Field Operation Proposal
Goals
1. Draw a handy 3D Rift map.
2. Find a potential crossing within the sparsest area of the Formidine Rift (Ketchup Zone on my map
https://i.imgur.com/t0k12tz.png).
3. Have a complete view of the Rift, not limited by the short spawn range of the GalMap.
4. Have an automatically calculated and visual rough star density indicator on a map.
5. Be able to add any marker we want (like the RR Line).
Way
1) The data gathering
Given the purpose of this map, we don't need extremely precise coordinates. We don't collect galactic data like EDSM. We only need coordinates with a 10ly accuracy.
To do this, two ways.
a. We navigate through cubes of 10x10x10ly and write down all the systems there, regardless of their position in the cube itself.
Probable useful requirement: a pre-prepared spreadsheet with formula-generated coordinates for each 10ly cube, then we can only Alt-Tab and add the systems names in order.
b. Alot and others are currently working on solving the naming pattern of the systems, from which we (already are, partly) will be able to derive approximate coordinates. It is already doable for Ax-x names with coordinates accurate down to 5ly in every direction (so in a 10ly cube), but these are unscoopables and (unfortunately, for once!) there are about none in the Ketchup. Bx-x names are pinpointable down to a 20ly cube, which would be a useful visual landmark. Pretty soon we would be able to pinpoint system name suffix A to D, thus including G,K,M stars, the most numerous in the area, with derived coordinates down to a 100ly cube, which would be good enough to have a rough sketch of the star density in there. Then, by selecting 100ly cubes, we would, if necessary, manually improve the accuracy with the abovementioned method, to subcubes of 10ly sides.
But since we don't know all the systems in a sector, this will only be that useful. So, to optimize the handiwork, we could start by mapping the M class stars, or something. We need organization, and as many people as possible.
2) The data processing
This is where we need a help. We'd use Python to process the data and generate a 3D map (using PyQtGraph (
http://www.pyqtgraph.org) or 3DS Max, not sure yet) from the lists of systems-coordinates.
3) The Cube Map
EfilOne has volunteered to take care of the 3D stuff - seems like it's really easy.
4) Web Integration
Finally, we need that map accessible via web browser, but given the tool used for 3D rendering, it doesn't seem to be a problem.
5) The difference with EDSM/EDD
We dont trilaterate, and we don't need to be in the system. It's GalMap work only.
6) The result
A 3D wireframe map of the Ketchup Zone, subdivided by cubes of custom size, with the GalMap coordinates, filled with all the systems we fed there, accessible via a web browser.