Difference between revisions of "Enclosing Circle Algorithm"
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Revision as of 16:31, 16 February 2017
Enclosing Circle Algorithm | |
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Contents
Overview
This program takes in a set of points and the minimum number that should be included inside a unit, and returns circles of the smallest total area which encompass all of the data points. Function make_circle and all of its helper functions were taken from https://www.nayuki.io/res/smallest-enclosing-circle/smallestenclosingcircle.py.
Input: A sequence of pairs of floats or ints, e.g. [(0,5), (3.1,-2.7)].
Output: A triple of floats representing a circle.
Returns the smallest circle that encloses all the given points. Runs in expected O(n) time, randomized.
Algorithm Description
Location
The original script is located in:
E:\McNair\Software\CodeBase\EnclosingCircle.py
Applications
VC Data
The Enclosing Circle Algorithm will be applied to VC data acquired through the SDC Platinum database. The script makes use of the Python GeoPy GeoCoder to get latitude and longitude coordinates to be used by the Enclosing Circle Algorithm.
Geopy Geocoder User Agreements can be found here.
The relevant files are located in:
E:\McNair\Projects\Accelerators\Enclosing_Circle
The results may eventually be plotted to a graph using python as well. Here is documentation for a python library called basemap.
CURRENT STATUS: Bug fixes needed in EnclosingCircle.py. The program errors with a key error on line 187 in cases where n is not a multiple of the length of the dataset. I made some temporary fixes to the enclosing circle file located in the above directory, but I am not certain if it is a permanent fix.
Speeding up with C
With the large amount of VC data we have, the enclosing circle algorithm would take an extremely long amount of time to run (on the order of weeks/months). If we can compile the code into C, we can speed up runtime dramatically. I've listed some possible sources for running python code as C.