression().rows(), _expression().cols(), s));
}
/** \array_module
*
* \returns an expression of the coefficient-wise != operator of *this and a scalar \a s
*
* \warning this performs an exact comparison, which is generally a bad idea with floating-point types.
* In order to check for equality between two vectors or matrices with floating-point coefficients, it is
* generally a far better idea to use a fuzzy comparison as provided by MatrixBase::isApprox() and
* MatrixBase::isMuchSmallerThan().
*
* \sa operator!=(const MatrixBase<OtherDerived> &) const
*/
/** \deprecated ArrayBase::operator!=(Scalar) */
template<typename ExpressionType>
inline const EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::not_equal_to)
Cwise<ExpressionType>::operator!=(Scalar s) const
@ -508,15 +294,7 @@ Cwise<ExpressionType>::operator!=(Scalar s) const
// scalar addition
/** \array_module
*
* \returns an expression of \c *this with each coeff incremented by the constant \a scalar
*
* Example: \include Cwise_plus.cpp
* Output: \verbinclude Cwise_plus.out
*
* \sa operator+=(), operator-()
*/
/** \deprecated ArrayBase::operator+(Scalar) */
template<typename ExpressionType>
inline const typename Cwise<ExpressionType>::ScalarAddReturnType
Cwise<ExpressionType>::operator+(const Scalar& scalar) const
@ -524,30 +302,14 @@ Cwise<ExpressionType>::operator+(const Scalar& scalar) const
return typename Cwise<ExpressionType>::ScalarAddReturnType(m_matrix, ei_scalar_add_op<Scalar>(scalar));
}
/** \array_module
*
* Adds the given \a scalar to each coeff of this expression.
*
* Example: \include Cwise_plus_equal.cpp
* Output: \verbinclude Cwise_plus_equal.out
*
* \sa operator+(), operator-=()
*/
/** \deprecated ArrayBase::operator+=(Scalar) */
template<typename ExpressionType>
inline ExpressionType& Cwise<ExpressionType>::operator+=(const Scalar& scalar)
{
return m_matrix.const_cast_derived() = *this + scalar;
}
/** \array_module
*
* \returns an expression of \c *this with each coeff decremented by the constant \a scalar
*
* Example: \include Cwise_minus.cpp
* Output: \verbinclude Cwise_minus.out
*
* \sa operator+(), operator-=()
*/
/** \deprecated ArrayBase::operator-(Scalar) */
template<typename ExpressionType>
inline const typename Cwise<ExpressionType>::ScalarAddReturnType
Cwise<ExpressionType>::operator-(const Scalar& scalar) const
@ -555,16 +317,7 @@ Cwise<ExpressionType>::operator-(const Scalar& scalar) const
return *this + (-scalar);
}
/** \array_module
*
* Substracts the given \a scalar from each coeff of this expression.
*
* Example: \include Cwise_minus_equal.cpp
* Output: \verbinclude Cwise_minus_equal.out
*
* \sa operator+=(), operator-()
*/
/** \deprecated ArrayBase::operator-=(Scalar) */
template<typename ExpressionType>
inline ExpressionType& Cwise<ExpressionType>::operator-=(const Scalar& scalar)
{

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@ -136,26 +136,26 @@ public:
template<class OtherDerived> Scalar angularDistance(const QuaternionBase<OtherDerived>& other) const;
/** \returns an equivalent 3x3 rotation matrix */
/** \returns an equivalent 3x3 rotation matrix */
Matrix3 toRotationMatrix() const;
/** \returns the quaternion which transform \a a into \a b through a rotation */
/** \returns the quaternion which transform \a a into \a b through a rotation */
template<typename Derived1, typename Derived2>
Derived& setFromTwoVectors(const MatrixBase<Derived1>& a, const MatrixBase<Derived2>& b);
template<class OtherDerived> EIGEN_STRONG_INLINE Quaternion<Scalar> operator* (const QuaternionBase<OtherDerived>& q) const;
template<class OtherDerived> EIGEN_STRONG_INLINE Derived& operator*= (const QuaternionBase<OtherDerived>& q);
/** \returns the quaternion describing the inverse rotation */
/** \returns the quaternion describing the inverse rotation */
Quaternion<Scalar> inverse() const;
/** \returns the conjugated quaternion */
/** \returns the conjugated quaternion */
Quaternion<Scalar> conjugate() const;
/** \returns an interpolation for a constant motion between \a other and \c *this
* \a t in [0;1]
* see http://en.wikipedia.org/wiki/Slerp
*/
/** \returns an interpolation for a constant motion between \a other and \c *this
* \a t in [0;1]
* see http://en.wikipedia.org/wiki/Slerp
*/
template<class OtherDerived> Quaternion<Scalar> slerp(Scalar t, const QuaternionBase<OtherDerived>& other) const;
/** \returns \c true if \c *this is approximately equal to \a other, within the precision

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@ -21,6 +21,24 @@ operator/(const EIGEN_CURRENT_STORAGE_BASE_CLASS<OtherDerived> &other) const
return CwiseBinaryOp<ei_scalar_quotient_op<Scalar>, Derived, OtherDerived>(derived(), other.derived());
}
/** \returns an expression of the coefficient-wise min of \c *this and \a other
*
* Example: \include Cwise_min.cpp
* Output: \verbinclude Cwise_min.out
*
* \sa max()
*/
EIGEN_MAKE_CWISE_BINARY_OP(min,ei_scalar_min_op)
/** \returns an expression of the coefficient-wise max of \c *this and \a other
*
* Example: \include Cwise_max.cpp
* Output: \verbinclude Cwise_max.out
*
* \sa min()
*/
EIGEN_MAKE_CWISE_BINARY_OP(max,ei_scalar_max_op)
/** \returns an expression of the coefficient-wise \< operator of *this and \a other
*
* Example: \include Cwise_less.cpp

