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/*
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This file is part of Magnum.
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Copyright © 2010, 2011, 2012, 2013, 2014
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Vladimír Vondruš <mosra@centrum.cz>
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Permission is hereby granted, free of charge, to any person obtaining a
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copy of this software and associated documentation files (the "Software"),
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to deal in the Software without restriction, including without limitation
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the rights to use, copy, modify, merge, publish, distribute, sublicense,
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and/or sell copies of the Software, and to permit persons to whom the
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Software is furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included
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in all copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
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THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
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FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
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DEALINGS IN THE SOFTWARE.
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*/
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namespace Magnum {
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/** @page transformations 2D and 3D transformations
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@brief Introduction to essential operations on vectors and points.
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- Previous page: @ref matrix-vector
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- Next page: @ref plugins
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Transformations are essential operations involved in scene management -- object
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relations, hierarchies, animations etc. They extend basic vectors and matrices
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in @ref Math namespace, see its documentation for more information about usage
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with CMake.
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@tableofcontents
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Magnum provides classes for transformations in both 2D and 3D. Each class is
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suited for different purposes, but their usage is nearly the same to make your
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life simpler. This page will explain the basic operation and differences
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between various representations.
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@section transformations-representation Representing transformations
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The first and most straightforward way to represent transformations is to use
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homogeneous transformation matrix, i.e. @ref Matrix3 for 2D and @ref Matrix4
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for 3D. The matrices are able to represent all possible types of
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transformations -- rotation, translation, scaling, reflection etc. and also
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projective transformation, thus they are used at the very core of graphics
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pipeline and are supported natively in OpenGL.
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On the other hand, matrices need 9 or 16 floats to represent the
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transformation, which has implications on both memory usage and performance
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(relatively slow matrix multiplication). It is also relatively hard to extract
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transformation properties (such as rotation angle/axis) from them, interpolate
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between them or compute inverse transformation. They suffer badly from
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so-called floating-point drift -- e.g. after a few combined rotations the
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transformation won't be pure rotation anymore, but will involve also a bit of
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scaling, shearing and whatnot.
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However, you can trade some transformation features for improved performance
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and better behavior -- for just a rotation you can use @ref Complex in 2D and
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@ref Quaternion in 3D, or @ref DualComplex and @ref DualQuaternion if you want
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also translation. It is not possible to represent scaling, reflection or other
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transformations with them, but they occupy only 2 or 4 floats (4 or 8 floats in
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dual versions), can be easily inverted and interpolated and have many other
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awesome properties. However, they are not magic so they also suffer slightly
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from floating-point drift, but not too much and the drift can be accounted for
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more easily than with matrices.
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@section transformations-types Transformation types
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Transformation matrices and (dual) complex numbers or quaternions have
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completely different internals, but they share the same API to achieve the same
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things, greatly simplifying their usage. In many cases it is even possible to
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hot-swap the transformation class type without changing any function calls.
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@subsection transformations-default Default (identity) transformation
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Default-constructed @ref Matrix3, @ref Matrix4, @ref Complex, @ref Quaternion,
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@ref DualComplex and @ref DualQuaternion represent identity transformation, so
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you don't need to worry about them in initialization.
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@subsection transformations-rotation Rotation
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2D rotation is represented solely by its angle in counterclockwise direction
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and rotation transformation can be created by calling @ref Matrix3::rotation(),
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@ref Complex::rotation() or @ref DualComplex::rotation(), for example:
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@code
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auto a = Matrix3::rotation(23.0_degf);
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auto b = Complex::rotation(Rad(Constants::pi()/2));
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auto c = DualComplex::rotation(-1.57_radf);
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@endcode
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3D rotation is represented by angle and (three-dimensional) axis. The rotation
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can be created by calling @ref Matrix4::rotation(), @ref Quaternion::rotation()
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or @ref DualQuaternion::rotation(). The axis must be always of unit length to
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avoid redundant normalization. Shortcuts @ref Vector3::xAxis(),
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@ref Vector3::yAxis() and @ref Vector3::zAxis() are provided for convenience.
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Matrix representation has also @ref Matrix4::rotationX(),
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@ref Matrix4::rotationY() and @ref Matrix4::rotationZ() which are faster than
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using the generic function for rotation around primary axes. Examples:
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@code
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auto a = Quaternion::rotation(60.0_degf, Vector3::xAxis());
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auto b = DualQuaternion::rotation(-1.0_degf, Vector3(1.0f, 0.5f, 3.0f).normalized());
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auto c = Matrix4::rotationZ(angle);
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@endcode
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Rotations are always around origin. Rotation about arbitrary point can be done
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by applying translation to have the point at origin, performing the rotation and
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then translating back. Read below for more information.
