{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Stochaskell, version 0.1.0\n",
       "Copyright (C) 2015-2020 David A Roberts\n",
       "This program comes with ABSOLUTELY NO WARRANTY.\n",
       "This is free software, and you are welcome to redistribute it\n",
       "under certain conditions; see the LICENSE for details.\n",
       "\n",
       "Using installation directory at \n",
       "  /home/jovyan/stochaskell"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "{-# LANGUAGE FlexibleContexts, MonadComprehensions, NoImplicitPrelude, RebindableSyntax, DeriveGeneric, DeriveAnyClass #-}\n",
    "import Language.Stochaskell\n",
    "stochaskell"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "soccer1 :: Z -> P (R,ZVec)\n",
    "soccer1 n = do\n",
    "  lam <- gamma 25 10\n",
    "  y <- joint vector [ poisson lam\n",
    "                    | _ <- 1...n ]\n",
    "  return (lam,y)\n",
    "\n",
    "soccer2 :: Z -> P (R,R,ZVec)\n",
    "soccer2 n = do\n",
    "  lam <- gamma 25 10\n",
    "  kap <- gamma 1 10\n",
    "  let a = 1/kap\n",
    "      b = a/lam\n",
    "  y <- joint vector [ negBinomial a b\n",
    "                    | _ <- 1...n ]\n",
    "  return (lam,kap,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import Language.Stochaskell.Expression\n",
    "import GHC.Generics (Generic)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "data Model = Model1 R ZVec\n",
    "           | Model2 R R ZVec\n",
    "           deriving (Show, Generic, ExprType, Constructor)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "soccer :: Z -> P (Expr Model)\n",
    "soccer n = do\n",
    "  (lam1,     y1) <- soccer1 n\n",
    "  (lam2,kap2,y2) <- soccer2 n\n",
    "  k <- bernoulli 0.5\n",
    "  return $ if k\n",
    "    then fromConcrete (Model1 lam1 y1)\n",
    "    else fromConcrete (Model2 lam2 kap2 y2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "soccerJump :: Model -> P (Expr Model)\n",
    "soccerJump (Model1 lam y) = do\n",
    "  u <- normal 0 1.5\n",
    "  let kap = 0.015 * exp u\n",
    "  return $ fromConcrete (Model2 lam kap y)\n",
    "soccerJump (Model2 lam _ y) =\n",
    "  return $ fromConcrete (Model1 lam y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "soccerHMC :: Z -> Model -> IO Model\n",
    "soccerHMC n (Model1 lam y) = do\n",
    "  let posterior =\n",
    "       [ lam'\n",
    "       | (lam',y') <- soccer1 n\n",
    "       , y' == y ]\n",
    "  samples <- hmcStanInit 10 posterior lam\n",
    "  let lam' = last samples\n",
    "  return (Model1 lam' y)\n",
    "soccerHMC n (Model2 lam kap y) = do\n",
    "  let posterior =\n",
    "       [ (lam',kap')\n",
    "       | (lam',kap',y') <- soccer2 n\n",
    "       , y' == y ]\n",
    "  let s0 = (lam,kap)\n",
    "  samples <- hmcStanInit 10 posterior s0\n",
    "  let (lam',kap') = last samples\n",
    "  return (Model2 lam' kap' y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "soccerStep :: Z -> Model -> IO Model\n",
    "soccerStep n m = do\n",
    "  m' <- soccerHMC n m\n",
    "  m'' <- soccer n `rjmcC` soccerJump\n",
    "           `runCC` fromConcrete m'\n",
    "  return $ fromRight (eval' m'')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "-- https://cran.r-project.org/web/packages/engsoccerdata/README.html\n",
