Coordinate System: Rotating 2D & 3D Axes & Impact on Directed Cosines

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SUMMARY

The discussion focuses on the transformation of coordinate axes in both 2D and 3D geometries and its effect on directed cosines. It confirms that rotating the X, Y, and Z axes in 3D geometry is indeed possible and directly impacts the numerical values of directed cosines. The relationship between the unit direction vector and the unit coordinate vectors is established through the dot product, leading to the equations for the directed cosines. Additionally, it is noted that the transformation of directional cosines is achieved through the application of a rotation matrix.

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  • Understanding of 2D and 3D coordinate systems
  • Familiarity with rotation matrices
  • Knowledge of unit vectors and their properties
  • Basic concepts of dot products in vector mathematics
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  • Study the properties and applications of rotation matrices in 3D geometry
  • Learn about the derivation and application of directed cosines
  • Explore transformations in coordinate systems using linear algebra
  • Investigate the implications of axis rotation on vector projections
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paragchitnis
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Co-ordinate axes can be drawn on plane or in space. In case of plane geometry (2D-geometry) the two axes, X-axis and Y-axis, can be rotated through some angle. For this transformation of axes we get the relation between the co-ordinates of a point in old and new system. Is this transformation is possible in 3D geometry (Rotation of X,Y,Z-axes)? If yes, then will it affect the numerical value of Directed Cosines of a fixed line?
 
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Yes, of course.
One way to think of the direction cosines is to consider the dot product of the (unit) direction vector in the direction of the line with the unit coordinate vectors which gives the coordinate values:

\mathbf{\hat{v}}\cdot\mathbf{\hat{\imath}} = \cos(\theta_x) = v_x
\mathbf{\hat{v}}\cdot \mathbf{\hat{\jmath}} = \cos(\theta_y) = v_y
\mathbf{\hat{v}}\cdot \mathbf{\hat{k}} = \cos(\theta_z) = v_z

Rotations of the axes affects the 3 components via multiplication by a rotation matrix and so the same matrix will transform the directional cosines.
 
Thank you very much
 

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