Adjacency Matrix to Coordinate Transformations

In summary, the question is about finding the minimum number of points needed to transform an adjacency matrix into a coordinate matrix in terms of N given Euclidean space. The coordinate matrix is a set of coordinates of N vertices or nodes, and the adjacency matrix represents the distances between each pair of points. The distances may not be Euclidean distances, but could be distances over the surface of a spheroid. When dealing with Euclidean distances, the number of equations needed is equal to n(n-1)/2, while the number of unknowns is 2n. Therefore, the minimum number of points needed for 2D is 5 and for 3D is 7.
  • #1
lightfire
8
0
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?
 
Physics news on Phys.org
  • #2
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".
 
  • #3
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}
 
  • #4
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.
 
  • #5
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.
 

Related to Adjacency Matrix to Coordinate Transformations

1. What is an adjacency matrix?

An adjacency matrix is a mathematical representation of a graph or network. It is a square matrix that shows the connections or relationships between vertices or nodes in a graph.

2. What is a coordinate transformation?

A coordinate transformation is a mathematical process that involves changing the coordinates of a point or object from one reference system to another. This is often used in geometry and computer graphics to represent objects in different coordinate systems.

3. How do you convert an adjacency matrix to a coordinate transformation?

To convert an adjacency matrix to a coordinate transformation, you need to identify the vertices or nodes in the graph and assign them coordinates. Then, using the information in the adjacency matrix, you can determine the relationships between the vertices and create a coordinate transformation that represents the graph.

4. What are the benefits of using an adjacency matrix to coordinate transformation?

An adjacency matrix to coordinate transformation allows for efficient representation and manipulation of graph data. It also allows for the use of geometric and algebraic methods to analyze and solve problems related to the graph.

5. Can an adjacency matrix to coordinate transformation be used for directed graphs?

Yes, an adjacency matrix to coordinate transformation can be used for both undirected and directed graphs. In a directed graph, the edges or connections between nodes have a specific direction, and this information can be represented in the adjacency matrix as well as the coordinate transformation.

Similar threads

Replies
13
Views
2K
Replies
12
Views
2K
  • Classical Physics
Replies
7
Views
759
Replies
11
Views
1K
  • Differential Geometry
Replies
11
Views
4K
Replies
11
Views
4K
  • Special and General Relativity
Replies
5
Views
952
  • Differential Geometry
Replies
8
Views
3K
Replies
54
Views
4K
Replies
12
Views
3K
Back
Top