Skip to main content

PragProWriBlockMo

PragProWriMo has been even more challenging than I'd feared thanks to my sub-gnat concentration span and memory like a... you know, round thing with holes. While others have been trotting out chapter outlines, finding their voice and defining their readership, I've been shuffling along the beach of irrelevancy and gazing out at the ocean of unfinishedness.

It's amazing / pathetic / pathological (select all that apply) just how intimidating this simple daily writing exercise has become. The main problem has been the notion of a book hovering over the writing. No matter how many times I've told myself to treat the writing as a pump-priming exercise rather than an examination, I haven't been able to shake the anxiety of not "seeing the book" in my mind's eye.

But I will not surrender ! Well, that's not quite true because I did a few days ago, giving up on the whole thing as too hard. Now though, I'm putting the white flag back in the cupboard and making a new start. Rather than imagining the goal as a book I'm going to structure it as a set of short web tutorials.

I wonder if I can count this post ?

Comments

  1. You can count everything you write during the month of November toward PragProWriMo! Why not? I counted the ASCII art I drew inline in my writing because I was too lazy to pull up a drawing program.

    Good luck!

    ReplyDelete

Post a Comment

Popular posts from this blog

Fitting an ellipse to point data

Some time ago I wrote an R function to fit an ellipse to point data, using an algorithm developed by Radim Halíř and Jan Flusser 1 in Matlab, and posted it to the r-help list . The implementation was a bit hacky, returning odd results for some data. A couple of days ago, an email arrived from John Minter asking for a pointer to the original code. I replied with a link and mentioned that I'd be interested to know if John made any improvements to the code. About ten minutes later, John emailed again with a much improved version ! Not only is it more reliable, but also more efficient. So with many thanks to John, here is the improved code: fit.ellipse <- function (x, y = NULL) { # from: # http://r.789695.n4.nabble.com/Fitting-a-half-ellipse-curve-tp2719037p2720560.html # # Least squares fitting of an ellipse to point data # using the algorithm described in: # Radim Halir & Jan Flusser. 1998. # Numerically stable direct least squares fitting of ellipses

Circle packing in R (again)

Back in 2010 I posted some R code for circle packing . Now, just five years later, I've ported the code to Rcpp and created a little package which you can find at GitHub . The main function is circleLayout which takes a set of overlapping circles and tries to find a non-overlapping arrangement for them. Here's an example: And here's the code: # Create some random circles, positioned within the central portion # of a bounding square, with smaller circles being more common than # larger ones. ncircles <- 200 limits <- c(-50, 50) inset <- diff(limits) / 3 rmax <- 20 xyr <- data.frame( x = runif(ncircles, min(limits) + inset, max(limits) - inset), y = runif(ncircles, min(limits) + inset, max(limits) - inset), r = rbeta(ncircles, 1, 10) * rmax) # Next, we use the `circleLayout` function to try to find a non-overlapping # arrangement, allowing the circles to occupy any part of the bounding square. # The returned value is a list with elements for

Graph-based circle packing

The previous two posts showed examples of a simple circle packing algorithm using the packcircles package (available from CRAN and GitHub ). The algorithm involved iterative pair-repulsion to jiggle the circles until (hopefully) a non-overlapping arrangement emerged. In this post we'll look an alternative approach. An algorithm to find an arrangement of circles satisfying a prior specification of circle sizes and tangencies was described by Collins and Stephenson in their 2003 paper in Computation Geometry Theory and Applications. A version of their algorithm was implemented in Python by David Eppstein as part of his PADS library (see CirclePack.py ). I've now ported David's version to R/Rcpp and included it in the packcircles package. In the figure below, the graph on the left represents the desired pattern of circle tangencies: e.g. circle 7 should touch all of, and only, circles 1, 2, 6 and 8. Circles 5, 7, 8 and 9 are internal , while the remaining circles are exter