| EAA |
A class for representing an equivalent angle-axis rotation
This class defines an equivalent-axis-angle orientation vector also known
as an \thetak vector or "axis+angle" vector
The equivalent-axis-angle vector is the product of a unit vector
\hat{\mathbf{k}} and an angle of rotation around that axis \theta
Note: given two EAA vectors \theta_1\mathbf{\hat{k}}_1 and
\theta_2\mathbf{\hat{k}}_2 it is generally not possible to subtract
or add these vectors, except for the special case when
\mathbf{\hat{k}}_1 == \mathbf{\hat{k}}_2 this is why this class does
not have any subtraction or addition operators
|
| EAAf |
A class for representing an equivalent angle-axis rotation
This class defines an equivalent-axis-angle orientation vector also known
as an \thetak vector or "axis+angle" vector
The equivalent-axis-angle vector is the product of a unit vector
\hat{\mathbf{k}} and an angle of rotation around that axis \theta
Note: given two EAA vectors \theta_1\mathbf{\hat{k}}_1 and
\theta_2\mathbf{\hat{k}}_2 it is generally not possible to subtract
or add these vectors, except for the special case when
\mathbf{\hat{k}}_1 == \mathbf{\hat{k}}_2 this is why this class does
not have any subtraction or addition operators
|
| EigenDecomposition |
Type representing a set of eigen values and eigen vectors.
|
| EigenDecomposition_f |
Type representing a set of eigen values and eigen vectors.
|
| EigenMatrix2d |
|
| EigenMatrix2f |
|
| EigenMatrix3d |
|
| EigenMatrix3f |
|
| EigenMatrix3id |
|
| EigenMatrix4d |
|
| EigenMatrix4f |
|
| EigenMatrixXd |
|
| EigenMatrixXf |
|
| EigenQuaterniond |
|
| EigenQuaternionf |
|
| EigenRowVector3d |
|
| EigenRowVector3f |
|
| EigenRowVector3id |
|
| EigenVector2d |
|
| EigenVector2f |
|
| EigenVector3d |
|
| EigenVector3f |
|
| EigenVector3id |
|
| EigenVector6d |
|
| EigenVector6f |
|
| EigenVector7d |
|
| EigenVector7f |
|
| EigenVectorXd |
|
| EigenVectorXf |
|
| EuclideanMetricQ |
Euclidean distance metric for vector types.
The distance between two points
P = (p_1, p_2, ..., p_n)
and
Q = (q_1, q_2, ..., q_n)
is defined as
\sqrt{\sum_{i=1}^{n}(p_i - q_i)^2}
|
| EuclideanMetricVector2D |
Euclidean distance metric for vector types.
The distance between two points
P = (p_1, p_2, ..., p_n)
and
Q = (q_1, q_2, ..., q_n)
is defined as
\sqrt{\sum_{i=1}^{n}(p_i - q_i)^2}
|
| EuclideanMetricVector3D |
Euclidean distance metric for vector types.
The distance between two points
P = (p_1, p_2, ..., p_n)
and
Q = (q_1, q_2, ..., q_n)
is defined as
\sqrt{\sum_{i=1}^{n}(p_i - q_i)^2}
|
| InertiaMatrixd |
A 3x3 inertia matrix
|
| InertiaMatrixf |
A 3x3 inertia matrix
|
| InfinityMetricQ |
Infinity norm distance metric for vector types.
InfinityMetric is a metric of the Euclidean n-Plane.
|
| InfinityMetricVector2D |
Infinity norm distance metric for vector types.
InfinityMetric is a metric of the Euclidean n-Plane.
|
| InfinityMetricVector3D |
Infinity norm distance metric for vector types.
InfinityMetric is a metric of the Euclidean n-Plane.
|
| Jacobian |
A Jacobian class.
|
| Line2D |
Describes a line segment in 2D.
|
| Line2D.IntersectResult |
definition of intersection result values for the intersection test
between two lines.
|
| Line2DPolar |
Describes a line in 2D in polar coordinates.
|
| LinearAlgebra |
Collection of Linear Algebra functions
|
| ManhattanMetricVector2D |
Manhattan distance metric for vector types.