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@ -78,13 +78,20 @@ This slows compilation down but at least you don't have to worry anymore about i
<a href="#" class="top">top</a>
\section TutorialCoreMatrixTypes Array, matrix and vector types
Eigen provides two kinds of dense objects: mathematical matrices and vectors which are both represented by the template class Matrix, and 1D and 2D arrays represented by the template class Array. While the former (Matrix) is specialized for the representation of mathematical objects, the latter (Array) represents a collection of scalar values arranged in a 1D or 2D fashion. In particular, all operations performed on arrays are coefficient wise. Conversion between the two worlds can be done using the MatrixBase::array() and ArrayBase::matrix() functions respectively without any overhead. See \ref TutorialCoreArithmeticOperators for further details.
Eigen provides two kinds of dense objects: mathematical matrices and vectors which are both represented by the template class Matrix, and 1D and 2D arrays represented by the template class Array. While the former (Matrix) is specialized for the representation of mathematical objects, the latter (Array) represents a collection of scalar values arranged in a 1D or 2D fashion. As a major difference, all operations performed on arrays are coefficient wise. Matrix and Array have a lot of similarities since they both inherits the DenseBase and DenseStorageBase classes. In the rest of this tutorial we will use the following symbols to emphasize the features which are specifics to a given kind of object:
\li <a name="matrixonly"><a/>\matrixworld for matrix/vector only features
\li <a name="arrayonly"><a/>\arrayworld for array only features
In most cases, you can simply use one of the \ref matrixtypedefs "convenience typedefs".
Note that conversion between the two worlds can be done using the MatrixBase::array() and ArrayBase::matrix() functions respectively without any overhead.
The template class Matrix, just like the class Array) take a number of template parameters, but for now it is enough to understand the 3 first ones (and the others can then be left unspecified):
In most cases, you can simply use one of the convenience typedefs for \ref matrixtypedefs "matrices" and \ref arraytypedefs "arrays".
\code Matrix<Scalar, RowsAtCompileTime, ColsAtCompileTime> \endcode
The template class Matrix (just like the class Array) take a number of template parameters, but for now it is enough to understand the 3 first ones (and the others can then be left unspecified):
\code
Matrix<Scalar, RowsAtCompileTime, ColsAtCompileTime>
Array<Scalar, RowsAtCompileTime, ColsAtCompileTime>
\endcode
\li \c Scalar is the scalar type, i.e. the type of the coefficients. That is, if you want a vector of floats, choose \c float here.
\li \c RowsAtCompileTime and \c ColsAtCompileTime are the number of rows and columns of the matrix as known at compile-time.
@ -96,23 +103,36 @@ For dynamic-size, that is in order to left the number of rows or of columns unsp
All combinations are allowed: you can have a matrix with a fixed number of rows and a dynamic number of columns, etc. The following are all valid:
\code
Matrix<double, 6, Dynamic> // Dynamic number of columns
Matrix<double, Dynamic, 2> // Dynamic number of rows
Matrix<double, Dynamic, Dynamic> // Fully dynamic
Matrix<double, 13, 3> // Fully fixed
Matrix<double, 6, Dynamic> // Dynamic number of columns
Matrix<double, Dynamic, 2> // Dynamic number of rows
Matrix<double, Dynamic, Dynamic> // Fully dynamic
Matrix<double, 13, 3> // Fully fixed
\endcode
Fixed-size and partially-dynamic-size matrices may use all the same API calls as fully dynamic
matrices, but the fixed dimension(s) must remain constant, or an assertion failure will occur.
<a href="#" class="top">top</a>\section TutorialCoreCoefficients Coefficient access
Finally, note that the default typedefs for array containers is slighlty different as we have to distinghish between 1D and 2D arrays:
\code
ArrayXf // 1D dynamic array of floats
Array2i // 1D array of integers of size 2
ArrayXXd // 2D fully dynamic array of doubles
Array44f // 2D array of floats of size 4x4
\endcode
Eigen supports the following syntaxes for read and write coefficient access:
<a href="#" class="top">top</a>
\section TutorialCoreCoefficients Coefficient access
Eigen supports the following syntaxes for read and write coefficient access of matrices, vectors and arrays:
\code
matrix(i,j);
vector(i)
vector[i]
\endcode
Vectors support also the following additional read-write accessors:
\code
vector.x() // first coefficient
vector.y() // second coefficient
vector.z() // third coefficient
@ -121,9 +141,11 @@ vector.w() // fourth coefficient
Notice that these coefficient access methods have assertions checking the ranges. So if you do a lot of coefficient access, these assertion can have an important cost. There are then two possibilities if you want avoid paying this cost:
\li Either you can disable assertions altogether, by defining EIGEN_NO_DEBUG or NDEBUG. Notice that some IDEs like MS Visual Studio define NDEBUG automatically in "Release Mode".
\li Or you can disable the checks on a case-by-case basis by using the coeff() and coeffRef() methods: see MatrixBase::coeff(int,int) const, MatrixBase::coeffRef(int,int), etc.
\li Or you can disable the checks on a case-by-case basis by using the coeff() and coeffRef() methods: see DenseBase::coeff(int,int) const, DenseBase::coeffRef(int,int), etc.
<a href="#" class="top">top</a>\section TutorialCoreMatrixInitialization Matrix and vector creation and initialization
<a href="#" class="top">top</a>
\section TutorialCoreMatrixInitialization Matrix and vector creation and initialization
\subsection TutorialCtors Matrix constructors
@ -169,7 +191,8 @@ Vector4f w(1.2f, 3.4f, 5.6f, 7.8f);
\endcode
\subsection TutorialPredefMat Predefined Matrices
Eigen offers several static methods to create special matrix expressions, and non-static methods to assign these expressions to existing matrices:
Eigen offers several static methods to create special matrix expressions, and non-static methods to assign these expressions to existing matrices.
The following are
<table class="tutorial_code">
<tr>
@ -180,13 +203,14 @@ Eigen offers several static methods to create special matrix expressions, and no
<tr style="border-bottom-style: none;">
<td>
\code
Matrix3f x;
typedef {Matrix3f|Array33f} FixedXD;
FixedXD x;
x = Matrix3f::Zero();
x = Matrix3f::Ones();
x = Matrix3f::Constant(value);
x = Matrix3f::Identity();
x = Matrix3f::Random();
x = FixedXD::Zero();
x = FixedXD::Ones();
x = FixedXD::Constant(value);
x = FixedXD::Identity();
x = FixedXD::Random();
x.setZero();
x.setOnes();
@ -197,13 +221,14 @@ x.setRandom();
</td>
<td>
\code
MatrixXf x;
typedef {MatrixXf|ArrayXXf} Dynamic2D;
Dynamic2D x;
x = MatrixXf::Zero(rows, cols);
x = MatrixXf::Ones(rows, cols);
x = MatrixXf::Constant(rows, cols, value);
x = MatrixXf::Identity(rows, cols);
x = MatrixXf::Random(rows, cols);
x = Dynamic2D::Zero(rows, cols);
x = Dynamic2D::Ones(rows, cols);
x = Dynamic2D::Constant(rows, cols, value);
x = Dynamic2D::Identity(rows, cols);
x = Dynamic2D::Random(rows, cols);
x.setZero(rows, cols);
x.setOnes(rows, cols);
@ -214,13 +239,14 @@ x.setRandom(rows, cols);
</td>
<td>
\code
VectorXf x;
typedef {VectorXf|ArrayXf} Dynamic1D;
Dynamic1D x;
x = VectorXf::Zero(size);
x = VectorXf::Ones(size);
x = VectorXf::Constant(size, value);
x = VectorXf::Identity(size);
x = VectorXf::Random(size);
x = Dynamic1D::Zero(size);
x = Dynamic1D::Ones(size);
x = Dynamic1D::Constant(size, value);
x = Dynamic1D::Identity(size);
x = Dynamic1D::Random(size);
x.setZero(size);
x.setOnes(size);
@ -231,7 +257,25 @@ x.setRandom(size);
</td>
</tr>
<tr style="border-top-style: none;"><td colspan="3">\redstar the Random() and setRandom() functions require the inclusion of the Array module (\c \#include \c <Eigen/Array>)</td></tr>
<tr><td colspan="3">Basis vectors \link MatrixBase::Unit [details]\endlink</td></tr>
<tr><td colspan="3">The following are for matrix only: \matrixworld</td></tr>
<tr style="border-bottom-style: none;">
<td>
\code
x = FixedXD::Identity();
x.setIdentity();
\endcode
</td>
<td>
\code
x = Dynamic2D::Identity(rows, cols);
x.setIdentity(rows, cols);
\endcode
</td>
<td>
</td>
</tr>
<tr><td colspan="3">Basis vectors \matrixworld \link MatrixBase::Unit [details]\endlink</td></tr>
<tr><td>\code
Vector3f::UnitX() // 1 0 0
Vector3f::UnitY() // 0 1 0
@ -265,7 +309,7 @@ v = 6 6 6
\subsection TutorialCasting Casting
In Eigen, any matrices of same size and same scalar type are all naturally compatible. The scalar type can be explicitly casted to another one using the template MatrixBase::cast() function:
In Eigen, any matrices of same size and same scalar type are all naturally compatible. The scalar type can be explicitly casted to another one using the template DenseBase::cast() function:
\code
Matrix3d md(1,2,3);
Matrix3f mf = md.cast<float>();
@ -280,6 +324,28 @@ res = a+b; // OK: res is resized to size 3x3
\endcode
Of course, fixed-size matrices can't be resized.
An array object or expression can be directly assigned to a matrix, and vice versa:
\code
Matrix4f res;
Array44f a, b;
res = a * b;
\endcode
On the other hand, an array and a matrix expressions cannot be mixed in an expression, and one have to be converted to the other using the MatrixBase::array() \matrixworld and ArrayBase::matrix() \arrayworld functions respectively:
\code
Matrix4f m1, m2;
Array44f a1, a2;
m2 = a1 * m1.array(); // coeffwise product
a2 = a1.matrix() * m1; // matrix product
\endcode
Finally it is possible to declare a variable wrapping a matrix as an array object and vice versa:
\code
MatrixXf m1;
ArrayWrapper<MatrixXf> a1(m1); // a1 and m1 share the same coefficients
// now you can use a1 as an alias for m1.array()
ArrayXXf a2;
MatrixWrapper<ArrayXXf> m2(a1); // a2 and m2 share the same coefficients
// ...
\endcode
\subsection TutorialMap Map