    "totgoal = [5, 1, 3, 2, 3, 2, 2, 5, 3, 1, 0, 7, 2, 4, 4, 2, 4, 5, 6, 0, 4, 1, 4, 1, 2, 4, 0, 2, 1, 2, 5, 3, 1, 3, 2, 0, 3, 2, 2, 1, 3, 1, 1, 0, 1, 1, 4, 3, 4, 3, 0, 5, 1, 2, 2, 3, 2, 1, 2, 2, 0, 5, 1, 2, 3, 1, 2, 7, 5, 3, 3, 2, 0, 2, 5, 2, 2, 2, 1, 0, 5, 2, 1, 3, 4, 2, 3, 2, 2, 1, 2, 1, 2, 5, 2, 1, 0, 2, 2, 1, 2, 0, 2, 2, 7, 4, 3, 4, 3, 2, 5, 0, 2, 1, 1, 3, 2, 6, 6, 2, 3, 5, 2, 2, 3, 1, 3, 2, 2, 3, 4, 5, 1, 1, 5, 0, 1, 4, 4, 2, 4, 4, 1, 2, 1, 1, 1, 4, 1, 4, 3, 1, 4, 6, 0, 3, 3, 3, 1, 1, 2, 3, 5, 1, 1, 4, 3, 1, 7, 3, 1, 1, 4, 2, 1, 1, 0, 5, 4, 6, 1, 0, 2, 2, 3, 1, 1, 1, 2, 3, 4, 4, 5, 0, 1, 5, 1, 2, 3, 1, 4, 1, 3, 3, 3, 2, 0, 3, 1, 2, 1, 3, 3, 5, 4, 1, 2, 6, 1, 2, 0, 2, 3, 0, 2, 3, 1, 4, 3, 4, 1, 2, 7, 3, 3, 1, 5, 0, 0, 5, 3, 2, 2, 6, 4, 2, 5, 1, 2, 1, 1, 4, 0, 1, 2, 2, 4, 1, 2, 4, 2, 5, 4, 3, 0, 4, 2, 2, 2, 4, 2, 3, 2, 1, 1, 4, 3, 4, 1, 0, 3, 2, 1, 2, 2, 3, 4, 1, 1, 0, 4, 3, 1, 3, 2, 3, 4, 3, 5, 5, 2, 2, 2, 1, 2, 0, 2, 5, 1, 4, 2, 2, 1, 0, 3, 3, 2, 2, 4, 5, 3, 2, 4, 3, 3, 5, 2, 0, 3, 3, 4, 0, 2, 2, 3, 2, 3, 3, 1, 2, 1, 3, 0, 4, 3, 4, 3, 0, 4, 4, 3, 3, 1, 3, 3, 6, 6, 2, 3, 1, 2, 5, 5, 2, 3, 3, 3, 1, 2, 1, 1, 7, 3, 2, 1, 3, 1, 3, 1, 3, 2, 8, 3, 4, 2, 2, 4, 3, 4, 3, 2, 2, 4, 3, 3, 3, 3, 1, 3, 1, 2, 1, 2, 0, 2, 2, 0, 4, 3, 2, 2, 0, 3, 3, 2, 2, 1, 2, 2, 3, 1, 5, 2, 2, 2, 1, 6, 1, 3, 4, 3, 6, 3, 2, 4, 3, 3, 4, 4, 3, 2, 1, 2, 3, 2, 0, 4, 0, 3, 5, 4, 1, 2, 1, 4, 1, 3, 3, 1, 2, 1, 2, 4, 3, 1, 3, 4, 2, 1, 0, 2, 2, 0, 4, 1, 2, 2, 3, 4, 3, 2, 4, 1, 3, 0, 3, 1, 3, 4, 3, 1, 4, 1, 4, 1, 1, 1, 1, 3, 5, 5, 3, 2, 6, 0, 3, 3, 2, 2, 3, 3, 2, 4, 3, 2, 2, 2, 3, 2, 1, 1, 4, 3, 3, 3, 2, 1, 1, 2, 0, 0, 1, 5, 4, 2, 3, 4, 2, 0, 4, 1, 1, 2, 2, 0, 2, 4, 3, 2, 3, 2, 1, 2, 3, 2, 0, 1, 3, 4, 0, 1, 1, 0, 0, 2, 0, 3, 0, 2, 1, 1, 4, 5, 5, 2, 2, 3, 6, 2, 4, 2, 2, 3, 5, 2, 1, 4, 1, 4, 2, 4, 1, 6, 2, 3, 3, 4, 0, 2, 3, 1, 4, 3, 4, 5, 5, 1, 2, 0, 4, 2, 3, 0, 0, 2, 3, 3, 1, 4, 0, 1, 5, 1, 4, 3, 4, 3, 0, 4, 3, 1, 1, 2, 2, 2, 3, 3, 3, 0, 3, 4, 4, 2, 3, 2, 1, 4, 2, 3, 1, 2, 1, 2, 1, 3, 1, 2, 5, 1, 0, 4, 4, 2, 6, 5, 1, 4, 0, 4, 3, 2, 2, 2, 2, 1, 3, 3, 3, 2, 3, 3, 1, 3, 3, 4, 3, 2, 5, 6, 3, 2, 0, 1, 3, 4, 3, 5, 3, 1, 2, 4, 1, 4, 3, 0, 3, 1, 4, 1, 3, 6, 3, 2, 3, 2, 2, 6, 0, 1, 0, 2, 2, 1, 2, 3, 4, 4, 5, 1, 6, 3, 1, 1, 2, 2, 3, 1, 1, 7, 1, 2, 1, 0, 3, 4, 5, 5, 2, 0, 4, 4, 4, 1, 1, 1, 1, 1, 6, 2, 3, 2, 2, 2, 2, 1, 5, 1, 3, 2, 1, 4, 2, 3, 4, 2, 5, 3, 2, 2, 3, 6, 2, 4, 2, 2, 2, 3, 3, 2, 5, 2, 5, 4, 4, 1, 3, 1, 2, 4, 3, 5, 1, 1, 2, 2, 2, 4, 4, 1, 3, 2, 2, 2, 4, 5, 1, 5, 2, 4, 3, 5, 1, 4, 0, 2, 0, 1, 2, 2, 4, 1, 6, 1, 2, 1, 4, 5, 2, 3, 3, 1, 1, 3, 0, 4, 0, 1, 0, 4, 1, 3, 2, 2, 1, 5, 3, 8, 5, 0, 2, 7, 2, 0, 0, 6, 3, 1, 3, 1, 1, 2, 2, 1, 2, 8, 6, 3, 3, 2, 2, 2, 4, 3, 2, 1, 1, 1, 4, 4, 0, 3, 5, 1, 5, 4, 4, 2, 2, 1, 1, 3, 3, 1, 1, 2, 4, 4, 1, 8, 0, 2, 3, 3, 3, 2, 4, 3, 3, 0, 1, 2, 6, 3, 3, 1, 2, 4, 4, 6, 1, 2, 2, 4, 0, 4, 4, 2, 6, 1, 2, 1, 1, 5, 3, 5, 3, 3, 4, 4, 2, 4, 1, 1, 4, 6, 2, 1, 2, 5, 0, 1, 4, 4, 4, 3, 1, 3, 2, 0, 3, 4, 1, 2, 2, 2, 5, 3, 2, 3, 3, 5, 6, 2, 0, 1, 1, 5, 4, 3, 3, 2, 3, 1, 2, 1, 2, 1, 2, 9, 4, 4, 2, 1, 4, 2, 3, 1, 2, 0, 3, 1, 0, 2, 4, 5, 2, 3, 2, 6, 2, 5, 3, 2, 4, 4, 1, 0, 2, 6, 1, 4, 2, 4, 0, 1, 0, 0, 2, 1, 0, 11, 1, 1, 0, 2, 4, 3, 3, 0, 2, 3, 1, 1, 2, 4, 2, 2, 2, 3, 2, 3, 1, 3, 3, 1, 2, 2, 3, 4, 1, 1, 1, 2, 2, 3, 4, 5, 2, 2, 3, 1, 3, 2, 4, 8, 5, 3, 2, 8, 4, 4, 6, 2, 3, 2, 2, 5, 2, 10, 2, 4, 4, 1, 4, 2, 3, 2, 4, 3, 2, 3, 1, 2, 3, 3, 4, 1, 2, 4, 2, 2, 0, 3, 2, 8, 1, 2, 2, 3, 2, 1, 2, 2, 1, 1, 2, 0, 3, 2, 1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "let goalData = list totgoal\n",