The ManhattanMetric, also known as the taxicab metric or the 1-norm, is a
metric on the Euclidean n-Plane.
|
| ManhattanMetricVector3D |
Manhattan distance metric for vector types.
The ManhattanMetric, also known as the taxicab metric or the 1-norm, is a
metric on the Euclidean n-Plane.
|
| ManhattenMatricQ |
Manhattan distance metric for vector types.
The ManhattanMetric, also known as the taxicab metric or the 1-norm, is a
metric on the Euclidean n-Plane.
|
| Math |
Utility functions for the rw::math module.
|
| MetricFactory |
Metric constructor functions.
The constructor functions are parameterized by a type of vector.
|
| MetricQ |
Template interface for metrics on type T.
A metric is a function that defines a scalar distance between elements.
|
| MetricQCPtr |
Ptr stores a pointer and optionally takes ownership of the value.
|
| MetricQPtr |
Ptr stores a pointer and optionally takes ownership of the value.
|
| MetricRotation3D |
Template interface for metrics on type T.
A metric is a function that defines a scalar distance between elements.
|
| MetricRotation3D_f |
Template interface for metrics on type T.
A metric is a function that defines a scalar distance between elements.
|
| MetricRotation3DCPtr |
Ptr stores a pointer and optionally takes ownership of the value.
|
| MetricRotation3DPtr |
Ptr stores a pointer and optionally takes ownership of the value.
|
| MetricTransform3D |
Template interface for metrics on type T.
A metric is a function that defines a scalar distance between elements.
|
| MetricTransform3D_f |
Template interface for metrics on type T.
A metric is a function that defines a scalar distance between elements.
|
| MetricTransform3DCPtr |
Ptr stores a pointer and optionally takes ownership of the value.
|
| MetricTransform3DPtr |
Ptr stores a pointer and optionally takes ownership of the value.
|
| MetricUtil |
Various metrics and other distance measures.
|
| MetricVector2D |
Template interface for metrics on type T.
A metric is a function that defines a scalar distance between elements.
|
| MetricVector2DCPtr |
Ptr stores a pointer and optionally takes ownership of the value.
|
| MetricVector2DPtr |
Ptr stores a pointer and optionally takes ownership of the value.
|
| MetricVector3D |
Template interface for metrics on type T.
A metric is a function that defines a scalar distance between elements.
|
| MetricVector3DCPtr |
Ptr stores a pointer and optionally takes ownership of the value.
|
| MetricVector3DPtr |
Ptr stores a pointer and optionally takes ownership of the value.
|
| PairConstQ |
|
| pairEigenMatrixX_d_EigenVectorX_d |
|
| pairEigenMatrixXComplex_d_EigenVectorXComplex_d |
|
| PairQ |
|
| PerspectiveTransform2D |
The PerspectiveTransform2D is a perspective transform in 2D.
The homographic transform can be used to map one arbitrary 2D
quadrilateral into another.
|
| PerspectiveTransform2Df |
The PerspectiveTransform2D is a perspective transform in 2D.
The homographic transform can be used to map one arbitrary 2D
quadrilateral into another.
|
| PolynomialNDdDouble |
Representation of a polynomial that can have non-scalar coefficients (polynomial
matrix).
Representation of a polynomial of the following form:
f(x) = C_n x^n + C_(n-1) x^(n-1) + C_2 x^2 + C_1 x + C_0
The polynomial is represented as a list of coefficients ordered from lowest-order term to
highest-order term, {c_0,c_1,...,c_n}.
|
| PolynomialNDEigenMatrix3dDouble |
Representation of a polynomial that can have non-scalar coefficients (polynomial
matrix).
Representation of a polynomial of the following form:
f(x) = C_n x^n + C_(n-1) x^(n-1) + C_2 x^2 + C_1 x + C_0
The polynomial is represented as a list of coefficients ordered from lowest-order term to
highest-order term, {c_0,c_1,...,c_n}.
|
| PolynomialNDEigenMatrix3fFloat |
Representation of a polynomial that can have non-scalar coefficients (polynomial
matrix).
