Fastgrid

This summer I worked on creating a stronger version of idea in lisp. The first code was fastmap which was the 2D point generator. Then instead of storing the data in a tree structure, they were stored in a grid structure. The size and number of quadrantas was determined by the square-root of the amount of the data divided by two. When looking to cluster the quadrants, the gridclus function could take a look at all directions surrounding it to find its' closest neighbors.
Then the neighbors of the neighbors were searched for acceptance rate of 0.5 also. Gaps was then coded to compare clusters and locate the closet neighbor feared by the cluster being looked at. Finally, Keys was created to look for the best treatment. It used (b/B)^2/((b/B) +(r/R)) to determine the best rule overall. b is the frequency the rules appears in the 20% best, while r is the frequency that the rule appears in the 80% rest. While all of these functions were coded up individually, they are not yielding the correct results.

As seen from the image, the grid still contains too many clusters. When taking a closer look, it can be seen tath several of tehse clusters should be mereged t into one. The gridclus error is the start of the problems with the different functions interacting.


This example is from the velocity 1.6 data.




There are 30 clusters with the most in one cluster equally 4 quadrants.
An example of the printout when keys is run on this data follows:

KEYS
(CLUSTER AB)
(ENVIES AL)
(TREATMENT #((0.0 $MOA)))
KEYS
(CLUSTER AL)
(ENVIES AZ)
(TREATMENT #((0.0 $NOC)))
KEYS
(CLUSTER AG)
(ENVIES AB)
(TREATMENT #((0.0 $LCOM)))