model.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.9/site-packages/tqdm/auto.py:22: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
      "  from .autonotebook import tqdm as notebook_tqdm\n"
     ]
    }
   ],
   "source": [
    "from cmdstanpy import CmdStanModel, from_csv\n",
    "\n",
    "import numpy as np\n",
    "import scipy.stats as stats\n",
    "import arviz as az\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import os\n",
    "import glob"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Remarks\n",
    "To run this notebook you need minimum of 16GBs of RAM. Also models are fitted and sampled using separate script, because it takes hours to fit them. In this notebook they're read from csvs, which are available here: https://drive.google.com/file/d/1K6SIB9vhR5yCagJBRwbji16pcLUo4bnw/view?usp=sharing\n",
    "\n",
    "You need this data to properly run this notebook, so download and unpack them beforehand in the same folder as this notebook!\n",
    "\n",
    "If you would like to fit models yourself, then you should use models_fitting.py script. Warning: it deletes previous fits, so create backup if you don't want to lose that data!\n",
    "\n",
    "Notebook is designed to run cell by cell, if done otherwise will probably crash."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# DATA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# load data\n",
    "df = pd.read_csv('delivery_time_data.csv', delimiter=';', decimal=',')\n",
    "\n",
    "df = df[df[\"Road distances [km]\"] < 20]\n",
    "\n",
    "# TEMP: only for testing plots and functions\n",
    "train_df = pd.DataFrame(df.iloc[:, :])\n",
    "\n",
    "# normalized distance\n",
    "train_df[\"Normalized distances\"] = (train_df[\"Road distances [km]\"] - train_df[\"Road distances [km]\"].mean()) / train_df[\"Road distances [km]\"].std()\n",
    "\n",
    "# normalized meal preparation time\n",
    "train_df[\"Normalized mealprep\"] = (train_df[\"Meal_preparation_time\"] - train_df[\"Meal_preparation_time\"].mean()) / train_df[\"Meal_preparation_time\"].std()\n",
    "\n",
    "# map categorical traffic density to numbers\n",
    "road_density_map = {'Jam ':1, 'High ':2, 'Medium ':3, 'Low ':4}\n",
    "\n",
    "train_df[\"Road_traffic_density\"] = train_df[\"Road_traffic_density\"].apply(lambda x: road_density_map[x])\n",
    "\n",
    "#------------------------------------------------------- parameters exclusive for model 2 --------------------------------------------------\n",
    "\n",
    "# delivery person rating\n",
    "train_df[\"Normalized person_rating\"] = (train_df[\"Delivery_person_Ratings\"] - train_df[\"Delivery_person_Ratings\"].mean()) / train_df[\"Delivery_person_Ratings\"].std()\n",
    "\n",
    "# number of deliveries\n",
    "train_df[\"multiple_deliveries\"] = train_df[\"multiple_deliveries\"]+1\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1800x1440 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot data\n",
    "\n",
    "fig, ax = plt.subplots(3,2, figsize=(25,20))\n",
    "fig.suptitle(\"Data used in inference\", fontsize=24)\n",
    "\n",
    "ax[0,0].hist(train_df[\"Normalized distances\"], bins=np.arange(-1.5,2.0,0.1))\n",
    "ax[0,0].set_title(\"Standarized delivery distance\")\n",
    "ax[0,0].set_xlabel(\"Standarized distance value\")\n",
    "ax[0,0].set_ylabel(\"Count\")\n",
    "\n",
    "ax[0,1].hist(train_df[\"Normalized mealprep\"], bins=20)\n",
    "ax[0,1].set_title(\"Standarized meal preparation time\")\n",
    "ax[0,1].set_xlabel(\"Standarized meal preparation time value\")\n",
    "ax[0,1].set_ylabel(\"Count\")\n",
    "\n",
    "ax[1,0].hist(train_df[\"Road_traffic_density\"], bins=20)\n",
    "ax[1,0].set_title(\"Categories of road traffic\")\n",
    "ax[1,0].set_xlabel(\"Categories type\")\n",
    "ax[1,0].set_ylabel(\"Count\")\n",
    "ax[1,0].set_xticks([1,2,3,4])\n",
    "ax[1,0].set_xticklabels([\"Jam\",\"High\",\"Medium\",\"Low\"])\n",
    "\n",
    "\n",
    "ax[1,1].hist(train_df[\"multiple_deliveries\"], bins=20)\n",
    "ax[1,1].set_title(\"Number of deliveries\")\n",
    "ax[1,1].set_xlabel(\"Amount of distinct deliveries\")\n",
    "ax[1,1].set_xticks([1,2,3,4])\n",
    "ax[1,1].set_ylabel(\"Count\")\n",
    "\n",
    "ax[2,0].hist(train_df[\"Normalized person_rating\"], bins=np.arange(-7,2,0.5))\n",
    "ax[2,0].set_title(\"Standarized delivery person rating\")\n",
    "ax[2,0].set_xlabel(\"Standardized rating value\")\n",
    "ax[2,0].set_ylabel(\"Count\")\n",
    "ax[2,0].set_xticks(np.arange(-7,2,1))\n",
    "\n",
    "ax[2,1].remove()\n",
    "\n",
    "fig.savefig('plots/data.png', facecolor='w')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PPC AND FIT - MODEL 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "data{\n",
      "    int N; // no of samples\n",
      "    array[N] real distance;   // distances\n",
      "    array[N] real meal_preparation_time;\n",
      "    array[N] int traffic_level;\n",
      "}\n",
      "\n",
      "generated quantities {\n",
      "   real distance_coeff = normal_rng(0, 0.3);\n",
      "   real meal_prep_coeff = normal_rng(0, 0.3);\n",
      "   real mean = normal_rng(3, 0.1);\n",
      "\n",
      "   array[4] real traffic_level_coeff;\n",
      "   traffic_level_coeff[1] = normal_rng(0, 0.3);\n",
      "   traffic_level_coeff[2] = normal_rng(0, 0.3);\n",
      "   traffic_level_coeff[3] = normal_rng(0, 0.3);\n",
      "   traffic_level_coeff[4] = normal_rng(0, 0.3);\n",
      "\n",
      "   array[N] real mu;\n",
      "   real sigma = exponential_rng(0.5);\n",
      "   array[N] real delivery_times;\n",
      "\n",
      "   for (i in 1:N){\n",
      "      mu[i] = exp(distance_coeff*distance[i] + traffic_level_coeff[traffic_level[i]]+meal_prep_coeff*meal_preparation_time[i]+mean);\n",
      "      delivery_times[i] = inv_gamma_rng(pow(mu[i], 2) / pow(sigma, 2) + 2, pow(mu[i],3) / pow(sigma, 2) + mu[i]);\n",
      "   }\n",
      "}\n"
     ]
    }
   ],
   "source": [
    "# read ppc for model 1\n",
    "with open('model1_ppc.stan') as file:\n",
    "    print(file.read())\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:cmdstanpy:found newer exe file, not recompiling\n",
      "INFO:cmdstanpy:CmdStan start processing\n",