Representation of a polynomial of the following form:
f(x) = C_n x^n + C_(n-1) x^(n-1) + C_2 x^2 + C_1 x + C_0
The polynomial is represented as a list of coefficients ordered from lowest-order term to
highest-order term, {c_0,c_1,...,c_n}.
|
| PolynomialNDEigenMatrix3ifComplexDouble |
Representation of a polynomial that can have non-scalar coefficients (polynomial
matrix).
Representation of a polynomial of the following form:
f(x) = C_n x^n + C_(n-1) x^(n-1) + C_2 x^2 + C_1 x + C_0
The polynomial is represented as a list of coefficients ordered from lowest-order term to
highest-order term, {c_0,c_1,...,c_n}.
|
| PolynomialNDEigenRowVector3dDouble |
Representation of a polynomial that can have non-scalar coefficients (polynomial
matrix).
Representation of a polynomial of the following form:
f(x) = C_n x^n + C_(n-1) x^(n-1) + C_2 x^2 + C_1 x + C_0
The polynomial is represented as a list of coefficients ordered from lowest-order term to
highest-order term, {c_0,c_1,...,c_n}.
|
| PolynomialNDEigenRowVector3fFloat |
Representation of a polynomial that can have non-scalar coefficients (polynomial
matrix).
Representation of a polynomial of the following form:
f(x) = C_n x^n + C_(n-1) x^(n-1) + C_2 x^2 + C_1 x + C_0
The polynomial is represented as a list of coefficients ordered from lowest-order term to
highest-order term, {c_0,c_1,...,c_n}.
|
| PolynomialNDEigenRowVector3idComplexDouble |
Representation of a polynomial that can have non-scalar coefficients (polynomial
matrix).
Representation of a polynomial of the following form:
f(x) = C_n x^n + C_(n-1) x^(n-1) + C_2 x^2 + C_1 x + C_0
The polynomial is represented as a list of coefficients ordered from lowest-order term to
highest-order term, {c_0,c_1,...,c_n}.
|
| PolynomialNDEigenVector3dDouble |
Representation of a polynomial that can have non-scalar coefficients (polynomial
matrix).
Representation of a polynomial of the following form:
f(x) = C_n x^n + C_(n-1) x^(n-1) + C_2 x^2 + C_1 x + C_0
The polynomial is represented as a list of coefficients ordered from lowest-order term to
highest-order term, {c_0,c_1,...,c_n}.
|
| PolynomialNDEigenVector3fFloat |
Representation of a polynomial that can have non-scalar coefficients (polynomial
matrix).
Representation of a polynomial of the following form:
f(x) = C_n x^n + C_(n-1) x^(n-1) + C_2 x^2 + C_1 x + C_0
The polynomial is represented as a list of coefficients ordered from lowest-order term to
highest-order term, {c_0,c_1,...,c_n}.
|
| PolynomialNDEigenVector3idComplexDouble |
Representation of a polynomial that can have non-scalar coefficients (polynomial
matrix).
Representation of a polynomial of the following form:
f(x) = C_n x^n + C_(n-1) x^(n-1) + C_2 x^2 + C_1 x + C_0
The polynomial is represented as a list of coefficients ordered from lowest-order term to
highest-order term, {c_0,c_1,...,c_n}.
|
| PolynomialNDfFloat |
Representation of a polynomial that can have non-scalar coefficients (polynomial
matrix).
Representation of a polynomial of the following form:
f(x) = C_n x^n + C_(n-1) x^(n-1) + C_2 x^2 + C_1 x + C_0
The polynomial is represented as a list of coefficients ordered from lowest-order term to
highest-order term, {c_0,c_1,...,c_n}.
|
| PolynomialNDidComplexDouble |
Representation of a polynomial that can have non-scalar coefficients (polynomial
matrix).
Representation of a polynomial of the following form:
f(x) = C_n x^n + C_(n-1) x^(n-1) + C_2 x^2 + C_1 x + C_0
The polynomial is represented as a list of coefficients ordered from lowest-order term to
highest-order term, {c_0,c_1,...,c_n}.
|
| PolynomialSolver |
Find solutions for roots of real and complex polynomial equations.
The solutions are found analytically if the polynomial is of maximum order 3.
For polynomials of order 4 and higher, Laguerre's Method is used to find
roots until the polynomial can be deflated to order 3.