    "    n = integer (length totgoal)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "/*\n",
       "let v_0_0 = getExternal x_cc_0_0 :: Union[(R, ZVec), (R, R, ZVec)]\n",
       " in do x_cc_0_0 <- switch i_0_0 of\n",
       "         C0 i_1_0 i_1_1 ->\n",
       "           let v_1_0 = getExternal x_cc_1_0 :: R\n",
       "               v_1_1 = gamma_lpdf i_1_0 25.0 10.0 :: R\n",
       "               v_1_2 = exp x_cc_1_0 :: R\n",
       "               v_1_3 = 1.5e-2 * v_1_2 :: R\n",
       "               v_1_4 = gamma_lpdf v_1_3 1.0 10.0 :: R\n",
       "               v_1_5 = 1.0 / v_1_3 :: R\n",
       "               v_1_6 = v_1_5 / i_1_0 :: R\n",
       "               v_1_7 = vectorSize i_1_1 :: Z\n",
       "               v_1_8 = \n",
       "                 [ i_2_1\n",
       "                 | i_2_1 <- 1...v_1_7 ] :: ZVec\n",
       "               v_1_9 = foldl 0.0 v_1_8 $ \\i_2_12 i_2_11 ->\n",
       "                 let v_2_0 = neg_binomial_lpdf i_1_1!i_2_11 v_1_5 v_1_6 :: R\n",
       "                     v_2_1 = i_2_12 + v_2_0 :: R\n",
       "                  in v_2_1 :: R\n",
       "               v_1_10 = +s -0.6931471805599453 v_1_1 v_1_4 v_1_9 :: R\n",
       "               v_1_11 = foldl 0.0 v_1_8 $ \\i_2_12 i_2_11 ->\n",
       "                 let v_2_0 = poisson_lpdf i_1_1!i_2_11 i_1_0 :: R\n",
       "                     v_2_1 = i_2_12 + v_2_0 :: R\n",
       "                  in v_2_1 :: R\n",
       "               v_1_12 = +s -0.6931471805599453 v_1_1 v_1_11 :: R\n",
       "               v_1_13 = v_1_10 - v_1_12 :: R\n",
       "               v_1_14 = normal_lpdf x_cc_1_0 0.0 1.5 :: R\n",
       "               v_1_15 = negate v_1_14 :: R\n",
       "               v_1_16 = +s -4.199705077879927 x_cc_1_0 v_1_15 :: R\n",
       "               v_1_17 = +s x_cc_1_0 v_1_13 v_1_15 -4.199705077879927 :: R\n",
       "               v_1_18 = exp v_1_17 :: R\n",
       "               v_1_19 = min 1.0 v_1_18 :: R\n",
       "               v_1_20 = getExternal x_cc_1_1 :: B\n",
       "               v_1_21 = ifThenElse x_cc_1_1 (C1 i_1_0 v_1_3 i_1_1 :: Union[(R, ZVec), (R, R, ZVec)]) (C0 i_1_0 i_1_1 :: Union[(R, ZVec), (R, R, ZVec)]) :: Union[(R, ZVec), (R, R, ZVec)]\n",
       "            in do x_cc_1_0 <- normal 0.0 1.5 :: P R\n",
       "                  x_cc_1_1 <- bernoulli v_1_19 :: P B\n",
       "                  return [v_1_21]\n",
       "         C1 i_1_0 i_1_1 i_1_2 ->\n",
       "           let v_1_0 = gamma_lpdf i_1_0 25.0 10.0 :: R\n",
       "               v_1_1 = vectorSize i_1_2 :: Z\n",
       "               v_1_2 = \n",
       "                 [ i_2_1\n",
       "                 | i_2_1 <- 1...v_1_1 ] :: ZVec\n",
       "               v_1_3 = foldl 0.0 v_1_2 $ \\i_2_12 i_2_11 ->\n",
       "                 let v_2_0 = poisson_lpdf i_1_2!i_2_11 i_1_0 :: R\n",
       "                     v_2_1 = i_2_12 + v_2_0 :: R\n",
       "                  in v_2_1 :: R\n",
       "               v_1_4 = +s -0.6931471805599453 v_1_0 v_1_3 :: R\n",