      "chain 1 |\u001b[34m███████▌  \u001b[0m| 00:29 Iteration: 700 / 1000 [ 70%]  (Sampling)"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[1;32m/home/project_repo/data_analytics_project/basic_model.ipynb Cell 4\u001b[0m in \u001b[0;36m<cell line: 8>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      <a href='vscode-notebook-cell://attached-container%2B7b22636f6e7461696e65724e616d65223a222f64615f636f6e7461696e6572227d/home/project_repo/data_analytics_project/basic_model.ipynb#W3sdnNjb2RlLXJlbW90ZQ%3D%3D?line=3'>4</a>\u001b[0m     os\u001b[39m.\u001b[39mremove(f)\n\u001b[1;32m      <a href='vscode-notebook-cell://attached-container%2B7b22636f6e7461696e65724e616d65223a222f64615f636f6e7461696e6572227d/home/project_repo/data_analytics_project/basic_model.ipynb#W3sdnNjb2RlLXJlbW90ZQ%3D%3D?line=5'>6</a>\u001b[0m model1_ppc\u001b[39m=\u001b[39mCmdStanModel(stan_file\u001b[39m=\u001b[39m\u001b[39m'\u001b[39m\u001b[39mmodel1_ppc.stan\u001b[39m\u001b[39m'\u001b[39m)\n\u001b[0;32m----> <a href='vscode-notebook-cell://attached-container%2B7b22636f6e7461696e65724e616d65223a222f64615f636f6e7461696e6572227d/home/project_repo/data_analytics_project/basic_model.ipynb#W3sdnNjb2RlLXJlbW90ZQ%3D%3D?line=7'>8</a>\u001b[0m model1_ppc_sim\u001b[39m=\u001b[39mmodel1_ppc\u001b[39m.\u001b[39;49msample(data\u001b[39m=\u001b[39;49m{\u001b[39m\"\u001b[39;49m\u001b[39mN\u001b[39;49m\u001b[39m\"\u001b[39;49m: \u001b[39mlen\u001b[39;49m(train_df), \u001b[39m\"\u001b[39;49m\u001b[39mdistance\u001b[39;49m\u001b[39m\"\u001b[39;49m: train_df[\u001b[39m\"\u001b[39;49m\u001b[39mNormalized distances\u001b[39;49m\u001b[39m\"\u001b[39;49m]\u001b[39m.\u001b[39;49mvalues,\n\u001b[1;32m      <a href='vscode-notebook-cell://attached-container%2B7b22636f6e7461696e65724e616d65223a222f64615f636f6e7461696e6572227d/home/project_repo/data_analytics_project/basic_model.ipynb#W3sdnNjb2RlLXJlbW90ZQ%3D%3D?line=8'>9</a>\u001b[0m                            \u001b[39m\"\u001b[39;49m\u001b[39mmeal_preparation_time\u001b[39;49m\u001b[39m\"\u001b[39;49m: train_df[\u001b[39m\"\u001b[39;49m\u001b[39mNormalized mealprep\u001b[39;49m\u001b[39m\"\u001b[39;49m]\u001b[39m.\u001b[39;49mvalues,\n\u001b[1;32m     <a href='vscode-notebook-cell://attached-container%2B7b22636f6e7461696e65724e616d65223a222f64615f636f6e7461696e6572227d/home/project_repo/data_analytics_project/basic_model.ipynb#W3sdnNjb2RlLXJlbW90ZQ%3D%3D?line=9'>10</a>\u001b[0m                            \u001b[39m\"\u001b[39;49m\u001b[39mtraffic_level\u001b[39;49m\u001b[39m\"\u001b[39;49m :train_df[\u001b[39m\"\u001b[39;49m\u001b[39mRoad_traffic_density\u001b[39;49m\u001b[39m\"\u001b[39;49m]\u001b[39m.\u001b[39;49mvalues}, \n\u001b[1;32m     <a href='vscode-notebook-cell://attached-container%2B7b22636f6e7461696e65724e616d65223a222f64615f636f6e7461696e6572227d/home/project_repo/data_analytics_project/basic_model.ipynb#W3sdnNjb2RlLXJlbW90ZQ%3D%3D?line=10'>11</a>\u001b[0m                      iter_sampling\u001b[39m=\u001b[39;49m\u001b[39m1000\u001b[39;49m,\n\u001b[1;32m     <a href='vscode-notebook-cell://attached-container%2B7b22636f6e7461696e65724e616d65223a222f64615f636f6e7461696e6572227d/home/project_repo/data_analytics_project/basic_model.ipynb#W3sdnNjb2RlLXJlbW90ZQ%3D%3D?line=11'>12</a>\u001b[0m                      iter_warmup\u001b[39m=\u001b[39;49m\u001b[39m0\u001b[39;49m, \n\u001b[1;32m     <a href='vscode-notebook-cell://attached-container%2B7b22636f6e7461696e65724e616d65223a222f64615f636f6e7461696e6572227d/home/project_repo/data_analytics_project/basic_model.ipynb#W3sdnNjb2RlLXJlbW90ZQ%3D%3D?line=12'>13</a>\u001b[0m                      chains\u001b[39m=\u001b[39;49m\u001b[39m1\u001b[39;49m, \n\u001b[1;32m     <a href='vscode-notebook-cell://attached-container%2B7b22636f6e7461696e65724e616d65223a222f64615f636f6e7461696e6572227d/home/project_repo/data_analytics_project/basic_model.ipynb#W3sdnNjb2RlLXJlbW90ZQ%3D%3D?line=13'>14</a>\u001b[0m                      fixed_param\u001b[39m=\u001b[39;49m\u001b[39mTrue\u001b[39;49;00m,\n\u001b[1;32m     <a href='vscode-notebook-cell://attached-container%2B7b22636f6e7461696e65724e616d65223a222f64615f636f6e7461696e6572227d/home/project_repo/data_analytics_project/basic_model.ipynb#W3sdnNjb2RlLXJlbW90ZQ%3D%3D?line=14'>15</a>\u001b[0m                      seed\u001b[39m=\u001b[39;49m\u001b[39m20230613\u001b[39;49m,\n\u001b[1;32m     <a href='vscode-notebook-cell://attached-container%2B7b22636f6e7461696e65724e616d65223a222f64615f636f6e7461696e6572227d/home/project_repo/data_analytics_project/basic_model.ipynb#W3sdnNjb2RlLXJlbW90ZQ%3D%3D?line=15'>16</a>\u001b[0m                      output_dir\u001b[39m=\u001b[39;49m\u001b[39m'\u001b[39;49m\u001b[39mmodels_output/model1/ppc/\u001b[39;49m\u001b[39m'\u001b[39;49m)\n",
      "File \u001b[0;32m/usr/local/lib/python3.9/site-packages/cmdstanpy/model.py:1037\u001b[0m, in \u001b[0;36mCmdStanModel.sample\u001b[0;34m(self, data, chains, parallel_chains, threads_per_chain, seed, chain_ids, inits, iter_warmup, iter_sampling, save_warmup, thin, max_treedepth, metric, step_size, adapt_engaged, adapt_delta, adapt_init_phase, adapt_metric_window, adapt_step_size, fixed_param, output_dir, sig_figs, save_latent_dynamics, save_profile, show_progress, show_console, refresh, time_fmt, force_one_process_per_chain)\u001b[0m\n\u001b[1;32m   1035\u001b[0m \u001b[39mwith\u001b[39;00m ThreadPoolExecutor(max_workers\u001b[39m=\u001b[39mparallel_procs) \u001b[39mas\u001b[39;00m executor:\n\u001b[1;32m   1036\u001b[0m     \u001b[39mfor\u001b[39;00m i \u001b[39min\u001b[39;00m \u001b[39mrange\u001b[39m(runset\u001b[39m.\u001b[39mnum_procs):\n\u001b[0;32m-> 1037\u001b[0m         executor\u001b[39m.\u001b[39msubmit(\n\u001b[1;32m   1038\u001b[0m             \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_run_cmdstan,\n\u001b[1;32m   1039\u001b[0m             runset\u001b[39m=\u001b[39mrunset,\n\u001b[1;32m   1040\u001b[0m             idx\u001b[39m=\u001b[39mi,\n\u001b[1;32m   1041\u001b[0m             show_progress\u001b[39m=\u001b[39mshow_progress,\n\u001b[1;32m   1042\u001b[0m             show_console\u001b[39m=\u001b[39mshow_console,\n\u001b[1;32m   1043\u001b[0m             progress_hook\u001b[39m=\u001b[39mprogress_hook,\n\u001b[1;32m   1044\u001b[0m         )\n\u001b[1;32m   1045\u001b[0m \u001b[39mif\u001b[39;00m show_progress \u001b[39mand\u001b[39;00m progress_hook \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[1;32m   1046\u001b[0m     progress_hook(\u001b[39m\"\u001b[39m\u001b[39mDone\u001b[39m\u001b[39m\"\u001b[39m, \u001b[39m-\u001b[39m\u001b[39m1\u001b[39m)  \u001b[39m# -1 == all chains finished\u001b[39;00m\n",
      "File \u001b[0;32m/usr/local/lib/python3.9/concurrent/futures/_base.py:637\u001b[0m, in \u001b[0;36mExecutor.__exit__\u001b[0;34m(self, exc_type, exc_val, exc_tb)\u001b[0m\n\u001b[1;32m    636\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39m__exit__\u001b[39m(\u001b[39mself\u001b[39m, exc_type, exc_val, exc_tb):\n\u001b[0;32m--> 637\u001b[0m     \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mshutdown(wait\u001b[39m=\u001b[39;49m\u001b[39mTrue\u001b[39;49;00m)\n\u001b[1;32m    638\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mFalse\u001b[39;00m\n",
      "File \u001b[0;32m/usr/local/lib/python3.9/concurrent/futures/thread.py:235\u001b[0m, in \u001b[0;36mThreadPoolExecutor.shutdown\u001b[0;34m(self, wait, cancel_futures)\u001b[0m\n\u001b[1;32m    233\u001b[0m \u001b[39mif\u001b[39;00m wait:\n\u001b[1;32m    234\u001b[0m     \u001b[39mfor\u001b[39;00m t \u001b[39min\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_threads:\n\u001b[0;32m--> 235\u001b[0m         t\u001b[39m.\u001b[39;49mjoin()\n",
