{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import bambi\n",
    "import pymc3 as pm\n",
    "import arviz as az\n",
    "from scipy.stats import spearmanr\n",
    "\n",
    "import seaborn as sns\n",
    "sns.set_context('paper')\n",
    "sns.set_style(\"ticks\")\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "# custom imports\n",
    "from utils.stats import sem_p, compute_ttests, get_var\n",
    "from utils.plotting import add_ttest, despine, cm2inch, violin\n",
    "from utils.general import make_sure_path_exists\n",
    "from utils.descriptives import compute_gaze_influence_score, compute_p_last_gaze_choice"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Descriptives & data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# directory of data\n",
    "subject_data_dir = 'data/subject_files/'\n",
    "summary_data_dir = 'data/summary_files/'\n",
    "# output directory for mixed effects models\n",
    "mfx_dir = 'results/posterior_traces/mixed_effects_models/'\n",
    "\n",
    "# make sure output dir exists\n",
    "make_sure_path_exists('figures/')\n",
    "make_sure_path_exists(mfx_dir)\n",
    "\n",
    "# choice set sizes\n",
    "setsizes = np.array([9, 16, 25, 36])\n",
    "colors = ['darkturquoise', 'orange', 'mediumseagreen', 'lightcoral']\n",
    "n_trials_per_setsize = 50\n",
    "\n",
    "# read in response data\n",
    "data =[]\n",
    "for setsize in setsizes:\n",
    "    df_setsize = pd.read_csv(summary_data_dir+'{}_data.csv'.format(setsize))\n",
    "    df_setsize['setsize'] = setsize\n",
    "    data.append(df_setsize)\n",
    "data = pd.concat(data, sort=True)\n",
    "\n",
    "# add RT in seconds\n",
    "data['rt_s'] = data['rt'].values / 1000.\n",
    "    \n",
    "# read out subject IDs\n",
    "subjects = np.unique(data.subject)\n",
    "n_subjects = subjects.size\n",
    "    \n",
    "# read in gaze data\n",
    "gaze_data = []\n",
    "for subject in subjects:\n",
    "    for c in setsizes:\n",
    "        tmp_data = pd.read_csv(subject_data_dir+'{}_{}_fixations.csv'.format(subject, c))\n",
    "        tmp_data = tmp_data[[c for c in tmp_data.columns if not 'Unnamed:' in c]]\n",
    "        gaze_data.append(tmp_data)\n",
    "gaze_data = pd.concat(gaze_data, sort=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>best_chosen</th>\n",
       "      <th>best_seen_chosen</th>\n",
       "      <th>choice</th>\n",
       "      <th>fixation_count</th>\n",
       "      <th>fixation_onset_0</th>\n",
       "      <th>fixation_onset_1</th>\n",
       "      <th>fixation_onset_10</th>\n",
       "      <th>fixation_onset_11</th>\n",
       "      <th>fixation_onset_12</th>\n",
       "      <th>fixation_onset_13</th>\n",
       "      <th>...</th>\n",
       "      <th>stimulus_35</th>\n",
       "      <th>stimulus_4</th>\n",
       "      <th>stimulus_5</th>\n",
       "      <th>stimulus_6</th>\n",
       "      <th>stimulus_7</th>\n",
       "      <th>stimulus_8</th>\n",
       "      <th>stimulus_9</th>\n",
       "      <th>subject</th>\n",
       "      <th>trial</th>\n",
       "      <th>rt_s</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>18.0</td>\n",
       "      <td>1662.0</td>\n",
       "      <td>1238.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>nr62.png</td>\n",
       "      <td>nr125.png</td>\n",
       "      <td>nr63.png</td>\n",
       "      <td>nr113.png</td>\n",
       "      <td>nr27.png</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>8.468078</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>907.0</td>\n",
       "      <td>625.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>nr76.png</td>\n",
       "      <td>nr93.png</td>\n",
       "      <td>nr79.png</td>\n",
       "      <td>nr4.png</td>\n",
       "      <td>nr92.png</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4.734945</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>20.0</td>\n",
       "      <td>893.0</td>\n",
       "      <td>503.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>nr56.png</td>\n",
       "      <td>nr91.png</td>\n",
       "      <td>nr30.png</td>\n",
       "      <td>nr106.png</td>\n",
       "      <td>nr121.png</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>7.822484</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3</td>\n",
       "      <td>12.0</td>\n",
       "      <td>773.0</td>\n",
       "      <td>4625.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>nr21.png</td>\n",
       "      <td>nr85.png</td>\n",
       "      <td>nr2.png</td>\n",
       "      <td>nr58.png</td>\n",
       "      <td>nr7.png</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>5.557554</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4</td>\n",
       "      <td>22.0</td>\n",
       "      <td>786.0</td>\n",
       "      <td>1010.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>nr69.png</td>\n",
       "      <td>nr81.png</td>\n",
       "      <td>nr79.png</td>\n",
       "      <td>nr58.png</td>\n",
       "      <td>nr28.png</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>9.125540</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 157 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   best_chosen  best_seen_chosen  choice  fixation_count  fixation_onset_0  \\\n",
       "0          1.0               1.0       1            18.0            1662.0   \n",
       "1          1.0               1.0       0            14.0             907.0   \n",
       "2          1.0               1.0       1            20.0             893.0   \n",
       "3          1.0               1.0       3            12.0             773.0   \n",
       "4          1.0               1.0       4            22.0             786.0   \n",
       "\n",
       "   fixation_onset_1  fixation_onset_10  fixation_onset_11  fixation_onset_12  \\\n",
       "0            1238.0                NaN                NaN                NaN   \n",
       "1             625.0                NaN                NaN                NaN   \n",
       "2             503.0                NaN                NaN                NaN   \n",
       "3            4625.0                NaN                NaN                NaN   \n",
       "4            1010.0                NaN                NaN                NaN   \n",
       "\n",
       "   fixation_onset_13  ...  stimulus_35  stimulus_4  stimulus_5  stimulus_6  \\\n",
       "0                NaN  ...          NaN    nr62.png   nr125.png    nr63.png   \n",
       "1                NaN  ...          NaN    nr76.png    nr93.png    nr79.png   \n",
       "2                NaN  ...          NaN    nr56.png    nr91.png    nr30.png   \n",
       "3                NaN  ...          NaN    nr21.png    nr85.png     nr2.png   \n",
       "4                NaN  ...          NaN    nr69.png    nr81.png    nr79.png   \n",
       "\n",
       "   stimulus_7  stimulus_8  stimulus_9  subject  trial      rt_s  \n",
       "0   nr113.png    nr27.png         NaN        0      2  8.468078  \n",
       "1     nr4.png    nr92.png         NaN        0      3  4.734945  \n",
       "2   nr106.png   nr121.png         NaN        0      7  7.822484  \n",
       "3    nr58.png     nr7.png         NaN        0      9  5.557554  \n",
       "4    nr58.png    nr28.png         NaN        0     14  9.125540  \n",
       "\n",
       "[5 rows x 157 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>choice</th>\n",
       "      <th>dur</th>\n",
       "      <th>fixnum</th>\n",
       "      <th>is_first</th>\n",
       "      <th>is_last</th>\n",
       "      <th>is_last_to_choice</th>\n",
       "      <th>is_refixation</th>\n",
       "      <th>item</th>\n",
       "      <th>onset</th>\n",
       "      <th>refixnum</th>\n",
       "      <th>setsize</th>\n",
       "      <th>stimulus</th>\n",
       "      <th>subject</th>\n",
       "      <th>trial</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>552</td>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>76</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9</td>\n",
       "      <td>nr62.png</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>188</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>678</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9</td>\n",
       "      <td>nr48.png</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>260</td>\n",
       "      <td>3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>922</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9</td>\n",
       "      <td>nr113.png</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>348</td>\n",
       "      <td>4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1238</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9</td>\n",
       "      <td>nr10.png</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>326</td>\n",
       "      <td>5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1662</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9</td>\n",
       "      <td>nr91.png</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   choice  dur  fixnum  is_first  is_last  is_last_to_choice  is_refixation  \\\n",
       "0       1  552       1       1.0      0.0                  1              0   \n",
       "1       1  188       2       0.0      0.0                  1              0   \n",
       "2       1  260       3       0.0      0.0                  1              0   \n",
       "3       1  348       4       0.0      0.0                  1              0   \n",
       "4       1  326       5       0.0      0.0                  1              0   \n",
       "\n",
       "   item  onset  refixnum  setsize   stimulus  subject  trial  value  \n",
       "0     4     76       0.0        9   nr62.png        0      2      0  \n",
       "1     3    678       0.0        9   nr48.png        0      2      0  \n",
       "2     7    922       0.0        9  nr113.png        0      2      0  \n",
       "3     1   1238       0.0        9   nr10.png        0      2      2  \n",
       "4     0   1662       0.0        9   nr91.png        0      2      0  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gaze_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4.15 (SE: 0.64) missing trials per participant per set size condition\n"
     ]
    }
   ],
   "source": [
    "# compute average number of trials dropped per participant\n",
    "n_trials_per_subject = data.groupby(['setsize','subject']).size().reset_index(name='counts')\n",
    "n_trials_per_subject['n_missing_trials'] = (n_trials_per_setsize -\n",
    "                                            n_trials_per_subject['counts'])\n",
    "mean_missing_trials = n_trials_per_subject.groupby(['subject']).n_missing_trials.mean().mean()\n",
    "sem_missing_trials = n_trials_per_subject.groupby(['subject']).n_missing_trials.mean().sem()\n",
    "print('{0:.2f} (SE: {1:.2f}) missing trials per participant per set size condition'.format(\n",
    "        mean_missing_trials, sem_missing_trials))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Mean RT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "rt_means = data.groupby(['setsize','subject']).rt_s.mean().groupby(level=0).mean()\n",
    "rt_sems = data.groupby(['setsize','subject']).rt_s.mean().groupby(level=0).sem()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/miniconda3/envs/GLAM/lib/python3.6/site-packages/ipykernel_launcher.py:3: FutureWarning: Support for multi-dimensional indexing (e.g. `obj[:, None]`) is deprecated and will be removed in a future version.  Convert to a numpy array before indexing instead.\n",
      "  This is separate from the ipykernel package so we can avoid doing imports until\n"
     ]
    }
   ],
   "source": [
    "# compute t-tests\n",
    "rt_sub_meas = np.concatenate([data.groupby(['setsize', 'subject']).rt_s.mean()[s][:,None]\n",
    "                               for s in setsizes], axis=1)\n",
    "T_rt, df_rt, P_rt = compute_ttests(rt_sub_meas)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fa3b01ed2b0>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 354.331x354.331 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1,1,figsize=cm2inch(9,9), dpi=100)\n",
    "ax = violin(data=pd.DataFrame(rt_sub_meas), ax=ax, palette=colors)\n",
    "add_ttest(ax,\n",
    "          T_rt, df_rt, P_rt,\n",
    "          [(0, 1), (1, 2), (2, 3)],\n",
    "          [(12, 12), (14,14), (16,16)],\n",
    "          -0.100, 0.25)\n",
    "ax.set_ylim(0,18)\n",
    "ax.set_ylabel('Mean response time (s)')\n",
    "ax.set_xlabel('Choice set size')\n",
    "ax.set_xticklabels(setsizes)\n",
    "despine(ax=ax)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## MFX: $RT \\sim setsize$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading mfx-summary from results/posterior_traces/mixed_effects_models/\n",
      "Intercept[0]; Mean: 3471.428784979065, 94% HPD: 3086.167479771974, 3834.2464491068986\n",
      "setsize[0]; Mean: 84.78048441671038, 94% HPD: 67.29167748588331, 102.28978782935144\n"
     ]
    }
   ],
   "source": [