       "               v_1_5 = gamma_lpdf i_1_1 1.0 10.0 :: R\n",
       "               v_1_6 = 1.0 / i_1_1 :: R\n",
       "               v_1_7 = v_1_6 / i_1_0 :: R\n",
       "               v_1_8 = foldl 0.0 v_1_2 $ \\i_2_12 i_2_11 ->\n",
       "                 let v_2_0 = neg_binomial_lpdf i_1_2!i_2_11 v_1_6 v_1_7 :: R\n",
       "                     v_2_1 = i_2_12 + v_2_0 :: R\n",
       "                  in v_2_1 :: R\n",
       "               v_1_9 = +s -0.6931471805599453 v_1_0 v_1_5 v_1_8 :: R\n",
       "               v_1_10 = v_1_4 - v_1_9 :: R\n",
       "               v_1_11 = log i_1_1 :: R\n",
       "               v_1_12 = v_1_11 - -4.199705077879927 :: R\n",
       "               v_1_13 = normal_lpdf v_1_12 0.0 1.5 :: R\n",
       "               v_1_14 = negate v_1_11 :: R\n",
       "               v_1_15 = v_1_13 + v_1_14 :: R\n",
       "               v_1_16 = +s v_1_10 v_1_13 v_1_14 :: R\n",
       "               v_1_17 = exp v_1_16 :: R\n",
       "               v_1_18 = min 1.0 v_1_17 :: R\n",
       "               v_1_19 = getExternal x_cc_1_0 :: B\n",
       "               v_1_20 = ifThenElse x_cc_1_0 (C0 i_1_0 i_1_2 :: Union[(R, ZVec), (R, R, ZVec)]) (C1 i_1_0 i_1_1 i_1_2 :: Union[(R, ZVec), (R, R, ZVec)]) :: Union[(R, ZVec), (R, R, ZVec)]\n",
       "            in do x_cc_1_0 <- bernoulli v_1_18 :: P B\n",
       "                  return [v_1_20]\n",
       "       return [x_cc_0_0]\n",
       "*/\n",
       "\n",
       "#include <cmath>\n",
       "#include <iostream>\n",
       "#include <random>\n",
       "#include <tuple>\n",
       "#include <boost/math/distributions.hpp>\n",
       "#include <boost/math/special_functions/factorials.hpp>\n",
       "#define eigen_assert(X) do { if(!(X)) throw std::runtime_error(#X); } while(false);\n",
       "#include <Eigen/Dense>\n",
       "#include <mpark/variant.hpp>\n",
       "#include <backward.hpp>\n",
       "using namespace std;\n",
       "using namespace Eigen;\n",
       "using namespace mpark;\n",
       "namespace backward { backward::SignalHandling sh; }\n",
       "IOFormat eigenFormat(StreamPrecision, DontAlignCols, \",\", \";\", \"\", \"\", \"[\", \"]\");\n",
       "#define LOG_DET(m) ((m).isLowerTriangular() ? (m).diagonal().array().log().sum() : (m).llt().matrixL().toDenseMatrix().diagonal().array().log().sum() * 2)\n",
       "\n",
       "int main() {\n",
       "  random_device rd;\n",
       "  mt19937 gen(rd());\n",
       "  variant<tuple<double, Matrix<int, Dynamic, 1>>, tuple<double, double, Matrix<int, Dynamic, 1>>> i_0_0; int i_1_0; cin >> i_1_0;\n",
       "  switch(i_1_0) {\n",
       "    case 0: {\n",
       "      double i_1_1; cin >> i_1_1;\n",
       "      Matrix<int, Dynamic, 1> i_1_2; int i_1_2_length; cin >> i_1_2_length;\n",
       "      i_1_2.resize(i_1_2_length);\n",
       "      for(int i_2_1 = 1; i_2_1 <= i_1_2_length; i_2_1++) {\n",
       "        cin >> i_1_2(i_2_1-1);\n",
       "      }\n",
       "      i_0_0 = make_tuple(i_1_1, i_1_2);\n",
       "      break;\n",
       "    }\n",
       "    case 1: {\n",
       "      double i_1_1; cin >> i_1_1;\n",
       "      double i_1_2; cin >> i_1_2;\n",
       "      Matrix<int, Dynamic, 1> i_1_3; int i_1_3_length; cin >> i_1_3_length;\n",