The remaining roots will then be found analytically.
Some Polynomials are particularly easy to solve.
|
| Pose2D |
A Pose3D \mathbf{x}\in \mathbb{R}^6 describes a position
and orientation in 3-dimensions.
{\mathbf{x}} = \left[
\begin{array}{c}
x \\
y \\
z \\
\theta k_x \\
\theta k_y \\
\theta k_z
\end{array}
\right]
where (x,y,z) is the 3d position and (\theta k_x, \theta k_y,
\theta k_z) describes the orientation in equal angle axis (EAA)
format.
|
| Pose2Df |
A Pose3D \mathbf{x}\in \mathbb{R}^6 describes a position
and orientation in 3-dimensions.
{\mathbf{x}} = \left[
\begin{array}{c}
x \\
y \\
z \\
\theta k_x \\
\theta k_y \\
\theta k_z
\end{array}
\right]
where (x,y,z) is the 3d position and (\theta k_x, \theta k_y,
\theta k_z) describes the orientation in equal angle axis (EAA)
format.
|
| Pose6D |
A Pose6D \mathbf{x}\in \mathbb{R}^6 describes a position
and orientation in 3-dimensions.
{\mathbf{x}} = \left[
\begin{array}{c}
x \\
y \\
z \\
\theta k_x \\
\theta k_y \\
\theta k_z
\end{array}
\right]
where (x,y,z) is the 3d position and (\theta k_x, \theta k_y,
\theta k_z) describes the orientation in equal angle axis (EAA)
format.
|
| Pose6Df |
A Pose6D \mathbf{x}\in \mathbb{R}^6 describes a position
and orientation in 3-dimensions.
{\mathbf{x}} = \left[
\begin{array}{c}
x \\
y \\
z \\
\theta k_x \\
\theta k_y \\
\theta k_z
\end{array}
\right]
where (x,y,z) is the 3d position and (\theta k_x, \theta k_y,
\theta k_z) describes the orientation in equal angle axis (EAA)
format.
|
| ProjectionMatrix |
projection matrix
|
| Q |
Configuration vector
|
| Quaternion |
A Quaternion \mathbf{q}\in \mathbb{R}^4 a complex
number used to describe rotations in 3-dimensional space.
q_w+{\bf i}\ q_x+ {\bf j} q_y+ {\bf k}\ q_z
Quaternions can be added and multiplied in a similar way as usual
algebraic numbers.
|
| Quaternion_f |
A Quaternion \mathbf{q}\in \mathbb{R}^4 a complex
number used to describe rotations in 3-dimensional space.
q_w+{\bf i}\ q_x+ {\bf j} q_y+ {\bf k}\ q_z
Quaternions can be added and multiplied in a similar way as usual
algebraic numbers.
|
| Random |
Generation of random numbers.
|
| Rotation2D |
|
| Rotation2Df |
|
| Rotation3D |
|
| Rotation3DAngleMetric_d |
a distance metric over rotations.
|
| Rotation3DAngleMetric_f |
a distance metric over rotations.
|
| Rotation3Df |
|
| Rotation3DVector |
An abstract base class for Rotation3D parameterisations
Classes that represents a parametrisation of a 3D rotation may inherit
from this class
|
| Rotation3DVectorf |
An abstract base class for Rotation3D parameterisations
Classes that represents a parametrisation of a 3D rotation may inherit
from this class
|
| RPY |
A class for representing Roll-Pitch-Yaw Euler angle rotations.
|
| RPYf |
A class for representing Roll-Pitch-Yaw Euler angle rotations.
|
| sdurw_math |
|
| sdurw_mathJNI |
|
| Statistics |
Class for collecting data and calculating simple statistics.
|
| Statistics_f |
Class for collecting data and calculating simple statistics.