    "np.random.seed(1678)\n",
    "mfx_filename = 'rt_setsize_mfx'\n",
    "if not os.path.isfile(mfx_dir+mfx_filename+'.csv'):\n",
    "    \n",
    "    # make model\n",
    "    samples = 2000\n",
    "    burn = 500\n",
    "    model = bambi.Model(data=data)\n",
    "    model.add('rt ~ setsize', random=['setsize|subject'], categorical=['subject'])\n",
    "    \n",
    "    # sample posterior\n",
    "    results = model.fit(samples=samples, \n",
    "                        tune=burn,\n",
    "                        chains=2,\n",
    "                        backend='pymc',\n",
    "                        init='ADVI',\n",
    "                        n_init=50000,\n",
    "                        random_seed=1678)\n",
    "\n",
    "    # save results\n",
    "    pm.trace_to_dataframe(model.backend.trace).to_csv(\n",
    "        mfx_dir+mfx_filename+'_mtrace.csv', index=False)\n",
    "    az.plot_trace(results)\n",
    "    plt.savefig(mfx_dir+mfx_filename+'.png', dpi=220)\n",
    "    summary = az.summary(results, round_to='none')\n",
    "    summary.to_csv(mfx_dir+mfx_filename+'.csv')\n",
    "            \n",
    "else:\n",
    "    print('Loading mfx-summary from '+mfx_dir)\n",
    "    summary = pd.read_csv(mfx_dir+mfx_filename+'.csv', index_col='Unnamed: 0')\n",
    "\n",
    "_ = get_var(summary, 'Intercept[0]')\n",
    "_ = get_var(summary, 'setsize[0]')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# P(best seen item chosen)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "best_seen_chosen_means = data.groupby(\n",
    "    ['setsize', 'subject']).best_seen_chosen.mean().groupby(level=0).mean()\n",
    "best_seen_chosen_sems = sem_p(data.groupby(\n",
    "    ['setsize','subject']).best_seen_chosen.mean().groupby(level=0).mean().values, n_subjects)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# compute t-tests\n",
    "sub_best_seen_chosen_means = np.concatenate(\n",
    "    [np.array(data.groupby(['setsize', 'subject']).best_seen_chosen.mean()[s])[:,None]\n",
    "     for s in setsizes], axis=1)\n",
    "(T_best_seen_chosen,\n",
    " df_best_seen_chosen,\n",
    " P_best_seen_chosen) = compute_ttests(sub_best_seen_chosen_means)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fa3f24f6ac8>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 354.331x354.331 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1,1,figsize=cm2inch(9,9), dpi=100)\n",
    "ax = violin(data=pd.DataFrame(sub_best_seen_chosen_means), ax=ax, palette=colors)\n",
    "add_ttest(ax,\n",
    "          [T_best_seen_chosen[-1]], df_best_seen_chosen, [P_best_seen_chosen[-1]],\n",
    "          [(0, 3)],\n",
    "          [(1.2, 1.2)],\n",
    "          -.02, .02)\n",
    "ax.set_ylim(0, 1.4)\n",
    "ax.set_ylabel('P(best seen item chosen)')\n",
    "ax.set_xlabel('Choice set size')\n",
    "ax.set_xticklabels(setsizes)\n",
    "despine(ax=ax)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## MFX: $P(best\\_seen\\_chosen) \\sim setsize$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading mfx-summary from results/posterior_traces/mixed_effects_models/\n",
      "Intercept[0]; Mean: 0.8345163474723156, 94% HPD: 0.8035956421385304, 0.8640880635701003\n",
      "setsize[0]; Mean: 0.0004862260444220538, 94% HPD: -0.00042628595596767393, 0.0014189473686468158\n"
     ]
    }
   ],
   "source": [
    "np.random.seed(1523)\n",
    "mfx_filename = 'p-choose-best-seen_setsize_mfx'\n",
    "if not os.path.isfile(mfx_dir+mfx_filename+'.csv'):\n",
    "    \n",
    "    # make model\n",
    "    samples = 2000\n",
    "    burn = 500\n",
    "    model = bambi.Model(data=data)\n",
    "    model.add('best_seen_chosen ~ setsize', random=['setsize|subject'], categorical=['subject'])\n",
    "\n",
    "    # sample posterior\n",
    "    results = model.fit(samples=samples, \n",
    "                        tune=burn,\n",
    "                        chains=2,\n",
    "                        backend='pymc',\n",
    "                        init='ADVI',\n",
    "                        n_init=50000,\n",
    "                        random_seed=1523)\n",
    "\n",
    "    # save results\n",
    "    pm.trace_to_dataframe(model.backend.trace).to_csv(\n",
    "        mfx_dir+mfx_filename+'_mtrace.csv', index=False)\n",
    "    az.plot_trace(results)\n",
    "    plt.savefig(mfx_dir+mfx_filename+'.png', dpi=220)\n",
    "    summary = az.summary(results, round_to='none')\n",
    "    summary.to_csv(mfx_dir+mfx_filename+'.csv')\n",
    "    \n",
    "else:\n",
    "    print('Loading mfx-summary from '+mfx_dir)\n",
    "    summary = pd.read_csv( mfx_dir+mfx_filename+'.csv', index_col='Unnamed: 0')\n",
    "\n",
    "_ = get_var(summary, 'Intercept[0]')\n",
    "_ = get_var(summary, 'setsize[0]')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# How many items were looked at in a trial?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "seen_items_count_means = data.groupby(\n",
    "    ['setsize','subject']).seen_items_count.mean().groupby(level=0).mean()\n",
    "seen_items_count_sems = data.groupby(\n",
    "    ['setsize','subject']).seen_items_count.mean().groupby(level=0).sem()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# compute t-tests\n",
    "sub_seen_items_count_means = np.concatenate(\n",
    "    [np.array(data.groupby(['setsize', 'subject']).seen_items_count.mean()[s])[:,None]\n",
    "     for s in setsizes], axis=1)\n",
    "(T_seen_items_count,\n",
    " df_seen_items_count,\n",
    " P_seen_items_count) =  compute_ttests(sub_seen_items_count_means)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# compute as a fraction of choice set size\n",
    "data['seen_items_count_fraction'] = (data['seen_items_count'] / data['setsize']).values.astype(np.float)\n",
    "n_seen_items_means = data.groupby(['setsize', 'subject']).seen_items_count_fraction.mean().groupby(level=0).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fa3e1cc3b70>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 354.331x354.331 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1,1,figsize=cm2inch(9,9), dpi=100)\n",
    "ax = violin(data=pd.DataFrame(sub_seen_items_count_means), ax=ax, palette=colors)\n",
    "add_ttest(ax,\n",
    "          T_seen_items_count, df_seen_items_count, P_seen_items_count,\n",
    "          [(0, 1), (1, 2), (2, 3)],\n",
    "          [(20, 20), (27,27), (35,35)],\n",
    "          -.5, .5)\n",
    "ax.set_ylabel('# seen items')\n",
    "ax.set_xlabel('Choice set size')\n",
    "ax.set_xticklabels(setsizes)\n",
    "despine(ax=ax)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## MFX: $seen\\_items\\_count \\sim setsize$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading mfx-summary from results/posterior_traces/mixed_effects_models/\n",
      "Intercept[0]; Mean: 5.635722011772934, 94% HPD: 5.323762389868767, 5.939443208847733\n",
      "setsize[0]; Mean: 0.26116128124683463, 94% HPD: 0.22155794215864788, 0.3014267283430889\n"
     ]
    }
   ],
   "source": [
    "np.random.seed(166132)\n",
    "mfx_filename = 'n-seen-items_setsize_mfx'\n",
    "if not os.path.isfile(mfx_dir+mfx_filename+'.csv'):\n",
    "    \n",
    "    # make model\n",
    "    samples = 2000\n",
    "    burn = 500\n",
    "    model = bambi.Model(data=data)\n",
    "    model.add('seen_items_count ~ setsize',  random=['setsize|subject'],\n",
    "              categorical=['subject'])\n",
    "\n",
    "    # sample posterior\n",
    "    results = model.fit(samples=samples, \n",
    "                        tune=burn,\n",
    "                        chains=2,\n",
    "                        backend='pymc',\n",
    "                        init='ADVI',\n",
    "                        n_init=50000,\n",
    "                        random_seed=166132)\n",
    "\n",
    "    # save results\n",
    "    pm.trace_to_dataframe(model.backend.trace).to_csv(\n",
    "        mfx_dir+mfx_filename+'_mtrace.csv', index=False)\n",
    "    az.plot_trace(results)\n",
    "    plt.savefig(mfx_dir+mfx_filename+'.png', dpi=220)\n",
    "    summary = az.summary(results, round_to='none')\n",
    "    summary.to_csv(mfx_dir+mfx_filename+'.csv')\n",
    "    \n",
    "else:\n",
    "    print('Loading mfx-summary from '+mfx_dir)\n",
    "    summary = pd.read_csv( mfx_dir+mfx_filename+'.csv', index_col='Unnamed: 0')\n",
    "\n",
    "_ = get_var(summary, 'Intercept[0]')\n",
    "_ = get_var(summary, 'setsize[0]')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## .. as a fraction of choice set size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "frac_items_seen_mean = np.concatenate(\n",
    "    [np.asarray(data.groupby(['setsize','subject']).seen_items_count_fraction.mean()[s])[:,None]\n",
    "     for s in setsizes], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fa3a00acc50>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAVQAAAFWCAYAAAA2WmW+AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD+naQAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8QZhcZAAAgAElEQVR4nOydd3Rc1bWHv2nqkiVZcu9t22CDAUMoAYwpBgIOOJCQ0JI8WgohIS/thSSEFEIKySMNeISakIQECCUQei8OJYANeGPcuyXZsmRZdWbeH3dkxtJImtHcNqPzraXlmXvPPWff65nf7NP2DsTjcQwGg8GQPUGvDTAYDIZ8wQiqwWAw2IQRVIPBYLAJI6gGg8FgE0ZQDQaDwSaMoBoMBoNNGEE1GAwGmzCCajAYDDZhBNVgMBhsIuy1AUMJEakGjlPVuxLvjwcmq+qNifczgFdVtSLx/jzgMiAG/FhV7xWRzwLrVfUxG+wpBp4APqWqa0SkBrgDKMb6sb1AVd/rcc13gROBAuAqVb1fRD4CfAeIAsuAS1R1wC14fnoeInIS8GOgBbhVVW/qcX4h8KNE27eo6u9FJARcB+yfeB5fUtWXs7TDT8/kCSCUeLsvcI2q/jzp/ETgNiACvAFcqqoxEbkCOCVx7Y2q+n/Z2JFLGA/VXfYDTgYQkSDwdeAPifclwM+BtqTyPwLmA8cBP00cuw34euL6QSMic4FngClJh78O/E1V5yfa/n6PaxYk7uGIxH1MEZEA8CvgRFU9AqgATkjTDF88j8S1v8MSgaOAT4jIuB7FfgKcgXXvXxGRUuB8oFVVP5x4PX2wNiThi2cCoKrHJj4LnwcU68cjme8AP0/8v5cCJ4nIPglbDgM+nLCjNBs7cgnjobrLN4G5IvJpYDOwTFWjiXP/C1wF/D2p/NtAeeJ1HEBVoyLyJrAQeLi7oIhcjfUh7ma7qi7ux5Yi4EysL183VwOtiddhoKPHNccDy4H7sTyyS1U1LiJHqmpjP9f1hV+eRw2wTVU3Jq59HTgY2JBU5i2gGqgHAom/44G3RORhrOf2uTTvuz/88kyS+RXwZVXt+f96ERAXkQgwAmgE3gc+lvhcxLG81ChDBCOo7vIT4NOqequI/Bh4E0BELgLeVNVXRSS5/PJEmSgfeB8AS7E8qT1fFlX9ViaGdHdNk9tT1R2JY9OwPKEzelxWC4wGPgocBNwEHKWqWxLXfQ6oxPJ808Evz6MOqBSRKcAmYAGWgCbzFtbwSBNwn6ruEpFaYJKqniQiHwd+AZyTQbup8MszIdHuPKBDVV/teS7RvR8JPAfsBJYnRLdBRMLALVjDJ209r81XjKB6Rw3wdOL1OUBMRM4ARiU8nm9gfbEnA53AAyLyvKr+G8tzOTy5soG8j0TdX0y8vUBV309llIgcCtyM9aV+u8fpBmCpqnYBS0RkQtJ1V2F5daepaizNZ5CMp88D+C/gVixh+E/iXrvLVgKXAzOxxPdmETkzUeahRLEHgCsHcd/94YfPyNlYn4eUqOpWYIaInANcC5wvImXAXVhjvVcN6s5zFCOo7hLjg3HrOixvDlU9qruAiKxJeDwTsbqR7araKSLbgapEsUpgW3LFA3kfqvp39u4q9kJEDsQar1vUh+C+AFwC/K9YblJd4rqrsTzXUxNimy6+eR4i8ikscQoAjwBLkoq3AruAloRXtgWr+/8C1gTdfVhjq8vTv/U+8c0zSXAU8N1U5UXkFuA3qvoa0IzV/Q9h/cjcMZQmo7oxguouK4F5InIx8CzWGNxdqQqq6loRuR14QUS6sL7gjyZOH0JSV85GfgIUAjclupVLVfVSEfkT8GUsL2y+iCzBEp7Pi8h44GvAy8Djiet+BqwGLlLVL/fTnp+exzbgFawJn1+q6o7EDPtcVf2ZiPwP8ISItAPrgO9hPYMbReQlrC73+QAi8lPgTlV9YxB2+OmZAFSqanP3m8Qwx69U9WysMd1fJ9puxfL0PwEciOVNn5247GzgaKBAVW+1wSbfEjABpr0h8Uv+GHB80qRDutf9C1g4yK61K4i1JOvbqnpFmuXz5nmIyCXAkz2XnA2innx6JvsAh/dcjpZvmGVTHpH4gvwUa+wuEz4D/MIvX5R+CGN5qmmRZ8/jn9mKKeTdM9lJP2Ox+YLxUA0Gg8EmzBhqjiEiRwC/xBqzu01Vr+9xXrA8gQDwuKp+N7HA+yZAsCYPzlPVbSKyGPgW1kTIj1T1/qR6fom1TOdWF25r0Jjn0RvzTLzDeKg+JbGO71SsiaH3k46/BizCmgF+AThZVeuSzj+Atfj7VeCfWF+GacACVf2CiHwCOBRrB85bWEudgsDzWGtLy7C2n84CfuCXL4t5Hr0xz8R/GA/VRRK7X07FWtIyHGv3ydM9yowFLsTa5fII8FTSuQogmLSj53mstYb3JVWxj6q+kjj/CNa2xIl8MPv7L6zdOLOwFmLvSpRdCewDbMfazrjQnrvuG/M8emOeSW5jBNV9Ilh7nacA92AF1gBARE7F6nZ9ASvwSM9JhQqsnTrdNPPBtsNuAj3Oj+lxXfc1KetS1TeB9WIFA3ED8zx6Y55JjpLXs/wiUiIiB4oVVMIvPKuqcVVdSWLRdhJPYe22+SJwrYjM6nG+55ejHGv2NJl4ivNNSdelOtZXXW5gnkdvzDPJVeLxeN7+zZgx48AZM2bEly1bFvcDd999d/wrX/lKPB6Px9esWRNfvHhxn2VfeeWV+Fe/+tX40qVL9zp+2mmnxTdv3hxvb2+Pn3766fFt27btdf7CCy+Mv/XWW/FYLBa/4IIL4kuXLo0/9NBD8e9///vxeDwef/DBB+NXXXVVvL29PX7SSSfFm5ub483NzfETTzwx3tHRsaee6667Ln733XfbdespMc+jN+aZ+JoBNcd0+V1m06ZNnH/++ezevZvvfe97fZabN28e8+bN63X8iiuu4NJLLyUajXL66adTW1uLqnLvvffyzW9+k2984xt85zvfob29ncMOO4zZs2cza9Ysnn32Wc466ywikQjXXnstBQUFfOUrX+H8888nFotx2WWXEYlEnLz1lJjn0RvzTHKXvJ7lT+xNf+2ee+5h33339doc7rnnHjZu3Mill17qtSm+wDyP3phn4msCAxXI6zFUg8FgcBPjoRoMBkN6GA/VYDAY3MIIqsFgMNiEEVSDwWCwCSOoBoPBYBOerkMVkR8Ao1X1ghTnZgO/wdopUoCVCz3t+JoGg8HgNp54qCIySUTuBb7aT7F7gN+r6lysfD0XichJrhhoMBgMg8CrLv/FwONYaXd7IVae758Bd8Oe9MYrgEku2WcwGAwZ40mXvzv7oohc2cf5TmBPxkQRORnLS70kVXkRGY2VdbMnM7O11S4WLFjAsmXLqK2t9doUX7BixQoApk+f7rEl/sE8k97U1dUxe/ZsnnzySa9NSQvf7+UXkQuBq4GPqeq6PopdjJWF0rcsW7aMpqYmI6gJOjs7vTbBd5hn0pumpiaWLVvmtRlp41tBTUQj/y1WXMhjVHVpP8VvAO5PcXwm8CcHzMuY2tpaamtrefvtt702xRcUFRUBmOeRhHkmvcm1HY6+FVSsFAvjgHmJMdQ+UdXNwOaexxM54g0Gg8EVfCWoIvIGcAFWANyzgJXAU0nCeH3PhGMGg8HgFzwVVFW9ssf7uUlvBwxEYDAYDH7C7JQyGAwGmzCCajAYDDZhBNVgMBhswgiqwWAw2IQRVIPBYLAJXy2bymc+8YlPeG2Crzj88MO9NsF3mGfSm1z73picUgaDwZAeJqeUwWAwuIURVIPBYLAJI6gGg8FgE0ZQDQaDwSaMoBoMBoNNGEE1eEfLOoh1eW2FwWAbRlBd4pWW3fx5e79hXYce6+6CziavrTAYbMMIqkv8ZUcjV2ze6rUZ/qKrFaK7vbbCYLANI6gusaK9nTUdHbTFYl6b4h+iLdBlBNWQPxhBdYmlbW3EgHfb2r02xT907oKuZq+tMBhswwiqC9R1drGmw8po+epu45HtobMJOo2gGvIHI6gu8EJLy57Xz7cYQd1D507rz2DIE4ygusBjzbv2vH68uZl8DkiTER07rD+DIU8wguowsXic+3Z+sDRoU2cXr+xu9dAiH9GxHdobvLbCYLANI6gO80LLbjZ2du517M87Gj2yxme010F7vddWGAy2YQTVYW6s7+2B3bF9h1k+FY9ZYtq2zWtLDAbbMILqIBs7OvlrY