       "      i_1_3.resize(i_1_3_length);\n",
       "      for(int i_2_1 = 1; i_2_1 <= i_1_3_length; i_2_1++) {\n",
       "        cin >> i_1_3(i_2_1-1);\n",
       "      }\n",
       "      i_0_0 = make_tuple(i_1_1, i_1_2, i_1_3);\n",
       "      break;\n",
       "    }\n",
       "  }\n",
       "  variant<tuple<double, Matrix<int, Dynamic, 1>>, tuple<double, double, Matrix<int, Dynamic, 1>>> x_cc_0_0; try { switch(i_0_0.index()) {\n",
       "    case 0: {\n",
       "      double i_1_0; Matrix<int, Dynamic, 1> i_1_1; tie(i_1_0, i_1_1) = get<0>(i_0_0);\n",
       "      double x_cc_1_0; try { x_cc_1_0 = std::normal_distribution<>(0, 1.5)(gen); } catch(const std::runtime_error& e) { cerr << \"x_cc_1_0: \" << e.what() << endl; }\n",
       "      double v_1_1; try { v_1_1 = log(boost::math::pdf(boost::math::gamma_distribution<>(25, 1./10), i_1_0)); } catch(const std::runtime_error& e) { cerr << \"v_1_1: \" << e.what() << endl; }\n",
       "      double v_1_2; try { v_1_2 = exp(x_cc_1_0); } catch(const std::runtime_error& e) { cerr << \"v_1_2: \" << e.what() << endl; }\n",
       "      double v_1_3; try { v_1_3 = 1.5e-2 * v_1_2; } catch(const std::runtime_error& e) { cerr << \"v_1_3: \" << e.what() << endl; }\n",
       "      double v_1_4; try { v_1_4 = log(boost::math::pdf(boost::math::gamma_distribution<>(1, 1./10), v_1_3)); } catch(const std::runtime_error& e) { cerr << \"v_1_4: \" << e.what() << endl; }\n",
       "      double v_1_5; try { v_1_5 = (double) 1 / (double) v_1_3; } catch(const std::runtime_error& e) { cerr << \"v_1_5: \" << e.what() << endl; }\n",
       "      double v_1_6; try { v_1_6 = (double) v_1_5 / (double) i_1_0; } catch(const std::runtime_error& e) { cerr << \"v_1_6: \" << e.what() << endl; }\n",
       "      int v_1_7; try { v_1_7 = i_1_1.size(); } catch(const std::runtime_error& e) { cerr << \"v_1_7: \" << e.what() << endl; }\n",
       "      Matrix<int, Dynamic, 1> v_1_8; try { v_1_8.resize(v_1_7);\n",
       "      for(int i_2_1 = 1; i_2_1 <= v_1_7; i_2_1++) {\n",
       "      \n",
       "        v_1_8(i_2_1-1) = i_2_1;\n",
       "      } } catch(const std::runtime_error& e) { cerr << \"v_1_8: \" << e.what() << endl; }\n",
       "      double v_1_9; try { v_1_9 = 0;\n",
       "      for(int i_2_0 = 1; i_2_0 <= v_1_8.size(); i_2_0++) {\n",
       "        int i_2_11 = v_1_8[i_2_0-1];\n",
       "        double i_2_12 = v_1_9;\n",
       "        double v_2_0; v_2_0 = log(boost::math::pdf(boost::math::negative_binomial_distribution<>(v_1_5, v_1_6 / (v_1_6 + 1)), i_1_1(i_2_11-1)));\n",
       "        double v_2_1; v_2_1 = i_2_12 + v_2_0;\n",
       "        v_1_9 = v_2_1;\n",
       "      \n",
       "      } } catch(const std::runtime_error& e) { cerr << \"v_1_9: \" << e.what() << endl; }\n",
       "      double v_1_10; try { v_1_10 = -0.6931471805599453 + v_1_1 + v_1_4 + v_1_9; } catch(const std::runtime_error& e) { cerr << \"v_1_10: \" << e.what() << endl; }\n",
       "      double v_1_11; try { v_1_11 = 0;\n",
       "      for(int i_2_0 = 1; i_2_0 <= v_1_8.size(); i_2_0++) {\n",
       "        int i_2_11 = v_1_8[i_2_0-1];\n",
       "        double i_2_12 = v_1_11;\n",
       "        double v_2_0; v_2_0 = log(boost::math::pdf(boost::math::poisson_distribution<>(i_1_0), i_1_1(i_2_11-1)));\n",