Any memory buffer can be mapped as an Eigen expression using the Map() static method:
@ -289,21 +355,21 @@ VectorXf::Map(&stlarray[0], stlarray.size()).squaredNorm();
\endcode
Here VectorXf::Map returns an object of class Map<VectorXf>, which behaves like a VectorXf except that it uses the existing array. You can write to this object, that will write to the existing array. You can also construct a named obtect to reuse it:
\code
float array[rows*cols];
Map<MatrixXf> m(array,rows,cols);
float data[rows*cols];
Map<MatrixXf> m(data,rows,cols);
m = othermatrix1 * othermatrix2;
m.eigenvalues();
\endcode
In the fixed-size case, no need to pass sizes:
\code
float array[9];
Map<Matrix3d> m(array);
Matrix3d::Map(array).setIdentity();
float data[9];
Map<Matrix3d> m(data);
Matrix3d::Map(data).setIdentity();
\endcode
\subsection TutorialCommaInit Comma initializer
Eigen also offers a \ref MatrixBaseCommaInitRef "comma initializer syntax" which allows you to set all the coefficients of a matrix to specific values:
Eigen also offers a \ref MatrixBaseCommaInitRef "comma initializer syntax" which allows you to set all the coefficients of any dense objects (matrix, vector, array, block, etc.) to specific values:
<table class="tutorial_code"><tr><td>
\include Tutorial_commainit_01.cpp
</td>
@ -328,12 +394,12 @@ Eigen's comma initializer usually compiles to very optimized code without any ov
<a href="#" class="top">top</a>
\section TutorialCoreArithmeticOperators Arithmetic Operators
In short, all arithmetic operators can be used right away as in the following example. Note however that for matrices and vectors arithmetic operators are only given their usual meaning from mathematics tradition while all array operators are performed coefficient wise.
<a href="#" class="top">top</a>\section TutorialCoreArithmeticOperators Arithmetic Operators
In short, all arithmetic operators can be used right away as in the following example. Note however that arithmetic operators are only given their usual meaning from mathematics tradition. For other operations, such as taking the coefficient-wise product of two vectors, see the discussion of \link Cwise .cwise() \endlink below. Anyway, here is an example demonstrating basic arithmetic operators:
Here is an example demonstrating basic arithmetic operators:
\code
mat4 -= mat1*1.5 + mat2 * (mat3/4);
\endcode
@ -342,7 +408,7 @@ a matrix addition ("+") and subtraction with assignment ("-=").
<table class="tutorial_code">
<tr><td>
matrix/vector product</td><td>\code
matrix/vector product \matrixworld</td><td>\code
col2 = mat1 * col1;
row2 = row1 * mat1; row1 *= mat1;
mat3 = mat1 * mat2; mat3 *= mat1; \endcode
@ -357,107 +423,108 @@ scalar product</td><td>\code
mat3 = mat1 * s1; mat3 = s1 * mat1; mat3 *= s1;
mat3 = mat1 / s1; mat3 /= s1;\endcode
</td></tr>
<tr><td>
Other coefficient wise operators</td><td>\code
mat1.cwiseProduct(mat2); mat1.cwiseQuotient(mat2);
mat1.cwiseMin(mat2); mat1.cwiseMax(mat2);
mat1.cwiseAbs2(); mat1.cwiseSqrt();
mat1.cwiseAbs();\endcode
</td></tr>
</table>
In Eigen, only traditional mathematical operators can be used right away.
But don't worry, thanks to the \link Cwise .cwise() \endlink operator prefix,
Eigen's matrices are also very powerful as a numerical container supporting
most common coefficient-wise operators.
In addition to the above operators, array objects supports all kind of coefficient wise operators which usually apply to scalar values. Recall that those operators can be used on matrices by converting them to arrays using the array() function (see \ref TutorialCasting Casting).
<table class="noborder">
<tr><td>
<table class="tutorial_code" style="margin-right:10pt">
<tr><td>Coefficient wise \link Cwise::operator*() product \endlink</td>
<td>\code mat3 = mat1.cwise() * mat2; \endcode
<tr><td>Coefficient wise \link ArrayBase::operator*() product \arrayworld \endlink</td>
<td>\code array3 = array1 * array2; \endcode
</td></tr>
<tr><td>
Add a scalar to all coefficients \redstar</td><td>\code
mat3 = mat1.cwise() + scalar;
mat3.array() += scalar;
mat3.array() -= scalar;
Add a scalar to all coefficients</td><td>\code
array3 = array1 + scalar;
array3 += scalar;
array3 -= scalar;
\endcode
</td></tr>
<tr><td>
Coefficient wise \link Cwise::operator/() division \endlink \redstar</td><td>\code
mat3 = mat1.array() / mat2.array(); \endcode
Coefficient wise \link ArrayBase::operator/() division \endlink \arrayworld</td><td>\code
array3 = array1 / array2; \endcode
</td></tr>
<tr><td>
Coefficient wise \link Cwise::inverse() reciprocal \endlink \redstar</td><td>\code
mat3 = mat1.array().inverse(); \endcode
Coefficient wise \link ArrayBase::inverse() reciprocal \endlink \arrayworld</td><td>\code
array3 = array1.inverse(); \endcode
</td></tr>
<tr><td>
Coefficient wise comparisons \redstar \n
Coefficient wise comparisons \arrayworld \n
(support all operators)</td><td>\code
mat3 = mat1.array() < mat2.array();
mat3 = mat1.array() <= mat2.array();
mat3 = mat1.array() > mat2.array();
array3 = array1 < array2;
