Adjacency Matrix to Coordinate Transformations

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Discussion Overview

The discussion revolves around the transformation of an NxN adjacency matrix into a coordinate matrix, particularly in the context of map-making and the implications of Euclidean versus non-Euclidean spaces. Participants explore the minimum number of points required for this transformation and the nature of the matrices involved.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested

Main Points Raised

  • One participant questions the minimum number of points necessary to transform an NxN adjacency matrix into a coordinate matrix, specifically in Euclidean space.
  • Another participant seeks clarification on what constitutes a "coordinate matrix" and requests an example.
  • A participant defines a coordinate matrix as a set of coordinates for vertices or nodes and provides examples of both a coordinate matrix and its corresponding adjacency matrix.
  • Some participants note that traditional adjacency matrices consist of binary entries (0's and 1's), while the discussed version includes distances, raising questions about how to assign coordinates consistent with these distances.
  • There is a suggestion that the distances might not adhere to Euclidean principles, potentially involving distances over a spheroid surface, prompting a need for precise question formulation.
  • One participant describes a "weighted" adjacency matrix and discusses their findings regarding the number of equations and unknowns when applying the distance formula in two and three dimensions.
  • The same participant concludes that 5 points are necessary for 2D transformations and 7 points for 3D transformations to convert relative distances to coordinates.

Areas of Agreement / Disagreement

Participants express differing views on the nature of adjacency matrices and the requirements for transforming them into coordinate matrices. There is no consensus on the minimum number of points necessary, as some participants question the assumptions underlying the transformation.

Contextual Notes

Limitations include the dependence on definitions of adjacency matrices and coordinate matrices, as well as the unresolved nature of whether the distances discussed are Euclidean or not.

lightfire
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I've come up with a curious two-part question while working on a map program:

What is the minimum number of points necessary in order to transform an NxN adjacency matrix into a coordinate matrix in terms of N given Euclidean space?

As this question relates to map-making, where I don't believe the parallel-postulate holds, what is the minimum number of point necessary for this transformation on the Earth's space?
 
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lightfire said:
to transform an NxN adjacency matrix into a coordinate matrix in terms of N given Euclidean space?

You should explain what you mean by "a coordinate matrix in terms of N". Give an example of "a coordinate matrix".
 
A coordinate matrix is just a set of coordinates of N vertices or nodes.

So the points (1,2), (3,4), (5,6) are stored as:

\begin{pmatrix} 1 & 2\\ 3 & 4\\ 5 & 6 \end{pmatrix}

It's adjacency matrix is roughly:

\begin{pmatrix} 0 & 2.82 & 5.66\\ 2.82 & 0 & 2.82\\ 5.66 & 2.82 & 0 \end{pmatrix}

\begin{pmatrix} 0 & (81/2) & (321/2)\\ (81/2) & 0 & (81/2) \\ (321/2) & (81/2) & 0 \end{pmatrix}
 
In graph theory, the entries of "adjacency" matrix are only 0's or 1's. I think your version of an adjacency matrix gives the distance between each pair of points. So the question is how to assign the points (x,y) coordinates that are consistent with the distances. You hint that the distances might not be Euclidean distances, but could be something like distances over the surface of spheroid. I suppose the (x,y) coordinates might not be coordinates on a plane, but might be some other system. We need to state the question precisely.

If we are dealing with Euclidean distances on a plane, then each given distance between a pair of points gives an equation. If we arbitrarily assign point 1 to have coordinates (0,0) then the question is whether the simultaneous equations can be solved. Since you mention a "transformation" perhaps your question is more complicated that this.
 
Stephen Tashi said:
In graph theory, the entries of "adjacency" matrix are only 0's or 1's. I think your version of an adjacency matrix gives the distance between each pair of points. So the question is how to assign the points (x,y) coordinates that are consistent with the distances. You hint that the distances might not be Euclidean distances, but could be something like distances over the surface of spheroid. I suppose the (x,y) coordinates might not be coordinates on a plane, but might be some other system. We need to state the question precisely.

If we are dealing with Euclidean distances on a plane, then each given distance between a pair of points gives an equation. If we arbitrarily assign point 1 to have coordinates (0,0) then the question is whether the simultaneous equations can be solved. Since you mention a "transformation" perhaps your question is more complicated that this.

I'm technically talking about a "weighted" adjacency matrix that can be used to represent distances. I have figured out the problem for Euclidean space in two and three dimensions using the distance formula comparisons, as you suggested.

\[d_{12}^{2}=(y_{1}-y{2})^2 + (x_{1}-x_{2})^2\]

\[d_{14}^{2}=(y_{1}-y{4})^2 + (x_{1}-x_{4})^2\]

\[d_{34}^{2}=(y_{3}-y{4})^2 + (x_{3}-x_{4})^2\]

\[d_{45}^{2}=(y_{4}-y{5})^2 + (x_{4}-x_{5})^2\]

\[d_{35}^{2}=(y_{3}-y{5})^2 + (x_{3}-x_{5})^2\]

\[d_{25}^{2}=(y_{2}-y{5})^2 + (x_{2}-x_{5})^2\]

Carry this out to its conclusion reveals that the number of determined equations that are instantiations of the distance formula given N points is
\[Number Of Equations=\frac{n(n-1)}{2}\]

Whereas the number of unknowns is:
\[Number of Unknowns = 2n \]

This is because the only unknowns are the coordinates(assume two-dimensions coordinates)

So, the answer is 5 points for 2D and 7 for 3D in order to be able to specifically convert relative distances to coordinates.
 

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