       "        double v_2_1; v_2_1 = i_2_12 + v_2_0;\n",
       "        v_1_11 = v_2_1;\n",
       "      \n",
       "      } } catch(const std::runtime_error& e) { cerr << \"v_1_11: \" << e.what() << endl; }\n",
       "      double v_1_12; try { v_1_12 = -0.6931471805599453 + v_1_1 + v_1_11; } catch(const std::runtime_error& e) { cerr << \"v_1_12: \" << e.what() << endl; }\n",
       "      double v_1_13; try { v_1_13 = v_1_10 - v_1_12; } catch(const std::runtime_error& e) { cerr << \"v_1_13: \" << e.what() << endl; }\n",
       "      double v_1_14; try { v_1_14 = log(boost::math::pdf(boost::math::normal_distribution<>(0, 1.5), x_cc_1_0)); } catch(const std::runtime_error& e) { cerr << \"v_1_14: \" << e.what() << endl; }\n",
       "      double v_1_15; try { v_1_15 = -v_1_14; } catch(const std::runtime_error& e) { cerr << \"v_1_15: \" << e.what() << endl; }\n",
       "      double v_1_16; try { v_1_16 = -4.199705077879927 + x_cc_1_0 + v_1_15; } catch(const std::runtime_error& e) { cerr << \"v_1_16: \" << e.what() << endl; }\n",
       "      double v_1_17; try { v_1_17 = x_cc_1_0 + v_1_13 + v_1_15 + -4.199705077879927; } catch(const std::runtime_error& e) { cerr << \"v_1_17: \" << e.what() << endl; }\n",
       "      double v_1_18; try { v_1_18 = exp(v_1_17); } catch(const std::runtime_error& e) { cerr << \"v_1_18: \" << e.what() << endl; }\n",
       "      double v_1_19; try { v_1_19 = min<double>(1, v_1_18); } catch(const std::runtime_error& e) { cerr << \"v_1_19: \" << e.what() << endl; }\n",
       "      int x_cc_1_1; try { do { x_cc_1_1 = std::bernoulli_distribution(v_1_19)(gen); } while(x_cc_1_1 < 0 || x_cc_1_1 > 1); } catch(const std::runtime_error& e) { cerr << \"x_cc_1_1: \" << e.what() << endl; }\n",
       "      variant<tuple<double, Matrix<int, Dynamic, 1>>, tuple<double, double, Matrix<int, Dynamic, 1>>> v_1_21; try { if(x_cc_1_1) v_1_21 = make_tuple(i_1_0, v_1_3, i_1_1); else v_1_21 = make_tuple(i_1_0, i_1_1); } catch(const std::runtime_error& e) { cerr << \"v_1_21: \" << e.what() << endl; }\n",
       "      x_cc_0_0 = v_1_21; break;\n",
       "    }\n",
       "    case 1: {\n",
       "      double i_1_0; double i_1_1; Matrix<int, Dynamic, 1> i_1_2; tie(i_1_0, i_1_1, i_1_2) = get<1>(i_0_0);\n",
       "      double v_1_0; try { v_1_0 = log(boost::math::pdf(boost::math::gamma_distribution<>(25, 1./10), i_1_0)); } catch(const std::runtime_error& e) { cerr << \"v_1_0: \" << e.what() << endl; }\n",
       "      int v_1_1; try { v_1_1 = i_1_2.size(); } catch(const std::runtime_error& e) { cerr << \"v_1_1: \" << e.what() << endl; }\n",
       "      Matrix<int, Dynamic, 1> v_1_2; try { v_1_2.resize(v_1_1);\n",
       "      for(int i_2_1 = 1; i_2_1 <= v_1_1; i_2_1++) {\n",
       "      \n",
       "        v_1_2(i_2_1-1) = i_2_1;\n",
       "      } } catch(const std::runtime_error& e) { cerr << \"v_1_2: \" << e.what() << endl; }\n",
       "      double v_1_3; try { v_1_3 = 0;\n",
       "      for(int i_2_0 = 1; i_2_0 <= v_1_2.size(); i_2_0++) {\n",
       "        int i_2_11 = v_1_2[i_2_0-1];\n",
       "        double i_2_12 = v_1_3;\n",
       "        double v_2_0; v_2_0 = log(boost::math::pdf(boost::math::poisson_distribution<>(i_1_0), i_1_2(i_2_11-1)));\n",
       "        double v_2_1; v_2_1 = i_2_12 + v_2_0;\n",