array3 = array1 <= array2;
array3 = array1 > array2;
etc.
\endcode
</td></tr></table>
</td>
<td><table class="tutorial_code">
<tr><td>
\b Trigo \redstar: \n
\link Cwise::sin sin \endlink, \link Cwise::cos cos \endlink</td><td>\code
mat3 = mat1.array().sin();
\b Trigo \arrayworld: \n
\link ArrayBase::sin sin \endlink, \link ArrayBase::cos cos \endlink</td><td>\code
array3 = array1.sin();
etc.
\endcode
</td></tr>
<tr><td>
\b Power \redstar: \n \link Cwise::pow() pow \endlink,
\b Power \arrayworld: \n \link ArrayBase::pow() pow \endlink,
\link ArrayBase::square square \endlink,
\link ArrayBase::cube cube \endlink, \n
\link ArrayBase::sqrt sqrt \endlink,
\link ArrayBase::exp exp \endlink,
\link ArrayBase::log log \endlink </td><td>\code
mat3 = mat1.array().square();
mat3 = mat1.array().pow(5);
mat3 = mat1.array().log();
array3 = array1.square();
array3 = array1.pow(5);
array3 = array1.log();
etc.
\endcode
</td></tr>
<tr><td>
\link Cwise::min min \endlink, \link Cwise::max max \endlink, \n
absolute value (\link Cwise::abs() abs \endlink, \link Cwise::abs2() abs2 \endlink)
\link ArrayBase::min min \endlink, \link ArrayBase::max max \endlink, \n
absolute value (\link ArrayBase::abs() abs \endlink, \link ArrayBase::abs2() abs2 \endlink \arrayworld)
</td><td>\code
mat3 = mat1.cwiseMin(mat2);
mat3 = mat1.cwiseMax(mat2);
mat3 = mat1.cwiseAbs();
mat3 = mat1.cwiseAbs2();
array3 = array1.min(array2);
array3 = array1.max(array2);
array3 = array1.abs();
array3 = array1.abs2();
\endcode</td></tr>
</table>
</td></tr></table>
\redstar Those functions require the inclusion of the Array module (\c \#include \c <Eigen/Array>).
<span class="note">\b Side \b note: If you think that the \c .cwise() syntax is too verbose for your own taste and prefer to have non-conventional mathematical operators directly available, then feel free to extend MatrixBase as described \ref ExtendingMatrixBase "here".</span>
So far, we saw the notation \code mat1*mat2 \endcode for matrix product, and \code mat1.cwise()*mat2 \endcode for coefficient-wise product. What about other kinds of products, which in some other libraries also use arithmetic operators? In Eigen, they are accessed as follows -- note that here we are anticipating on further sections, for convenience.
So far, we saw the notation \code mat1*mat2 \endcode for matrix product, and \code array1*array2 \endcode for coefficient-wise product. What about other kinds of products, which in some other libraries also use arithmetic operators? In Eigen, they are accessed as follows -- note that here we are anticipating on further sections, for convenience.
<table class="tutorial_code">
<tr><td>\link MatrixBase::dot() dot product \endlink (inner product)</td><td>\code
<tr><td>\link MatrixBase::dot() dot product \endlink (inner product) \matrixworld</td><td>\code
scalar = vec1.dot(vec2);\endcode
</td></tr>
<tr><td>
outer product</td><td>\code
outer product \matrixworld</td><td>\code
mat = vec1 * vec2.transpose();\endcode
</td></tr>
<tr><td>
\link MatrixBase::cross() cross product \endlink</td><td>\code
\link MatrixBase::cross() cross product \endlink \matrixworld</td><td>\code
#include <Eigen/Geometry>
vec3 = vec1.cross(vec2);\endcode</td></tr>
</table>
<a href="#" class="top">top</a>\section TutorialCoreReductions Reductions
<a href="#" class="top">top</a>
\section TutorialCoreReductions Reductions
Eigen provides several reduction methods such as:
\link MatrixBase::minCoeff() minCoeff() \endlink, \link MatrixBase::maxCoeff() maxCoeff() \endlink,
\link MatrixBase::sum() sum() \endlink, \link MatrixBase::trace() trace() \endlink,
\link MatrixBase::norm() norm() \endlink, \link MatrixBase::squaredNorm() squaredNorm() \endlink,
\link MatrixBase::all() all() \endlink \redstar,and \link MatrixBase::any() any() \endlink \redstar.
\link DenseBase::minCoeff() minCoeff() \endlink, \link DenseBase::maxCoeff() maxCoeff() \endlink,
\link DenseBase::sum() sum() \endlink, \link MatrixBase::trace() trace() \endlink \matrixworld,
\link MatrixBase::norm() norm() \endlink \matrixworld, \link MatrixBase::squaredNorm() squaredNorm() \endlink \matrixworld,
\link DenseBase::all() all() \endlink \redstar,and \link DenseBase::any() any() \endlink \redstar.
All reduction operations can be done matrix-wise,
\link MatrixBase::colwise() column-wise \endlink \redstar or
\link MatrixBase::rowwise() row-wise \endlink \redstar. Usage example:
\link DenseBase::colwise() column-wise \endlink \redstar or
\link DenseBase::rowwise() row-wise \endlink \redstar. Usage example:
<table class="tutorial_code">
<tr><td rowspan="3" style="border-right-style:dashed">\code
5 3 1
@ -472,7 +539,7 @@ mat = 2 7 8
\endcode</td></tr>
</table>
Also note that maxCoeff and minCoeff can takes optional arguments returning the coordinates of the respective min/max coeff: \link MatrixBase::maxCoeff(int*,int*) const maxCoeff(int* i, int* j) \endlink, \link MatrixBase::minCoeff(int*,int*) const minCoeff(int* i, int* j) \endlink.
