BikeClusters

A collection of programs to analyse clusters within urban areas as produced by usage patterns of hire bicycle systems. Requires the output of bike-correlations, in particular the correlation (R2) and distance matrices. Currently able to analyse data from London, NYC, Boston, Chicago, and Washington DC, using cluster methods of ward, complete, k-means, and skater.

Analyses are ultimately based on comparisons of the total distances ridden within clusters to equivalent distances ridden between them.

Use makefile to build. Note that the C++ routines can take a long time to execute, and so are built as stand-alones, rather than being integrated into R. The two routines are ClustersNeutral, which generates neutrally expected values of inter- and intra-cluster distance, and Clusters Actual, which does the corresponding calculations for the observed rides.

All calculations are repeated for a range of numbers of clusters (up to 100, except skater only up to 50).

Usage for a given city and clustering method:

1. >./ClustersNeutral city
2. R> get.clusters (city method)
3. R> get.skater.groups (city, method)
4. >./ClustersActual city
5. R> calc.pnc (city, method
6. R> clust.sig (city, method)
7. >/randomClusters city direction (0/1)

See aaaread-this for further details.

build:

1. cd ./build
2. cmake ..
3. make

Build fails because of CGAL/Exact_predicates!