      "File \u001b[0;32m/usr/local/lib/python3.9/threading.py:1053\u001b[0m, in \u001b[0;36mThread.join\u001b[0;34m(self, timeout)\u001b[0m\n\u001b[1;32m   1050\u001b[0m     \u001b[39mraise\u001b[39;00m \u001b[39mRuntimeError\u001b[39;00m(\u001b[39m\"\u001b[39m\u001b[39mcannot join current thread\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[1;32m   1052\u001b[0m \u001b[39mif\u001b[39;00m timeout \u001b[39mis\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[0;32m-> 1053\u001b[0m     \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_wait_for_tstate_lock()\n\u001b[1;32m   1054\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m   1055\u001b[0m     \u001b[39m# the behavior of a negative timeout isn't documented, but\u001b[39;00m\n\u001b[1;32m   1056\u001b[0m     \u001b[39m# historically .join(timeout=x) for x<0 has acted as if timeout=0\u001b[39;00m\n\u001b[1;32m   1057\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_wait_for_tstate_lock(timeout\u001b[39m=\u001b[39m\u001b[39mmax\u001b[39m(timeout, \u001b[39m0\u001b[39m))\n",
      "File \u001b[0;32m/usr/local/lib/python3.9/threading.py:1073\u001b[0m, in \u001b[0;36mThread._wait_for_tstate_lock\u001b[0;34m(self, block, timeout)\u001b[0m\n\u001b[1;32m   1070\u001b[0m     \u001b[39mreturn\u001b[39;00m\n\u001b[1;32m   1072\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[0;32m-> 1073\u001b[0m     \u001b[39mif\u001b[39;00m lock\u001b[39m.\u001b[39;49macquire(block, timeout):\n\u001b[1;32m   1074\u001b[0m         lock\u001b[39m.\u001b[39mrelease()\n\u001b[1;32m   1075\u001b[0m         \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_stop()\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "chain 1 |\u001b[34m█████████▏\u001b[0m| 00:37 Iteration: 900 / 1000 [ 90%]  (Sampling)"
     ]
    }
   ],
   "source": [
    "# remove previously sampled ppc for model 1\n",
    "files = glob.glob('models_output/model1/ppc/*')\n",
    "for f in files:\n",
    "    os.remove(f)\n",
    "\n",
    "model1_ppc=CmdStanModel(stan_file='model1_ppc.stan')\n",
    "\n",
    "model1_ppc_sim=model1_ppc.sample(data={\"N\": len(train_df), \"distance\": train_df[\"Normalized distances\"].values,\n",
    "                           \"meal_preparation_time\": train_df[\"Normalized mealprep\"].values,\n",
    "                           \"traffic_level\" :train_df[\"Road_traffic_density\"].values}, \n",
    "                     iter_sampling=1000,\n",
    "                     iter_warmup=0, \n",
    "                     chains=1, \n",
    "                     fixed_param=True,\n",
    "                     seed=20230613,\n",
    "                     output_dir='models_output/model1/ppc/')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1800x1080 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1800x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1800x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot preparation\n",
    "fig, ax = plt.subplots(2,2, figsize=(25,15))\n",
    "fig.suptitle(\"Prior checks for parameters used in link function - MODEL 1\", fontsize=24)\n",
    "\n",
    "# get distance coeff\n",
    "model1_ppc_distance_coeff = model1_ppc_sim.stan_variable('distance_coeff')\n",
    "\n",
    "# plot distance coeff\n",
    "ax[0,0].hist(model1_ppc_distance_coeff,label=\"Distance coefficient\", bins=np.linspace(-1.2,1.2,50))\n",
    "ax[0,0].legend()\n",
    "ax[0,0].set_xlabel(\"Parameter value\")\n",
    "ax[0,0].set_ylabel(\"Parameter count\")\n",
    "ax[0,0].set_title(\"Histogram of distance coefficients\")\n",
    "\n",
    "# get meal_prep_coeff coeff\n",
    "model1_ppc_meal_prep_coeff = model1_ppc_sim.stan_variable('meal_prep_coeff')\n",
    "\n",
    "# plot meal_prep_coeff coeff\n",
    "ax[0,1].hist(model1_ppc_meal_prep_coeff,label=\"Meal preparation time coefficient\", bins=np.linspace(-1.2,1.2,50))\n",
    "ax[0,1].legend()\n",
    "ax[0,1].set_xlabel(\"Parameter value\")\n",
    "ax[0,1].set_ylabel(\"Parameter count\")\n",
    "ax[0,1].set_title(\"Histogram of meal preparation time coefficients\")\n",
    "\n",
    "# get mean\n",
    "model1_ppc_mean = model1_ppc_sim.stan_variable('mean')\n",
    "\n",
    "# plot mean\n",
    "ax[1,0].hist(model1_ppc_mean,label=\"Mean intercept\", bins=np.linspace(2.5,3.5,50))\n",
    "ax[1,0].legend()\n",
    "ax[1,0].set_xlabel(\"Parameter value\")\n",
    "ax[1,0].set_ylabel(\"Parameter count\")\n",
    "ax[1,0].set_title(\"Histogram of mean intercept\")\n",
    "\n",
    "# get traffic level coeff\n",
    "model1_ppc_traffic_coeff = model1_ppc_sim.stan_variable('traffic_level_coeff')\n",
    "\n",
    "# plot traffic coeff\n",
    "ax[1,1].hist(model1_ppc_traffic_coeff[:,0],label=\"Jam\", alpha=0.3, bins=np.linspace(-1.2,1.2,50))\n",
    "ax[1,1].hist(model1_ppc_traffic_coeff[:,1],label=\"High\", alpha=0.3, bins=np.linspace(-1.2,1.2,50))\n",
    "ax[1,1].hist(model1_ppc_traffic_coeff[:,2],label=\"Medium\", alpha=0.3, bins=np.linspace(-1.2,1.2,50))\n",
    "ax[1,1].hist(model1_ppc_traffic_coeff[:,3],label=\"Low\", alpha=0.3, bins=np.linspace(-1.2,1.2,50))\n",
    "ax[1,1].legend()\n",
    "ax[1,1].set_xlabel(\"Parameter value\")\n",
    "ax[1,1].set_ylabel(\"Parameter count\")\n",
    "ax[1,1].set_title(\"Histogram of traffic level coefficients\")\n",
    "plt.show()\n",
    "\n",
    "# save plot\n",
    "fig.savefig('plots/model1/link_params_ppc.png', facecolor='w')\n",
    "\n",
    "#-------------------------------------PARAMS FOR MODEL-------------------------------------------------\n",
    "# plot preparation\n",
    "fig1, ax1= plt.subplots(1,2, figsize=(25,8))\n",
    "fig1.suptitle(\"Prior checks for parameters used in likelihood - MODEL 1\", fontsize=24)\n",
    "\n",
    "# get distance coeff (flatten because its MxN matrix (data samples x algo samples))\n",
    "model1_ppc_mu = model1_ppc_sim.stan_variable('mu').flatten()\n",
    "\n",
    "# plot distance coeff\n",
    "az.plot_posterior(model1_ppc_mu, kind='hist', ax=ax1[0], bins=np.linspace(0,100,50), group='prior')\n",
    "ax1[0].set_frame_on(True)\n",
    "ax1[0].set_xlabel(\"Parameter value\")\n",
    "ax1[0].set_ylabel(\"Parameter count\")\n",
    "ax1[0].set_title(\"Histogram of mu (mean of delivery time)\")\n",
    "\n",
    "# get meal_prep_coeff coeff\n",
    "model1_ppc_sigma = model1_ppc_sim.stan_variable('sigma')\n",
    "\n",
    "# plot meal_prep_coeff coeff\n",
    "ax1[1].hist(model1_ppc_sigma,label=\"Standard deviation\", bins=np.linspace(0,15,50))\n",
    "ax1[1].legend()\n",
    "ax1[1].set_xlabel(\"Parameter value\")\n",
    "ax1[1].set_ylabel(\"Parameter count\")\n",
    "ax1[1].set_title(\"Histogram of standard deviation of delivery time\")\n",
    "plt.show()\n",
    "\n",
    "# save plot\n",
    "fig1.savefig('plots/model1/model_params_ppc.png', facecolor='w')\n",
    "\n",
    "#--------------------------------------PPC MEASUREMENTS------------------------------------------------------\n",
    "\n",
    "fig2, ax2= plt.subplots(1,2, figsize=(25,8))\n",
    "fig2.suptitle(\"Prior predictive checks - generated delivery time data - MODEL 1\", fontsize=24)\n",
    "\n",
    "# get measurements\n",