|
| SWIGTYPE_p_double |
|
| SWIGTYPE_p_Eigen__Matrix3d |
|
| SWIGTYPE_p_Eigen__Matrix3f |
|
| SWIGTYPE_p_Eigen__MatrixT_double_4_1_t |
|
| SWIGTYPE_p_Eigen__MatrixT_double_5_1_t |
|
| SWIGTYPE_p_Eigen__MatrixT_double_Eigen__Dynamic_1_t |
|
| SWIGTYPE_p_Eigen__MatrixT_double_Eigen__Dynamic_Eigen__Dynamic_t |
|
| SWIGTYPE_p_Eigen__MatrixT_float_4_1_t |
|
| SWIGTYPE_p_Eigen__MatrixT_float_5_1_t |
|
| SWIGTYPE_p_Eigen__MatrixT_float_Eigen__Dynamic_1_t |
|
| SWIGTYPE_p_Eigen__MatrixT_float_Eigen__Dynamic_Eigen__Dynamic_t |
|
| SWIGTYPE_p_Eigen__MatrixT_std__complexT_float_t_3_3_t |
|
| SWIGTYPE_p_Eigen__Rotation2DT_double_t |
|
| SWIGTYPE_p_Eigen__Rotation2DT_float_t |
|
| SWIGTYPE_p_Eigen__Vector3d |
|
| SWIGTYPE_p_Eigen__Vector3f |
|
| SWIGTYPE_p_float |
|
| SWIGTYPE_p_rw__math__LinearAlgebra__EigenMatrixT_double_t__type |
|
| SWIGTYPE_p_rw__math__LinearAlgebra__EigenMatrixT_std__complexT_double_t_t__type |
|
| SWIGTYPE_p_rw__math__LinearAlgebra__EigenVectorT_double_t__type |
|
| SWIGTYPE_p_rw__math__LinearAlgebra__EigenVectorT_std__complexT_double_t_t__type |
|
| SWIGTYPE_p_rw__math__PolynomialNDT_Eigen__Matrix3d_double_t |
|
| SWIGTYPE_p_rw__math__PolynomialNDT_Eigen__Matrix3f_float_t |
|
| SWIGTYPE_p_rw__math__PolynomialNDT_Eigen__Vector3d_double_t |
|
| SWIGTYPE_p_rw__math__PolynomialNDT_Eigen__Vector3f_float_t |
|
| SWIGTYPE_p_rw__math__PolynomialT_double_t |
|
| SWIGTYPE_p_rw__math__PolynomialT_float_t |
|
| SWIGTYPE_p_rw__math__PolynomialT_std__complexT_double_t_t |
|
| SWIGTYPE_p_rw__math__Rotation3DT_t |
|
| SWIGTYPE_p_rw__math__Transform2DT_double_t |
|
| SWIGTYPE_p_rw__math__Transform2DT_float_t |
|
| SWIGTYPE_p_std__listT_double_t |
|
| SWIGTYPE_p_std__listT_float_t |
|
| SWIGTYPE_p_std__vectorT_Eigen__MatrixT_std__complexT_double_t_1_3_t_t |
|
| SWIGTYPE_p_std__vectorT_Eigen__MatrixT_std__complexT_float_t_3_3_t_t |
|
| SWIGTYPE_p_std__vectorT_rw__math__Rotation3DT_double_t_t |
|
| SWIGTYPE_p_std__vectorT_rw__math__Rotation3DT_float_t_t |
|
| SWIGTYPE_p_std__vectorT_rw__math__Transform3DT_double_t_t |
|
| SWIGTYPE_p_std__vectorT_rw__math__Transform3DT_float_t_t |
|
| SWIGTYPE_p_std__vectorT_rw__math__Vector2DT_double_t_t |
|
| SWIGTYPE_p_std__vectorT_rw__math__Vector2DT_float_t_t |
|
| SWIGTYPE_p_std__vectorT_rw__math__Vector3DT_double_t_t |
|
| SWIGTYPE_p_std__vectorT_rw__math__Vector3DT_float_t_t |
|
| Transform3D |
|
| Transform3DAngleMetric_d |
distance metrics between points in SE3.
|
| Transform3DAngleMetric_f |
distance metrics between points in SE3.
|
| Transform3Df |
|
| Transform3DVector |
this class is a interpolatable Transform3D, consisting of a Vecor3D and a Quaternion.
It is implemented to be very Interconvertable with a Transform3D, and allow operations souch
as Transform * scalar and Transform + Transform.
|
| Transform3DVector_f |
this class is a interpolatable Transform3D, consisting of a Vecor3D and a Quaternion.