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@todo DualQuaternion and rotation around arbitrary axis
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@subsection transformations-translation Translation
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2D translation is defined by two-dimensional vector and can be created with
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@ref Matrix3::translation() or @ref DualComplex::translation(). You can use
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@ref Vector2::xAxis() or @ref Vector2::yAxis() to translate only along given
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axis. Examples:
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@code
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auto a = Matrix3::translation(Vector2::xAxis(-5.0f));
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auto b = DualComplex::translation({-1.0f, 0.5f});
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@endcode
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3D translation is defined by three-dimensional vector and can be created with
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@ref Matrix4::translation() or @ref DualQuaternion::translation(). You can use
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@ref Vector3::xAxis() and friends also here. Examples:
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@code
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auto a = Matrix4::translation(vector);
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auto b = DualQuaternion::translation(Vector3::zAxis(1.3f));
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@endcode
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@subsection transformations-scaling Scaling and reflection
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Scaling is defined by two- or three-dimensional vector and is represented by
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matrices. You can create it with @ref Matrix3::scaling() or @ref Matrix4::scaling().
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You can use @ref Vector3::xScale(), @ref Vector3::yScale(), @ref Vector3::zScale()
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or their 2D counterparts to scale along one axis and leave the rest unchanged
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or call explicit one-parameter vector constructor to scale uniformly on all
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axes. Examples:
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@code
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auto a = Matrix3::scaling(Vector2::xScale(2.0f));
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auto b = Matrix4::scaling({2.0f, -2.0f, 1.5f});
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auto c = Matrix4::scaling(Vector3(10.0f));
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@endcode
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Reflections are defined by normal along which to reflect (i.e., two- or
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three-dimensional vector of unit length) and they are also represented by
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matrices. Reflection is created with @ref Matrix3::reflection() or
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@ref Matrix4::reflection(). You can use @ref Vector3::xAxis() and friends also
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here. Examples:
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@code
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auto a = Matrix3::reflection(Vector2::yAxis());
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auto b = Matrix4::reflection(axis.normalized());
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@endcode
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Scaling and reflection is also done relative to origin, you can use method
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mentioned above to scale or reflect around arbitrary point.
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Scaling and reflection can be (to some extent) also represented by complex
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numbers and quaternions, but it has some bad properties and would make some
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operations more expensive, so it's not implemented.
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@subsection transformations-projective Projective transformations
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Projective transformations eploit the full potential of transformation
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matrices. In 2D there is only one projection type, which can be created with
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@ref Matrix3::projection() and it is defined by area which will be projected
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into unit rectangle. In 3D there is orthographic projection, created with
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@ref Matrix4::orthographicProjection() and defined by volume to project into
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unit cube, and perspective projection. Perspective projection is created with
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@ref Matrix4::perspectiveProjection() and is defined either by field-of-view,
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aspect ratio and distance to near and far plane of view frustum or by size of
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near plane, its distance and distance to far plane. Some examples:
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@code
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auto a = Matrix3::projection({4.0f, 3.0f});
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auto b = Matrix4::orthographicProjection({4.0f, 3.0f, 100.0f});
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auto c = Matrix4::perspectiveProjection(35.0_degf, 1.333f, 0.001f, 100.0f);
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@endcode
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@section transformations-composing Composing and inverting transformations
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Transformations (of the same representation) can be composed simply by
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multiplying them, it works the same for matrices, complex numbers, quaternions
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and their dual counterparts. Order of multiplication matters -- the
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transformation on the right-hand side of multiplication is applied first, the
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transformation on the left-hand side is applied second. For example, rotation
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followed by translation is done like this:
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@code
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auto a = DualComplex::translation(Vector2::yAxis(2.0f))*
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DualComplex::rotation(25.0_degf);
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auto b = Matrix4::translation(Vector3::yAxis(5.0f))*
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Matrix4::rotationY(25.0_degf);
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@endcode
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Inverse transformation can be computed using @ref Matrix3::inverted(),
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@ref Matrix4::inverted(), @ref Complex::inverted(), @ref Quaternion::inverted(),
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@ref DualComplex::inverted() or @ref DualQuaternion::inverted(). Matrix
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inversion is quite costly, so if your transformation involves only translation
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and rotation, you can use faster alternatives @ref Matrix3::invertedRigid() and
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@ref Matrix4::invertedRigid(). If you are sure that the (dual) complex number
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or (dual) quaternion is of unit length, you can use @ref Complex::invertedNormalized(),
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@ref Quaternion::invertedNormalized(), @ref DualComplex::invertedNormalized()
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or @ref DualQuaternion::invertedNormalized() which is a little bit faster,
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because it doesn't need to renormalize the result.
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@section transformations-transforming Transforming vectors and points
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Transformations can be used directly for transforming vectors and points.
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Vector transformation does not involve translation, in 2D can be done using
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@ref Matrix3::transformVector() and @ref Complex::transformVector(), in 3D
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using @ref Matrix4::transformVector() and @ref Quaternion::transformVector().