+9Jl4ZolD8O9V1TbXWWqLZt8doSg8E2jKA6yM+21dHZxwTUT7b2fW5I0LrR+nf3Rm/tMBhsxAiqQ6xqb+d3Kbr73azs6OCGfs7nPbvX7/2vwZAHGEF1gHg8zmUbNg3ogX5381a2dQ7RaEsta61/O7abxf2GvMEIqgP8rXEnDzYNLBI7olEu2zBEu7zNKz94vWuVd3YYDDZiBNVmNnR0cMn69EXyL407uXMoTlA1r0j9eojz/JZlXptgyAIjqDbSGY/zyTXr2BGNZnTdJes3srytzSGrfErT8tSvhzjLd5ox5VzGCKqNXL5h06D26jfHYixevZadGQpxztLVAi2rP3i/823vbPEZTR0m1kMuYwTVJn5dV89vspi1f7etnTNXrx0aS6kae3RrG9/yxg4f0tixa+BCBt9iBNUG7mncyZc3bMq6nsead3Hhug3E8l1Ud7y+9/um5SbQdAIjqLlN2MvGReQHwGhVvSDFueHALcA0IAR8XVXvc9nEAXm8qZlPrlmHXRtJb9u+g+pQiF+MHU0gELCpVp/R8Mre7+Mx2P46jPiwN/b4iIY2s4Qsl/HEQxWRSSJyL/DVfor9DlimqvsAC4EbRGS8KwamyTPNu1i0ag0dNnuUv6yr59ubt+RvmL/6l9I7NsToikXZ3m6SFuYyXnX5LwYeB36R6qSIhIFTgesBVHUN8AjwKZfsG5Bnd+3iI6vW0OqQ6F29tY7vbt6af6LaVpd6Vr/uOfdt8RktXW20dLUTiw/xwDk5jCddflX9FoCIXNlHkRqgGNiQdGwDMCFVYREZDYxOcWrm4K3sm6ead3HKqtXsjjkrdj/cuo0u4vx49Kj86f5ve6aP489CLArBkLv2+Ihdna3EidPS1U55pNhrcwyDwK+TUt3q0VOx+vrpvhh4LcXfn+w27F9NzZy8cpBi+vvfZnzJT7bWcfnGzfnjqW55LPXxzp2w/VV3bfEZTZ3WxNyuThOAPFfxq6BuA9qAMUnHxgLr+ih/A3BQir+z7TTqH407WbRqDW2DFTfVQV32q7p6Llm/Mfdn/+Nx2PRw3+f7OzcEaOpo2etfQ+7h6Sx/X6hqVETuAz4HXCEiE4ETgR/1UX4zsLnncRGxzaY/b9/BuWvX49XS+xsbttMai3HzxPGEc7X737i0/+hSmx6E/a50zRy/0ZgQ0kYjqDmLrzxUEXlDROYl3n4R2EdElmFNSF2uqp5s+r61YTtneyim3dyxo5Gz16zL3cX/G+7t//z216Clr05I/tMtpDvMWtScxVMPVVWv7PF+btLremCx2zb15Kb6Bi7MINiJ09zVuJPO1Wv56+SJRHLJU43HYd3fBi637m8wq7/VdPnLjvbmvf415B6+8lD9xs0N230lpt3cu7OJs3Jtm2rj0vT27K/9s/O2+JSGhJBuN4KasxhB7YM/b9/BBes2DFzQI+7Z2cSn167PnYmqNXf0OvTdv6cot/012PmO8/b4kIY2K/9YfVvvPGSG3MAIagoe3tnEeWvX91qz5Tfu3NHIlzZs8v+SqlgnrL691+E31vZRftUtztrjU+oSQlpnBDVnMYLag//sbuXMNevIlcQkv61v4BfbfJ7bfuMDmaWLXnUbRNuds8enGEHNfYygJlHX2cWiVWtoieXW1r+vb9rMQzt9vAf8vd9lVr69Dtbf7YwtPmVXZystXVaQ8bq2RrP9NEG8vZ2u9bkTdNsIaoJYPM7Za9exobPTa1MyJg6cs3Y9azs6vDalNzvfga1PZH6d/tp+W3zM1tYP0uB0xqLsaDdLpwDiHR3Em3Nnks4IaoLf1jfwWHPufoh3RKN8dq0PY6ku/9Xgrmt4GeqGTgSqLa07+n0/VIl3dhLvypUBOCOoAGzs6OSbm3pttMo5nty1i9v8lPCvdWvK2f20WZ4yGFlesnn39n7fD1m6uiCHeo1GUIErNm9xPHKUW3x70xZ2+2UM+L3rIJpF8sH190DTe/bZ42N6CWrr4NPp5BPxzk7iRlBzh/UdHfzRT15dlmzu6uIOP9xPx054L/PoWnsTh3euscUcv7Np994rNTa2GEEFoKODuB/nBvpgyAvqzQ07cmaJVLr8Potkgbbx3q+tkHzZsvp22LUm+3p8zsbde/+f9RTYoUq8owNySFB9GW3KTe5pdG7N34grv0tla1Jsy7ZW+MbXAGgsLmbblVc50u6brW2sam9nSmGhI/UPSGcTLL/WnrriXfDO1XDIDfbU50Ni8RibenikxkO1iLe355SHOqQFtSka5a22LMb4BqCytRV99JGU5+SEhWSw1D1jXmzZ7Z2g6nXQYeOww8qbYZ9vQdkk++r0EQ1tTbTH9h4n3NbWSHu0g8JQgUdW+YO46fLnDtqWv7tx3nHwh6JfOhrhXZtn5+Nd8PYP7a3TR2zoo3tvvFSgrY24V5/lQTCkBXV71OsIp87R0OXRvS3/JXQ22l/vqluh+X376/UBG1pSC2pfQjuUiLe3E2/PHcdnSAtqPt+8J1H92+otQXWCeBTe+p4zdXvMhpa6jI4PJeLGQ80dhofzN8OmJ/f2zk+gy8Ftgmv/DI3LnKvfI5I91LV/fDHl8aFKvL3dCGquIIVF5FDM+4yY5faE1O5NsCLbdacDEYe3rnC4DfdJ9kRbVtelPD5UMR5qDlEaCrJ/cZHXZjjCYaWl7jb49g+z2xWVLhvug4ZXnG/HJWLxWJ+e6PpdRlDjbW3Q3u7/mL8JhrSgApxUUe61CbYjhYVMKnRxuc2u1bDyJvfaezN/vNS6tp10xFJvLalvb6K1K3cmZJwg3tZm5SPLkaVTQ15QP1lV6bUJtnN2tcv3tOwqKyq/W2x5FLY96157DrJ+gG79xiE+09/d3c+Vbv+QF9Q5xcUcWlLitRm2EQI+U13lXoNNmjK9ieO8+W3Lc8lxBurWr981xAU1sWQqV5ZODXlBBbh8RI3XJtjGmZXDGFfgYnd/6ffBi+jydc8PLnC1zxhoJn8gDzafiSd19XNFUIf01tNuFlcOY1ZRIe/avHOq/v33WbRoUZ/n7CYAfHvUSNvr7ZOd78Dav7jXXk/e+i6MPBa8WHNrEwMJ5pCe6U8K22cENYcIBQJ8f9RIPr5mna311kybxv3335/ynJywELtDCH+ichiz3Vy1sPQq8DI3bP1LsOUxGH2CdzZkyUCCOaQ91OSJqByJiWq6/AnOqBzGwSXFXpsxaCKBAD8cM8q9Bne+C+vucq+9vlj6/ZwdS+2KRdm0u//9+kZQe7/2M0ZQEwQCAX4+drTXZgyaL9YMZ6qbi/nf/jGeeqfd1L8I25722opBsXn3dqIDjD/v7GihqaPFJYt8RnIuqRzJK2UENYmjyso4fViF12ZkTFUoxBWjRrjXYPNKWHune+0NxLIfeG3BoFjXkl4Ax3VD1EvtTs7XlkOJ+oyg9uCnY0cTybFJju+NGkl12MXh8Hd/6s3Mfl9sfQrql3htRcas25WeoK5Ns1zeEY3y14YG/j19On98+mmvrUkLI6g9mFZYyOdqqr02I22mFRa4a2/rZiuUnt9452qvLciYNbu2plVubXN65fKNtt27GX3QQXxk8WJGTp1Kew7M9BtBTcF3Ro2kPJgbj+ZHo0dR4Kat+r8Q8+EEwYb7YOdyr63IiNXNW9Irtyu9cvlGUUEBm159lX/ecw9bVqyg0KsMFBmQG6rhMjXhcE4s9t+/uIgzKoe512BnM6y43r32MmW5zZkCHCQWj7EmTUFNt1zeEY9zVk0Nh6xYwTmHH+61NWlhBLUPLqut8b2X+p1RIwm6Od678mZ7Mpk6xeo7oC03xhu37N5BazQ9T39L6w52dbYOXDBPKYpEvDYhbTxZ2C8iC4FrgCJgPXCeqm7uUWYMcDMwBmuL+i9V1bWQRlXhMBfXVPPzbf7cSz2tsIDT3FyREIta3X0/E2uH934H+13ptSUDsqJpY0bl32/axNzhUx2yxmAXrrtgIlIL3Amcq6ozgQeAW1IU/THwlqruBxwHXCsiU9yzFD5fU+PbANRfqBlOyE3vdOMD0LLavfYGy/vXQ9T/kxe6c4Oj5fOC5M93jqy88aJPewLwpqouTby/HlggIj23+YSAYSISAEqAGODqYrTJhQUcW17mZpNpEQkEONfNiFIA713nbnuDpW2rP3ZwDcDyxsy2OWdaPi/IQUH1oss/HqubD4CqdohIXeJ48uj7N4FngU3AcOBKVU35qRKR0UCqbU4zszX2U1WVPN68K9tqbOXE8jKGu7nudOc71lrPXOG938Hkc722ok9i8RjvZCiQbzeudcgaH5MkogGfz2d044WVAVLvWey5UvxO4LeqOhqYCnxGRE7ro86LgddS/P0pW2M/UlHhu27/R92c2QdY8Xt328uWhpdh++teW9Enq5u30NKVWcDkzbu3U9/m4wlBJ8hBDzUjQRWRYhG5JPFaRORJEfmbiGQSM24tMDapzgKgBliXdKwGOAprOABVXQ/cjTWWmoobgINS/J2dgV0pGREJM9dneaeOc3MYomu3NXuea7x/o9cW9Ml/GlYO6ro3GlbZbInPSfZK81FQgd9geYNgiV0dsDvxOl0eBQ4QkdmJ9xcCS1Q1ecNyA5bwfhJARMqxxl5fSlWhqm5W1dd7/gG2rPQ+wu2Ed/0wNhJhopsBpNf9zd9LpfpizZ3Q6a+hmm5er18xuOsaBnddzpLvHiqwAGsCaThwJPBl4CJgfroVqGo9cBZwu4i8A5wJnAsgIm+IyDxVjQOnAueIyNtYQvo3Vc26Cz8Y/JQZ1XVveVWqBRg5QFczrL/bayt60RWL8toghXHJtuU5k/3TFnJQUDOd2agAGrEEUVV1s4h0z8Cnjao+DhyY4vjcpNdLgWMytM8RZhX5R1BnFrm4/W7XKtj2jHvt2c2qW2DK+V5bsRdLt69m9yAzmW5ra2R18xamVORumMl8J1MP9TXg98D/AP9IjHXeCLxot2F+YmKBf3ZqTIi42N1f46MQfYNh2zPQsn7gci7y3NalAxfq9/plNlmSAyR74znimWcqqJ/BWhP6EvADrNn3Cj4YV81LRri5RGkARkVcsiUez31BBW9zXvUgFo/x7JbsBPGZzW/ZZE0OkIOCmtG3U1U3AuclHVoCpM5Cl0cUBIOUBYPsinkfA7Q6FHKnoaZ3rb9cZ/3fYZ+veW0FAMt2rGFr646s6ljRtJG1u7YysczFZIxekfx988F3Lx0yElQRGQ/8NzCRHt6tqua1sJb7RFDL3RLU9fe4047TNPwbdm+AknFeW8KjG+1ZG/vYxte5QE6ypS5fE43ueRlPeu1nMu3y3wXsD7xJ70X0eU2xT3ZqlARdmu3c+KA77bjBpoe8toC2aAdP2CSoD69/ZcBcVPlAPAdzSmU6IDcbqFXVzLZ55AFFbgnZABQGXBD2tnrLs8sXNj0M0y7y1ISnN7/Frgx3R/XFtrZGXqlTDh0xy5b6fEtS6uh4jqSRzlRQXwWmAUNoqtGiwCfr4FyxY9szOJXR9NybR7CzqxKA+gAsStrQNCzcyB2fdSCe6danrPCDQZeGS1Jw31p7F8L8Y+2LeS+ouZhGOlNB/SrwpIj8C2s96h5U9Uu2WeVDitzwDNPAFU/ZwbWnO7squf9pTXlu0XwBHBDUzp2wcylUzR24rANo43qW7Vhja50vbn2HTS0NjCkdbmu9fiLeluTR50A+KchcUH+OtS0UoNxmW3xN8SCErLG4GDlh4QcHdjbCsMo95waDK8LekHsZRAekfolngvrX1fb/QMWJ8/c1z/KlfU+3vW6/EG9tTfnaz2QqqIcAI1W1xQlj/EzZICaltl151d7+1pe/BNf8LDs7Qg4LaqwTdrzpbBtesP1VvFguvbV1B09uesORuh9ct4TPTF9IeUGJI/V7TXz37j2vY0mv/Uym3853sSJDDTkq3Vqu1A+lwSBhp8dQd62yUonkGzvf9qTZv6x82rEZ+dZoB3eved6Ruv1ArOUDvy2+y5+BbnqSqYf6D+BpEfkLUE/SzIWqXmunYX6jxge7pWrCLoh603vOt+EFTanHbZ1ke3szD6x72dE2/rb6WT4+5WhKwv5PsZwp8ebmD163tBCPxXwfaDpT644D1gCHAqdgRYQ6NfE6rxnrg8yL49ywoSVPI8N3bIcud0eq/rLyadpjzi73aerczb1rXnC0Da+INTV98CYezwkvNdOtp76I/uQFkwpdDErSlw1uxEFt3eR8G17RuhnKp7nS1I72Zu5d647Q/XnVU5w+6Yi88lLj0SjxZEEFYo2NBCtczPQ7CDL2n0VkfxH5tYjcKyLDReQyJwzzGzMLvf+wihuh+zqy22vua1y8tztXPkVb1J21kzs7Wrgnz8ZSY42NvY/t8P9nM9MUKB8FnsLybBcARcB/i8h3HbDNV0hRIUUeL+4/YJBLrTLC5W6xq7h0b/VtO10XuDtXPklzZ24sLUqH2PbtvY81NKQo6S8y9VCvAk5T1c8BsUT0qYXABbZb5jPCgQAHlrggaP1wSIkLy2PiuRGEYlC4dG+3rXiMjpi7e8+bO1v566qnXW3TSWL19b2ORfNQUCcAzyVed8/wv8sQWeR/VJl3uaVmFhYywo1YqD7ZEeYILtzbxpZ6x2f2++KuVc+wo7154II5QHRb7x1zsRTH/Eamn7B3gI/3OHYKNiXD8zsnlnv3u7GwwqW2Q9564Y4SdD6VzR/e+5dnkaBaox3cvuJxT9q2m2Tx/NGTT1rHGhp8HyQlU0H9GvB/IvIoUCIifwVuA75uu2U+5PCyUqo8WuB/iluCWjDMnXa8oKDS0erfb9rI4xv/42gbA3HfuhfZvLv3+GMuEY9GiW7duuf90i1bEifiKT1XP5GRoKrqi8C+wOPAH7Dioh6kqs/1e2GeEAkEOG2Y+8s2asIh5peXudNYYR5vhHP43m5c/jr5m6UAACAASURBVDBxh6J0pUtnLMrN7/3LUxuyJbZt217BpZOJbvL3sr5MI/bfqKoXAT/tcfyvqvoJWy3zKedWV3HLdneXb3yqqtL5LafdFHsf2d4RggWOCupb21fx0rZ3HKs/Ex7Z8BqfmrqAyeWjvDZlUHRt2NDnueiGDXDwwS5akxkDCmoi7cmZibfnikjP8dJhWDP9Q4Kjy0qZXFDAahfjM36mutq1tiid6F5bblI60bHc7vF4nBuW/9ORugdDnDg3Ln+Iqw/+rNemDIro+r4z1fZ3zg+k46FuBA7DCooSwdpqmkw78AWb7fItwUCAi2uq+eamLa60d0hJMXPdXK5VPt29ttzEwftaUrect7avdqz+wfD81mW8s2Mt+1Tl1g9kPB6na23f259jO3YQa2ry7Y6pAQVVVWMkPFQR+bWqXuq4VT7nv4ZXc+XmrbS5kNr2S7Uuj2kWjYBIJXT23qmS01TMdKTaWDzGjcu9z1mVihv1IX516Oe8NiMjYjt29Npy2pOu1asp2H9/lyzKjLTGUEVkf1V9E7hFRA5MVUZV7clAlgPUhMOcV13FjQ3OzqaOiYQ5s9LlWfdAACrnQF2ezTNWznGk2me3LGVF00ZH6s6W1+pX8J/69zmgxp34BXbQtXLlwGVWrcptQcVazF+BlVMqFXHA+4ChLnL5iBr+r2G7o3O6l9XWUOBFuLKq/R0T1OWr61m0KHXG8eWre++OsY3K/WyvMhqPcfN7j9her5384b1/8evhXyDgk5xoA5GWoK5cSTwe9+U9pSWoqlqR+DePt9FkhhQVcfqwCu7Z2X/3ZLAMCwW5pMajfEFVKTshtjBzcg33339/ynNWTikHvP5gAQybbXu1T29+k9XN7oylD5Y3t6/itYYVzKuZ4bUpAxLv6qJr1aqBy7W0EN20ifDYsS5YlRlGILPgW6NGOFb3F2pqqPAqS8Dwed606xSVcyBkb+jDWDzGbSses7VOp7j1vUe9NiEtulat2it1dL9ll/tzc6YR1CyYV1LC8Q4suC8OBPiy25NRyVTMglAe5SkafojtVT63ZZnvvdNu3ty+ijcaBu5Ke03nu++mX9YIan7yPyPt91IvrKmm1o1AKH0RDEP1Qd61bzfV9i4Ej8fj/PH9J2yt02n8bm88GqVL009TE6uv9+U2VCOoWXJ0WSmHldrnzUUCAf57RK1t9Q0aB7w6z6j5kK3Vvd7wPst3+nuBeU+W1C3nfZ+uRgCru59pqujOt71JvNgfmW49DQEfA2bQQ4xV9Sob7coZAoEA3xxZy0dX2ZOL6eyqSsa7kepkIIb7d3tfRoTLoFxsrfKvq56xtT63+OuqZ/n23E96bUZKOpcty/yapUspnD/fV7P9mfYrbwI+CvwbSB49zmj1kIgsBK7Bivi/HjhPVTf3KFOEFTPgKKAEuE1Vf5Shva5wSkUFs4oKebct+/TLX/ODdwpQnScTU9UHQtC+yb11u7bZvme/7jfPU9Rh+Sejo+U0X/siAG0FMWq/+GHb2nl84+tcMvMjDC/y1y6jeEdHRuOn3cR27CC6cSPhcf6JP5GpoJ4CHKGqmd99AhGpBe4E5qvqUhH5EnALcGKPolcDY4F5WIL6HxF5SVWfHGzbThEMBPhKbQ0Xrc+uS3VyRTn7FDsfszMtyqZAZBh07vTakuyweQnYP9a+aGt9AEUdQd54sndQ6rkLDrW1na54lH+uX8J504+3td5s6Xz33bRn93td++abvhLUTMdQ24CBF4r1zwnAm6q6NPH+emCBiPQMjXM+8D1V7VLVJuBY4I0s23aMc6qrGJ7lMidPZ/Z7EghYC/xznaq5tlXVHu3g4Q2v2FafF9y/7mViHgXA7ouONwb/te5Ytox4l7vpZvojUw/1p8D1IvIToC75hKqmuyJ7PFY3v/u6DhGpSxzfAiAiI4Aq4MMi8pvE6z+q6s9SVSgio4HRKU45s4E7BcXBIBcMr+aabXUDF07BjMICjnMr5mm6VO4H25712orssHGH1HNb3mZXjifC29q6g9cb3vfNQv/o9u1E16wZfAVtbXS++y4Fc5zZWpwpmXqoP8XyHN/FEtQ6oJ4e4joAAVKPuSb/bEYS/87C8kyPxQodeHYfdV4MvJbi708Z2JU1F9UMPszexTXDfTW4DsCwfb22IEsCtgZFeSTHvdNu/rW+rx3k7tP5n+wzHHS87p8wIpl6qHZ8OtdipaAGQEQKsEIDrksqU4c16XWbqkaBehH5J3A4qUXyBiDVfsaZfZR3hCmFhRxTVspTuzJLVxwGzq2qcsaobHAoQpNrlE6CsD2hD5s7dvNK/Xu21OU1z29dRke0i4KQh2udsdaeZtPd7ya6Zg3R+npCNd4PmWWaAmWtqq7FEsB5wGagPXEsXR4FDhCR7s3VFwJLVHWPl6uqHVgC+RkAESnFGntd0oddm1X19Z5/eJA88PzqzIXxI8MqvF3I3xe5HhvVRvtf2PaOZ8n37Kalq43XfPDj0KVKfNcuW+rqeO01W+rJlowEVUTGisirwFPArcAUYKWIHJ1uHapaD5wF3C4i72DFWj03Uf8bItK9XudCoCJR5g3gX8AdmdjrBadXDqMww677WVXOJo8bNMWjIVjotRWDp2yybVW9vG3QC1t8yct13m/dbH/FviGUjjfe8EVG1Ezdot9gJeg7FKhT1eUi8nWssdW0t6Oo6uNAr/Usqjo36fUOrPHanKIiFOKE8jIeaEovP3phIOBeRtNMCQShZDzset9rSwaHTelcYvEYr/rAo7OTV+u8vZ/otm3ZTUb1pK2NzrfeouAgb7dMZzop9WHgu6raxQcTS78H7N2KkuOclkFQ6OPLyyjzKqpUOpT4Z41fxthk+/qWOnZ2ZDYu7nfWtWxjR7s93e3B0P5y73W3Wde5ZAlxF7Jo9EemgroTa7F9MuOABnvMyQ9OzMDjPNmnuXH2UJxqNVqOYJPt7zauG7hQDuLVfcVaWuh86y37662rSytAtZNkKqg3AQ+KyKeAkIicBPwNuNl2y3KYMZEIs4vS2/F0QoXP1p72pGik1xYMnkJ7IoGtbNo8cKEcZFWzN/fVsWQJRKOO1N3+ov072TJhMOtQ/wBcgTX++ivgXuAnNtuV8ywoLx2wzIRIhCl+CITSHw7msnecInviIqxvGdxmDb/jxX3F29vpsHEyqifR1avp2rTJsfoHIqNJqUQG1GsTf4Z+OLK0lOvq+h8J+XBZqf8W8/ek0KM0LHZQYI/tm3c7m4zRK7Z4cF8dr7xCvK3N0Tban32W8FlnOdpGX2S8+FFETgUuwhpLPRn4BvB1VfV+zYKPOLxsYA/VzjiqjpGrghousy3tSWOHd5M3TuL2fcU7Omh/6SXH2+lSJbp5M6HR7o//Z7oO9SKspVPPY61BjQLHAL+w37TcZkwkwthIpN8yh5TkgKAW+HAHVzrYaHeu79/vi2aX76v95ZeJ797tSlttTz3lSjs9yXQM9XLgFFW9BogndjedgrU439CDA/sJxRcG9vNLqL7+sKnb7Do2etZdMWcmULzGzZ1fsd27XZ0w6lqxgq619gR9z4RMBbUW6M470L3gazPg85kVb5hb0vc+8plFRRQFcyADTeHgA754SoF9dnu7stE5Yi6u2Wx/5hlozz4Aeya0Pfqo6+tSM/1GvwZ8pcexzwLZh4zJQ/brZ+lUTninAIU+ySCQKTbaXRTqf+gmVym2ObV2X0Tr6+l41f0IV9FNm+hcunTggjaS6aTUl4FHReRioExElmDFMT3BdsvygH37Ec1901yn6jnhEmuCpyvHJmaK7MtGWxIuojXaYVt9PdmyagOLFi1KedzJTcnFYecFNR6P0/bwwxDzJrBM22OPEREhUOhOTIpMl029IyICfASYCGwE/qmqOZ4nwxmmFRYSBlLFE9+nKIeCjpSMhab0U/z6Ahu3zFYXltPQ3mRbfT0ZNWUc99/fO/qk3SlQelJd6Pwuva5336VrVbZJPgZPfNcu2p56iuITe2ZYcobBDOIVqOpdWIv6w8AR9pqUP0QCAab18cs4M6cEdbzXFmSOjTbXFKUfmyGXqHE4WV+8rY3Whx92tI106Pj3v4ludmdXWKZppM8DfguUY+2OOhuIich1qmp2S6VgRlEhy3sMxofA/zukkimfDlset6WqYeFGFs23YunU74Kasr3P2YaNsVDHluToSocBGFvi7C64tieesC3eaVbE4+x+4AHKLriAgMMTwZmOoV4OnC4iYeACYCFWHqhnMdtPUzKjsLdwTioooCAXZvi7sTGv/R2f3QZsA2DRL+D+i2yrem9sFNTxZTk6MTcA40qdu6+uNWs8mYjqi9jmzXS89BKFRzjboc70Wz0hEcv0MKBDVV9W1TVAfvaJbGB6ii5/qmO+Jteyn5ZOhgL7PpKTy3sm5M0PplY4s5Mo3tlJ6wMPOFJ3NrQ99RTR+npH28hUULeKyBHAp4EnAUTkoyRlMTXszdRkD1UsT29aCq/V11QdgJVbMUeo7hW7PCumlY+xtT4/EAmGGO+Qh9r25JPEtvsw/kE0Suv99xN3cMVBpoL6PeAJYDHww0Tqk78C37bbsHxhr0mpz30B6CGyuUDBMKj0R5retKg90tbqygtKGJNn46jTKsYSDtof2Lxr/Xo6HAgebRfR9evp+Pe/Has/0yR9dwFVwBhVXQq8DkxS1fucMC4fGBeJ9BqonpprXX6AEfO9tiB9Rs63vcqZlTm40qEfZg2z/37iXV203ud/KWh74gmiDnnQGc+MqGqrqrYmXjer6hb7zcofQoEAk3p4pJNzaYa/mzEne21BehSPhcr9bK92n0p78lP5hVlV9t9P+7PPEmvIgeQdXV20PvigI9tSc2iqOXfpKaA5Kagj50PYp8kEkxl7KjgQY3a2AwLkJXbfT3TbNtpfeMHWOp0kuno1nW+8YXu9RlBdIFlAR4TDlIZy8LGHCmH86V5bMTATnQksPL1iHAXBjMMH+5LKgjJb16DG43FaH3rIs+2lg6Xt8ceJt9obwjDTeKhHJb22d+Q/j5mUJKgTC3I40Maks722oH9KxsMIZz6WBaEw4sC4oxfMqZpka6aIzmXLiHoQKi9b4rt32x43NS1BFZFrReQE4MGkw/4fffYJk5JEdGIudve7GXkslE7y2oq+mfpfEHDO+59dNcmxut1kXxvvI97VRdsTT9hWn9t0vPoqURvHfdPtw6wELsWKMPUaVsT+iIjMUNX3bLMmT5mQLx5qMATTLoY3v+W1Jb0JhGDqBY42kS/jqHb+MHS89hrxnfbGRrrkkUdoTvKgG0tKOPvRRwEoj8e5fuFC+xqLx2l/6ilKzjjDlurSElRV/S3wWxFpBs4HjsQKKn2PiIwD3lHVw22xKA8ZnySi4yM57KECTLsQll0FUZ+lBZnwcSsqloPY6dl5RSgQRCrticQVj0YdicLfHAjwYB8TXKc4sHW08+23iS5YQKg6+6Dk6Xb5f5TYIRVX1WWq+nugRVVnA6OwvFdDH4yJRPbsMxqXyx4qWKlFpnzWayt6M+urjjcxvKiCkcU5mmMrwdSKMRTZFFi68+23iTc5F9bQTTpsSh6Y7oDTDuAHQKmIvCAi12B1+ceqapuqvmaLNXlKOBBgZNjqDIyN5MFM8az/hoCP7mP0Qqg+yJWmZlVOcKUdp7DT/o7/5E+ijo6lS4l3Zp+4OS1BVdWfq+oCoBW4DCvCVAHwjIjUi0jujkq7xJhEBtQxA2RCzQnKJsHkc7224gP2dW/n88wcn+m3a4dUbOdOomvW2FKXL2hvp+u97KeDMp0SfV9VX1XVXwLLVHUaVjrp72ZtSZ4zKuGZdnuqOc++37Ymgrxm5LGOLZVKhV3jj15hl/2dK1bYUo+fsOOeMt3LPzfp9UGJf5tUNXe2SHjEyHCYqlCIwlyKg9of5VNh8vleWwH7fd/V5mZUODvx5SQFwTCTyuwJRehlWhOnsOOe8uTb7X9GRsLUhn3g0dnJ7O9A0MMhjNEnQq27GXgqCkpzdmJqcvko2yJMRTdtsqUePxFvbibW3JxVHUZQXWJ4KExNvnT3uymbBFOdCrmfBvv/0JNmp+eolzrNJrvj7e22rz31C9GtW7O63pNvuIgsBK4BirCCU5+nqimzaIlIIVaKlQdU1ZtvkA0MD4cYHsozDxVg9rdh1c3ur0sdv9i1mf2eTKsYw/Nbl3nSdjZMq7AnUHYsT8UUyPqHwnUPVURqgTuBc1V1JvAAcEs/l/wGa+Irp6kKhajKNw8VoHg0zHB7GXIA5lzlcpsfYJcwuY1tgpplt9jP5GKX/wTgzUSAaoDrgQUi0mu0XEQuBAqBf7ponyMMC4UYlotRptJh1tcgXDZwObuY+Emo3Ne99nqQq4I61S67OzrsqceHZLsW1QuXaTxJOahUtUNE6hLH9wSrFpFDgAuB+cDv+qtQREYDqTKOzbTBXluoCAWpcCDlhC8oqgH5Erz9Y+fbCgRhjrer9EaXVFMcKqQ12j5wYZ8wqriK8kixLXXFo1Fb6vElXV1ZXe6FoAaAVKGy9wRTTAwL/AE4XVV3iwyYxvhirHxXvqU8GKI8Xz1UgJmXg14HXQ7nYZ/4SaiwL631YAgGgkyrGMPSHas9tSMTbJ1IcyCAdzK6bh2LFi3q85yjZHlvXgjqWmBB9xsRKQBqgOQn9VGgDPh7QkwnAO0iMkxVv5aizhuA+1Mcnwn8ySa7s6I0GKQ0X9agpqJwOEz/PLz7UwcbCbi6K6o/pg8ba5ugthXEmLvgUAC6mtoIVxTtOW5XjoTpw+wT1IDDk6syYQL335/q6+xMcJS9yPLevBDUR4HrRGS2qi7D6tYvUdW67gKqehNwU/d7EbkVa5dWyln+xAqBXqsE0vBsXaM0GKQknwUVYOZXQP8XYg51hcefDsNmOVN3hti5BbX2ix/e8/qdH9zHPpdb/oadCWfsDI4dyOWYvgMQyDKBpuvfcFWtB84CbheRd4AzgXMBROQNEZnntk1uUBIMILmY7TQTikfBFAd3T836unN1Z0iuBUmZZWPW1kBRkW11+Y1sBdWTdTyq+jhwYIrjc1MUR1U/7bRNTlMQDHJEWanXZjjPzMvh/Rvtr7f2CKj5kP31DpIJZbWURYrZ1emzuLApGFMynKpC+/zdQGn+fo6zvbc874MaXKdCrC2hdiOX2V9nFgQDQWbnSGrpOVWTba0vUFJia31+IpjlvRlBNdjP9M/bW1/RKBh3mr112sDc4dO8NiEtDhg+1db6ApEI5OnwVaA8O0/eCKrBfsacBCU2hrmb+l/eBmHpgwNrckRQHbAzWFFhe51+INv7MoJqsJ9gGKZ8xr76pvow5Qogw8YxrMDf44njS2sZUzLc9nrzUlALC3Nvlt8wRLArVuqIo6HMn6EcgoEgH6r1zWa8lBw6whn7gpWVjtTrJXbckxFUgzOUT4Waw7KvZ9LZ2dfhIEeOmu21Cf1y5Kg5jtRrBLWPOmyww2BIzcSzsrs+GIHxH7PHFof4UO1MCn04vgtQWVDGftXOePfB4fYPI3iNHfdkBNXgHBPOBLLYGz3yOCjMPle6kxSHCzlilHeRr/pjwej9CQWc+YoHa2ocqddLQkZQDb6meHR23f4J/vZOuzlhrDeBrgfi+HHO2RUcPhzyLL5vcOTI7OuwwQ6DoW/Gnz7ICwMw9lRbTXGKD9XOpNrGnUh2MLFsJPs6uPEgEAwSGjHCsfpdJxCw5X6MoBqcZbCiWHMYFOXGFzYcDHHSuIO9NmMvThn/IQIOh9kLjbcvPoDXhMaMsTYsZIkRVIOzVAiUDWJh+dhT7LfFQRZNPIxANuPFNlIQDHPSeOcFPjwxN7bepkNogj3BboygGpxnzMmDuOYk++1wkDElwzli5D5emwHA8WMPdGXDQXjyZMiTkJSR6dNtqSc/nobB34zJMFhK0Uio3N8ZWxzkjMlHeW0CAGdMPtKVdgJFRYQnTXKlLUcpLLTNQ82vaTqDPxlxFAQLILZ3cre5ffUYR53geJoNJzhw+DSmV4xlRdNGz2yYVzODaXamOxmAyJw5dK1aZWud5fH4XpH5G3bvZngiClR5PFX2pOwo2Hdf27IQGEE1OE+41IpnuvWpvQ5fdUYf5Ucf77xNDhAIBPjk1Plc9R/vsu6cNWW+q+1FZs2i9eGHbc2Eev3ChXu9P+vOO/nTac5FG4vMTRmGeVCYLr/BHUYdl37Zkcc6Z4fDHDN6LqOLvdmMML1iLIfUupv2J1BYSIGNguQ2oTFjCI2zLzKaEVSDO4xcMHAZgIqZUJKbee/BWkL1yanHeNL2udOOdXypVCoKDz00J4doAAoOO8zWZ2YE1eAO1QdBuGzgcukKr485efwhDC90N7zdhNIRHDV6P1fb7CZYVWVrt9ktgiNGENnX3m3DRlAN7hCMQG0as88j5ztuitMUhiKuj2WeM+1Yx/btp0PR0Ufn3FbUomPt9+iNoBrcY0Qay4pq/bH0KFs+OvEw14JPjy6p5vixvXJeukpw2DAKP/zhgQv6hPC0aYRtWnuajBFUg3sMJKgVAsXZB6jwA8XhQj4x5WhX2jpn6rGEg/Ys+8mGwiOOIFjt7+hgAITDFJ14oiPjzUZQDe5RfRCE+snpns6QQA6xeOKHKYsUO9rGiKJKV7aZpkMgHKb4VP8HtCmaP9+WUH2pMIJqcI9QIVT38+WvPaLvczlIaaSIMyc5+yPxqanHEAn6Z+wyPGkSBQf7Q+BTERozhoLDbMgk0QdGUA3uUnt43+dq+jmXo5wx+UiKQ86kXK4uLOeUCR9ypO5sKDr+eH9G9A+HKV68mICD8QeMoBrcpa+A0wXVUG7/JIHXVBSUctpEZ34oPjHlaApDBY7UnQ2BSITixYt9FzilaOFCx7r63fjrjg35z/BD+j6eo4vDB+LjU46mwOZueVmkmI9O8K9HHx4zhqIF/llTHJ45k4KDnM+sYATV4C7Fo6E4RfCO4f4dd8uWmqIK2wNQnz7xCEoj/Uzw+YCCww8nPMX7FOCBigqKTz3VlV1kRlAN7lOdwlNIdSyP+PiUo20LQB0JhlwL0ZcNgUCA4tNPJ1DqznrcPoyg5GMfI5iIVuU0RlAN7lN1QHrH8ogJZSM4YqQ92xxPGDvPdzms+iJYVkbx6YPNK5Y9hUcfTdimWKfpYATV4D5VPYJHRyqhJH/yE/XFx6fYswvMrQ0DdhGZOpWCw90f7w1NnEjhke568kZQDe5TOaf3+zydkEpmbvVUplVkF0nroJrpTC4fZZNF7lG0YAGh0aNdbLCIktNPd3SJVCqMoBrcp3Ty3jumhtkb8cevBAIBPjYpu/3ui7O83isCoZC1lMqlACrFp5xCcNgwV9pKxpMtFiKyELgGKALWA+ep6uYeZWYDvwEqgQLgFlX9mdu2GhwgGIJygcY3rfcVM721x0WOHXMAv33nfnZ1tWV87YiiSg4f4Y9EgIMhVFND0fHH0/bww462E5kzhwKbw/Kli+seqojUAncC56rqTOAB4JYURe8Bfq+qc4EjgItEJLdSYRr6JnkRf8UM7+xwmeJwISeMmzeoa0+Z8CFfBEHJhoKDDybkYGK/QFkZRSd5JxNedPlPAN5U1aWJ99cDC0Rkz8CQiESAnwF3A6jqDmAFMMldUw2OkSyoZdO8s8MDThmf+XbRAAFOHt/HpogcIhAIWAFUHOr6F598MsFiZwPS9IcXXf7xWN18AFS1Q0TqEse3JI51Av/XXUZETsbyUi9JVaGIjAZSjXgPnb5krlE2OfEiAKV9pT/NT6YPG5txdtSDaqYzsrjKQavcI1RdTdH8+bQ9/rit9YZnziQya5atdWaKFx5qAEiVCzaWqrCIXAjcDnxMVdf1UefFwGsp/rxLP2non9JJ1r/FY8CH+9GdZmGG3f5My/udgkMPJVhTY1+F4TDFJ55oX32DxAtBXQvs2XsoIgVADbCXWIpIWERuAL4JHKOq/f2c3QAclOLvbHtNN9hGSSLT5BBYf5qKY8cckPbOqYJgmKNGzXbYIncJhEIU2zjWWXjkkZ7M6vfEiy7/o8B1IjJbVZcBFwJLVLWuR7k7gHHAvMQYap8kVghs7nlcxN2UuoYMKBm7979DjJqiCvavnsIb21fudbx0cm2vsoeN2IeSsL/37Q+G8JQphGfMoOu997KqJ1BRQaGDMU4zwXVBVdV6ETkLuF1EioBtwLkAIvIGcAHWkMBZwErgqSRhvF5Vr3fbZoMDhMshVAxFubdI3S6OGbN/L0GdeE7vHUXzR+/f61i+UHTssexasQLiqUYB06xj/nwCkYiNVg0eT9ahJrrvvbKKJZZIdZP/W2eGMoEAFI20/oYoR4zcl18uu6ffMuFAiMNGeDvR4iShESOIzJ5N59KlAxdOQbC6msj+/vnBMTulDN5RWANFNk5M5Bgji6uYMWxcv2UOqJnm+zB92VJ41OBjHBQedZTr20v7wz+WGIYehcOhwIepMlxkIO/zsNr89U67CdXUEB7EcqdARQWR2f6arDOCavCOgirrbwhzSG3/S6UPGTE0JlYL+4lGNWdU6nH2wkMPJRDy184xI6gG7xh9IpR5H9HdS/apnEBxH+twa4uGMaF0hMsWeUN43DhCY1JH4vp2qlQqkQgFB/gvhq4RVIN3TDkfyqd6bYWnhIMh9qtO/aNywPBprqTt8AuZpJ8umDOHQJH/xpaNoBoMHrP/8NSCun8fQpuvRPbdFwrS2zUXcSHh3mAwgmoweMzsqkkpj8+pnpzyeL4SiETSmmQKjhjhbrDqDDCCajB4zMxh4wn2WHZdEi5kYtnQGD9NpmDOnAHLRObM8e1QiBFUg8FjisOFTCrfe4ODDBtHMDD0vp6hiRMJlPefgNCr4NHpMPT+xwwGHzK9Yly/74cKgUCAyMy+l5IFR48mWOXfpXZGUA0GHzClYu+1llMr/DlG6Ab9CWrE5wGPjKAaDD5gSvneApqLmU3tIjRhAvQR7CQyfXrK437BCKrBN8HEXgAAC9JJREFU4AMm9JiAGioL+lMRCIcJT+69wiFQUkLQp7P73RhBNRh8wMjiKgqCVvC36sLyvA+IMhCpBDU8ebJvZ/e7MYJqMPiAUCDIqOJqAMaVDt0IXN2EJ/bOMxZKccxvGEE1GHzC6BJLUEcXD+0IXADBkSN77ZoKj/d/uhwjqAaDTxhZXLnXv0OZQDC4d7CUSITgCP+PKxtBNRh8wohEmuhaI6gAe20vDY0a5atA0n3hfwsNhiHC8EJrh1BNYYXHlviD0MiRKV/7GSOoBoNPqE4IaVVh/1svhwqhpC5+sLZ3Nlg/YgTVYPAJlQWlAFQVlnlsiT8IDv9gci5UkxsrH4ygGgw+obLAEtJhkVKPLfEHgYKCPYFSgtXVHluTHkZQDQafUB4pJhQIUhIu9NoU3xCsrIRgkEBFbowrG0E1GHxCSaSIskix73cDuUlw2DAC5eU5McMPRlANBt8QCgSpLRrmtRm+IlBeTjBHvFMwgmow+AqzZGpvgmVlBEpzZ0zZCKrB4COqi4ygJhMoKSFYUuK1GWkT9toAg8HwAWaGf2+CNTUQj3ttRtoYQTUYfMRpkw732gRfER43DsblTjoY0+U3GHzEmBITaSqXMYJqMBgMNmEE1WAwGGzCCKrBYDDYhCeTUiKyELgGKALWA+ep6uYeZYYDtwDTgBDwdVW9z21bDQaDIV1c91BFpBa4EzhXVWcCD2AJZ09+ByxT1X2AhcANIuL/HAgGg2HI4kWX/wTgTVVdmnh/PbBARPYkIheRMHBq4hyqugZ4BPiUu6YaDAZD+njR5R+P1c0HQFU7RKQucXxL4nANUAxsSLpuAzAhVYUiMhpIlbB7ph0GGwwGQzp4IagBINXWh1iPMqQoFyM1FwPfy9Iug8FgyAovBHUtsKD7jYgUYHmk65LKbAPagDHAxsSxscDbfdR5A3B/iuMzgT9laa/BYDCkhReC+ihwnYjMVtVlwIXAElWt6y6gqlERuQ/4HHCFiEwETgR+lKrCxAqBzT2Pi0gRwMqVK+2/C4PBMKRYvHjxgcByVd3dV5lA3IPAAyJyHPBTrGVT24DzVXWtiLwBXKCqr4pIDXAjMANL+K9S1TszbOdTGA/VYDDYx0Gq+npfJz0RVLdIrGVdCKzBGkLwku7hh7OB5R7b4gfM8+iNeSa98dsz6ddDzetoU6ragLXm1XNEpPvl8v5+4YYK5nn0xjyT3uTaMzFbTw0Gg8EmjKAaDAaDTRhBNRgMBpswgmowGAw2YQTVPTYD3yfFetkhinkevTHPpDc59UzyetmUwWAwuInxUA0Gg8EmjKAaDAaDTRhBNRgMBpvI651SfkFELgEuAzqwomp9TlU39H9VfiIiPwBGq+oFifcfBn6OFf+2Gfisqr7noYmukfhcfAErLOVu4DJV/beIrEq870oU/Yuq/sQjM11DRD4DXI4VtrMeuERV3xOR04ErgAKsuMjnq+o27yztG+OhOoyIzMeK1bpQVfcH7gL+7qlRHiAik0TkXuCrScfGYoVdvCzxbP4M3OSRia4iIocD3wKOSdz7j4D7Es+kDJijqnMTf0NBTAX4CXCsqu4H3AvcKCIHYoXn/ISqzgGWYf0A+xIjqM4zD3haVbvjvd4DfCgRknAocTHwOPCLpGNnAE+q6pLE+5uAS9w2zCN2ABeqan3i/b+BEcBxwC7gMRFZKiK/EpESr4x0C1VVYJyqbkukQJqA5aWeC9yuqu8niv4AuMojMwfECKrz/Bs4WkQmJ96fl/h3jEf2eIKqfktVfwtEkw4L0CwifxaR14G7+aCbm9eo6ruq+iiAiASBXwIPJk4/DiwCDsESll+krCTPUNVOETkSq1t/MdZ9CxAUkX+IyJtY3mqLh2b2ixFUh1HVZ4HvAHeLyCtY3bkGrPHUoU4EOAUr1u2BWBlwH+z/kvxCRCqwei2TscYGb1PVi1R1t6q2Yg0FLPbUSBdR1edUdRSWZ/oQ1mfkI8DngbnAauB27yzsHyOoDiMiZcBzqnqgqh4M3AxUAiaNgJXe5iVVfTfx/lZgeiLVeN4jIjOwejBNwAJVbRSRT4rIwUnFAkCnJwa6SGKMfU9qJFW9D8vpaAMeUdVNqhoHbgMO98jMATGC6jxjgOdEpCrx/jvA/ara6KFNfuEe4HARmZ54vxjrh6bBO5PcQUQmAM8BN6nqearaHQB9BnC1iBQkxhK/hjVZl+9UA3eJyDgAETkZa3jo/4BTRGREotxiYEnqKrzHLJtymMSyj+8BLyS+IK8Dn/XYLF+gqm+JyH8BfxORCJantlhV+8pum098DagCzhGRc5KOLwJGAm9idXefwPoRzmtU9XUR+W/gYRGJAo3Ayar6hoiMAp4UkRDW+OqnPTS1X8xefoPBYLAJ0+U3GAwGmzCCajAYDDZhBNVgMBhswgiqwWAw2IQRVIPBYLAJI6gGQ5aIyBSvbTD4A7MO1eAIInIM8HXgYCAEvANcraoPJs7fCuxS1S8Oou7rgRZV/eqAhR1GRA7AWitaneF1RwJ/S2yzNOQJRlANtiMi52GFWLsY+ChWfMszgb+KyDmqem829auqnyJSDcOK05kRqvocYMQ0zzAL+w22kgg1txn4dE/hFJFLgRJVvSbhoQ7D2g10BFY4u68k9nAjIvtjRRuaB2zHCu13japGk71bESnACiByLlAIPAtcpKpbE9sY/xc4CitC0U1YXnJyxKtu247Bivg0OWH/Lap6TeJcynqwdjStBIoSx/dT1VUp7vmriXt9H/ieqj6UiJP7oKqWichv2Hv3TwTL2SnD2s/+NeBCrBgQzwNfGKoByv2OGUM12M3hWB5br6hRqvrrbpFKcByWMFVjBb24SUQCIlIDPIXVlR4BnAx8BktYevId4ETgMGA0VqT7GxPbFB/ACsAyAZgPfBzoa4jhduAXqjosUe7bIrJff/Wo6ibgJKzhh7IUYjoN+BlwvKpWYYWe+0OizuTn8sXE9WXAJGA98M1EtKnLgPOBhcBYQLECUQf6uA+DhxhBNdhNLbBdVdOJkPSgqr6QiCL0Z6AGy5NbBDSo6tWq2qGqy7GCCqeKgXAO8GNVXZ0IMHIplsjOw4ql+VVVbVXVNcCPgYv6sKUNOFNETgRWAJWq+tYg6kmmE2v8+CIROQS4BRiTykMGEJFCrEj1z6rqzxKHLwR+pKrvJ+7vf7ACqMxLo32DyxhBNdjNZmB4ItjJXohIWY/o88lRpbrjw4axutJre1y+GstD7MlorDxdAKhqfUIIJ2INAdSJSKOINGJ5iGP7sPs4rGGHm7GGGG5JxCrNtJ49qOpa4HhgFlbQ6C3At/rxLv+ANd6cPEY8Efh9Utv1WCI9aaD2De5jJqUMdvMS0Io1GdUzd9a3EsdnD1DHOnoLxlQsQerJBmBc95tEapmLsIITN6jqiKRzVVge8F4kPMMZwGdUNZYYv/0zVsK4x9KtJ0W9tUC7qp6S+IE5DssDfTFF2SuxhksOUdXk4OMbgS+r6j+Tys7C+oEx+AwjqAZbUdV2EfkallcVwxp/DANnY03OfCqNav4JXCsi/4O1WmAyVtbL21KUvQP45v+3d7csEQVRHMafJCiY/AAGw2kmm9jEskHMBotFsPkBfAt+ArFZBMFisZgsgkWTL2Ewq6gsLGixGc4sLIuIYYLh+cEty+7scMOfmTOXeyLiily97QLjwBbwFhE75BZ9DDgha6yLQ2P0Sw7bEbEPPJOdSLvkC6B/G+cLGImI0VrzHDRJ9oZaKKVcRcRL/bwLTPS/FBHLZK10dqDHVN8hsBkR92Rtda3ek6k6T/0jbvnVXCml32xvA3glywArwFIp5fQPv++RhzDzwBtwARyTYTlsDzgnV31P5PZ8tdZwO8A0GUSPwDs/vEuzrgiXyH5fPeCB3KIf/GGcW+CaLAnMDI17U+/BUUR8kj2z1kspd0NT2K3zvoyIj4j4rNcceah1Rh7S9er/duqBmP4ZH5uSpEZcoUpSIwaqJDVioEpSIwaqJDVioEpSIwaqJDVioEpSIwaqJDVioEpSIwaqJDVioEpSIwaqJDXyDRRb4QLAI/EtAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 354.331x354.331 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1,1,figsize=cm2inch(9,9), dpi=100)\n",
    "ax = violin(data=pd.DataFrame(frac_items_seen_mean), ax=ax, palette=colors)\n",
    "add_ttest(ax,\n",
    "          T_seen_items_count, df_seen_items_count, P_seen_items_count,\n",
    "          [(0, 1), (1, 2), (2, 3)],\n",
    "          [(1.2, 1.2), (1.2, 1.2), (1.2, 1.2)],\n",
    "          -.05, .05)\n",
    "ax.set_ylabel('# seen items')\n",
    "ax.set_xlabel('Choice set size')\n",
    "ax.set_xticklabels(setsizes)\n",
    "despine(ax=ax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading mfx-summary from results/posterior_traces/mixed_effects_models/\n",
      "Intercept[0]; Mean: 0.922912861007202, 94% HPD: 0.8842237417998551, 0.9606130346419218\n",
      "setsize[0]; Mean: -0.01523579210446952, 94% HPD: -0.015952514326691696, -0.01448943488825521\n"
     ]
    }
   ],
   "source": [
    "np.random.seed(142112)\n",
    "mfx_filename = 'frac-items-seen_setsize_mfx'\n",
    "if not os.path.isfile(mfx_dir+mfx_filename+'.csv'):\n",
    "    \n",
    "    # make model\n",
    "    samples = 2000\n",
    "    burn = 500\n",
    "    model = bambi.Model(data=data)\n",
    "    model.add('seen_items_count_fraction ~ setsize',  random=['setsize|subject'],\n",
    "              categorical=['subject'])\n",
    "\n",
    "    # sample posterior\n",
    "    results = model.fit(samples=samples, \n",
    "                        tune=burn,\n",
    "                        chains=2,\n",
    "                        backend='pymc',\n",
    "                        init='ADVI',\n",
    "                        n_init=50000,\n",
    "                        random_seed=142112)\n",
    "\n",
    "    # save results\n",
    "    pm.trace_to_dataframe(model.backend.trace).to_csv(\n",
    "        mfx_dir+mfx_filename+'_mtrace.csv', index=False)\n",
    "    az.plot_trace(results)\n",
    "    plt.savefig(mfx_dir+mfx_filename+'.png', dpi=220)\n",
    "    summary = az.summary(results, round_to='none')\n",
    "    summary.to_csv(mfx_dir+mfx_filename+'.csv')\n",
    "    \n",
    "else:\n",
    "    print('Loading mfx-summary from '+mfx_dir)\n",
    "    summary = pd.read_csv(mfx_dir+mfx_filename+'.csv', index_col='Unnamed: 0')\n",
    "\n",
    "_ = get_var(summary, 'Intercept[0]')\n",
    "_ = get_var(summary, 'setsize[0]')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# P(choose last seen item)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/thomas/projects/many-item-choice/utils/descriptives.py:151: FutureWarning: Support for multi-dimensional indexing (e.g. `obj[:, None]`) is deprecated and will be removed in a future version.  Convert to a numpy array before indexing instead.\n",
      "  for s in setsizes], axis=1)\n"
     ]
    }
   ],
   "source": [
    "(last_gaze_data, \n",
    " sub_p_last_gaze_choice_means, \n",
    " p_last_gaze_choice_means,\n",
    " p_last_gaze_choice_sems ) = compute_p_last_gaze_choice(data,\n",
    "                                                        gaze_data,\n",
    "                                                        is_return_subject_means=True,\n",
    "                                                        is_return_data=True)\n",
    "\n",
    "(T_last_gaze_choice,\n",
    " df_p_last_gaze_choice,\n",
    " P_last_gaze_choice) =  compute_ttests(sub_p_last_gaze_choice_means)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fa3e1d14da0>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 354.331x354.331 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1,1,figsize=cm2inch(9,9), dpi=100)\n",
    "ax = violin(data=pd.DataFrame(sub_p_last_gaze_choice_means), ax=ax, palette=colors)\n",
    "add_ttest(ax,\n",
    "          [T_last_gaze_choice[-1]],\n",
    "          df_p_last_gaze_choice,\n",
    "          [P_last_gaze_choice[-1]],\n",
    "          [(0, 3)],\n",
    "          [(1.3, 1.3)],\n",
    "          -.02, .02)\n",
    "ax.set_ylabel('P(choose last seen item)')\n",
    "ax.set_xlabel('Choice set size')\n",
    "ax.set_xticklabels(setsizes)\n",
    "despine(ax=ax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Avg. probability of choosing the last seen item: 0.44548746176475496\n"
     ]
    }
   ],
   "source": [
