A FITS full of dollars

Obviously the data is there and kstars does a good job of integration. I just need to figure out how to use what is already done and extend it a bit with some python.

This is a reasonable start and as a guess, the ascent from chaos in the galaxy requires that something be sacrificed to the queen of the holy dark and as I see it, we are on the altar and 120k years is not a lot of time to make a choice this big. Perhaps this is the real ringworld and the flight of the Peirson's Puppeteers?

Reference to Sloan data.

I have decided to bite the bullet and make a python application that snarfs the FITS data from the net and does the necessary manipulation to find specific traits that I find relevant using various methods including OpenCV on images. I want to establish a list of sources that can be downloaded and explored and then deleted as the volume of data is too large. If I had a petabyte drive I would just keep the data for my next analysis. Perhaps I can schedule several tests at once on the data before I move on to another file.

CONTINUING DEVELOPMENTS: I already have a fits viewer in python and it can be extended using the python web-kit and some xml magic. It seems that what I should generate is a parametric relationship of the universe with it dependent sets. While rewriting the "einstein" game I developed methods for set inclusion and exclusion and association as well as spatial relationship analysis. Though it is more complex, the parametric solution of the universe is a worthwhile model IMHO. Given that I have some unique perspective on the relationships in terms of gravity, it seems that a model could ( will ) be devised that uses the relationships based on physical laws to determine the validity of the relationships and develop a 4 dimensional view of the universe as seen from various temporal and spatial angles.

By establishing a matrix that is devised from the information it would automatically compensate for new data to establish a whole, based on the laws of physics and some short cuts to deal with the scale of various elements. It is then presented as a model in OpenGL which can navigated at scales and reflect variations on the base assumptions. By making the rules that govern different effects fungible, it is possible to explore what effect a different cosmological model generates and compute a probability that it fits the data observed.

It serves to create the same type of information interface that I am building for a wiki that naturally exhibits the dependent relationships of concepts and automatically extends the associations based on their n-dimensional characterization.

As a template it also serves to use data points from genotype to phenotype association in this same way to correlate and confirm the association of a specific gene or protein to the expressed phenotype of an organism. The same types of relationships exist in the proteome of an organism and by establishing a generalized approach I hope to use it for many different purposes including web analysis of the structural relationship of data.

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