floswald

#
#
# To build a target, enter:
#
#   make <target>
#
# Targets:
#
#   all		- builds exe, dbg
#   clean	- deletes all .o, .a, binaries, in source/ directory

floswald

This gist compares the performance of Julia, Nim, C++ and R - the latter using either POMP, or LibBi in a simple simulation of an SIR epidemiological model. In addition to keeping track of susceptibles, infecteds and recovereds, I also store the cumulative number of infections. Time moves in discrete steps, and the algorithm avoids language-specific syntax features to make the comparison as fair as possible, including using the same algorithm for generating binomial random numbers and the same random number generator; the exception are the R versions, POMP uses the standard R Mersenne Twister for the random number generator; I'm not sure what LibBi uses. The algorithm for generating random binomial numbers is only really suitable for small np.

Benchmarks were run on a Mac Pro (Late 2013), with 3 Ghz 8-core Intel Xeon E3, 64GB 1866 Mhz RAM, running OSX v 10.11.3 (El Capitan

floswald

acs_catcher <- function(tbl, state, year=2017 ){
    done = FALSE
    while(!done){
        out <- tryCatch(
            {
                x = get_acs(geography = "tract", state = state, table = tbl, year = year,keep_geo_vars = TRUE,cache_table = TRUE)
                done = TRUE
                return(x)
            },
            error = function(e) {

floswald

    using BasisMatrices, Optim, QuantEcon, Parameters
    using BasisMatrices: Degree, Derivative
    using Printf, Random
    using LinearAlgebra

    """
    The stochastic Neoclassical growth model type contains parameters
    which define the model

floswald

# download data
download.file("http://microdata.worldbank.org/index.php/catalog/428/download/28457","~/Downloads/data.zip")
unzip("~/Downloads/data.zip")

# read data
library(data.table)
x = fread("Downloads/edattainxtry_1.csv")
d = x[,list(year,country,aAll_6,aQuint1x_6,aQuint5x_6)]

# plot data

floswald

Probability Distribution Viewer Shiny App

Base R code created by Irvin Alcaraz
Shiny app files created by Irvin Alcaraz

Cal Poly Statistics Dept Shiny Series 
http://statistics.calpoly.edu/shiny

floswald

@import url(https://fonts.googleapis.com/css?family=Droid+Serif);
@import url(https://fonts.googleapis.com/css?family=Yanone+Kaffeesatz);
@import url(https://fonts.googleapis.com/css?family=Ubuntu+Mono:400,700,400italic);

body {
    font-family: 'Droid Serif';
}
h1, h2, h3 {
    font-family: 'Yanone Kaffeesatz';
    font-weight: 400;

floswald

Keybase proof

I hereby claim:

• I am floswald on github.
• I am floswald (https://keybase.io/floswald) on keybase.
• I have a public key whose fingerprint is 07C0 B518 D738 3F47 01B0 FAEC 717D 527B 629B 41B8

To claim this, I am signing this object:

floswald

# context: http://stackoverflow.com/questions/39448808/julia-tcp-server-and-connection

# Use fn to process messages from sock.
# Loop till sock is open and fn returns true.
function processor(fn, sock)
    proc = true
    try
        while proc && ((nb_available(sock) > 0) || isopen(sock))
            proc = fn(sock)
        end

floswald

static double adraw (struct aspacestruct *aspace)
{   /*returns the next value in the stream of guesses of A
      terminates the sequence by sending -INFINITY
    */    
    double aa,bb,mstep,astep,upper;
    int i;
    
    aspace[0].ncalls+=1.0;
    if (aspace[0].ncalls>=ngridmax)
    {