Also note that maxCoeff and minCoeff can takes optional arguments returning the coordinates of the respective min/max coeff: \link DenseBase::maxCoeff(int*,int*) const maxCoeff(int* i, int* j) \endlink, \link DenseBase::minCoeff(int*,int*) const minCoeff(int* i, int* j) \endlink.
<span class="note">\b Side \b note: The all() and any() functions are especially useful in combination with coeff-wise comparison operators.</span>
@ -482,8 +549,8 @@ Also note that maxCoeff and minCoeff can takes optional arguments returning the
<a href="#" class="top">top</a>\section TutorialCoreMatrixBlocks Matrix blocks
Read-write access to a \link MatrixBase::col(int) column \endlink
or a \link MatrixBase::row(int) row \endlink of a matrix:
Read-write access to a \link DenseBase::col(int) column \endlink
or a \link DenseBase::row(int) row \endlink of a matrix (or array):
\code
mat1.row(i) = mat2.col(j);
mat1.col(j1).swap(mat1.col(j2));
@ -505,34 +572,34 @@ Read-write access to sub-vectors:
Read-write access to sub-matrices:</td><td></td><td></td></tr>
<tr>
<td>\code mat1.block(i,j,rows,cols)\endcode
\link MatrixBase::block(int,int,int,int) (more) \endlink</td>
\link DenseBase::block(int,int,int,int) (more) \endlink</td>
<td>\code mat1.block<rows,cols>(i,j)\endcode
\link MatrixBase::block(int,int) (more) \endlink</td>
\link DenseBase::block(int,int) (more) \endlink</td>
<td>the \c rows x \c cols sub-matrix \n starting from position (\c i,\c j)</td></tr><tr>
<td>\code
mat1.corner(TopLeft,rows,cols)
mat1.corner(TopRight,rows,cols)
mat1.corner(BottomLeft,rows,cols)
mat1.corner(BottomRight,rows,cols)\endcode
\link MatrixBase::corner(CornerType,int,int) (more) \endlink</td>
\link DenseBase::corner(CornerType,int,int) (more) \endlink</td>
<td>\code
mat1.corner<rows,cols>(TopLeft)
mat1.corner<rows,cols>(TopRight)
mat1.corner<rows,cols>(BottomLeft)
mat1.corner<rows,cols>(BottomRight)\endcode
\link MatrixBase::corner(CornerType) (more) \endlink</td>
\link DenseBase::corner(CornerType) (more) \endlink</td>
<td>the \c rows x \c cols sub-matrix \n taken in one of the four corners</td></tr>
<tr><td>\code
mat4x4.minor(i,j) = mat3x3;
mat3x3 = mat4x4.minor(i,j);\endcode
</td><td></td><td>
\link MatrixBase::minor() minor \endlink (read-write)</td>
\link DenseBase::minor() minor \endlink (read-write)</td>
</tr>
</table>
<a href="#" class="top">top</a>\section TutorialCoreDiagonalMatrices Diagonal matrices
<a href="#" class="top">top</a>\section TutorialCoreDiagonalMatrices Diagonal matrices \matrixworld
<table class="tutorial_code">
<tr><td>
@ -549,23 +616,29 @@ mat3 = mat1 * vec2.asDiagonal();\endcode
</tr>
</table>
<a href="#" class="top">top</a>\section TutorialCoreTransposeAdjoint Transpose and Adjoint operations
<a href="#" class="top">top</a>
\section TutorialCoreTransposeAdjoint Transpose and Adjoint operations
<table class="tutorial_code">
<tr><td>
\link MatrixBase::transpose() transposition \endlink (read-write)</td><td>\code
\link DenseBase::transpose() transposition \endlink (read-write)</td><td>\code
mat3 = mat1.transpose() * mat2;
mat3.transpose() = mat1 * mat2.transpose();
\endcode
</td></tr>
<tr><td>
\link MatrixBase::adjoint() adjoint \endlink (read only)\n</td><td>\code
\link MatrixBase::adjoint() adjoint \endlink (read only) \matrixworld\n</td><td>\code
mat3 = mat1.adjoint() * mat2;
\endcode
</td></tr>
</table>
<a href="#" class="top">top</a>\section TutorialCoreDotNorm Dot-product, vector norm, normalization
<a href="#" class="top">top</a>
\section TutorialCoreDotNorm Dot-product, vector norm, normalization \matrixworld
<table class="tutorial_code">
<tr><td>
@ -586,7 +659,10 @@ vec1.normalize();\endcode
</td></tr>
</table>
<a href="#" class="top">top</a>\section TutorialCoreTriangularMatrix Dealing with triangular matrices
<a href="#" class="top">top</a>
\section TutorialCoreTriangularMatrix Dealing with triangular matrices \matrixworld
Currently, Eigen does not provide any explicit triangular matrix, with storage class. Instead, we
can reference a triangular part of a square matrix or expression to perform special treatment on it.
@ -629,7 +705,9 @@ m1.adjoint().triangularView<Eigen::UpperTriangular>().solveInPlace(m2)\endcode
</table>
<a href="#" class="top">top</a>\section TutorialCoreSelfadjointMatrix Dealing with symmetric/selfadjoint matrices
<a href="#" class="top">top</a>
\section TutorialCoreSelfadjointMatrix Dealing with symmetric/selfadjoint matrices \matrixworld
Just as for triangular matrix, you can reference any triangular part of a square matrix to see it a selfadjoint
matrix to perform special and optimized operations. Again the opposite triangular is never referenced and can be
@ -673,7 +751,8 @@ m1.selfadjointView<Eigen::UpperTriangular>().ldlt().solveInPlace(m2);
</table>
<a href="#" class="top">top</a>\section TutorialCoreSpecialTopics Special Topics
<a href="#" class="top">top</a>
\section TutorialCoreSpecialTopics Special Topics
\ref TopicLazyEvaluation "Lazy Evaluation and Aliasing": Thanks to expression templates, Eigen is able to apply lazy evaluation wherever that is beneficial.