    "model1_ppc_measurements = model1_ppc_sim.stan_variable('delivery_times').flatten()  # flatten makes it row/column vector (one of these)\n",
    "\n",
    "# set bins\n",
    "bins = np.linspace(0, 120, 120)\n",
    "\n",
    "az.plot_posterior(model1_ppc_measurements, kind='hist', ax=ax2[0], bins=bins, group='prior', backend=\"matplotlib\")\n",
    "ax2[0].set_xlabel(\"Parameter value\")\n",
    "ax2[0].set_ylabel(\"Parameter count\")\n",
    "ax2[0].set_title(\"Normalized histogram of generated data\")\n",
    "\n",
    "# plot measurements\n",
    "ax2[1].hist(model1_ppc_measurements, density=True, bins=bins,  alpha=0.5, label=\"Generated data\")\n",
    "\n",
    "# compare with real data, density set to True because each data point sampled 999 times\n",
    "ax2[1].hist(train_df[\"Time_taken(min)\"], density=True, bins=bins, alpha=0.5, label=\"Measured data\")\n",
    "ax2[1].legend()\n",
    "ax2[1].set_xlabel(\"Parameter value\")\n",
    "ax2[1].set_ylabel(\"Parameter count\")\n",
    "ax2[1].set_title(\"Comparison between real and generated data\")\n",
    "plt.show()\n",
    "\n",
    "# save plot\n",
    "fig2.savefig('plots/model1/generated_data_ppc.png', facecolor='w')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "data{\n",
      "    int N;                          // Number of samples\n",
      "    vector[N] distance;             // Distances\n",
      "    vector[N] meal_preparation_time; // Meal preparation times\n",
      "    vector[N] delivery_times;       // Delivery times\n",
      "    array[N] int traffic_level;           // Traffic levels\n",
      "}\n",
      "\n",
      "parameters{\n",
      "    real distance_coeff;\n",
      "    real mean;\n",
      "    vector[4] traffic_level_coeff;\n",
      "    real meal_prep_coeff;\n",
      "    real<lower=0> sigma;\n",
      "}\n",
      "\n",
      "transformed parameters {\n",
      "    vector[N] mu;\n",
      "    for(i in 1:N){\n",
      "        mu[i] = exp(distance_coeff * distance[i] + traffic_level_coeff[traffic_level[i]] + meal_prep_coeff * meal_preparation_time[i]+mean);\n",
      "    }\n",
      "\n",
      "}\n",
      "\n",
      "model{\n",
      "    mean ~ normal(3, 0.1);\n",
      "    distance_coeff ~ normal(0,0.5);\n",
      "    meal_prep_coeff ~ normal(0,0.5);\n",
      "    sigma ~ exponential(0.5);\n",
      "    delivery_times ~ inv_gamma(pow(mu, 2) / pow(sigma, 2) + 2, pow(mu,3) / pow(sigma, 2) + mu);\n",
      "    traffic_level_coeff[1] ~ normal(0, 0.5);\n",
      "    traffic_level_coeff[2] ~ normal(0, 0.5);\n",
      "    traffic_level_coeff[3] ~ normal(0, 0.5);\n",
      "    traffic_level_coeff[4] ~ normal(0, 0.5);\n",
      "}\n",
      "\n",
      "generated quantities {\n",
      "    vector[N] delivery_time;\n",
      "    vector[N] log_lik;\n",
      "    for (i in 1:N){\n",
      "        delivery_time[i] = inv_gamma_rng(pow(mu[i], 2) / pow(sigma, 2) + 2, pow(mu[i],3) / pow(sigma, 2) + mu[i]);\n",
      "        log_lik[i] = inv_gamma_lpdf(delivery_times[i] | pow(mu[i], 2) / pow(sigma, 2) + 2, pow(mu[i],3) / pow(sigma, 2) + mu[i]);\n",
      "    }\n",
      "}\n"
     ]
    }
   ],
   "source": [
    "# read ppc for model 1\n",
    "with open('model1_fit.stan') as file:\n",
    "    print(file.read())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# load model from previously sampled csvs\n",
    "model1_sample = from_csv('/home/project_repo/data_analytics_project/models_output/model1/fit')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1800x1080 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1800x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "chain 1 |\u001b[34m█████████▏\u001b[0m| 06:34 Iteration: 1000 / 1000 [100%]  (Sampling)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1800x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot preparation\n",
    "fig, ax = plt.subplots(2,2, figsize=(25,15))\n",
    "fig.suptitle(\"Posterior checks for parameters used in link function - MODEL 1\", fontsize=24)\n",
    "\n",
    "# get distance coeff\n",
    "model1_fit_distance_coeff = model1_sample.stan_variable('distance_coeff')\n",
    "\n",
    "# plot distance coeff\n",
    "ax[0,0].hist(model1_fit_distance_coeff,label=\"Distance coefficient\", bins=np.linspace(-0.01,0.01,50))\n",
    "ax[0,0].legend()\n",
    "ax[0,0].set_xlabel(\"Parameter value\")\n",
    "ax[0,0].set_ylabel(\"Parameter count\")\n",
    "ax[0,0].set_title(\"Histogram of distance coefficients\")\n",
    "\n",
    "# get meal_prep_coeff coeff\n",
    "model1_fit_meal_prep_coeff = model1_sample.stan_variable('meal_prep_coeff')\n",
    "\n",
    "# plot meal_prep_coeff coeff\n",
    "ax[0,1].hist(model1_fit_meal_prep_coeff,label=\"Meal preparation time coefficient\", bins=np.linspace(0.02,0.06,50))\n",
    "ax[0,1].legend()\n",
    "ax[0,1].set_xlabel(\"Parameter value\")\n",
    "ax[0,1].set_ylabel(\"Parameter count\")\n",
    "ax[0,1].set_title(\"Histogram of meal preparation time coefficients\")\n",
    "\n",
    "# get mean\n",
    "model1_fit_mean = model1_sample.stan_variable('mean')\n",
    "\n",
    "# plot mean\n",
    "ax[1,0].hist(model1_fit_mean,label=\"Mean intercept\", bins=np.linspace(2.5,3.5,50))\n",
    "ax[1,0].legend()\n",
    "ax[1,0].set_xlabel(\"Parameter value\")\n",
    "ax[1,0].set_ylabel(\"Parameter count\")\n",
    "ax[1,0].set_title(\"Histogram of mean intercept\")\n",
    "\n",
    "# get traffic level coeff\n",
    "model1_fit_traffic_coeff = model1_sample.stan_variable('traffic_level_coeff')\n",
    "\n",
    "# plot traffic coeff\n",
    "ax[1,1].hist(model1_fit_traffic_coeff[:,0],label=\"Jam\", alpha=0.3, bins=np.linspace(-0.5,1.2,50))\n",
    "ax[1,1].hist(model1_fit_traffic_coeff[:,1],label=\"High\", alpha=0.3, bins=np.linspace(-0.5,1.2,50))\n",
    "ax[1,1].hist(model1_fit_traffic_coeff[:,2],label=\"Medium\", alpha=0.3, bins=np.linspace(-0.5,1.2,50))\n",
    "ax[1,1].hist(model1_fit_traffic_coeff[:,3],label=\"Low\", alpha=0.3, bins=np.linspace(-0.5,1.2,50))\n",
    "ax[1,1].legend()\n",
    "ax[1,1].set_xlabel(\"Parameter value\")\n",
    "ax[1,1].set_ylabel(\"Parameter count\")\n",
    "ax[1,1].set_title(\"Histogram of traffic level coefficients\")\n",
    "plt.show()\n",
    "\n",
    "# save plot\n",
    "fig.savefig('plots/model1/link_params_fit.png', facecolor='w')\n",
    "\n",
    "#-------------------------------------PARAMS FOR MODEL-------------------------------------------------\n",
    "# plot preparation\n",
    "fig1, ax1= plt.subplots(1,2, figsize=(25,8))\n",
    "fig1.suptitle(\"Posterior checks for parameters used in likelihood - MODEL 1\", fontsize=24)\n",
    "\n",
    "# get distance coeff (flatten because its MxN matrix (data samples x algo samples))\n",
    "model1_fit_mu = model1_sample.stan_variable('mu').flatten()\n",
    "\n",
    "# plot distance coeff\n",
    "az.plot_posterior(model1_fit_mu, kind='hist', ax=ax1[0], bins=np.linspace(10,50,50), group='prior')\n",
    "ax1[0].set_frame_on(True)\n",
    "ax1[0].set_xlabel(\"Parameter value\")\n",