It is implemented to be very Interconvertable with a Transform3D, and allow operations souch
as Transform * scalar and Transform + Transform.
|
| Vector |
Configuration vector
|
| Vector2D |
A 2D vector \mathbf{v}\in \mathbb{R}^2
\robabx{i}{j}{\mathbf{v}} = \left[
\begin{array}{c}
v_x \\
v_y
\end{array}
\right]
In addition, Vector2D supports the cross product operator:
v3 = cross(v1, v2)
Usage example:
using namespace rw::math;
Vector2D<> v1(1.0, 2.0);
Vector2D<> v2(6.0, 7.0);
Vector2D<> v3 = cross( v1, v2 );
Vector2D<> v4 = v2 - v1;
|
| Vector2Df |
A 2D vector \mathbf{v}\in \mathbb{R}^2
\robabx{i}{j}{\mathbf{v}} = \left[
\begin{array}{c}
v_x \\
v_y
\end{array}
\right]
In addition, Vector2D supports the cross product operator:
v3 = cross(v1, v2)
Usage example:
using namespace rw::math;
Vector2D<> v1(1.0, 2.0);
Vector2D<> v2(6.0, 7.0);
Vector2D<> v3 = cross( v1, v2 );
Vector2D<> v4 = v2 - v1;
|
| Vector3D |
A 3D vector \mathbf{v}\in \mathbb{R}^3
\robabx{i}{j}{\mathbf{v}} = \left[
\begin{array}{c}
v_x \\
v_y \\
v_z
\end{array}
\right]
Usage example:
const Vector3D<> v1(1.0, 2.0, 3.0);
const Vector3D<> v2(6.0, 7.0, 8.0);
const Vector3D<> v3 = cross(v1, v2);
const double d = dot(v1, v2);
const Vector3D<> v4 = v2 - v1;
|
| Vector3Df |
A 3D vector \mathbf{v}\in \mathbb{R}^3
\robabx{i}{j}{\mathbf{v}} = \left[
\begin{array}{c}
v_x \\
v_y \\
v_z
\end{array}
\right]
Usage example:
const Vector3D<> v1(1.0, 2.0, 3.0);
const Vector3D<> v2(6.0, 7.0, 8.0);
const Vector3D<> v3 = cross(v1, v2);
const double d = dot(v1, v2);
const Vector3D<> v4 = v2 - v1;
|
| Vector4Dd |
A N-Dimensional Vector
|
| Vector4Df |
A N-Dimensional Vector
|
| Vector5Dd |
A N-Dimensional Vector
|
| Vector5Df |
A N-Dimensional Vector
|
| Vector6Dd |
A N-Dimensional Vector
|
| Vector6Df |
A N-Dimensional Vector
|
| VectorEigenMatrix3d |
|
| VectorEigenMatrix3f |
|
| VectorEigenMatrix3id |
|
| VectorEigenRowVector3d |
|
| VectorEigenRowVector3f |
|
| VectorEigenVector3d |
|
| VectorEigenVector3f |
|
| VectorEigenVector3id |
|
| Vectorf |
Configuration vector
|
| VectorQ |
|
| VectorRotation3D |
|
| VectorRotation3D_f |
|
| VectorTransform3D |
|
| VectorTransform3D_f |
|
| VectorVector2D |
|
| VectorVector2D_f |
|
| VectorVector3D |
|
| VectorVector3D_f |
|
| VelocityScrew6D |
Class for representing 6 degrees of freedom velocity screws.
\mathbf{\nu} =
\left[
\begin{array}{c}
v_x\\
v_y\\
v_z\\
\omega_x\\
\omega_y\\
\omega_z
\end{array}
\right]
A VelocityScrew is the description of a frames linear and rotational velocity
with respect to some reference frame.
|
| VelocityScrew6Df |
Class for representing 6 degrees of freedom velocity screws.
\mathbf{\nu} =
\left[
\begin{array}{c}
v_x\\
v_y\\
v_z\\
\omega_x\\
\omega_y\\
\omega_z
\end{array}
\right]
A VelocityScrew is the description of a frames linear and rotational velocity
with respect to some reference frame.
|
| WeightedEuclideanMetricQ |
Weighted Euclidean metric for vector types.