View File

@ -208,6 +208,8 @@ ALIASES = "only_for_vectors=This is only for vectors (either row-
"svd_module=This is defined in the %SVD module. \code #include <Eigen/SVD> \endcode" \
"label=\bug" \
"redstar=<a href='#warningarraymodule' style='color:red;text-decoration: none;'>*</a>" \
"matrixworld=<a href='#matrixonly' style='color:green;text-decoration: none;'>*</a>" \
"arrayworld=<a href='#arrayonly' style='color:blue;text-decoration: none;'>*</a>" \
"nonstableyet=\warning This is not considered to be part of the stable public API yet. Changes may happen in future releases. See \ref Experimental \"Experimental parts of Eigen\"" \
"note_about_arbitrary_choice_of_solution=If there exists more than one solution, this method will arbitrarily choose one." \
"note_about_using_kernel_to_study_multiple_solutions=If you need a complete analysis of the space of solutions, take the one solution obtained by this method and add to it elements of the kernel, as determined by kernel()." \

View File

@ -1,2 +1,2 @@
Vector3d v(1,-2,-3);
cout << v.cwise().abs() << endl;
Array3d v(1,-2,-3);
cout << v.abs() << endl;

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@ -1,2 +1,2 @@
Vector3d v(1,-2,-3);
cout << v.cwise().abs2() << endl;
Array3d v(1,-2,-3);
cout << v.abs2() << endl;

View File

@ -1,2 +1,2 @@
Vector3d v(M_PI, M_PI/2, M_PI/3);
cout << v.cwise().cos() << endl;
Array3d v(M_PI, M_PI/2, M_PI/3);
cout << v.cos() << endl;

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@ -1,2 +1,2 @@
Vector3d v(2,3,4);
cout << v.cwise().cube() << endl;
Array3d v(2,3,4);
cout << v.cube() << endl;

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@ -1,2 +1,2 @@
Vector3d v(1,2,3), w(3,2,1);
cout << (v.cwise()==w) << endl;
Array3d v(1,2,3), w(3,2,1);
cout << (v==w) << endl;

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@ -1,2 +1,2 @@
Vector3d v(1,2,3);
cout << v.cwise().exp() << endl;
Array3d v(1,2,3);
cout << v.exp() << endl;

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@ -1,2 +1,2 @@
Vector3d v(1,2,3), w(3,2,1);
cout << (v.cwise()>w) << endl;
Array3d v(1,2,3), w(3,2,1);
cout << (v>w) << endl;

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@ -1,2 +1,2 @@
Vector3d v(1,2,3), w(3,2,1);
cout << (v.cwise()>=w) << endl;
Array3d v(1,2,3), w(3,2,1);
cout << (v>=w) << endl;

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@ -1,2 +1,2 @@
Vector3d v(2,3,4);
cout << v.cwise().inverse() << endl;
Array3d v(2,3,4);
cout << v.inverse() << endl;

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@ -1,2 +1,2 @@
Vector3d v(1,2,3), w(3,2,1);
cout << (v.cwise()<w) << endl;
Array3d v(1,2,3), w(3,2,1);
cout << (v<w) << endl;

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@ -1,2 +1,2 @@
Vector3d v(1,2,3), w(3,2,1);
cout << (v.cwise()<=w) << endl;
Array3d v(1,2,3), w(3,2,1);
cout << (v<=w) << endl;

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@ -1,2 +1,2 @@
Vector3d v(1,2,3);
cout << v.cwise().log() << endl;
Array3d v(1,2,3);
cout << v.log() << endl;

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@ -1,2 +1,2 @@
Vector3d v(2,3,4), w(4,2,3);
cout << v.cwise().max(w) << endl;
Array3d v(2,3,4), w(4,2,3);
cout << v.max(w) << endl;

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@ -1,2 +1,2 @@
Vector3d v(2,3,4), w(4,2,3);
cout << v.cwise().min(w) << endl;
Array3d v(2,3,4), w(4,2,3);
cout << v.min(w) << endl;

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@ -1,2 +1,2 @@
Vector3d v(1,2,3);
cout << v.cwise()-5 << endl;
Array3d v(1,2,3);
cout << v-5 << endl;

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@ -1,3 +1,3 @@
Vector3d v(1,2,3);
v.cwise() -= 5;
Array3d v(1,2,3);
v -= 5;
cout << v << endl;

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@ -1,2 +1,2 @@
Vector3d v(1,2,3), w(3,2,1);
cout << (v.cwise()!=w) << endl;
Array3d v(1,2,3), w(3,2,1);
cout << (v!=w) << endl;

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@ -1,2 +1,2 @@
Vector3d v(1,2,3);
cout << v.cwise()+5 << endl;
Array3d v(1,2,3);
cout << v+5 << endl;

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@ -1,3 +1,3 @@
Vector3d v(1,2,3);
v.cwise() += 5;
Array3d v(1,2,3);
v += 5;
cout << v << endl;

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@ -1,2 +1,2 @@
Vector3d v(8,27,64);
cout << v.cwise().pow(0.333333) << endl;
Array3d v(8,27,64);
cout << v.pow(0.333333) << endl;

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@ -1,4 +1,4 @@
Matrix3i a = Matrix3i::Random(), b = Matrix3i::Random();
Matrix3i c = a.cwise() * b;
Array33i a = Array33i::Random(), b = Array33i::Random();
Array33i c = a * b;
cout << "a:\n" << a << "\nb:\n" << b << "\nc:\n" << c << endl;