    "ax1[0].set_ylabel(\"Parameter count\")\n",
    "ax1[0].set_title(\"Histogram of mu (mean of delivery time)\")\n",
    "\n",
    "# get meal_prep_coeff coeff\n",
    "model1_fit_sigma = model1_sample.stan_variable('sigma')\n",
    "\n",
    "# plot meal_prep_coeff coeff\n",
    "ax1[1].hist(model1_fit_sigma,label=\"Standard deviation\", bins=np.linspace(9,11,50))\n",
    "ax1[1].legend()\n",
    "ax1[1].set_xlabel(\"Parameter value\")\n",
    "ax1[1].set_ylabel(\"Parameter count\")\n",
    "ax1[1].set_title(\"Histogram of standard deviation of delivery time\")\n",
    "plt.show()\n",
    "\n",
    "# save plot\n",
    "fig1.savefig('plots/model1/model_params_fit.png', facecolor='w')\n",
    "\n",
    "#--------------------------------------PPC MEASUREMENTS------------------------------------------------------\n",
    "\n",
    "fig2, ax2= plt.subplots(1,2, figsize=(25,8))\n",
    "fig2.suptitle(\"Posterior predictive checks - predicted delivery time data - MODEL 1\", fontsize=24)\n",
    "\n",
    "# get measurements\n",
    "model1_fit_measurements = model1_sample.stan_variable('delivery_time').flatten()  # flatten makes it row/column vector (one of these)\n",
    "\n",
    "# set bins\n",
    "bins = np.linspace(0, 100, 100)\n",
    "\n",
    "az.plot_posterior(model1_fit_measurements, kind='hist', ax=ax2[0], bins=bins, group='prior', backend=\"matplotlib\")\n",
    "ax2[0].set_xlabel(\"Parameter value\")\n",
    "ax2[0].set_ylabel(\"Parameter count\")\n",
    "ax2[0].set_title(\"Normalized histogram of predicted data\")\n",
    "\n",
    "# plot measurements\n",
    "ax2[1].hist(model1_fit_measurements, density=True, bins=bins,  alpha=0.5, label=\"Generated data\")\n",
    "\n",
    "# compare with real data, density set to True because each data point sampled 999 times\n",
    "ax2[1].hist(train_df[\"Time_taken(min)\"], density=True, bins=bins, alpha=0.5, label=\"Measured data\")\n",
    "ax2[1].legend()\n",
    "ax2[1].set_xlabel(\"Parameter value\")\n",
    "ax2[1].set_ylabel(\"Parameter count\")\n",
    "ax2[1].set_title(\"Comparison between real and predicted data\")\n",
    "plt.show()\n",
    "\n",
    "# save plot\n",
    "fig2.savefig('plots/model1/sampled_data_fit.png', facecolor='w')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PPC AND FIT - MODEL 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "data{\n",
      "    int N; // no of samples\n",
      "    array[N] real distance;   // distances\n",
      "    array[N] real meal_preparation_time;\n",
      "    array[N] int traffic_level;\n",
      "    array[N] real delivery_person_rating;\n",
      "    array[N] int number_of_deliveries;\n",
      "}\n",
      "\n",
      "generated quantities {\n",
      "   real distance_coeff = normal_rng(0, 0.3);\n",
      "   real person_rating_coeff = normal_rng(0,0.3);\n",
      "   real meal_prep_coeff = normal_rng(0, 0.3);\n",
      "   real mean = normal_rng(3, 0.1);\n",
      "\n",
      "   array[4] real traffic_level_coeff;\n",
      "   traffic_level_coeff[1] = normal_rng(0, 0.3);\n",
      "   traffic_level_coeff[2] = normal_rng(0, 0.3);\n",
      "   traffic_level_coeff[3] = normal_rng(0, 0.3);\n",
      "   traffic_level_coeff[4] = normal_rng(0, 0.3);\n",
      "\n",
      "   array[4] real deliveries_number_coeff; \n",
      "   deliveries_number_coeff[1] = normal_rng(0, 0.3);\n",
      "   deliveries_number_coeff[2] = normal_rng(0, 0.3);\n",
      "   deliveries_number_coeff[3] = normal_rng(0, 0.3);\n",
      "   deliveries_number_coeff[4] = normal_rng(0, 0.3);\n",
      "\n",
      "   array[N] real mu;\n",
      "   real sigma = exponential_rng(0.5);\n",
      "   array[N] real delivery_times;\n",
      "\n",
      "   for (i in 1:N){\n",
      "      mu[i] = exp(distance_coeff*distance[i] + traffic_level_coeff[traffic_level[i]]+meal_prep_coeff*meal_preparation_time[i]+person_rating_coeff*delivery_person_rating[i]+deliveries_number_coeff[number_of_deliveries[i]]+mean);\n",
      "      delivery_times[i] = inv_gamma_rng(pow(mu[i], 2) / pow(sigma, 2) + 2, pow(mu[i],3) / pow(sigma, 2) + mu[i]);\n",
      "   }\n",
      "}\n"
     ]
    }
   ],
   "source": [
    "# read ppc for model 2\n",
    "with open('model2_ppc.stan') as file:\n",
    "    print(file.read())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:cmdstanpy:found newer exe file, not recompiling\n",
      "INFO:cmdstanpy:CmdStan start processing\n",
      "chain 1 |\u001b[34m██████████\u001b[0m| 00:37 Sampling completed                      "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                                                                "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "INFO:cmdstanpy:CmdStan done processing.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "# remove previously sampled ppc for model 2\n",
    "files = glob.glob('models_output/model2/ppc/*')\n",
    "for f in files:\n",
    "    os.remove(f)\n",
    "\n",
    "model2_ppc=CmdStanModel(stan_file='model2_ppc.stan')\n",
    "\n",
    "model2_ppc_sim=model2_ppc.sample(data={\"N\": len(train_df), \"distance\": train_df[\"Normalized distances\"].values,\n",
    "                           \"meal_preparation_time\": train_df[\"Normalized mealprep\"].values,\n",
    "                           \"traffic_level\": train_df[\"Road_traffic_density\"].values,\n",
    "                           \"delivery_person_rating\": train_df[\"Normalized person_rating\"].values,\n",
    "                           \"number_of_deliveries\": train_df[\"multiple_deliveries\"].values}, \n",
    "                     iter_sampling=1000,\n",
    "                     iter_warmup=0, \n",
    "                     chains=1, \n",
    "                     fixed_param=True,\n",
    "                     seed=20230613,\n",
    "                     output_dir='models_output/model2/ppc/')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1800x1080 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1800x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1800x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot preparation\n",
    "fig, ax = plt.subplots(3,2, figsize=(25,15))\n",
    "fig.suptitle(\"Prior checks for parameters used in link function - MODEL 2\", fontsize=24)\n",
    "\n",
    "# get distance coeff\n",
    "model2_ppc_distance_coeff = model2_ppc_sim.stan_variable('distance_coeff')\n",
    "\n",
    "# plot distance coeff\n",
    "ax[0,0].hist(model2_ppc_distance_coeff,label=\"Distance coefficient\", bins=np.linspace(-1.2,1.2,50))\n",
    "ax[0,0].legend()\n",
    "ax[0,0].set_xlabel(\"Parameter value\")\n",
    "ax[0,0].set_ylabel(\"Parameter count\")\n",
    "ax[0,0].set_title(\"Histogram of distance coefficients\")\n",
    "\n",
    "# get meal_prep_coeff coeff\n",
    "model2_ppc_meal_prep_coeff = model2_ppc_sim.stan_variable('meal_prep_coeff')\n",
    "\n",
    "# plot meal_prep_coeff coeff\n",
    "ax[0,1].hist(model2_ppc_meal_prep_coeff,label=\"Meal preparation time coefficient\", bins=np.linspace(-1.2,1.2,50))\n",
