pao

load("interface.jl")

type Blah; end
type Bluh; end

@interface FooBar{T} [
                     (:foo, :(T, Integer,))
                     (:bar, :(T, String, Integer))
                     ]

pprett

{"error": 42716.2954, "samples": 506, "value": [22.532806324110698], "label": "RM <= 6.94", "type": "split", "children": [{"error": 17317.3210, "samples": 430, "value": [19.93372093023257], "label": "LSTAT <= 14.40", "type": "split", "children": [{"error": 6632.2175, "samples": 255, "value": [23.349803921568636], "label": "DIS <= 1.38", "type": "split", "children": [{"error": 390.7280, "samples": 5, "value": [45.58], "label": "CRIM <= 10.59", "type": "split", "children": [{"error": 0.0000, "samples": 4, "value": [50.0], "label": "Leaf - 4", "type": "leaf"}, {"error": 0.0000, "samples": 1, "value": [27.9], "label": "Leaf - 5", "type": "leaf"}]}, {"error": 3721.1632, "samples": 250, "value": [22.90520000000001], "label": "RM <= 6.54", "type": "split", "children": [{"error": 1636.0675, "samples": 195, "value": [21.629743589743576], "label": "LSTAT <= 7.57", "type": "split", "children": [{"error": 129.6307, "samples": 43, "value": [23.969767441860473], "label": "TAX <= 222.50", "type": "split", "children": [{"err

simonbyrne

require("extras/distributions.jl")
require("slicesampler.jl")

import Distributions.*

macro buildslicesampler(model)
    # pull apart the model into variables and distributions 
    variables = Dict{Symbol,Expr}()
    unboundvars = Set{Symbol}()
    for line in model.args

kjhealy

[
// Modified Sublime-REPL keybindings for an "R-friendly" set of shortcuts.
// Copy and paste this text into the Key Bindings - User (under Preferences menu).
// For more information, see http://tomschenkjr.net/2012/05/17/using-sublime-text-2-for-r/

// Executes a selection of text in REPL, latter only displays code and does not execute
{ "keys": ["super+shift+enter"], "command": "repl_transfer_current", "args": {"scope": "selection"}},

// I disabled this one
//{ "keys": ["super+shift+enter", "r"], "command": "repl_transfer_current", "args": {"scope": "selection", "action":"view_write"}},

Chutes.jl

module Chutes

abstract Graph
abstract DGraph <: Graph
abstract UGraph <: Graph

typealias LabelType Dict{Int,Any}

type DenseGraph <: Graph
    mat :: Matrix{Uint8}

dmbates

Formula, ModelFrame and ModelMatrix types

In R, the functions for fitting statistical models based on a linear predictor usually allow for a formula/data specification of the model. The data part is a data.frame object in R. In Julia the corresponding type is a DataFrame as implemented in the DataFrames package.

A formula object in R is an expression whose top-level operator is a unary or binary tilde, ~. The interpretation of many operators, including +, *, ^, \ and : are overridden in the formula language. See the result of

?formula

in R for the details.

cykl

package bench;

import java.util.Arrays;
import java.util.concurrent.TimeUnit;

import org.openjdk.jmh.annotations.BenchmarkType;
import org.openjdk.jmh.annotations.GenerateMicroBenchmark;
import org.openjdk.jmh.annotations.OutputTimeUnit;
import org.openjdk.jmh.annotations.State;

carlobaldassi

module NZipTest

import Base.start, Base.next, Base.done, Base.length

using Benchmark

immutable NZip0
end
immutable NZip1{I1}
    i1::I1

phaedryx

Original text here: https://whydavewhy.com/2013/08/16/loyalty-and-layoffs/

romainfrancois

#include <Rcpp.h>
using namespace Rcpp;

typedef SEXP (*CCODE)(SEXP, SEXP, SEXP, SEXP);

/* Information for Deparsing Expressions */
typedef enum {
    PP_INVALID  =  0,
    PP_ASSIGN   =  1,
    PP_ASSIGN2  =  2,