       "        v_1_3 = v_2_1;\n",
       "      \n",
       "      } } catch(const std::runtime_error& e) { cerr << \"v_1_3: \" << e.what() << endl; }\n",
       "      double v_1_4; try { v_1_4 = -0.6931471805599453 + v_1_0 + v_1_3; } catch(const std::runtime_error& e) { cerr << \"v_1_4: \" << e.what() << endl; }\n",
       "      double v_1_5; try { v_1_5 = log(boost::math::pdf(boost::math::gamma_distribution<>(1, 1./10), i_1_1)); } catch(const std::runtime_error& e) { cerr << \"v_1_5: \" << e.what() << endl; }\n",
       "      double v_1_6; try { v_1_6 = (double) 1 / (double) i_1_1; } catch(const std::runtime_error& e) { cerr << \"v_1_6: \" << e.what() << endl; }\n",
       "      double v_1_7; try { v_1_7 = (double) v_1_6 / (double) i_1_0; } catch(const std::runtime_error& e) { cerr << \"v_1_7: \" << e.what() << endl; }\n",
       "      double v_1_8; try { v_1_8 = 0;\n",
       "      for(int i_2_0 = 1; i_2_0 <= v_1_2.size(); i_2_0++) {\n",
       "        int i_2_11 = v_1_2[i_2_0-1];\n",
       "        double i_2_12 = v_1_8;\n",
       "        double v_2_0; v_2_0 = log(boost::math::pdf(boost::math::negative_binomial_distribution<>(v_1_6, v_1_7 / (v_1_7 + 1)), i_1_2(i_2_11-1)));\n",
       "        double v_2_1; v_2_1 = i_2_12 + v_2_0;\n",
       "        v_1_8 = v_2_1;\n",
       "      \n",
       "      } } catch(const std::runtime_error& e) { cerr << \"v_1_8: \" << e.what() << endl; }\n",
       "      double v_1_9; try { v_1_9 = -0.6931471805599453 + v_1_0 + v_1_5 + v_1_8; } catch(const std::runtime_error& e) { cerr << \"v_1_9: \" << e.what() << endl; }\n",
       "      double v_1_10; try { v_1_10 = v_1_4 - v_1_9; } catch(const std::runtime_error& e) { cerr << \"v_1_10: \" << e.what() << endl; }\n",
       "      double v_1_11; try { v_1_11 = log(i_1_1); } catch(const std::runtime_error& e) { cerr << \"v_1_11: \" << e.what() << endl; }\n",
       "      double v_1_12; try { v_1_12 = v_1_11 - -4.199705077879927; } catch(const std::runtime_error& e) { cerr << \"v_1_12: \" << e.what() << endl; }\n",
       "      double v_1_13; try { v_1_13 = log(boost::math::pdf(boost::math::normal_distribution<>(0, 1.5), v_1_12)); } catch(const std::runtime_error& e) { cerr << \"v_1_13: \" << e.what() << endl; }\n",
       "      double v_1_14; try { v_1_14 = -v_1_11; } catch(const std::runtime_error& e) { cerr << \"v_1_14: \" << e.what() << endl; }\n",
       "      double v_1_15; try { v_1_15 = v_1_13 + v_1_14; } catch(const std::runtime_error& e) { cerr << \"v_1_15: \" << e.what() << endl; }\n",
       "      double v_1_16; try { v_1_16 = v_1_10 + v_1_13 + v_1_14; } catch(const std::runtime_error& e) { cerr << \"v_1_16: \" << e.what() << endl; }\n",
       "      double v_1_17; try { v_1_17 = exp(v_1_16); } catch(const std::runtime_error& e) { cerr << \"v_1_17: \" << e.what() << endl; }\n",
       "      double v_1_18; try { v_1_18 = min<double>(1, v_1_17); } catch(const std::runtime_error& e) { cerr << \"v_1_18: \" << e.what() << endl; }\n",
       "      int x_cc_1_0; try { do { x_cc_1_0 = std::bernoulli_distribution(v_1_18)(gen); } while(x_cc_1_0 < 0 || x_cc_1_0 > 1); } catch(const std::runtime_error& e) { cerr << \"x_cc_1_0: \" << e.what() << endl; }\n",