    "ax[0,1].legend()\n",
    "ax[0,1].set_xlabel(\"Parameter value\")\n",
    "ax[0,1].set_ylabel(\"Parameter count\")\n",
    "ax[0,1].set_title(\"Histogram of meal preparation time coefficients\")\n",
    "\n",
    "# get mean\n",
    "model2_ppc_mean = model2_ppc_sim.stan_variable('mean')\n",
    "\n",
    "# plot mean\n",
    "ax[1,0].hist(model2_ppc_mean,label=\"Mean intercept\", bins=np.linspace(2.5,3.5,50))\n",
    "ax[1,0].legend()\n",
    "ax[1,0].set_xlabel(\"Parameter value\")\n",
    "ax[1,0].set_ylabel(\"Parameter count\")\n",
    "ax[1,0].set_title(\"Histogram of mean intercept\")\n",
    "\n",
    "# get traffic level coeff\n",
    "model2_ppc_traffic_coeff = model2_ppc_sim.stan_variable('traffic_level_coeff')\n",
    "\n",
    "# plot traffic coeff\n",
    "ax[1,1].hist(model2_ppc_traffic_coeff[:,0],label=\"Jam\", alpha=0.3, bins=np.linspace(-1.2,1.2,50))\n",
    "ax[1,1].hist(model2_ppc_traffic_coeff[:,1],label=\"High\", alpha=0.3, bins=np.linspace(-1.2,1.2,50))\n",
    "ax[1,1].hist(model2_ppc_traffic_coeff[:,2],label=\"Medium\", alpha=0.3, bins=np.linspace(-1.2,1.2,50))\n",
    "ax[1,1].hist(model2_ppc_traffic_coeff[:,3],label=\"Low\", alpha=0.3, bins=np.linspace(-1.2,1.2,50))\n",
    "ax[1,1].legend()\n",
    "ax[1,1].set_xlabel(\"Parameter value\")\n",
    "ax[1,1].set_ylabel(\"Parameter count\")\n",
    "ax[1,1].set_title(\"Histogram of traffic level coefficients\")\n",
    "\n",
    "# get delivery person rating coeff\n",
    "model2_ppc_mean = model2_ppc_sim.stan_variable('person_rating_coeff')\n",
    "\n",
    "# plot elivery person rating coeff\n",
    "ax[2,0].hist(model2_ppc_mean,label=\"Delivery person rating coefficient\", bins=np.linspace(-1.2,1.2,50))\n",
    "ax[2,0].legend()\n",
    "ax[2,0].set_xlabel(\"Parameter value\")\n",
    "ax[2,0].set_ylabel(\"Parameter count\")\n",
    "ax[2,0].set_title(\"Histogram of delivery person rating coefficients\")\n",
    "\n",
    "# get number of deliveries coeffs\n",
    "model2_ppc_traffic_coeff = model2_ppc_sim.stan_variable('deliveries_number_coeff')\n",
    "\n",
    "# plot traffic coeff\n",
    "ax[2,1].hist(model2_ppc_traffic_coeff[:,0],label=\"0 deliveries\", alpha=0.3, bins=np.linspace(-1.2,1.2,50))\n",
    "ax[2,1].hist(model2_ppc_traffic_coeff[:,1],label=\"1 delivery\", alpha=0.3, bins=np.linspace(-1.2,1.2,50))\n",
    "ax[2,1].hist(model2_ppc_traffic_coeff[:,2],label=\"2 deliveries\", alpha=0.3, bins=np.linspace(-1.2,1.2,50))\n",
    "ax[2,1].hist(model2_ppc_traffic_coeff[:,3],label=\"3 deliveries\", alpha=0.3, bins=np.linspace(-1.2,1.2,50))\n",
    "ax[2,1].legend()\n",
    "ax[2,1].set_xlabel(\"Parameter value\")\n",
    "ax[2,1].set_ylabel(\"Parameter count\")\n",
    "ax[2,1].set_title(\"Histogram of deliveries numbers coefficients\")\n",
    "plt.show()\n",
    "\n",
    "# save plot\n",
    "fig.savefig('plots/model2/link_params_ppc.png', facecolor='w')\n",
    "\n",
    "#-------------------------------------PARAMS FOR MODEL-------------------------------------------------\n",
    "# plot preparation\n",
    "fig1, ax1= plt.subplots(1,2, figsize=(25,8))\n",
    "fig1.suptitle(\"Prior checks for parameters used in likelihood - MODEL 2\", fontsize=24)\n",
    "\n",
    "# get distance coeff (flatten because its MxN matrix (data samples x algo samples))\n",
    "model2_ppc_mu = model2_ppc_sim.stan_variable('mu').flatten()\n",
    "\n",
    "# plot distance coeff\n",
    "az.plot_posterior(model2_ppc_mu, kind='hist', ax=ax1[0], bins=np.linspace(0,100,50), group='prior')\n",
    "ax1[0].set_frame_on(True)\n",
    "ax1[0].set_xlabel(\"Parameter value\")\n",
    "ax1[0].set_ylabel(\"Parameter count\")\n",
    "ax1[0].set_title(\"Histogram of mu (mean of delivery time)\")\n",
    "\n",
    "# get meal_prep_coeff coeff\n",
    "model2_ppc_sigma = model2_ppc_sim.stan_variable('sigma')\n",
    "\n",
    "# plot meal_prep_coeff coeff\n",
    "ax1[1].hist(model2_ppc_sigma,label=\"Standard deviation\", bins=np.linspace(0,15,50))\n",
    "ax1[1].legend()\n",
    "ax1[1].set_xlabel(\"Parameter value\")\n",
    "ax1[1].set_ylabel(\"Parameter count\")\n",
    "ax1[1].set_title(\"Histogram of standard deviation of delivery time\")\n",
    "plt.show()\n",
    "\n",
    "# save plot\n",
    "fig1.savefig('plots/model2/model_params_ppc.png', facecolor='w')\n",
    "\n",
    "#--------------------------------------PPC MEASUREMENTS------------------------------------------------------\n",
    "\n",
    "fig2, ax2= plt.subplots(1,2, figsize=(25,8))\n",
    "fig2.suptitle(\"Prior predictive checks - generated delivery time data - MODEL 2\", fontsize=24)\n",
    "\n",
    "# get measurements\n",
    "model2_ppc_measurements = model2_ppc_sim.stan_variable('delivery_times').flatten()  # flatten makes it row/column vector (one of these)\n",
    "\n",
    "# set bins\n",
    "bins = np.linspace(0, 120, 120)\n",
    "\n",
    "az.plot_posterior(model2_ppc_measurements, kind='hist', ax=ax2[0], bins=bins, group='prior', backend=\"matplotlib\")\n",
    "ax2[0].set_xlabel(\"Parameter value\")\n",
    "ax2[0].set_ylabel(\"Parameter count\")\n",
    "ax2[0].set_title(\"Normalized histogram of generated data\")\n",
    "\n",
    "# plot measurements\n",
    "ax2[1].hist(model2_ppc_measurements, density=True, bins=bins,  alpha=0.5, label=\"Generated data\")\n",
    "\n",
    "# compare with real data, density set to True because each data point sampled 999 times\n",
    "ax2[1].hist(train_df[\"Time_taken(min)\"], density=True, bins=bins, alpha=0.5, label=\"Measured data\")\n",
    "ax2[1].legend()\n",
    "ax2[1].set_xlabel(\"Parameter value\")\n",
    "ax2[1].set_ylabel(\"Parameter count\")\n",
    "ax2[1].set_title(\"Comparison between real and generated data\")\n",
    "plt.show()\n",
    "\n",
    "# save plot\n",
    "fig2.savefig('plots/model2/generated_data_ppc.png', facecolor='w')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "data{\n",
      "    int N;                          // Number of samples\n",
      "    vector[N] distance;             // Distances\n",
      "    vector[N] meal_preparation_time; // Meal preparation times\n",
      "    vector[N] delivery_times;       // Delivery times\n",
      "    array[N] int traffic_level;           // Traffic levels\n",
      "    array[N] real delivery_person_rating;\n",
      "    array[N] int number_of_deliveries;\n",
      "}\n",
      "\n",
      "parameters{\n",
      "    real distance_coeff;\n",
      "    real mean;\n",
      "    vector[4] traffic_level_coeff;\n",
      "    real meal_prep_coeff;\n",
      "    real<lower=0> sigma;\n",
      "    real person_rating_coeff;\n",
      "    vector[4] deliveries_number_coeff;\n",
      "}\n",
      "\n",
      "transformed parameters {\n",
      "    vector[N] mu;\n",
      "    for(i in 1:N){\n",
      "        mu[i] = exp(distance_coeff * distance[i] + traffic_level_coeff[traffic_level[i]] + meal_prep_coeff * meal_preparation_time[i]+person_rating_coeff*delivery_person_rating[i]+deliveries_number_coeff[number_of_deliveries[i]]+mean);\n",
