Finding an Orthogonal Transformation for Mapping Points

In summary, the conversation discusses the process of finding an orthogonal transformation matrix that maps the point (0,5) to the point (3,4). The transformation matrix is derived using the equation M = [cos(2θ) sin(2θ); sin(2θ) -cos(2θ)]. However, there are discrepancies in the results obtained when solving for the angle θ using different methods. The conversation also explores the derivation process and discusses the reasoning behind certain steps.
  • #1
Lunat1c
66
0
Hi,

I am trying to find an orthogonal transformation that maps the point (0,5) to the point (3,4).
Now, I found that the transformation matrix M for a reflection in the line y=mx is as follows:

[tex] M = \left(
\begin{array}{cc}
cos(2\theta) & sin(2\theta)\\
sin(2\theta) & -cos(2\theta)
\end{array}
\right)
[/tex]

[tex] \therefore \left(
\begin{array}{cc}
cos(2\theta) & sin(2\theta)\\
sin(2\theta) & -cos(2\theta)
\end{array}
\right)
\left(
\begin{array}{c} 0 \\
5 \\
\end{array}
\right)=
\left(
\begin{array}{c} 3 \\
4\\
\end{array}
\right)

[/tex]

However this means that
[tex] 5sin(2\theta)=3 [/tex]
[tex] -5cos(2\theta)=4 [/tex]

[tex] \frac{5sin2\theta}{-5cos2\theta} = 3/4 [/tex]
[tex] \theta = arctan(-\frac{3}{4}) [/tex]
[tex]\therefore m=\frac{3}{4}
[/tex]

I noticed that if instead I find the angle by taking [tex] 5sin(2\theta)=3 [/tex]
[tex] \theta = 18.43 and tan(\theta)=0.333 [/tex]
Or [tex] -5cos(2\theta)=4 [/tex]
[tex] \theta = 71.56 [/tex] and [tex] tan(71.56)=3[/tex]

Why don't they all yield the same result? isn't this like solving a system of linear equations?

Having said this, I tried to derive the matrix of the transformation myself. I drew the basis vectors i(1,0) and j(0,1) and checked what their new coordinates would be when reflected in a line that makes an angle [tex] \theta [/tex] with the x-axis.

When considering the j(0,1) vector, the angle between j and j' & that between i and i' is [tex] 2\theta [/tex].

The new coordinates for i' would be:
[tex] x = cos(2\theta)
y = sin(2\theta) [/tex]

and those for j' would be:

[tex] x = sin(2\theta)
y = cos(2\theta).
[/tex]

Why would you say that for j' [tex] y=-cos(2\theta)? [/tex]
The only way j' will have negative y coordinates is if the gradient of the line is >45, and if this happens, cos(2x) will be negative (since 90 < 2x < 180, cos(2x) is negative).

Sorry for the very long post, I just wanted to show what I tried before asking any questions. With this being said, could someone please tell me what's wrong with the derivation I attempted? And most of all, why the first one doesn't work?

Thank you!
 
Last edited:
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  • #2
Lunat1c said:
Hi,

I am trying to find an orthogonal transformation that maps the point (0,5) to the point (3,4).
Now, I found that the transformation matrix M for a reflection in the line y=mx is as follows:

[tex] M = \left(
\begin{array}{cc}
cos(2\theta) & sin(2\theta)\\
sin(2\theta) & -cos(2\theta)
\end{array}
\right)
[/tex]

[tex] \therefore \left(
\begin{array}{cc}
cos(2\theta) & sin(2\theta)\\
sin(2\theta) & -cos(2\theta)
\end{array}
\right)
\left(
\begin{array}{c} 0 \\
5 \\
\end{array}
\right)=
\left(
\begin{array}{c} 3 \\
4\\
\end{array}
\right)

[/tex]

However this means that
[tex] 5sin(2\theta)=3 [/tex]
[tex] -5cos(2\theta)=4 [/tex]

[tex] \frac{5sin2\theta}{-5cos2\theta} = 3/4 [/tex]
[tex] \theta = arctan(-\frac{3}{4}) [/tex]
NO, this is 2[itex]\theta[/itex]

[tex]\therefore m=\frac{3}{4}
[/tex]

I noticed that if instead I find the angle by taking [tex] 5sin(2\theta)=3 [/tex]
[tex] \theta = 18.43 and tan(\theta)=0.333 [/tex]
[itex]2\theta= 36.86[/itex] and [itex]tan(36.86)= 0.75[/itex]

Or [tex] -5cos(2\theta)=4 [/tex]
[tex] \theta = 71.56 [/tex]
NO, cos(71.56)= 0.3163, nowhere near -.8. I don't know how you got this. If [itex]cos(\theta)= -.8[/itex] then [itex]\theta= 143[/itex] or [itex]\theta= -37[/itex]. tan(143)= -.75 but tan(-37)= .75.

