Parallel Enclosing Circle Algorithm - Revision history

Ed at 17:47, 21 September 2020

2020-09-21T17:47:40Z

2020-09-21T17:34:34Z

2020-09-20T17:20:07Z

2020-09-20T17:12:20Z

2017-12-01T19:12:58Z

2017-11-27T20:23:39Z

Example Usage

2017-11-27T20:20:13Z

Example Usage

2017-11-27T20:18:14Z

Progress on the bug

2017-11-17T22:49:00Z

St. Louis bug

2017-11-13T19:09:11Z

Bugs/Issues

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 {{Project
-|Has project output=
+|Has project output=Tool
 |Has sponsor=McNair Center
 |Has title=Parallel Enclosing Circle Algorithm

@@ Line 1: / Line 1: @@
 {{Project
 |Has sponsor=McNair Center
 |Has title=Parallel Enclosing Circle Algorithm

@@ Line 1: / Line 1: @@
 {{Project
 |Has title=Parallel Enclosing Circle Algorithm
 |Has owner=Oliver Chang,

@@ Line 1: / Line 1: @@
-{{McNair Projects
+{{Project
 |Has title=Parallel Enclosing Circle Algorithm
 |Has owner=Oliver Chang,

@@ Line 9: / Line 9: @@
 A thin-wrapper around [[Enclosing_Circle_Algorithm_(Rework)|the enclosing circle algorithm]] which allows for instance-level parallelization.
-This project consists of the python files in <code>E:\McNair\Projects\OliverLovesCircles\src\python</code>.
+This project consists of the python files in <code>E:\McNair\Projects\OliverLovesCircles\src\python</code>. There is another version of the project with plotting functionality that uses a slightly different approach (removes duplicate points and uses their counts before running the algorithm) in <code>E:\McNair\Projects\KyranLovesCircles\src\python</code>.
 Parallelization is implemented via Python2's [https://docs.python.org/2/library/subprocess.html#subprocess.Popen <code>subprocess.open()</code>] which is non-blocking and available in the standard library.

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 ==== Running on already split files ====
-<nowiki>
+ <nowiki>
 $ python vc_circles.py</nowiki>

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 === Example Usage ===
   <nowiki>
 $ python vc_circles.py --infile E:/McNair/Projects/OliverLovesCircles/CoLevelForCirclesNotRunGTE200.txt</nowiki>
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 <code>placestate, place, statecode, year, latitude, longitude, coname, datefirstinv, placens, geoid, city</code>
 This command will populate (and overwrite) any files in <code>data/</code>, <code>out/</code>, and <code>reports/</code>.
 == Bugs/Issues ==

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 === Progress on the bug ===
 # Removing duplicate points from the data actually removes all of the errors, but this doesn't give you the solution with the smallest area.
-# I tried removing duplicates but keeping track of a "count," though this reintroduces errors.
+# I tried removing duplicates but keeping track of a "count."
 # I narrowed down the bug to the constrained_kmeans method in ckmeans.py [https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/tr-2000-65.pdf (paper here)]
 ## For some reason, this returns clusters with smaller numbers of points than n

← Older revision		Revision as of 22:49, 17 November 2017
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	This image shows a rendering of the results of running St. Louis. There are four circles (the centers of circles are green dots), but two have radii of 0.0.		This image shows a rendering of the results of running St. Louis. There are four circles (the centers of circles are green dots), but two have radii of 0.0.
		+
		+	=== Progress on the bug ===
		+	# Removing duplicate points from the data actually removes all of the errors, but this doesn't give you the solution with the smallest area.
		+	# I tried removing duplicates but keeping track of a "count," though this reintroduces errors.
		+	## % error before change (n=997 sample, A-Carlsbad):
		+	## % error after change (n=997 sample):
		+	# I narrowed down the bug to the constrained_kmeans method in ckmeans.py [https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/tr-2000-65.pdf (paper here)]
		+	## For some reason, this returns clusters with smaller numbers of points than n
		+	## [http://adared.ch/constrained-k-means-implementation-in-python/ This is a good overview of the algorithm]
		+	# I wrote a plotter, the plot method in circles.py

	== Related Pages ==		== Related Pages ==

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 # Some place/state/year combinations do not run to completion regardless of how tractable the number of points
 # How to merge small enclosing circles? This is a better measure of agglomeration regardless
 # How to separate outliers?
 == Makeshift way to plot circles ==