       "      variant<tuple<double, Matrix<int, Dynamic, 1>>, tuple<double, double, Matrix<int, Dynamic, 1>>> v_1_20; try { if(x_cc_1_0) v_1_20 = make_tuple(i_1_0, i_1_2); else v_1_20 = make_tuple(i_1_0, i_1_1, i_1_2); } catch(const std::runtime_error& e) { cerr << \"v_1_20: \" << e.what() << endl; }\n",
       "      x_cc_0_0 = v_1_20; break;\n",
       "    }\n",
       "  } } catch(const std::runtime_error& e) { cerr << \"x_cc_0_0: \" << e.what() << endl; }\n",
       "  switch(x_cc_0_0.index()) {\n",
       "    case 0: {\n",
       "      double i_1_1; Matrix<int, Dynamic, 1> i_1_2; tie(i_1_1, i_1_2) = get<0>(x_cc_0_0);\n",
       "      cout << 0 << ' ';\n",
       "      cout << i_1_1 << ' ';\n",
       "      cout << i_1_2.size() << ' ';\n",
       "      for(int i_2_1 = 1; i_2_1 <= i_1_2.size(); i_2_1++) {\n",
       "        cout << i_1_2(i_2_1-1) << ' ';\n",
       "      }\n",
       "      break;\n",
       "    }\n",
       "    case 1: {\n",
       "      double i_1_1; double i_1_2; Matrix<int, Dynamic, 1> i_1_3; tie(i_1_1, i_1_2, i_1_3) = get<1>(x_cc_0_0);\n",
       "      cout << 1 << ' ';\n",
       "      cout << i_1_1 << ' ';\n",
       "      cout << i_1_2 << ' ';\n",
       "      cout << i_1_3.size() << ' ';\n",
       "      for(int i_2_1 = 1; i_2_1 <= i_1_3.size(); i_2_1++) {\n",
       "        cout << i_1_3(i_2_1-1) << ' ';\n",
       "      }\n",
       "      break;\n",
       "    }\n",
       "  } cout << endl;\n",
       "}\n",
       "\n",
       "g++ -std=c++11 -Ibackward-cpp -Ieigen -Ivariant/include -DBACKWARD_HAS_BFD=1 -g -rdynamic /home/jovyan/stochaskell/cache/cc/sampler_576e8212a8171ab5532cf51f6363c4521cf709eb.cc -lbfd -ldl -o /home/jovyan/stochaskell/cache/cc/sampler_576e8212a8171ab5532cf51f6363c4521cf709eb"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "compileCC (soccer n `rjmcC` soccerJump)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "-- reduce number of iterations from 5000 to speed this up\n",
    "samples <- silence' $ iterateLimit 5000 (soccerStep n) (Model1 1 goalData)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Posterior probability in favour of model 1:"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "0.7056588682263547"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "putStrLn \"Posterior probability in favour of model 1:\"\n",
    "sum [case m of Model1{} -> 1; _ -> 0 | m <- samples] / genericLength samples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    ":opt svg\n",
    "import Language.Stochaskell.Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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   ],
   "source": [
    "let plot' = layoutToGrid . execEC . plot\n",
    "    hist s vals rng = return . histToPlot $ defaultNormedPlotHist\n",
    "      { _plot_hist_title = s, _plot_hist_values = vals, _plot_hist_range = Just rng }\n",
    "\n",
    "toRenderable $ \n",
    "  (plot' (hist \"λ₁\" [real lam | Model1 lam _ <- samples] (2.4,2.7)) `beside`\n",
    "   plot' (line \"lpdf\" [[(i, real $ soccer n `lpdfAuxC` fromConcrete m) | (i,m) <- [1..] `zip` tail samples]]))\n",
    "  `above`\n",
    "  (plot' (hist \"λ₂\" [real lam | Model2 lam kap _ <- samples] (2.4,2.7)) `beside`\n",
    "   plot' (hist \"κ₂\" [real kap | Model2 lam kap _ <- samples] (0,0.08)))"
   ]
  }
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