      "    }\n",
      "\n",
      "}\n",
      "\n",
      "model{\n",
      "    mean ~ normal(3, 0.1);\n",
      "    person_rating_coeff ~ normal(0,0.3);\n",
      "    distance_coeff ~ normal(0,0.3);\n",
      "    meal_prep_coeff ~ normal(0,0.3);\n",
      "    sigma ~ exponential(0.5);\n",
      "    delivery_times ~ inv_gamma(pow(mu, 2) / pow(sigma, 2) + 2, pow(mu,3) / pow(sigma, 2) + mu);\n",
      "    traffic_level_coeff[1] ~ normal(0, 0.3);\n",
      "    traffic_level_coeff[2] ~ normal(0, 0.3);\n",
      "    traffic_level_coeff[3] ~ normal(0, 0.3);\n",
      "    traffic_level_coeff[4] ~ normal(0, 0.3);\n",
      "    deliveries_number_coeff[1] ~ normal(0, 0.3);\n",
      "    deliveries_number_coeff[2] ~ normal(0, 0.3);\n",
      "    deliveries_number_coeff[3] ~ normal(0, 0.3);\n",
      "    deliveries_number_coeff[4] ~ normal(0, 0.3);\n",
      "}\n",
      "\n",
      "generated quantities {\n",
      "    vector[N] delivery_time;\n",
      "    vector[N] log_lik;\n",
      "    for (i in 1:N){\n",
      "        delivery_time[i] = inv_gamma_rng(pow(mu[i], 2) / pow(sigma, 2) + 2, pow(mu[i],3) / pow(sigma, 2) + mu[i]);\n",
      "        log_lik[i] = inv_gamma_lpdf(delivery_times[i] | pow(mu[i], 2) / pow(sigma, 2) + 2, pow(mu[i],3) / pow(sigma, 2) + mu[i]);\n",
      "    }\n",
      "}\n"
     ]
    }
   ],
   "source": [
    "# read fit for model 2\n",
    "with open('model2_fit.stan') as file:\n",
    "    print(file.read())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# delete model 1 from memory (it weighs around 4GBs...)\n",
    "del model1_sample\n",
    "del model2_ppc_sim\n",
    "\n",
    "# load model from previously sampled csvs\n",
    "model2_sample = from_csv('/home/project_repo/data_analytics_project/models_output/model2/fit')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1800x1080 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1800x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1800x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot preparation\n",
    "fig, ax = plt.subplots(3,2, figsize=(25,15))\n",
    "fig.suptitle(\"Posterior checks for parameters used in link function - MODEL 2\", fontsize=24)\n",
    "\n",
    "# get distance coeff\n",
    "model2_fit_distance_coeff = model2_sample.stan_variable('distance_coeff')\n",
    "\n",
    "# plot distance coeff\n",
    "ax[0,0].hist(model2_fit_distance_coeff,label=\"Distance coefficient\", bins=np.linspace(-0.01,0.01,50))\n",
    "ax[0,0].legend()\n",
    "ax[0,0].set_xlabel(\"Parameter value\")\n",
    "ax[0,0].set_ylabel(\"Parameter count\")\n",
    "ax[0,0].set_title(\"Histogram of distance coefficients\")\n",
    "\n",
    "# get meal_prep_coeff coeff\n",
    "model2_fit_meal_prep_coeff = model2_sample.stan_variable('meal_prep_coeff')\n",
    "\n",
    "# plot meal_prep_coeff coeff\n",
    "ax[0,1].hist(model2_fit_meal_prep_coeff,label=\"Meal preparation time coefficient\", bins=np.linspace(0.02,0.04,50))\n",
    "ax[0,1].legend()\n",
    "ax[0,1].set_xlabel(\"Parameter value\")\n",
    "ax[0,1].set_ylabel(\"Parameter count\")\n",
    "ax[0,1].set_title(\"Histogram of meal preparation time coefficients\")\n",
    "\n",
    "# get mean\n",
    "model2_fit_mean = model2_sample.stan_variable('mean')\n",
    "\n",
    "# plot mean\n",
    "ax[1,0].hist(model2_fit_mean,label=\"Mean intercept\", bins=np.linspace(2.5,3.5,50))\n",
    "ax[1,0].legend()\n",
    "ax[1,0].set_xlabel(\"Parameter value\")\n",
    "ax[1,0].set_ylabel(\"Parameter count\")\n",
    "ax[1,0].set_title(\"Histogram of mean intercept\")\n",
    "\n",
    "# get traffic level coeff\n",
    "model2_fit_traffic_coeff = model2_sample.stan_variable('traffic_level_coeff')\n",
    "\n",
    "# plot traffic coeff\n",
    "ax[1,1].hist(model2_fit_traffic_coeff[:,0],label=\"Jam\", alpha=0.3, bins=np.linspace(-0.5,1,50))\n",
    "ax[1,1].hist(model2_fit_traffic_coeff[:,1],label=\"High\", alpha=0.3, bins=np.linspace(-0.5,1,50))\n",
    "ax[1,1].hist(model2_fit_traffic_coeff[:,2],label=\"Medium\", alpha=0.3, bins=np.linspace(-0.5,1,50))\n",
    "ax[1,1].hist(model2_fit_traffic_coeff[:,3],label=\"Low\", alpha=0.3, bins=np.linspace(-0.5,1,50))\n",
    "ax[1,1].legend()\n",
    "ax[1,1].set_xlabel(\"Parameter value\")\n",
    "ax[1,1].set_ylabel(\"Parameter count\")\n",
    "ax[1,1].set_title(\"Histogram of traffic level coefficients\")\n",
    "\n",
    "# get delivery person rating coeff\n",
    "model2_fit_person_rating = model2_sample.stan_variable('person_rating_coeff')\n",
    "\n",
    "# plot elivery person rating coeff\n",
    "ax[2,0].hist(model2_fit_person_rating,label=\"Delivery person rating coefficient\", bins=np.linspace(-0.1,-0.08,50))\n",
    "ax[2,0].legend()\n",
    "ax[2,0].set_xlabel(\"Parameter value\")\n",
    "ax[2,0].set_ylabel(\"Parameter count\")\n",
    "ax[2,0].set_title(\"Histogram of delivery person rating coefficients\")\n",
    "\n",
    "# get number of deliveries coeffs\n",
    "model2_fit_delivery_number_coeff = model2_sample.stan_variable('deliveries_number_coeff')\n",
    "\n",
    "# plot traffic coeff\n",
    "ax[2,1].hist(model2_fit_delivery_number_coeff[:,0],label=\"0 deliveries\", alpha=0.3, bins=np.linspace(-1.2,1.2,50))\n",
    "ax[2,1].hist(model2_fit_delivery_number_coeff[:,1],label=\"1 delivery\", alpha=0.3, bins=np.linspace(-1.2,1.2,50))\n",
    "ax[2,1].hist(model2_fit_delivery_number_coeff[:,2],label=\"2 deliveries\", alpha=0.3, bins=np.linspace(-1.2,1.2,50))\n",
    "ax[2,1].hist(model2_fit_delivery_number_coeff[:,3],label=\"3 deliveries\", alpha=0.3, bins=np.linspace(-1.2,1.2,50))\n",
    "ax[2,1].legend()\n",
    "ax[2,1].set_xlabel(\"Parameter value\")\n",
    "ax[2,1].set_ylabel(\"Parameter count\")\n",
    "ax[2,1].set_title(\"Histogram of deliveries numbers coefficients\")\n",
    "plt.show()\n",
    "\n",
    "# save plot\n",
    "fig.savefig('plots/model2/link_params_fit.png', facecolor='w')\n",
    "\n",
    "#-------------------------------------PARAMS FOR MODEL-------------------------------------------------\n",
    "# plot preparation\n",
    "fig1, ax1= plt.subplots(1,2, figsize=(25,8))\n",
    "fig1.suptitle(\"Posterior checks for parameters used in likelihood - MODEL 2\", fontsize=24)\n",
    "\n",
    "# get distance coeff (flatten because its MxN matrix (data samples x algo samples))\n",
    "model2_fit_mu = model2_sample.stan_variable('mu').flatten()\n",
    "\n",
    "# plot distance coeff\n",
    "az.plot_posterior(model2_fit_mu, kind='hist', ax=ax1[0], bins=np.linspace(10,50,50), group='prior')\n",
    "ax1[0].set_frame_on(True)\n",
    "ax1[0].set_xlabel(\"Parameter value\")\n",
    "ax1[0].set_ylabel(\"Parameter count\")\n",
    "ax1[0].set_title(\"Histogram of mu (mean of delivery time)\")\n",
    "\n",
    "# get meal_prep_coeff coeff\n",
    "model2_fit_sigma = model2_sample.stan_variable('sigma')\n",
    "\n",
    "# plot meal_prep_coeff coeff\n",
    "ax1[1].hist(model2_fit_sigma,label=\"Standard deviation\", bins=np.linspace(7.5,8.5,50))\n",
