E. Ariño de la Rubia earino

I hereby claim:

I am earino on github.
I am earino (https://keybase.io/earino) on keybase.
I have a public key whose fingerprint is EC06 4396 DCB2 701F 2747 9DD5 32A3 4E21 1D49 484A

To claim this, I am signing this object:

	from pyspark.mllib.classification import LogisticRegressionWithSGD
	from numpy import array

	# Load and parse the data
	data = sc.textFile("mllib/data/sample_svm_data.txt")
	parsedData = data.map(lambda line: array([float(x) for x in line.split(' ')]))
	model = LogisticRegressionWithSGD.train(parsedData)

	# Build the model
	labelsAndPreds = parsedData.map(lambda point: (int(point.item(0)),

	/* from http://madebyevan.com/webgl-water/water.js
	used in the awesome WebGL water demo
	http://madebyevan.com/webgl-water/*/

	this.dropShader = new GL.Shader(vertexShader, '\
	const float PI = 3.141592653589793;\
	uniform sampler2D texture;\
	uniform vec2 center;\
	uniform float radius;\
	uniform float strength;\

	package LedgerSMB::Currency;
	use Moose;
	with 'LedgerSMB::PGOSimple::Role', 'LedgerSMB::MooseTypes';

	use PGObject::Util::DBMethod;

	sub _set_prefix { 'currency__' }

	has id => (is => 'rw', isa => 'Int', required => '0');
	has symbol => (is => 'ro', isa => 'Str', required => '1');

	print("start.207")
	for (i in 1:5) {
	t <- get(paste0("d", i));
	y <- factor(t[,c("start.207")], levels=c("1", "0"))
	x <- t[,c("stop.165","stop.166","stop.167","stop.168","stop.169","stop.185",
	"stop.186","stop.187","stop.188","stop.189","stop.205","stop.206",
	"stop.207","stop.208","stop.209","stop.225","stop.226","stop.227",
	"stop.228","stop.229","stop.245","stop.246","stop.247","stop.248","stop.249")]

	md <- train(x, y, method="rf", ntree=ntrees, trControl=trainControl(method="cv"))

	#that title doesn't get me on a list...
	use Parallel::ForkManager;
	use Data::Dumper;

	my @sleep = (
	10,
	60,
	60,
	60,
	60,

	joke_map <- function(states_to_highlight, title="", highlight_colors=c("#aaaaaa", "#ee0000")) {
	library(dplyr)
	library(ggplot2)
	library(RColorBrewer)
	library(maps)

	highlighting = data.frame(region=tolower(state.name[match(states_to_highlight, state.abb)]),
	highlight=TRUE)

	d = map_data("state") %>% left_join(highlighting, by="region")