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For transformation with normalized quaternion you can use faster alternative
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@ref Quaternion::transformVectorNormalized(). Example:
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@code
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auto transformation = Matrix3::rotation(-30.0_degf)*Matrix3::scaling(Vector2(3.0f));
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Vector2 transformed = transformation.transformVector({1.5f, -7.9f});
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@endcode
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Point transformation involves also translation, in 2D is done with
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@ref Matrix3::transformPoint() and @ref DualComplex::transformPoint(), in 3D
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with @ref Matrix4::transformPoint() and @ref DualQuaternion::transformPoint().
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Also here you can use faster alternative @ref DualQuaternion::transformPointNormalized():
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@code
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auto transformation = DualQuaternion::rotation(-30.0_degf, Vector3::xAxis())*
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DualQuaternion::translation(Vector3::yAxis(3.0f));
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Vector3 transformed = transformation.transformPointNormalized({1.5f, 3.0f, -7.9f});
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@endcode
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@section transformations-properties Transformation properties and conversion
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It is possible to extract some transformation properties from transformation
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matrices, particularly translation vector, rotation/scaling part of the matrix
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(or pure rotation if the matrix has uniform scaling) and also base vectors:
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@code
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Matrix4 a;
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auto rotationScaling = transformation.rotationScaling();
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Vector3 up = transformation.up();
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Vector3 right = transformation.right();
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Matrix3 b;
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auto rotation = b.rotation();
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Float xTranslation = b.translation().x();
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@endcode
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Extracting scaling and rotation from arbitrary transformation matrices is
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harder and can be done using @ref Math::Algorithms::svd(). Extracting rotation
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angle (and axis in 3D) from rotation part is possible using by converting it to
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complex number or quaternion, see below.
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You can also recreate transformation matrix from rotation and translation
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parts:
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@code
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Matrix3 c = Matrix3::from(rotation, {1.0f, 3.0f});
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@endcode
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Complex numbers and quaternions are far better in this regard and they allow
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you to extract rotation angle using @ref Complex::angle() or
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@ref Quaternion::angle() or rotation axis in 3D using @ref Quaternion::axis().
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Their dual versions allow to extract both rotation and translation part using
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@link DualComplex::rotation() const @endlink, @link DualQuaternion::rotation() const @endlink,
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@link DualComplex::translation() const @endlink and
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@link DualQuaternion::translation() const @endlink.
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@todoc Remove workaround when Doxygen can handle const
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@code
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DualComplex a;
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Rad rotationAngle = a.rotation().angle();
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Vector2 translation = a.translation();
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Quaternion b;
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Vector3 rotationAxis = b.axis();
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@endcode
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You can convert Complex and Quaternion to rotation matrix using
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@ref Complex::toMatrix() and @ref Quaternion::toMatrix() or their dual version
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to rotation and translation matrix using @ref DualComplex::toMatrix() and
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@ref DualQuaternion::toMatrix():
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@code
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Quaternion a;
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auto rotation = Matrix4::from(a.toMatrix(), {});
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DualComplex b;
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Matrix3 transformation = b.toMatrix();
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@endcode
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Conversion the other way around is possible only from rotation matrices using
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@ref Complex::fromMatrix() or @ref Quaternion::fromMatrix() and from rotation
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and translation matrices using @ref DualComplex::fromMatrix() and
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@ref DualQuaternion::fromMatrix():
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@code
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Matrix3 rotation;
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auto a = Complex::fromMatrix(rotation.rotationScaling());
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Matrix4 transformation;
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auto b = DualQuaternion::fromMatrix(transformation);
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@endcode
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@section transformations-interpolation Transformation interpolation
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@todoc Write this when interpolation is done also for (dual) complex numbers and
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dual quaternions
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@section transformations-normalization Normalizing transformations
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When doing multiplicative transformations, e.g. adding rotating to an
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transformation many times during an animation, the resulting transformation will
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accumulate rounding errors and behave strangely. For transformation matrices
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this can't always be fixed, because they can represent any transformation (and
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thus no algorithm can't tell if the transformation is in expected form or not).
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If you restrict yourselves (e.g. only uniform scaling and no skew), the matrix
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can be reorthogonalized using @ref Math::Algorithms::gramSchmidtOrthogonalize()
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(or @ref Math::Algorithms::gramSchmidtOrthonormalize(), if you don't have any
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scaling). You can also use @ref Math::Algorithms::svd() to more precisely (but
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way more slowly) account for the drift. Example:
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@code
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Matrix4 transformation;
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Math::Algorithms::gramSchmidtOrthonormalizeInPlace(transformation);
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@endcode
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For quaternions and complex number this problem can be solved far more easily
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using @ref Complex::normalized(), @ref Quaternion::normalized(),
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@ref DualComplex::normalized() and @ref DualQuaternion::normalized().
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Transformation quaternions and complex numbers are always of unit length, thus
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normalizing them reduces the drift.
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@code
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DualQuaternion transformation;
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transformation = transformation.normalized();
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@endcode
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- Previous page: @ref matrix-vector
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- Next page: @ref plugins
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*/
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}
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