    "print('Avg. probability of choosing the last seen item: {}'.format(np.mean(p_last_gaze_choice_means)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## MFX: $P(last\\_gaze\\_to\\_choice) \\sim setsize$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading mfx-summary from results/posterior_traces/mixed_effects_models/\n",
      "Intercept[0]; Mean: 0.4163788644279891, 94% HPD: 0.34299429887786403, 0.4804551105029498\n",
      "setsize[0]; Mean: 0.0013657368936168446, 94% HPD: -1.357368994267731e-05, 0.0026183111528046373\n"
     ]
    }
   ],
   "source": [
    "np.random.seed(365)\n",
    "mfx_filename = 'p-last-fix-choice_setsize_mfx'\n",
    "if not os.path.isfile(mfx_dir+mfx_filename+'.csv'):\n",
    "    \n",
    "    # make model\n",
    "    samples = 2000\n",
    "    burn = 500\n",
    "    model = bambi.Model(data=last_gaze_data)\n",
    "    model.add('last_gaze_to_choice ~ setsize', random=['setsize|subject'],\n",
    "              categorical=['subject'])\n",
    "\n",
    "    # sample posterior\n",
    "    results = model.fit(samples=samples, \n",
    "                        tune=burn,\n",
    "                        chains=2,\n",
    "                        backend='pymc',\n",
    "                        init='ADVI',\n",
    "                        n_init=50000,\n",
    "                        random_seed=365)\n",
    "\n",
    "    # save results\n",
    "    pm.trace_to_dataframe(model.backend.trace).to_csv(\n",
    "        mfx_dir+mfx_filename+'_mtrace.csv', index=False)\n",
    "    az.plot_trace(results)\n",
    "    plt.savefig(mfx_dir+mfx_filename+'.png', dpi=220)\n",
    "    summary = az.summary(results, round_to='none')\n",
    "    summary.to_csv(mfx_dir+mfx_filename+'.csv')\n",
    "    \n",
    "else:\n",
    "    print('Loading mfx-summary from '+mfx_dir)\n",
    "    summary = pd.read_csv(mfx_dir+mfx_filename+'.csv', index_col='Unnamed: 0')\n",
    "\n",
    "_ = get_var(summary, 'Intercept[0]')\n",
    "_ = get_var(summary, 'setsize[0]')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ..when participants don't look at all items of a choice set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "sub_p_last_gaze_choice_not_all_seen = np.concatenate(\n",
    "    [np.asarray(last_gaze_data[last_gaze_data['seen_items_count']<last_gaze_data['setsize']].groupby(\n",
    "        ['setsize', 'subject']).last_gaze_to_choice.mean()[s])[:,None] for s in setsizes], axis=1)\n",
    "\n",
    "(T_last_gaze_choice_not_all_seen,\n",
    " df_last_gaze_choice_not_all_seen,\n",
    " P_last_gaze_choice_not_all_seen) =  compute_ttests(sub_p_last_gaze_choice_not_all_seen)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fa3f3508828>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 354.331x354.331 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1,1,figsize=cm2inch(9,9), dpi=100)\n",
    "ax = violin(data=pd.DataFrame(sub_p_last_gaze_choice_not_all_seen), ax=ax, palette=colors)\n",
    "add_ttest(ax,\n",
    "          [T_last_gaze_choice_not_all_seen[-1]],\n",
    "          df_last_gaze_choice_not_all_seen,\n",
    "          [P_last_gaze_choice_not_all_seen[-1]],\n",
    "          [(0, 3)],\n",
    "          [(1.3, 1.3)],\n",
    "          -.02, .02)\n",
    "ax.set_ylabel('P(choose last seen item)')\n",
    "ax.set_xlabel('Choice set size')\n",
    "ax.set_xticklabels(setsizes)\n",
    "despine(ax=ax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Avg. probability of choosing the last seen item: 0.4410419787862564\n"
     ]
    }
   ],
   "source": [
    "means_p_last_gaze_choice_not_all_seen = last_gaze_data[\n",
    "    last_gaze_data['seen_items_count']<last_gaze_data['setsize']].groupby(\n",
    "    ['setsize', 'subject']).last_gaze_to_choice.mean().groupby(level=0).mean()\n",
    "print('Avg. probability of choosing the last seen item: {}'.format(np.mean(means_p_last_gaze_choice_not_all_seen)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## MFX: $P(last\\_gaze\\_to\\_choice) \\sim setsize$ "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading mfx-summary from results/posterior_traces/mixed_effects_models/\n",
      "Intercept[0]; Mean: 0.4223682926721905, 94% HPD: 0.3519244431856446, 0.4965585704068978\n",
      "setsize[0]; Mean: 0.001247431707855298, 94% HPD: -0.00032693803363172363, 0.002625489844523641\n"
     ]
    }
   ],
   "source": [
    "np.random.seed(58745)\n",
    "mfx_filename = 'p-last-fix-choice-when-not-all-seen_setsize_mfx'\n",
    "if not os.path.isfile(mfx_dir+mfx_filename+'.csv'):\n",
    "    \n",
    "    # make model\n",
    "    samples = 2000\n",
    "    burn = 500\n",
    "    model = bambi.Model(data=last_gaze_data[last_gaze_data['seen_items_count']<\n",
    "                                            last_gaze_data['setsize']].copy())\n",
    "    model.add('last_gaze_to_choice ~ setsize', random=['setsize|subject'], \n",
    "              categorical=['subject'])\n",
    "\n",
    "    # sample posterior\n",
    "    results = model.fit(samples=samples, \n",
    "                        tune=burn,\n",
    "                        chains=2,\n",
    "                        backend='pymc',\n",
    "                        init='ADVI',\n",
    "                        n_init=50000,\n",
    "                        random_seed=58745)\n",
    "\n",
    "    # save results\n",
    "    pm.trace_to_dataframe(model.backend.trace).to_csv(\n",
    "        mfx_dir+mfx_filename+'_mtrace.csv', index=False)\n",
    "    az.plot_trace(results)\n",
    "    plt.savefig(mfx_dir+mfx_filename+'.png', dpi=220)\n",
    "    summary = az.summary(results, round_to='none')\n",
    "    summary.to_csv(mfx_dir+mfx_filename+'.csv')\n",
    "    \n",
    "else:\n",
    "    print('Loading mfx-summary from '+mfx_dir)\n",
    "    summary = pd.read_csv(mfx_dir+mfx_filename+'.csv', index_col='Unnamed: 0')\n",
    "\n",
    "_ = get_var(summary, 'Intercept[0]')\n",
    "_ = get_var(summary, 'setsize[0]')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## MFX: $P(current\\_gaze\\_is\\_last) \\sim cached\\_value + time + setsize$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading mfx-summary from results/posterior_traces/mixed_effects_models/\n",
      "Intercept[0]; Mean: 0.02172374863213656, 94% HPD: 0.015254710835992747, 0.028350066692895824\n",
      "cached_value[0]; Mean: 0.026714367220029712, 94% HPD: 0.020487560959620853, 0.032842435313960375\n",
      "cumulative_time[0]; Mean: 2.261978314163816e-05, 94% HPD: 1.6908006313800006e-05, 2.803711694896359e-05\n",
      "setsize[0]; Mean: -0.002229159023236356, 94% HPD: -0.002416883429320555, -0.002021983029034647\n"
     ]
    }
   ],
   "source": [
    "np.random.seed(6532)\n",
    "mfx_filename = 'p-is-last-fix_cached-value-time_mfx'\n",
    "if not os.path.isfile(mfx_dir+mfx_filename+'.csv'):\n",
    "\n",
    "    # load gaze data\n",
    "    gaze_data_tmp = []\n",
    "    for subject in subjects:\n",
    "        # load subject data\n",
    "        subject_data = data[data['subject']==subject].copy()\n",
    "        subject_gaze_data = gaze_data[gaze_data['subject']==subject].copy()\n",
    "        cached_value = []\n",
    "        cumulative_time = []\n",
    "        for trial in subject_gaze_data.trial.unique():\n",
    "            trial_gaze_data = subject_gaze_data[subject_gaze_data['trial']==trial].copy()\n",
    "            trial_cached_value = np.maximum.accumulate(trial_gaze_data['value'].values)\n",
    "            cached_value.append(trial_cached_value)\n",
    "            trial_cumulative_time = np.cumsum(trial_gaze_data['dur'])\n",
    "            cumulative_time.append(trial_cumulative_time)\n",
    "        subject_gaze_data['cached_value'] = np.concatenate(cached_value).astype('float64')\n",
    "        subject_gaze_data['cumulative_time'] = np.concatenate(cumulative_time).astype('float64')\n",
    "        gaze_data_tmp.append(subject_gaze_data)\n",
    "    gaze_data_tmp = pd.concat(gaze_data_tmp, sort=True)\n",
    "    gaze_data_tmp.reset_index(drop=True, inplace=True)\n",
    "\n",
    "    # make model\n",
    "    samples = 2000\n",
    "    burn = 500\n",
    "    model = bambi.Model(data=gaze_data_tmp)\n",
    "\n",
    "    # fixed effects\n",
    "    model.add('is_last ~ cached_value + cumulative_time + setsize',\n",
    "              categorical=['subject'])\n",
    "\n",
    "    # random effects\n",
    "    model.add(random=['1|subject'])\n",
    "    model.add(random=['0+setsize|subject'])\n",
    "    model.add(random=['0+cached_value|subject'])\n",
    "    model.add(random=['0+cumulative_time|subject'])\n",
    "\n",
    "    # sample posterior\n",
    "    results = model.fit(samples=samples, \n",
    "                        tune=burn,\n",
    "                        chains=2,\n",
    "                        backend='pymc',\n",
    "                        init='ADVI',\n",
    "                        n_init=50000,\n",
    "                        random_seed=6532)\n",
    "\n",
    "    # save results\n",
    "    pm.trace_to_dataframe(model.backend.trace).to_csv(\n",
    "        mfx_dir+mfx_filename+'_mtrace.csv', index=False)\n",
    "    az.plot_trace(results)\n",
    "    plt.savefig(mfx_dir+mfx_filename+'.png', dpi=220)\n",
    "    summary = az.summary(results, round_to='none')\n",
    "    summary.to_csv(mfx_dir+mfx_filename+'.csv')\n",
    "    \n",
    "else:\n",
    "    print('Loading mfx-summary from '+mfx_dir)\n",
    "    summary = pd.read_csv(mfx_dir+mfx_filename+'.csv', index_col='Unnamed: 0')\n",
    "\n",
    "_ = get_var(summary, 'Intercept[0]')\n",
    "_ = get_var(summary, 'cached_value[0]')\n",
    "_ = get_var(summary, 'cumulative_time[0]')\n",
    "_ = get_var(summary, 'setsize[0]')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Gaze influence on P(choose item)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 354.331x354.331 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sub_gaze_influence_scores = []\n",
    "for setsize in setsizes:\n",
    "    sub_gaze_influence_scores.append(\n",
    "        compute_gaze_influence_score(data[data['setsize']==setsize].copy())[:,None])\n",
    "sub_gaze_influence_scores = pd.DataFrame(np.concatenate(sub_gaze_influence_scores, axis=1))\n",
    "\n",
    "(T_gaze_influence_score,\n",
    " df_gaze_influence_score,\n",
    " P_gaze_influence_score) =  compute_ttests(sub_gaze_influence_scores.values)\n",
    "\n",
    "fig, ax = plt.subplots(1,1,figsize=cm2inch(9,9), dpi=100)\n",
    "ax = violin(data=sub_gaze_influence_scores, ax=ax, palette=colors)\n",
    "add_ttest(ax,\n",
    "          T_gaze_influence_score,\n",
    "          df_gaze_influence_score,\n",
    "          P_gaze_influence_score,\n",
    "          [(0, 1), (1, 2), (2, 3)],\n",
    "          [(0.8, 0.8), (0.9, 0.9), (1, 1)],\n",
    "          -.02, .02)\n",
    "ax.set_ylim(0, 1.1)\n",
    "ax.set_ylabel('Gaze influence on P(choose item)', fontsize=7)\n",
    "ax.set_xlabel('Choice set size', fontsize=7)\n",
    "ax.set_xticks(np.arange(4))\n",
    "ax.set_xticklabels([9,16,25,36], fontsize=7)\n",
    "ax = despine(ax=ax)\n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## MFX: $gaze\\_influence \\sim setsize$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading mfx-summary from results/posterior_traces/mixed_effects_models/\n",
      "Intercept[0]; Mean: 0.19155085442793354, 94% HPD: 0.15264032018318996, 0.2314303825841681\n",
      "setsize[0]; Mean: 0.0026367614685309762, 94% HPD: 0.001490499263907034, 0.003941752488429872\n"
     ]
    }
   ],
   "source": [
    "np.random.seed(38192)\n",
    "mfx_filename = 'gaze-influence_setsize_mfx'\n",
    "if not os.path.isfile(mfx_dir+mfx_filename+'.csv'):\n",
    "    \n",
    "    # collect scores\n",
    "    mfx_df = []\n",
    "    for setsize in setsizes:\n",
    "        setsize_scores = compute_gaze_influence_score(data[data['setsize']==setsize].copy())\n",
    "        df_tmp = pd.DataFrame({'gaze_influence':setsize_scores,\n",
    "                               'setsize': setsize,\n",
    "                               'subject': np.arange(49)})\n",
    "        mfx_df.append(df_tmp)\n",
    "    mfx_df = pd.concat(mfx_df)\n",
    "    \n",
    "    # make model\n",
    "    samples = 2000\n",
    "    burn = 500\n",
    "    model = bambi.Model(data=mfx_df)\n",
    "    model.add('gaze_influence ~ setsize', random=['setsize|subject'], \n",
    "              categorical=['subject'])\n",
    "\n",
    "    # sample posterior\n",
    "    results = model.fit(samples=samples, \n",
    "                        tune=burn,\n",
    "                        chains=2,\n",
    "                        backend='pymc',\n",
    "                        init='ADVI',\n",
    "                        n_init=50000,\n",
    "                        random_seed=38192)\n",
    "\n",
    "    # save results\n",
    "    pm.trace_to_dataframe(model.backend.trace).to_csv(\n",
    "        mfx_dir+mfx_filename+'_mtrace.csv', index=False)\n",
    "    az.plot_trace(results)\n",
    "    plt.savefig(mfx_dir+mfx_filename+'.png', dpi=220)\n",