Given a vector of weights \mathbf{\omega}\in\mathbb{R}^n ,
the distance between two points
P = (p_1, p_2, ..., p_n)
and
Q = (q_1, q_2, ..., q_n)
is defined as
\sqrt{\sum_{i=1}^{n}(\omega_i * (p_i - q_i))^2} .
|
| WeightedEuclideanMetricVector2D |
Weighted Euclidean metric for vector types.
Given a vector of weights \mathbf{\omega}\in\mathbb{R}^n ,
the distance between two points
P = (p_1, p_2, ..., p_n)
and
Q = (q_1, q_2, ..., q_n)
is defined as
\sqrt{\sum_{i=1}^{n}(\omega_i * (p_i - q_i))^2} .
|
| WeightedEuclideanMetricVector3D |
Weighted Euclidean metric for vector types.
Given a vector of weights \mathbf{\omega}\in\mathbb{R}^n ,
the distance between two points
P = (p_1, p_2, ..., p_n)
and
Q = (q_1, q_2, ..., q_n)
is defined as
\sqrt{\sum_{i=1}^{n}(\omega_i * (p_i - q_i))^2} .
|
| WeightedInfinityMetricQ |
Weighted infinity norm metric for vector types.
Given a vector of weights \mathbf{\omega}\in\mathbb{R}^n, the
distance between two points
P = (p_1, p_2, ..., p_n)
and
Q = (q_1, q_2, ..., q_n)
is defined as
max_i |\omega_i * (p_i - q_i)|
|
| WeightedInfinityMetricVector2D |
Weighted infinity norm metric for vector types.
Given a vector of weights \mathbf{\omega}\in\mathbb{R}^n, the
distance between two points
P = (p_1, p_2, ..., p_n)
and
Q = (q_1, q_2, ..., q_n)
is defined as
max_i |\omega_i * (p_i - q_i)|
|
| WeightedInfinityMetricVector3D |
Weighted infinity norm metric for vector types.
Given a vector of weights \mathbf{\omega}\in\mathbb{R}^n, the
distance between two points
P = (p_1, p_2, ..., p_n)
and
Q = (q_1, q_2, ..., q_n)
is defined as
max_i |\omega_i * (p_i - q_i)|
|
| WeightedManhattenMetricQ |
Weighted Manhattan distance metric for vector types.
Given a vector of weights \mathbf{\omega}\in\mathbb{R}^n ,
the distance between two points
P = (p_1, p_2, ..., p_n)
and
Q = (q_1, q_2, ..., q_n)
is defined as
\sum_{i=1}^{n} |\omega_i * (p_i - q_i)| .
|
| WeightedManhattenMetricVector2D |
Weighted Manhattan distance metric for vector types.
Given a vector of weights \mathbf{\omega}\in\mathbb{R}^n ,
the distance between two points
P = (p_1, p_2, ..., p_n)
and
Q = (q_1, q_2, ..., q_n)
is defined as
\sum_{i=1}^{n} |\omega_i * (p_i - q_i)| .
|
| WeightedManhattenMetricVector3D |
Weighted Manhattan distance metric for vector types.
Given a vector of weights \mathbf{\omega}\in\mathbb{R}^n ,
the distance between two points
P = (p_1, p_2, ..., p_n)
and
Q = (q_1, q_2, ..., q_n)
is defined as
\sum_{i=1}^{n} |\omega_i * (p_i - q_i)| .
|
| Wrench6D |
Class for representing 6 degrees of freedom wrenches.
\mathbf{\nu} =
\left[
\begin{array}{c}
f_x\\
f_y\\
f_z\\
\tau_x\\
\tau_y\\
\tau_z
\end{array}
\right]
A Wrench is the description of a frames linear force and rotational torque
with respect to some reference frame.
|
| Wrench6Df |
Class for representing 6 degrees of freedom wrenches.
\mathbf{\nu} =
\left[
\begin{array}{c}
f_x\\
f_y\\
f_z\\
\tau_x\\
\tau_y\\
\tau_z
\end{array}
\right]
A Wrench is the description of a frames linear force and rotational torque
with respect to some reference frame.
|