{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import modules\n",
    "import papa_utils as pu\n",
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# read configuration file\n",
    "config = pu.read_config('settings.toml')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# sort PAPA, DR, and other trajectories\n",
    "pu.sort_PAPA_DR(config)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# do state array analysis on all trajectories\n",
    "[SA,posterior_occs,condition_names] = pu.analyze_PAPA_DR_stateArray(config,nworkers=6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# analyze the same number of subsampled trajectories from each sorted category of each condition\n",
    "[SA_sameN,posterior_occs_sameN,condition_names_sameN] = pu.analyze_PAPA_DR_stateArray_sameN(config,nworkers=6,randseed=1234)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# plot number of localizations over the whole movie\n",
    "pu.plot_Nlocs_wholemovie(config)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# plot number of localizations averaged over a violet/green cycle\n",
    "pu.plot_Nlocs_bycycle(config)"
   ]
  }
 ],
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