    "    summary = az.summary(results, round_to='none')\n",
    "    summary.to_csv(mfx_dir+mfx_filename+'.csv')\n",
    "    \n",
    "else:\n",
    "    print('Loading mfx-summary from '+mfx_dir)\n",
    "    summary = pd.read_csv(mfx_dir+mfx_filename+'.csv', index_col='Unnamed: 0')\n",
    "\n",
    "_ = get_var(summary, 'Intercept[0]')\n",
    "_ = get_var(summary, 'setsize[0]')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## MFX: $P(choose\\_item) \\sim gaze\\_advantage + relative\\_rating + value\\_range\\_others + setsize$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "# get gaze data\n",
    "gaze_influence_df = []\n",
    "for setsize in setsizes:\n",
    "    # subset\n",
    "    data_setsize = data[data['setsize']==setsize].copy()\n",
    "    # index choice\n",
    "    choice = np.zeros((data_setsize.shape[0], setsize))\n",
    "    choice[np.arange(data_setsize.shape[0]), data_setsize['choice'].values.astype('int32')] = 1\n",
    "    # get data\n",
    "    gaze = data_setsize[['gaze_{}'.format(i) for i in range(setsize)]].values\n",
    "    values = data_setsize[['item_value_{}'.format(i) for i in range(setsize)]].values\n",
    "    gaze_advantage = np.zeros_like(values)\n",
    "    rel_values = np.zeros_like(values)\n",
    "    value_range = np.zeros_like(values)\n",
    "    for t in range(values.shape[0]):\n",
    "        for i in range(setsize):\n",
    "            index = np.arange(setsize)!=i\n",
    "            gaze_advantage[t,i] = gaze[t,i] - np.max(gaze[t, index])\n",
    "            rel_values[t,i] = values[t,i] - np.mean(values[t, index])\n",
    "            value_range[t, i] = (np.max(values[t, index]) - np.min(values[t, index]))\n",
    "    # collect\n",
    "    df_tmp = pd.DataFrame(dict(subject=np.repeat(data_setsize['subject'].values, setsize),\n",
    "                               setsize=setsize,\n",
    "                               is_choice=choice.ravel(),\n",
    "                               value=values.ravel(),\n",
    "                               rel_value=rel_values.ravel(),\n",
    "                               value_range_others=value_range.ravel(),\n",
    "                               rel_gaze=gaze_advantage.ravel(),\n",
    "                               gaze=gaze.ravel()))\n",
    "    gaze_influence_df.append(df_tmp)\n",
    "gaze_influence_df = pd.concat(gaze_influence_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading mfx-summary from results/posterior_traces/mixed_effects_models/\n",
      "Intercept[0]; Mean: 0.2979436923418969, 94% HPD: 0.27745025548065305, 0.3190009728681377\n",
      "rel_gaze[0]; Mean: 0.004586160930335409, 94% HPD: 0.003973114472133895, 0.005236689603052982\n",
      "rel_value[0]; Mean: 0.03639788974048213, 94% HPD: 0.032303966402904116, 0.040049144831917335\n",
      "value_range_others[0]; Mean: -0.027772304363575823, 94% HPD: -0.031439128811815764, -0.023811526957106872\n",
      "setsize[0]; Mean: -0.001587776534078616, 94% HPD: -0.0017782504515327536, -0.0013946719551829162\n"
     ]
    }
   ],
   "source": [
    "np.random.seed(84123)\n",
    "mfx_filename = 'p-choice_relative-rating-and-range_mfx'\n",
    "if not os.path.isfile(mfx_dir+mfx_filename+'.csv'):\n",
    "    \n",
    "    # make model\n",
    "    samples = 2000\n",
    "    burn = 500\n",
    "    gaze_influence_df['rel_gaze'] = gaze_influence_df['rel_gaze'] * 100\n",
    "    model = bambi.Model(data=gaze_influence_df)\n",
    "    model.add('is_choice ~ rel_gaze + rel_value + value_range_others + setsize',\n",
    "                               random=['1|subject',\n",
    "                                       '0+setsize|subject',\n",
    "                                       '0+rel_gaze|subject',\n",
    "                                       '0+rel_value|subject',\n",
    "                                       '0+value_range_others|subject'],\n",
    "                               categorical=['subject'])\n",
    "\n",
    "    # sapmle posterior\n",
    "    results = model.fit(samples=samples,\n",
    "                        tune=burn,\n",
    "                        chains=2,\n",
    "                        family='bernoulli',\n",
    "                        backend='pymc',\n",
    "                        init='ADVI',\n",
    "                        n_init=50000,\n",
    "                        random_seed=84123)\n",
    "\n",
    "    # save results\n",
    "    pm.trace_to_dataframe(model.backend.trace).to_csv(\n",
    "        mfx_dir+mfx_filename+'_mtrace.csv', index=False)\n",
    "    az.plot_trace(results)\n",
    "    plt.savefig(mfx_dir+mfx_filename+'.png', dpi=220)\n",
    "    summary = az.summary(results, round_to='none')\n",
    "    summary.to_csv(mfx_dir+mfx_filename+'.csv')\n",
    "    \n",
    "else:\n",
    "    print('Loading mfx-summary from '+mfx_dir)\n",
    "    summary = pd.read_csv(mfx_dir+mfx_filename+'.csv', index_col='Unnamed: 0')\n",
    "\n",
    "_ = get_var(summary, 'Intercept[0]')\n",
    "_ = get_var(summary, 'rel_gaze[0]')\n",
    "_ = get_var(summary, 'rel_value[0]')\n",
    "_ = get_var(summary, 'value_range_others[0]')\n",
    "_ = get_var(summary, 'setsize[0]')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## MFX: $P(choose\\_first\\_seen\\_item) \\sim dur(first\\_gaze) + rating + setsize$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading mfx-summary from results/posterior_traces/mixed_effects_models/\n",
      "Intercept[0]; Mean: 0.07201901331085205, 94% HPD: 0.05168522805338442, 0.09011498742104693\n",
      "first_gaze_dur[0]; Mean: 0.00017818842689314423, 94% HPD: 0.0001372017357860861, 0.0002221429215583116\n",
      "value[0]; Mean: 0.06004897294358232, 94% HPD: 0.05454845634812575, 0.06582913110421479\n",
      "setsize[0]; Mean: -0.0027104565398859285, 94% HPD: -0.003216646989714988, -0.0021678664366557828\n"
     ]
    }
   ],
   "source": [
    "np.random.seed(574135)\n",
    "mfx_filename = 'p-choose-first-seen_dur-first-gaze_mfx'\n",
    "if not os.path.isfile(mfx_dir+mfx_filename+'.csv'):\n",
    "    \n",
    "    # compute gaze times per item\n",
    "    first_gaze_data = gaze_data[gaze_data['fixnum']==1].copy()\n",
    "    is_choice = (first_gaze_data['item']==first_gaze_data['choice']).astype(np.int)\n",
    "    df_tmp = pd.DataFrame(dict(is_choice=is_choice,\n",
    "                               first_gaze_dur=first_gaze_data['dur'].astype(np.int),\n",
    "                               value=first_gaze_data['value'],\n",
    "                               setsize=first_gaze_data['setsize'],\n",
    "                               subject=first_gaze_data['subject']))\n",
    "    \n",
    "    # make model\n",
    "    samples = 2000\n",
    "    burn = 500\n",
    "    model = bambi.Model(data=df_tmp)\n",
    "    model.add('is_choice ~ first_gaze_dur + value + setsize',\n",
    "              random=['1|subject',\n",
    "                      '0+first_gaze_dur|subject',\n",
    "                      '0+value|subject',\n",
    "                      '0+setsize|subject'],\n",
    "              categorical=['subject'])\n",
    "\n",
    "    # sample posterior\n",
    "    results = model.fit(samples=samples,\n",
    "                        tune=burn,\n",
    "                        chains=2,\n",
    "                        family='bernoulli',\n",
    "                        backend='pymc',\n",
    "                        init='ADVI',\n",
    "                        n_init=50000,\n",
    "                        random_seed=574135)\n",
    "\n",
    "    # save results\n",
    "    pm.trace_to_dataframe(model.backend.trace).to_csv(\n",
    "        mfx_dir+mfx_filename+'_mtrace.csv', index=False)\n",
    "    az.plot_trace(results)\n",
    "    plt.savefig(mfx_dir+mfx_filename+'.png', dpi=220)\n",
    "    summary = az.summary(results, round_to='none')\n",
    "    summary.to_csv(mfx_dir+mfx_filename+'.csv')\n",
    "    \n",
    "else:\n",
    "    print('Loading mfx-summary from '+mfx_dir)\n",
    "    summary = pd.read_csv(mfx_dir+mfx_filename+'.csv', index_col='Unnamed: 0')\n",
    "\n",
    "_ = get_var(summary, 'Intercept[0]')\n",
    "_ = get_var(summary, 'first_gaze_dur[0]')\n",
    "_ = get_var(summary, 'value[0]')\n",
    "_ = get_var(summary, 'setsize[0]')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Figure 4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "def compute_assocoiations_figure_4F(data, gaze_data, setsizes=np.array([9,16,25,36]), verbose=False):\n",
    "    \"\"\"Compute Spearman rank correlations for associations  \n",
    "    shown in Fig. 4 F of the manuscript. \n",
    "    \n",
    "    Args:\n",
    "        data (dataframe): choice data   \n",
    "        gaze_data (dataframe): gaze data\n",
    "        setsizes (array of int): choice set size conditions\n",
    "        verbose (bool): whether to print results of each\n",
    "            association test\n",
    "                \n",
    "    Returns:\n",
    "        matrix with correlation coefficients and p-values:\n",
    "        (var A x var B x (correlation coefficient, p-value))\n",
    "    \"\"\"\n",
    "    \n",
    "    # 1. Seen items count vs set-size\n",
    "    data['frac_items_seen'] = (data['seen_items_count'] / data['setsize']).values.astype(np.float)\n",
    "    sub_frac_items_seen = np.concatenate(\n",
    "        [data.groupby(['setsize', 'subject']).frac_items_seen.mean()[s][:,None] for s in setsizes],\n",
    "        axis=1)\n",
    "    \n",
    "    # 2. Response time vs set-size\n",
    "    sub_rt_means = np.concatenate(\n",
    "        [data.groupby(['setsize', 'subject']).rt_s.mean()[s][:,None] for s in setsizes],\n",
    "        axis=1)\n",
    "    \n",
    "    # 3. P(choose best seen item )\n",
    "    sub_best_seen_chosen_means = np.concatenate(\n",
    "        [data.groupby(['setsize','subject']).best_seen_chosen.mean()[s][:,None] for s in setsizes],\n",
    "        axis=1)\n",
    "    \n",
    "    # 4. P(last gaze to choice)\n",
    "    (sub_p_last_fix_choice_means,\n",
    "     p_last_fix_choice_means,\n",
    "     p_last_fix_choice_sems) = compute_p_last_gaze_choice(data, gaze_data)\n",
    "    \n",
    "    # 5. Gaze Influence on choice probability\n",
    "    sub_gaze_influence_scores = []\n",
    "    for setsize in setsizes:\n",
    "        sub_gaze_influence_scores.append(compute_gaze_influence_score(data[data['setsize']==setsize].copy()))\n",
    "    sub_gaze_influence_scores = np.concatenate([s[:,None] for s in sub_gaze_influence_scores],\n",
    "                                               axis=1)\n",
    "    \n",
    "    # Make df (average over setsizes)\n",
    "    assoc_df = pd.DataFrame({'subject': subjects,\n",
    "                             'frac_items_seen': sub_frac_items_seen.mean(axis=1),\n",
    "                             'RT': sub_rt_means.mean(axis=1),\n",
    "                             'best_chosen': sub_best_seen_chosen_means.mean(axis=1),\n",
    "                             'last_gaze_to_choice': sub_p_last_fix_choice_means.mean(axis=1),\n",
    "                             'gaze_influence': sub_gaze_influence_scores.mean(axis=1)})\n",
    "    \n",
    "    # Define combinations\n",
    "    xs = ['best_chosen', 'best_chosen', 'best_chosen', 'best_chosen', 'best_chosen',\n",
    "          'frac_items_seen', 'frac_items_seen', 'frac_items_seen', 'frac_items_seen',\n",
    "          'RT', 'RT', 'RT',\n",
    "          'last_gaze_to_choice', 'last_gaze_to_choice',\n",
    "          'gaze_influence']\n",
    "    ys = ['best_chosen', 'frac_items_seen', 'RT', 'last_gaze_to_choice', 'gaze_influence',\n",
    "          'frac_items_seen', 'RT', 'last_gaze_to_choice', 'gaze_influence',\n",
    "          'RT', 'last_gaze_to_choice', 'gaze_influence',\n",
    "          'last_gaze_to_choice', 'gaze_influence',\n",
    "          'gaze_influence']\n",
    "    pos = [(0,0), (1,0), (2,0), (3,0), (4,0),\n",
    "           (1,1), (2,1), (3,1), (4,1),\n",
    "           (2,2), (3,2), (4,2),\n",
    "           (3,3), (4,3),\n",
    "           (4,4)]\n",
    "    \n",
    "    if verbose:\n",
    "        print('\\nCorrelation coefficients:')\n",
    "    \n",
    "    # Compute correlations\n",
    "    association_mat = np.zeros((5,5,2)) * np.nan\n",
    "    for x, y, (xi, yi) in zip(xs, ys, pos):\n",
    "        if verbose:\n",
    "            print('\\n{} ~ {}'.format(x,y))\n",
    "        r, p = spearmanr(assoc_df[x], assoc_df[y])\n",
    "        if verbose:\n",
    "            print('Spearman r = {}, p = {}'.format(r, p))\n",
    "        association_mat[xi, yi] = r, p\n",
    "    \n",
    "    return association_mat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "def figure_4(data, gaze_data, colors=['darkturquoise', 'orange', 'mediumseagreen', 'lightcoral']):\n",
    "    \"\"\"Create figure 4 of the manuscript.\n",
    "    \n",
    "    Args:\n",
    "        data (dataframe): choice data   \n",
    "        gaze_data (dataframe): gaze data\n",