Why don't they all yield the same result? isn't this like solving a system of linear equations?

Having said this, I tried to derive the matrix of the transformation myself. I drew the basis vectors i(1,0) and j(0,1) and checked what their new coordinates would be when reflected in a line that makes an angle [tex] \theta [/tex] with the x-axis.

When considering the j(0,1) vector, the angle between j and j' & that between i and i' is [tex] 2\theta [/tex].

The new coordinates for i' would be:
[tex] x = cos(2\theta)
y = sin(2\theta) [/tex]

and those for j' would be:

[tex] x = sin(2\theta)
y = cos(2\theta).
[/tex]

Why would you say that for j' [tex] y=-cos(2\theta)? [/tex]
The only way j' will have negative y coordinates is if the gradient of the line is >45, and if this happens, cos(2x) will be negative (since 90 < 2x < 180, cos(2x) is negative).

Sorry for the very long post, I just wanted to show what I tried before asking any questions. With this being said, could someone please tell me what's wrong with the derivation I attempted? And most of all, why the first one doesn't work?

Thank you!
 
  • #3
The gradient of the line is [tex] tan(\theta) [/itex] not [tex] tan(2\theta) [/itex], or am I wrong?

[tex]2\theta [/itex] is the angle with which the vectors i and j will be rotated when they're reflected in the line [tex] y=(tan\theta)x [/itex].
 
  • #4
HallsofIvy said:
NO, this is 2[itex]\theta[/itex][itex]2\theta= 36.86[/itex] and [itex]tan(36.86)= 0.75[/itex]

Ok fair enough, I meant [tex] tan(2\theta) = -\frac{3}{4} [/itex]
[tex] \therefore \theta = \frac{arctan(-\frac{3}{4})}{2} [/itex].

NO, cos(71.56)= 0.3163, nowhere near -.8. I don't know how you got this. If [itex]cos(\theta)= -.8[/itex] then [itex]\theta= 143[/itex] or [itex]\theta= -37[/itex]. tan(143)= -.75 but tan(-37)= .75.

[tex] -5cos(2\theta)=4 [/itex]
then [tex] cos(2\theta) = -4/5 = -0.8 [/itex]
therefore [tex] \theta = \frac{arccos(-0.8)}{2} = 71.56 [/itex]
and hence [tex] cos(2 * 71.56) = -0.8 [/itex]
 
Last edited:

FAQ: Finding an Orthogonal Transformation for Mapping Points

What is a linear transformation?

A linear transformation is a mathematical function that maps one vector space to another in a way that preserves the basic structure of the original space. This means that the transformation must follow two rules: 1) The transformation must be closed under addition, meaning that the sum of any two vectors in the original space must also be mapped to a sum in the new space. 2) The transformation must be closed under scalar multiplication, meaning that multiplying a vector in the original space by a constant must also result in a vector in the new space.

What is the difference between linear and non-linear transformations?

A linear transformation follows the two rules mentioned above (closure under addition and scalar multiplication), while a non-linear transformation does not. This means that a non-linear transformation can result in a different structure in the new space, such as a curved or twisted shape, while a linear transformation will always maintain the original structure of the space.

What are some real-world applications of linear transformations?

Linear transformations have many applications in fields such as physics, engineering, and computer graphics. They are used to describe physical phenomena such as rotation, translation, and scaling, and are also used in data analysis and machine learning to transform and manipulate data.

What is the "matrix representation" of a linear transformation?

The matrix representation of a linear transformation is a way to represent the transformation using a matrix. This matrix is determined by the transformation's effect on a set of basis vectors in the original space. The columns of the matrix represent the images of the basis vectors in the new space.

How can I determine if a transformation is linear?

To determine if a transformation is linear, you can check if it follows the two rules mentioned above: closure under addition and scalar multiplication. You can also check if the transformation can be represented by a matrix, as this is a characteristic of linear transformations. Additionally, you can use the properties of linear transformations, such as the preservation of lines and the origin, to determine linearity.

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