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An infinitesimal rotation matrix or differential rotation matrix is a matrix representing an infinitely small rotation. While a rotation matrix is an orthogonal matrix representing an element of (the special orthogonal group), the differential of a rotation is a skew-symmetric matrix in the tangent space (the special orthogonal Lie algebra), which is not itself a rotation matrix. An infinitesimal rotation matrix has the form where is the identity matrix, is vanishingly small, and For example, if representing an infinitesimal three-dimensional rotation about the x-axis, a basis element of The computation rules for infinitesimal rotation matrices are as usual except that infinitesimals of second order are routinely dropped. With these rules, these matrices do not satisfy all the same properties as ordinary finite rotation matrices under the usual treatment of infinitesimals. It turns out that the order in which infinitesimal rotations are applied is irrelevant. An infinitesimal rotation matrix is a skew-symmetric matrix where: As any rotation matrix has a single real eigenvalue, which is equal to +1, the corresponding eigenvector defines the rotation axis. Its module defines an infinitesimal angular displacement. The shape of the matrix is as follows: We can introduce here the associated infinitesimal rotation tensor: Such that its associated rotation matrix is . When it is divided by the time, this will yield the angular velocity vector. These matrices do not satisfy all the same properties as ordinary finite rotation matrices under the usual treatment of infinitesimals . To understand what this means, consider First, test the orthogonality condition, QTQ = I. The product is differing from an identity matrix by second order infinitesimals, discarded here. So, to first order, an infinitesimal rotation matrix is an orthogonal matrix. Next, examine the square of the matrix, Again discarding second order effects, note that the angle simply doubles.
def rotation_matrix(d):
"""
Calculates a rotation matrix given a vector d. The direction of d
corresponds to the rotation axis. The length of d corresponds to
the sin of the angle of rotation.
Variant of: http://mail.scipy.org/pipermail/numpy-discuss
[2]Paolo Prandoni, [3]LCAV, EPFL
The concept of "basis" for a vector space is one of the most profound
and fruitful ideas in linear algebra. Basis vectors are the "building
blocks" that all other vectors are built from; by "disassembling" a
vector into a linear combination of basis elements we are able to "look
inside" the vector and highlight many of its relevant features.
A vector space has an infinite number o