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#include <iostream>
#include <stdint.h>

class Area;
class Quest;

template <typename T, typename Meaning>
struct Explicit
{
    Explicit() {}

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[254, 253, 3].map { |v| v.to_s(16).rjust(2, '0') }.join

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defmodule Loop do
  def each([head|tail], fun) do
    [fun.(head)|each(tail, fun)]
  end
  def each([], _) do
    []
  end
end

Loop.each [1, 2], fn element ->

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0.02620087336,0,0,0,0,1,0,0,0,0,0,0,0,0.237037037,0.5070422535,0.6,0.6923076923,0,0.1212121212,0.5,0.6367980884,0.5735080058,0.6797752809,0.6111111111,0.7682926829,0.2727272727,0.479638009,0.7974683544,0.7183098592,0.4277777778,0.2958823529,0,0.2083333333,1
0.2358078603,0,0,1,0,0,0,0,0,0,0,0,0,0.6790123457,0.01408450704,0,0.07692307692,0,0,0,0.05256869773,0.03881610869,0.1011235955,0.05555555556,0.0487804878,0,0.01357466063,0.1392405063,0.1549295775,0.6777777778,0.3594117647,0.2173913043,0.5416666667,1
0.2139737991,0,0,0,1,0,0,0,0,0,0,0,0,0.1265432099,1,0.3333333333,0.1538461538,0,1,0.714,0.3261648746,0.3352741388,0.2921348315,0.1111111111,0.2682926829,0.09090909091,0.2805429864,0.2151898734,0.2253521127,0.2916666667,0.2111764706,0,0.375,1
0.05021834061,0,0,0,0,1,0,0,0,0,0,0,0,0.3067901235,0.3943661972,0.06666666667,0.2307692308,0,0.3333333333,0.25,0.146953405,0.1358563804,0.1853932584,0.2222222222,0.1341463415,0,0.09502262443,0.2025316456,0.2253521127,0.4222222222,0.3223529412,0.1739130435,0.4166666667,1
0.0

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library(dplyr)
library(ggplot2)

extract_input <- function(data) {
  return(data %>% select(c(Sepal.Length, Sepal.Width, Petal.Length, Petal.Width)))
}

extract_labels <- function(data) {
  return(data %$% Species %>% factor)
}

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library(plyr)

num_data <- 100
true_lambda <- 1

sample_from_distribution <- function(candidates, distribution, threshold) {
  while (TRUE) {
    x <- sample(candidates, size = 1)
    dice <- runif(n = 1, min = 0, max = 1)
    if (dice < distribution(x) / threshold) {

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library(magrittr)

F <- function(y, theta) {
  dnorm(y, mean = theta, sd = 1)
}

G0 <- function(theta) {
  dnorm(theta, mean = 0, sd = 1)
}

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def show_mat(mat):
    fig = plt.figure()
    ax = fig.add_subplot(111)
    cax = ax.matshow(mat)
    fig.colorbar(cax)

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import scipy.linalg
import numpy as np
import sys


num_samples = 500000
n = 7


def inv(Q, x, num_eqs):

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 np.set_printoptions(formatter={'float': lambda x: '%+1.1f' % x}, linewidth=50)