    "        colors (array of strings): colors to use for set sizes\n",
    "                \n",
    "    Returns:\n",
    "        matplotlib figure / axis\n",
    "    \"\"\"\n",
    "    \n",
    "    # create figure\n",
    "    fig, axs = plt.subplots(2, 3, figsize=cm2inch(16,10), dpi=300)\n",
    "    axs = axs.ravel()\n",
    "        \n",
    "    # extract subject count\n",
    "    n_subjects = data.subject.unique().size\n",
    "    \n",
    "    \n",
    "    # 1. P(choose best seen item )\n",
    "    sub_best_seen_chosen_means = np.concatenate(\n",
    "        [np.asarray(data.groupby(['setsize','subject']).best_seen_chosen.mean()[s])[:,None]\n",
    "         for s in setsizes], axis=1)\n",
    "    axs[0] = violin(data=pd.DataFrame(sub_best_seen_chosen_means), ax=axs[0], palette=colors)\n",
    "    axs[0].set_ylim(0, 1)\n",
    "    axs[0].set_ylabel('P(best seen item chosen)', fontsize=7)\n",
    "    axs[0].set_xlabel('Choice set size', fontsize=7)\n",
    "    axs[0].set_xticks(np.arange(4))\n",
    "    axs[0].set_xticklabels([9,16,25,36], fontsize=7)\n",
    "    axs[0] = despine(ax=axs[0])\n",
    "    \n",
    "    \n",
    "    # 1. % items seen vs set-size\n",
    "    frac_items_seen_means = np.concatenate(\n",
    "        [np.asarray(data.groupby(['setsize','subject']).seen_items_count_fraction.mean()[s])[:,None]\n",
    "         for s in setsizes], axis=1)\n",
    "    axs[1] = violin(data=pd.DataFrame(frac_items_seen_means), ax=axs[1], palette=colors)\n",
    "    axs[1].set_ylim(0,1)\n",
    "    axs[1].set_ylabel('% of items seen', fontsize=7)\n",
    "    axs[1].set_xlabel('Choice set size', fontsize=7)\n",
    "    axs[1].set_xticks(np.arange(4))\n",
    "    axs[1].set_xticklabels([9,16,25,36], fontsize=7)\n",
    "    despine(ax=axs[1])\n",
    "    \n",
    "    \n",
    "    # 2. Response time vs set-size\n",
    "    sub_rt_means = np.concatenate(\n",
    "        [np.asarray(data.groupby(['setsize','subject']).rt_s.mean()[s])[:,None]\n",
    "         for s in setsizes], axis=1)\n",
    "    axs[2] = violin(data=pd.DataFrame(sub_rt_means), ax=axs[2], palette=colors)\n",
    "    axs[2].set_ylabel('Mean RT (s)', fontsize=7)\n",
    "    axs[2].set_xlabel('Choice set size', fontsize=7)\n",
    "    axs[2].set_xticks(np.arange(4))\n",
    "    axs[2].set_xticklabels([9,16,25,36], fontsize=7)\n",
    "    axs[2].set_ylim(0,15)\n",
    "    axs[2].set_yticks([0,5,10,15])\n",
    "    axs[2] = despine(ax=axs[2])\n",
    "    \n",
    "    \n",
    "    # 4. P(last gaze to choice)\n",
    "    # load gaze data\n",
    "    (sub_p_last_fix_choice_means, _, _) = compute_p_last_gaze_choice(data, gaze_data)\n",
    "    axs[3] = violin(data=pd.DataFrame(sub_p_last_fix_choice_means), ax=axs[3], palette=colors)\n",
    "    axs[3].set_ylim(0, 1)\n",
    "    axs[3].set_ylabel('P(last seen item chosen)', fontsize=7)\n",
    "    axs[3].set_xlabel('Choice set size', fontsize=7)\n",
    "    axs[3].set_xticks(np.arange(4))\n",
    "    axs[3].set_xticklabels([9,16,25,36], fontsize=7)\n",
    "    axs[3] = despine(ax=axs[3])\n",
    "    \n",
    "    \n",
    "    # 5. Gaze Influence Score\n",
    "    sub_gaze_influence_scores = []\n",
    "    for setsize in setsizes:\n",
    "        sub_gaze_influence_scores.append(\n",
    "            compute_gaze_influence_score(data[data['setsize']==setsize].copy())[:,None])\n",
    "    axs[4] = violin(data=pd.DataFrame(np.concatenate(sub_gaze_influence_scores, axis=1)), ax=axs[4], palette=colors)\n",
    "    axs[4].set_ylim(0, 1)\n",
    "    axs[4].set_ylabel('Gaze influence\\non P(choose item)', fontsize=7)\n",
    "    axs[4].set_xlabel('Choice set size', fontsize=7)\n",
    "    axs[4].set_xticks(np.arange(4))\n",
    "    axs[4].set_xticklabels([9,16,25,36], fontsize=7)\n",
    "    axs[4] = despine(ax=axs[4])\n",
    "    \n",
    "    \n",
    "    # association matrix\n",
    "    axs[5].set_title('Spearman rank correlation \\nof behavioural metrics', fontsize=7)\n",
    "    assoc_mat = compute_assocoiations_figure_4F(data, gaze_data, setsizes=np.array([9,16,25,36]), verbose=True)\n",
    "    im = axs[5].imshow(assoc_mat[:,:,0], cmap='viridis', vmax=1, vmin=-0.3)\n",
    "    despine(ax=axs[5])\n",
    "    axs[5].set_xticks(np.arange(5))\n",
    "    axs[5].set_yticks(np.arange(5))\n",
    "    axs[5].set_xticklabels(['A', 'B', 'C', 'D', 'E'], fontsize=7)\n",
    "    axs[5].set_yticklabels(['A', 'B', 'C', 'D', 'E'], fontsize=7)\n",
    "    axs[5].set_ylim(4.5, -0.5)\n",
    "    axs[5].set_xlim(-0.5, 4.5)\n",
    "    # label\n",
    "    pos = [(0,0), (1,0), (2,0), (3,0), (4,0),\n",
    "           (1,1), (2,1), (3,1), (4,1),\n",
    "           (2,2), (3,2), (4,2),\n",
    "           (3,3), (4,3),\n",
    "           (4,4)]\n",
    "    thresh = 0.4\n",
    "    for (i, j) in pos:\n",
    "        if assoc_mat[i, j, 1] < (0.1 / 10.) and i!=j:\n",
    "            axs[5].text(j, i, \"{:1.2f}\".format(assoc_mat[i, j, 0]),\n",
    "                        horizontalalignment=\"center\",\n",
    "                        color=\"white\" if assoc_mat[i, j, 0] < thresh else \"black\",\n",
    "                        fontsize=6, fontweight='bold')\n",
    "        else:\n",
    "            axs[5].text(j, i, \"{:1.2f}\".format(assoc_mat[i, j, 0]),\n",
    "                    horizontalalignment=\"center\",\n",
    "                    color=\"white\" if assoc_mat[i, j, 0] < thresh else \"black\",\n",
    "                    fontsize=6)\n",
    "        \n",
    "    \n",
    "    # index axes\n",
    "    for label, ax in zip(list('ABCDEF'), axs):\n",
    "        ax.text(-0.35, 1.15, label, transform=ax.transAxes,\n",
    "            fontsize=10, fontweight='bold', va='top')\n",
    "    for ax in axs[:5]:\n",
    "        ax.tick_params(axis='both', which='major', labelsize=7)\n",
    "    \n",
    "    fig.tight_layout(h_pad=1)\n",
    "    \n",
    "    return fig, axs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/thomas/projects/many-item-choice/utils/descriptives.py:151: FutureWarning: Support for multi-dimensional indexing (e.g. `obj[:, None]`) is deprecated and will be removed in a future version.  Convert to a numpy array before indexing instead.\n",
      "  for s in setsizes], axis=1)\n",
      "/opt/miniconda3/envs/GLAM/lib/python3.6/site-packages/ipykernel_launcher.py:20: FutureWarning: Support for multi-dimensional indexing (e.g. `obj[:, None]`) is deprecated and will be removed in a future version.  Convert to a numpy array before indexing instead.\n",
      "/opt/miniconda3/envs/GLAM/lib/python3.6/site-packages/ipykernel_launcher.py:25: FutureWarning: Support for multi-dimensional indexing (e.g. `obj[:, None]`) is deprecated and will be removed in a future version.  Convert to a numpy array before indexing instead.\n",
      "/opt/miniconda3/envs/GLAM/lib/python3.6/site-packages/ipykernel_launcher.py:30: FutureWarning: Support for multi-dimensional indexing (e.g. `obj[:, None]`) is deprecated and will be removed in a future version.  Convert to a numpy array before indexing instead.\n",
      "/Users/thomas/projects/many-item-choice/utils/descriptives.py:151: FutureWarning: Support for multi-dimensional indexing (e.g. `obj[:, None]`) is deprecated and will be removed in a future version.  Convert to a numpy array before indexing instead.\n",
      "  for s in setsizes], axis=1)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Correlation coefficients:\n",
      "\n",
      "best_chosen ~ best_chosen\n",
      "Spearman r = 0.9999999999999999, p = 0.0\n",
      "\n",
      "best_chosen ~ frac_items_seen\n",
      "Spearman r = -0.15071428571428572, p = 0.3012839002824282\n",
      "\n",
      "best_chosen ~ RT\n",
      "Spearman r = -0.1646938775510204, p = 0.2581230306467912\n",
      "\n",
      "best_chosen ~ last_gaze_to_choice\n",
      "Spearman r = -0.1410204081632653, p = 0.3337936826992217\n",
      "\n",
      "best_chosen ~ gaze_influence\n",
      "Spearman r = -0.36612244897959184, p = 0.009675567275816413\n",
      "\n",
      "frac_items_seen ~ frac_items_seen\n",
      "Spearman r = 0.9999999999999999, p = 0.0\n",
      "\n",
      "frac_items_seen ~ RT\n",
      "Spearman r = 0.9177551020408162, p = 1.7779076759637664e-20\n",
      "\n",
      "frac_items_seen ~ last_gaze_to_choice\n",
      "Spearman r = -0.009591836734693876, p = 0.947846763369648\n",
      "\n",
      "frac_items_seen ~ gaze_influence\n",
      "Spearman r = -0.017755102040816324, p = 0.9036223528652839\n",
      "\n",
      "RT ~ RT\n",
      "Spearman r = 0.9999999999999999, p = 0.0\n",
      "\n",
      "RT ~ last_gaze_to_choice\n",
      "Spearman r = -0.007857142857142856, p = 0.9572690362622425\n",
      "\n",
      "RT ~ gaze_influence\n",
      "Spearman r = 0.033571428571428565, p = 0.8188705514148003\n",
      "\n",
      "last_gaze_to_choice ~ last_gaze_to_choice\n",
      "Spearman r = 0.9999999999999999, p = 0.0\n",
      "\n",
      "last_gaze_to_choice ~ gaze_influence\n",
      "Spearman r = 0.5579591836734693, p = 3.108677800837112e-05\n",
      "\n",
      "gaze_influence ~ gaze_influence\n",
      "Spearman r = 0.9999999999999999, p = 0.0\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1889.76x1181.1 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "np.random.seed(10)\n",
    "\n",
    "fig, _ = figure_4(data, gaze_data)\n",
    "fig.savefig('figures/Figure-4_choice-psychometrics.pdf', dpi=300)\n",
    "fig.savefig('figures/Figure-4_choice-psychometrics.png', dpi=300)\n",
    "fig.savefig('figures/Figure-4_choice-psychometrics.jpg', dpi=300)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Test association of Gaze influence with P(best seen item chosen) and P(last seen item chosen)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/thomas/projects/many-item-choice/utils/descriptives.py:151: FutureWarning: Support for multi-dimensional indexing (e.g. `obj[:, None]`) is deprecated and will be removed in a future version.  Convert to a numpy array before indexing instead.\n",
      "  for s in setsizes], axis=1)\n"
     ]
    }
   ],
   "source": [
    "# 1. P(choose best seen item )\n",
    "sub_best_seen_chosen_means = np.concatenate([\n",
    "    np.array(data.groupby(['setsize','subject']).best_seen_chosen.mean()[s])[:,None]\n",
    "    for s in setsizes], axis=1)\n",
    "    \n",
    "# 2. P(last gaze to choice)\n",
    "(sub_p_last_fix_choice_means,\n",
    " p_last_fix_choice_means,\n",
    " p_last_fix_choice_sems) = compute_p_last_gaze_choice(data, gaze_data)\n",
    "    \n",
    "# 3. Gaze Influence on choice probability\n",
    "sub_gaze_influence_scores = []\n",
    "for setsize in setsizes:\n",
    "    sub_gaze_influence_scores.append(compute_gaze_influence_score(data[data['setsize']==setsize].copy()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "mfx_df = []\n",
    "for si, setsize in enumerate(setsizes):\n",
    "    df_tmp = pd.DataFrame({'subject': subjects,\n",
    "                           'setsize': setsize,\n",
    "                           'best_chosen': sub_best_seen_chosen_means[:,si]*100,\n",
    "                           'last_gaze_to_choice': sub_p_last_fix_choice_means[:,si]*100,\n",
    "                           'gaze_influence': sub_gaze_influence_scores[si]*100})\n",
    "    mfx_df.append(df_tmp)\n",
    "mfx_df = pd.concat(mfx_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "Computing: best_chosen ~ gaze_influence\n",
      "Loading mfx-summary from results/posterior_traces/mixed_effects_models/\n",
      "Intercept[0]; Mean: 89.9042406203782, 94% HPD: 86.4155827482559, 93.11473325187642\n",
      "gaze_influence[0]; Mean: -0.21964009867884773, 94% HPD: -0.35630963944673405, -0.08387558317717361\n",
      "\n",
      "\n",
      "Computing: last_gaze_to_choice ~ gaze_influence\n",
      "Loading mfx-summary from results/posterior_traces/mixed_effects_models/\n",
      "Intercept[0]; Mean: 17.524358102686932, 94% HPD: 9.806543250452508, 24.710549689222173\n",
      "gaze_influence[0]; Mean: 1.0966744293682746, 94% HPD: 0.8743681897553279, 1.3141771092555925\n"
     ]
    }
   ],
   "source": [
    "# estimate mfx models:\n",
    "\n",
    "seed = 4121\n",
    "\n",
    "for x, y in zip(['gaze_influence', 'gaze_influence'],\n",
    "                ['best_chosen', 'last_gaze_to_choice']):\n",
    "    \n",
    "    print('\\n\\nComputing: {} ~ {}'.format(y, x))\n",
    "    \n",
    "    mfx_filename = '{}_{}_mfx'.format('-'.join(y.split('_')), '-'.join(x.split('_')))\n",
    "    if not os.path.isfile(mfx_dir+mfx_filename+'.csv'):\n",
    "            \n",
    "        # make model\n",
    "        samples = 2000\n",
    "        burn = 500\n",
    "        model = bambi.Model(data=mfx_df)\n",
    "        model.add('{} ~ {}'.format(y, x),\n",
    "                  random=['1|setsize','0+{}|setsize'.format(x)],\n",
    "                  categorical=['setsize'])\n",
    "\n",
    "        # sample posterior\n",
    "        results = model.fit(samples=samples,\n",
    "                            tune=burn,\n",