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@ -1,2 +1,2 @@
Vector3d v(2,3,4), w(4,2,3);
cout << v.cwise()/w << endl;
Array3d v(2,3,4), w(4,2,3);
cout << v/w << endl;

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@ -1,2 +1,2 @@
Vector3d v(M_PI, M_PI/2, M_PI/3);
cout << v.cwise().sin() << endl;
Array3d v(M_PI, M_PI/2, M_PI/3);
cout << v.sin() << endl;

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@ -1,4 +1,3 @@
Vector3d v(3,2,4);
Vector3d w(5,4,2);
v.cwise() /= w;
Array3d v(3,2,4), w(5,4,2);
v /= w;
cout << v << endl;

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@ -1,2 +1,2 @@
Vector3d v(1,2,4);
cout << v.cwise().sqrt() << endl;
Array3d v(1,2,4);
cout << v.sqrt() << endl;

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@ -1,2 +1,2 @@
Vector3d v(2,3,4);
cout << v.cwise().square() << endl;
Array3d v(2,3,4);
cout << v.square() << endl;

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@ -1,4 +1,3 @@
Vector3d v(1,2,3);
Vector3d w(2,3,0);
v.cwise() *= w;
Array3d v(1,2,3), w(2,3,0);
v *= w;
cout << v << endl;

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@ -1,7 +1,7 @@
Vector3f boxMin(Vector3f::Zero()), boxMax(Vector3f::Ones());
Vector3f p0 = Vector3f::Random(), p1 = Vector3f::Random().cwise().abs();
Vector3f p0 = Vector3f::Random(), p1 = Vector3f::Random().cwiseAbs();
// let's check if p0 and p1 are inside the axis aligned box defined by the corners boxMin,boxMax:
cout << "Is (" << p0.transpose() << ") inside the box: "
<< ((boxMin.cwise()<p0).all() && (boxMax.cwise()>p0).all()) << endl;
<< ((boxMin.array()<p0.array()).all() && (boxMax.array()>p0.array()).all()) << endl;
cout << "Is (" << p1.transpose() << ") inside the box: "
<< ((boxMin.cwise()<p1).all() && (boxMax.cwise()>p1).all()) << endl;
<< ((boxMin.array()<p1.array()).all() && (boxMax.array()>p1.array()).all()) << endl;

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@ -1,4 +1,4 @@
Vector3d v(1,2,3);
v.cwise() += 3;
v.cwise() -= 2;
v.array() += 3;
v.array() -= 2;
cout << v << endl;

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@ -0,0 +1,4 @@
Vector3d v(-1,2,-3);
cout << "the absolute values:" << endl << v.array().abs() << endl;
cout << "the absolute values plus one:" << endl << v.array().abs()+1 << endl;
cout << "sum of the squares: " << v.array().square().sum() << endl;

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@ -2,4 +2,4 @@ Matrix3d m = Matrix3d::Random();
cout << "Here is the matrix m:" << endl << m << endl;
cout << "Here is the sum of each column:" << endl << m.colwise().sum() << endl;
cout << "Here is the maximum absolute value of each column:"
<< endl << m.cwise().abs().colwise().maxCoeff() << endl;
<< endl << m.cwiseAbs().colwise().maxCoeff() << endl;

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@ -1,4 +0,0 @@
Vector3d v(-1,2,-3);
cout << "the absolute values:" << endl << v.cwise().abs() << endl;
cout << "the absolute values plus one:" << endl << v.cwise().abs().cwise()+1 << endl;
cout << "sum of the squares: " << v.cwise().square().sum() << endl;

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@ -1,5 +0,0 @@
Matrix2d m; m << 1,2,3,4;
cout << (m*m).lazy().row(0) << endl;
// this computes only one row of the product. By contrast,
// if we did "(m*m).row(0);" then m*m would first be evaluated into
// a temporary, because the Product expression has the EvalBeforeNestingBit.

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@ -0,0 +1,3 @@
Matrix2d a, b, c; a << 1,2,3,4; b << 5,6,7,8;
c.noalias() = a * b; // this computes the product directly to c
cout << c << endl;

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@ -2,4 +2,4 @@ Matrix3d m = Matrix3d::Random();
cout << "Here is the matrix m:" << endl << m << endl;
cout << "Here is the sum of each row:" << endl << m.rowwise().sum() << endl;
cout << "Here is the maximum absolute value of each row:"
<< endl << m.cwise().abs().rowwise().maxCoeff() << endl;
<< endl << m.cwiseAbs().rowwise().maxCoeff() << endl;

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@ -1,6 +1,6 @@
MatrixXi m(3, 3);
m << 1, 2, 3,
4, 5, 6,
m << 1, 2, 3,
4, 5, 6,
7, 8, 9;
m = (m.cwise() >= 5).select(-m, m);
m = (m.array() >= 5).select(-m, m);
cout << m << endl;

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@ -1,3 +1,3 @@
Matrix3d m = Matrix3d::Random();
cout << "Here is the matrix m:" << endl << m << endl;
cout << "Here is the count of elements larger or equal than 0.5 of each row:" << endl << (m.cwise() >= 0.5).rowwise().count() << endl;
cout << "Here is the count of elements larger or equal than 0.5 of each row:" << endl << (m.array() >= 0.5).rowwise().count() << endl;

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@ -4,8 +4,8 @@ namespace Eigen {
/** \defgroup Unsupported_modules Unsupported modules
*
* The unsupported modules are contributions from various users. They are
* provided "as is", without any support. Nevertheless, they are subject to be
* included in Eigen in the future.
* provided "as is", without any support. Nevertheless, some of them are
* subject to be included in Eigen in the future.
*/
// please list here all unsupported modules