    "ax1[1].legend()\n",
    "ax1[1].set_xlabel(\"Parameter value\")\n",
    "ax1[1].set_ylabel(\"Parameter count\")\n",
    "ax1[1].set_title(\"Histogram of standard deviation of delivery time\")\n",
    "plt.show()\n",
    "\n",
    "# save plot\n",
    "fig1.savefig('plots/model2/model_params_fit.png', facecolor='w')\n",
    "\n",
    "#--------------------------------------PPC MEASUREMENTS------------------------------------------------------\n",
    "\n",
    "fig2, ax2= plt.subplots(1,2, figsize=(25,8))\n",
    "fig2.suptitle(\"Posterior predictive checks - predicted delivery time data - MODEL 2\", fontsize=24)\n",
    "\n",
    "# get measurements\n",
    "model2_fit_measurements = model2_sample.stan_variable('delivery_time').flatten()  # flatten makes it row/column vector (one of these)\n",
    "\n",
    "# set bins\n",
    "bins = np.linspace(0, 100, 100)\n",
    "\n",
    "az.plot_posterior(model2_fit_measurements, kind='hist', ax=ax2[0], bins=bins, group='prior', backend=\"matplotlib\")\n",
    "ax2[0].set_xlabel(\"Parameter value\")\n",
    "ax2[0].set_ylabel(\"Parameter count\")\n",
    "ax2[0].set_title(\"Normalized histogram of predicted data\")\n",
    "\n",
    "# plot measurements\n",
    "ax2[1].hist(model2_fit_measurements, density=True, bins=bins,  alpha=0.5, label=\"Generated data\")\n",
    "\n",
    "# compare with real data, density set to True because each data point sampled 999 times\n",
    "ax2[1].hist(train_df[\"Time_taken(min)\"], density=True, bins=bins, alpha=0.5, label=\"Measured data\")\n",
    "ax2[1].legend()\n",
    "ax2[1].set_xlabel(\"Parameter value\")\n",
    "ax2[1].set_ylabel(\"Parameter count\")\n",
    "ax2[1].set_title(\"Comparison between real and predicted data\")\n",
    "plt.show()\n",
    "\n",
    "# save plot\n",
    "fig2.savefig('plots/model2/sampled_data_fit.png', facecolor='w')\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Comparison"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# plots and models are too much for my computer; need to delete all variables from jupyter, load models and then make comparison \n",
    "\n",
    "%reset -f\n",
    "\n",
    "import arviz as az\n",
    "import matplotlib.pyplot as plt\n",
    "from cmdstanpy import from_csv\n",
    "\n",
    "model2_sample = from_csv('/home/project_repo/data_analytics_project/models_output/model2/fit')\n",
    "\n",
    "model2_az = az.from_cmdstanpy(\n",
    "    posterior=model2_sample,\n",
    ")\n",
    "\n",
    "# delete them, because they use too much RAM\n",
    "del model2_sample\n",
    "\n",
    "model1_sample = from_csv('/home/project_repo/data_analytics_project/models_output/model1/fit')\n",
    "\n",
    "# convert models to arviz format for comparison purposes\n",
    "model1_az = az.from_cmdstanpy(\n",
    "    posterior=model1_sample,\n",
    ")\n",
    "\n",
    "del model1_sample"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>rank</th>\n",
       "      <th>loo</th>\n",
       "      <th>p_loo</th>\n",
       "      <th>d_loo</th>\n",
       "      <th>weight</th>\n",
       "      <th>se</th>\n",
       "      <th>dse</th>\n",
       "      <th>warning</th>\n",
       "      <th>loo_scale</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>model_2</th>\n",
       "      <td>0</td>\n",
       "      <td>-95433.216525</td>\n",
       "      <td>13.902664</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.998148</td>\n",
       "      <td>129.845900</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>False</td>\n",
       "      <td>log</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>model_1</th>\n",
       "      <td>1</td>\n",
       "      <td>-99845.481867</td>\n",
       "      <td>8.822705</td>\n",
       "      <td>4412.265342</td>\n",
       "      <td>0.001852</td>\n",
       "      <td>122.230901</td>\n",
       "      <td>81.50089</td>\n",
       "      <td>False</td>\n",
       "      <td>log</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         rank           loo      p_loo        d_loo    weight          se  \\\n",
       "model_2     0 -95433.216525  13.902664     0.000000  0.998148  129.845900   \n",
       "model_1     1 -99845.481867   8.822705  4412.265342  0.001852  122.230901   \n",
       "\n",
       "              dse  warning loo_scale  \n",
       "model_2   0.00000    False       log  \n",
       "model_1  81.50089    False       log  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "compare_dict = {\"model_1\": model1_az, \"model_2\": model2_az}\n",
    "\n",
    "# loo criterion\n",
    "loo_diff = az.compare(compare_dict=compare_dict, ic=\"loo\")\n",
    "display(loo_diff)\n",
    "fig, ax = plt.subplots(figsize=(15,8))\n",
    "\n",
    "az.plot_compare(loo_diff, ax=ax)\n",
    "ax.set_title(\"Comparison of models with LOO criterion\")\n",
    "\n",
    "fig.savefig('plots/loo_comparison.png', facecolor='w')\n",
    "# for safety\n",
    "del loo_diff"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>rank</th>\n",
       "      <th>waic</th>\n",
       "      <th>p_waic</th>\n",
       "      <th>d_waic</th>\n",
       "      <th>weight</th>\n",
       "      <th>se</th>\n",
       "      <th>dse</th>\n",
       "      <th>warning</th>\n",
       "      <th>waic_scale</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>model_2</th>\n",
       "      <td>0</td>\n",
       "      <td>-95433.216943</td>\n",
       "      <td>13.903081</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.998148</td>\n",
       "      <td>129.845911</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>False</td>\n",
       "      <td>log</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>model_1</th>\n",
       "      <td>1</td>\n",
       "      <td>-99845.481799</td>\n",
       "      <td>8.822636</td>\n",
       "      <td>4412.264856</td>\n",
       "      <td>0.001852</td>\n",
       "      <td>122.230899</td>\n",
       "      <td>81.500907</td>\n",
       "      <td>False</td>\n",
       "      <td>log</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         rank          waic     p_waic       d_waic    weight          se  \\\n",
       "model_2     0 -95433.216943  13.903081     0.000000  0.998148  129.845911   \n",
       "model_1     1 -99845.481799   8.822636  4412.264856  0.001852  122.230899   \n",
       "\n",
       "               dse  warning waic_scale  \n",
       "model_2   0.000000    False        log  \n",
       "model_1  81.500907    False        log  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# waic criterion\n",
    "waic_diff = az.compare(compare_dict=compare_dict, ic=\"waic\")\n",
    "display(waic_diff)\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(15,8))\n",
    "\n",
    "az.plot_compare(waic_diff, ax=ax)\n",
    "ax.set_title(\"Comparison of models with WAIC criterion\")\n",
    "\n",
    "fig.savefig('plots/waic_comparison.png', facecolor='w')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.11"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}