    "                            chains=2,\n",
    "                            backend='pymc',\n",
    "                            init='ADVI',\n",
    "                            n_init=50000,\n",
    "                            random_seed=seed)\n",
    "\n",
    "        # save results\n",
    "        pm.trace_to_dataframe(model.backend.trace).to_csv(\n",
    "            mfx_dir+mfx_filename+'_mtrace.csv', index=False)\n",
    "        az.plot_trace(results)\n",
    "        plt.savefig(mfx_dir+mfx_filename+'.png', dpi=220)\n",
    "        summary = az.summary(results, round_to='none')\n",
    "        summary.to_csv(mfx_dir+mfx_filename+'.csv')\n",
    "\n",
    "    else:\n",
    "        print('Loading mfx-summary from '+mfx_dir)\n",
    "        summary = pd.read_csv(mfx_dir+mfx_filename+'.csv', index_col='Unnamed: 0')\n",
    "\n",
    "    _ = get_var(summary, 'Intercept[0]')\n",
    "    _ = get_var(summary, '{}[0]'.format(x))\n",
    "    \n",
    "    seed += 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Figure 4-figure supplement 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "def _scatter(x, y, ax, color, label=None):\n",
    "    ax.scatter(x, y, marker='o', color='none', edgecolor=color, \n",
    "               linewidth=0.75, alpha=1, s=20)\n",
    "    ax.scatter(x, y, marker='o', color=color, alpha=0.2,\n",
    "               linewidth=0, s=20, label=label)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "def _annotation(i,j,corr_mat):\n",
    "    rval, pval = corr_mat[i,j,:]\n",
    "    if pval < 0.0001:\n",
    "        p_string = r'$P < 0.0001$'\n",
    "    else:\n",
    "        p_string = r'$P = {}$'.format(np.round(pval, 4))\n",
    "    annotation = (r'$\\rho(48)$'+r'$ = {:.2f}$, '.format(rval)) + p_string\n",
    "    return annotation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "def figure_4_figure_supplement_1(data, gaze_data, colors=['darkturquoise', 'orange', 'mediumseagreen', 'lightcoral'], \n",
    "              fontsize=8, dpi=300):\n",
    "    \"\"\"Create SI Figure 4 of the manuscript.\n",
    "    \n",
    "    Args:\n",
    "        data (dataframe): choice data   \n",
    "        gaze_data (dataframe): gaze data\n",
    "        colors (array of strings): colors to use for set sizes\n",
    "        fontsize (int): fontisze for labeling \n",
    "        dpi (int): dpi of figure\n",
    "                \n",
    "    Returns:\n",
    "        matplotlib figure / axis\n",
    "    \"\"\"\n",
    "    \n",
    "    # COMPUTE SUBJECT MEANS:\n",
    "    n_subjects = data.subject.unique().size\n",
    "    \n",
    "    # 1. Seen items count vs set-size\n",
    "    data['frac_items_seen'] = (data['seen_items_count'] / data['setsize']).values.astype(np.float)\n",
    "    sub_frac_items_seen = np.concatenate(\n",
    "        [data.groupby(['setsize', 'subject']).frac_items_seen.mean()[s][:,None]\n",
    "         for s in setsizes], axis=1)\n",
    "    \n",
    "    # 2. Response time vs set-size\n",
    "    sub_rt_means = np.concatenate(\n",
    "        [data.groupby(['setsize', 'subject']).rt_s.mean()[s][:,None]\n",
    "         for s in setsizes], axis=1)\n",
    "    # 3. P(choose best seen item )\n",
    "    sub_best_seen_chosen_means = np.concatenate(\n",
    "        [data.groupby(['setsize','subject']).best_seen_chosen.mean()[s][:,None]\n",
    "         for s in setsizes], axis=1)\n",
    "    \n",
    "    # 4. P(last gaze to choice)\n",
    "    (sub_p_last_fix_choice_means,\n",
    "     p_last_fix_choice_means,\n",
    "     p_last_fix_choice_sems) = compute_p_last_gaze_choice(data, gaze_data)\n",
    "    \n",
    "    # 5. Gaze Influence on choice probability\n",
    "    sub_gaze_influence_scores = []\n",
    "    for setsize in setsizes:\n",
    "        sub_gaze_influence_scores.append(\n",
    "            compute_gaze_influence_score(data[data['setsize']==setsize].copy())[:,None])\n",
    "    sub_gaze_influence_scores = np.concatenate(sub_gaze_influence_scores, axis=1)\n",
    "    \n",
    "    # compute correlation matrix\n",
    "    corr_mat = compute_assocoiations_figure_4F(data, gaze_data, setsizes=np.array([9,16,25,36]))\n",
    "    \n",
    "    # PLOT: \n",
    "    fig, axs = plt.subplots(4,4,figsize=cm2inch(20,20), dpi=dpi)\n",
    "        \n",
    "    axs[0,0].set_xlim(-0.05,1.05)\n",
    "    axs[0,0].set_ylim(-0.05,1.05)\n",
    "    axs[0,0].set_xlabel('P(best seen item chosen)', fontsize=fontsize)\n",
    "    axs[0,0].set_ylabel('% items seen', fontsize=fontsize)\n",
    "    _scatter(sub_best_seen_chosen_means.mean(axis=1), sub_frac_items_seen.mean(axis=1), \n",
    "             ax=axs[0,0], color='gray')\n",
    "    annotation = _annotation(1,0,corr_mat)\n",
    "    axs[0,0].set_title(annotation, fontsize=6)\n",
    "        \n",
    "    axs[1,0].set_xlim(-0.05,1.05)\n",
    "    axs[1,0].set_ylim(0,15)\n",
    "    axs[1,0].set_xlabel('P(best seen item chosen)', fontsize=fontsize)\n",
    "    axs[1,0].set_ylabel('Mean RT (s)', fontsize=fontsize)\n",
    "    _scatter(sub_best_seen_chosen_means.mean(axis=1), sub_rt_means.mean(axis=1),\n",
    "            ax=axs[1,0], color='gray')\n",
    "    annotation = _annotation(2,0,corr_mat)\n",
    "    axs[1,0].set_title(annotation, fontsize=6)\n",
    "        \n",
    "    axs[2,0].set_xlim(-0.05,1.05)\n",
    "    axs[2,0].set_ylim(-0.05,1.05)\n",
    "    axs[2,0].set_xlabel('P(best seen item chosen)', fontsize=fontsize)\n",
    "    axs[2,0].set_ylabel('P(last seen item chosen)', fontsize=fontsize)\n",
    "    _scatter(sub_best_seen_chosen_means.mean(axis=1), sub_p_last_fix_choice_means.mean(axis=1),\n",
    "            ax=axs[2,0], color='gray')\n",
    "    annotation = _annotation(3,0,corr_mat)\n",
    "    axs[2,0].set_title(annotation, fontsize=6)\n",
    "        \n",
    "    axs[3,0].set_xlim(-0.05,1.05)\n",
    "    axs[3,0].set_ylim(-0.05,1.05)\n",
    "    axs[3,0].set_xlabel('P(best seen item chosen)', fontsize=fontsize)\n",
    "    axs[3,0].set_ylabel('Gaze influence\\non P(choose item)', fontsize=fontsize)\n",
    "    _scatter(sub_best_seen_chosen_means.mean(axis=1), sub_gaze_influence_scores.mean(axis=1),\n",
    "            ax=axs[3,0], color='gray')\n",
    "    annotation = _annotation(4,0,corr_mat)\n",
    "    axs[3,0].set_title(annotation, fontsize=6) \n",
    "            \n",
    "    axs[1,1].set_xlim(-0.05,1.05)\n",
    "    axs[1,1].set_ylim(0,15)\n",
    "    axs[1,1].set_xlabel('% items seen', fontsize=fontsize)\n",
    "    axs[1,1].set_ylabel('Mean RT (s)', fontsize=fontsize)\n",
    "    _scatter(sub_frac_items_seen.mean(axis=1), sub_rt_means.mean(axis=1),\n",
    "             ax=axs[1,1], color='gray')\n",
    "    annotation = _annotation(2,1,corr_mat)\n",
    "    axs[1,1].set_title(annotation, fontsize=6)\n",
    "        \n",
    "    axs[2,1].set_xlim(-0.05,1.05)\n",
    "    axs[2,1].set_ylim(-0.05,1.05)\n",
    "    axs[2,1].set_xlabel('% items seen', fontsize=fontsize)\n",
    "    axs[2,1].set_ylabel('P(last seen item chosen)', fontsize=fontsize)\n",
    "    _scatter(sub_frac_items_seen.mean(axis=1), sub_p_last_fix_choice_means.mean(axis=1),\n",
    "             ax=axs[2,1], color='gray')\n",
    "    annotation = _annotation(3,1,corr_mat)\n",
    "    axs[2,1].set_title(annotation, fontsize=6)\n",
    "        \n",
    "    axs[3,1].set_xlim(-0.05,1.05)\n",
    "    axs[3,1].set_ylim(-0.05,1.05)\n",
    "    axs[3,1].set_xlabel('% items seen', fontsize=fontsize)\n",
    "    axs[3,1].set_ylabel('Gaze influence\\non P(choose item)', fontsize=fontsize)\n",
    "    _scatter(sub_frac_items_seen.mean(axis=1), sub_gaze_influence_scores.mean(axis=1),\n",
    "             ax=axs[3,1], color='gray')\n",
    "    annotation = _annotation(4,1,corr_mat)\n",
    "    axs[3,1].set_title(annotation, fontsize=6)\n",
    "        \n",
    "    axs[2,2].set_xlim(0,15)\n",
    "    axs[2,2].set_ylim(-0.05,1.05)\n",
    "    axs[2,2].set_xlabel('Mean RT (s)', fontsize=fontsize)\n",
    "    axs[2,2].set_ylabel('P(last seen item chosen)', fontsize=fontsize)\n",
    "    _scatter(sub_rt_means.mean(axis=1), sub_p_last_fix_choice_means.mean(axis=1),\n",
    "             ax=axs[2,2], color='gray')\n",
    "    annotation = _annotation(3,2,corr_mat)\n",
    "    axs[2,2].set_title(annotation, fontsize=6)\n",
    "        \n",
    "    axs[3,2].set_xlim(0, 15)\n",
    "    axs[3,2].set_ylim(-0.05,1.05)\n",
    "    axs[3,2].set_xlabel('Mean RT (s)', fontsize=fontsize)\n",
    "    axs[3,2].set_ylabel('Gaze influence\\non P(choose item)', fontsize=fontsize)\n",
    "    _scatter(sub_rt_means.mean(axis=1), sub_gaze_influence_scores.mean(axis=1),\n",
    "             ax=axs[3,2], color='gray')\n",
    "    annotation = _annotation(4,2,corr_mat)\n",
    "    axs[3,2].set_title(annotation, fontsize=6)\n",
    "        \n",
    "    axs[3,3].set_xlim(-0.05,1.05)\n",
    "    axs[3,3].set_ylim(-0.05,1.05)\n",
    "    axs[3,3].set_xlabel('P(last seen item chosen)', fontsize=fontsize)\n",
    "    axs[3,3].set_ylabel('Gaze influence\\non P(choose item)', fontsize=fontsize)\n",
    "    _scatter(sub_p_last_fix_choice_means.mean(axis=1), sub_gaze_influence_scores.mean(axis=1),\n",
    "             ax=axs[3,3], color='gray')\n",
    "    annotation = _annotation(4,3,corr_mat)\n",
    "    axs[3,3].set_title(annotation, fontsize=6) \n",
    "        \n",
    "    # despine\n",
    "    for label, ax in zip(list('A   BC  DEF GHIJ'), axs.ravel()):\n",
    "        ax.text(-0.25, 1.25, label, transform=ax.transAxes,\n",
    "            fontsize=10, fontweight='bold', va='top')\n",
    "        despine(ax=ax)\n",
    "        ax.tick_params(axis='both', which='major', labelsize=8)\n",
    "        \n",
    "    # remove unused axes\n",
    "    axs[0,1].set_visible(False)\n",
    "    axs[0,2].set_visible(False)\n",
    "    axs[1,2].set_visible(False)\n",
    "    axs[0,3].set_visible(False)\n",
    "    axs[1,3].set_visible(False)\n",
    "    axs[2,3].set_visible(False)\n",
    "    \n",
    "    fig.tight_layout()\n",
    "    return fig, axs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/miniconda3/envs/GLAM/lib/python3.6/site-packages/ipykernel_launcher.py:23: FutureWarning: Support for multi-dimensional indexing (e.g. `obj[:, None]`) is deprecated and will be removed in a future version.  Convert to a numpy array before indexing instead.\n",
      "/opt/miniconda3/envs/GLAM/lib/python3.6/site-packages/ipykernel_launcher.py:28: FutureWarning: Support for multi-dimensional indexing (e.g. `obj[:, None]`) is deprecated and will be removed in a future version.  Convert to a numpy array before indexing instead.\n",
      "/opt/miniconda3/envs/GLAM/lib/python3.6/site-packages/ipykernel_launcher.py:32: FutureWarning: Support for multi-dimensional indexing (e.g. `obj[:, None]`) is deprecated and will be removed in a future version.  Convert to a numpy array before indexing instead.\n",
      "/Users/thomas/projects/many-item-choice/utils/descriptives.py:151: FutureWarning: Support for multi-dimensional indexing (e.g. `obj[:, None]`) is deprecated and will be removed in a future version.  Convert to a numpy array before indexing instead.\n",
      "  for s in setsizes], axis=1)\n",
      "/opt/miniconda3/envs/GLAM/lib/python3.6/site-packages/ipykernel_launcher.py:20: FutureWarning: Support for multi-dimensional indexing (e.g. `obj[:, None]`) is deprecated and will be removed in a future version.  Convert to a numpy array before indexing instead.\n",
      "/opt/miniconda3/envs/GLAM/lib/python3.6/site-packages/ipykernel_launcher.py:25: FutureWarning: Support for multi-dimensional indexing (e.g. `obj[:, None]`) is deprecated and will be removed in a future version.  Convert to a numpy array before indexing instead.\n",
      "/opt/miniconda3/envs/GLAM/lib/python3.6/site-packages/ipykernel_launcher.py:30: FutureWarning: Support for multi-dimensional indexing (e.g. `obj[:, None]`) is deprecated and will be removed in a future version.  Convert to a numpy array before indexing instead.\n",
      "/Users/thomas/projects/many-item-choice/utils/descriptives.py:151: FutureWarning: Support for multi-dimensional indexing (e.g. `obj[:, None]`) is deprecated and will be removed in a future version.  Convert to a numpy array before indexing instead.\n",
      "  for s in setsizes], axis=1)\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 2362.2x2362.2 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "np.random.seed(11)\n",
    "\n",
    "fig, _ = figure_4_figure_supplement_1(data, gaze_data)\n",
    "fig.savefig('figures/Figure-4-figure-supplement-1_choice-psychometrics-associations.pdf', dpi=300)\n",
    "fig.savefig('figures/Figure-4-figure-supplement-1_choice-psychometrics-associations.png', dpi=300)\n",
    "fig.savefig('figures/Figure-4-figure-supplement-1_choice-psychometrics-associations.jpg', dpi=300)"
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "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": "3.6.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}