eval.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import jax.numpy as jnp\n",
    "import glob\n",
    "import data_loading\n",
    "import eval\n",
    "import partitioning\n",
    "import impact\n",
    "import math\n",
    "from functools import partial\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import scipy.stats as st\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
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'/data1/sascha/data/data/GOOG/raw/GOOG_2022-05-10_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-05-11_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-05-12_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-05-13_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-05-16_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-05-17_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-05-18_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-05-19_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-05-20_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-05-23_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-05-24_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-05-25_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-05-26_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-05-27_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-05-31_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-06-01_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-06-02_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-06-03_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-06-06_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-06-07_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-06-08_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-06-09_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-06-10_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-06-13_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-06-14_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-06-16_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-06-17_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-06-21_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-06-22_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-06-23_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-06-24_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-06-27_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-06-28_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-06-29_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-06-30_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-07-01_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-07-05_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-07-06_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-07-07_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-07-11_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-07-12_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-07-13_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-07-14_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-07-15_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-07-18_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-07-19_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-07-20_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-07-21_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-07-22_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-07-25_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-07-26_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-07-27_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-07-28_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-07-29_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-08-01_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-08-02_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-08-03_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-08-04_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-08-05_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-08-08_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-08-09_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-08-10_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-08-11_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-08-12_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-08-15_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-08-16_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-08-17_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-08-18_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-08-19_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-08-22_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-08-23_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-08-24_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-08-25_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-08-26_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-08-29_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-08-30_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-08-31_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-09-01_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-09-02_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-09-06_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-09-07_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-09-08_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-09-09_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-09-12_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-09-13_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-09-14_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-09-15_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-09-16_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-09-19_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-09-20_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-09-21_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-09-22_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-09-23_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-09-26_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-09-27_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-09-28_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-09-29_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-09-30_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-10-03_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-10-04_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-10-05_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-10-06_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-10-07_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-10-10_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-10-11_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-10-12_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-10-13_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-10-14_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-10-17_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-10-18_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-10-19_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-10-20_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-10-21_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-10-24_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-10-25_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-10-26_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-10-27_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-10-28_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-10-31_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-11-01_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-11-02_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-11-03_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-11-04_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-11-07_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-11-08_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-11-09_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-11-10_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-11-11_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-11-14_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-11-15_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-11-16_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-11-17_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-11-18_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-11-21_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-11-22_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-11-23_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-11-25_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-11-28_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-11-29_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-11-30_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-12-01_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-12-02_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-12-05_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-12-06_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-12-07_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-12-08_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-12-09_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-12-12_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-12-13_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-12-14_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-12-15_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-12-16_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-12-19_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-12-20_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-12-21_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-12-22_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-12-23_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-12-27_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-12-28_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-12-29_34200000_57600000_orderbook_10.csv', '/data1/sascha/data/data/GOOG/raw/GOOG_2022-12-30_34200000_57600000_orderbook_10.csv']\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "249"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# load sample lobster data\n",
    "#message_paths = sorted(glob.glob('/data1/sascha/data/raw/CSCO*message*.csv'))\n",
    "#book_paths = sorted(glob.glob('/data1/sascha/data/raw/CSCO*orderbook*.csv'))\n",
    "message_paths = sorted(glob.glob('/data1/sascha/data/data/GOOG/raw/GOOG*message*.csv'))\n",
    "book_paths = sorted(glob.glob('/data1/sascha/data/data/GOOG/raw/GOOG*orderbook*.csv'))\n",
    "# message_paths = glob.glob('/homes/80/kang/AlphaTrade/testing_oneDay/data/*message*.csv')\n",
    "# book_paths = glob.glob('/homes/80/kang/AlphaTrade/testing_oneDay/data/*orderbook*.csv')\n",
    "print(sorted(message_paths))\n",
    "print(sorted(book_paths))\n",
    "\n",
    "len(book_paths)\n",
    "# "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "m_seqs = [data_loading.load_message_df(path) for path in message_paths]\n",
    "b_seqs = [data_loading.load_book_df(path) for path in book_paths]\n",
    "\n",
    "# DATA FORMAT:\n",
    "\n",
    "# (base) peer@Peers-MacBook-Pro lob_bench % ls -l data_test_cond \n",
    "# total 78472\n",
    "# -rw-rw-rw-  1 peer  staff   6094817 Apr 10 14:13 GOOG_2012-06-21_34200000_57600000_message_real_id_0_10.csv\n",
    "# -rw-rw-rw-  1 peer  staff  34073243 Apr 10 14:13 GOOG_2012-06-21_34200000_57600000_orderbook_real_id_0_10.csv\n",
    "# (base) peer@Peers-MacBook-Pro lob_bench % ls -l data_test_gen \n",
    "# total 156912\n",
    "# -rw-rw-rw-  1 peer  staff   6094817 Apr  4 18:06 GOOG_2012-06-21_34200000_57600000_message_real_id_0_gen_id_0_10.csv\n",
    "# -rw-rw-rw-  1 peer  staff   6094817 Apr  4 18:07 GOOG_2012-06-21_34200000_57600000_message_real_id_0_gen_id_1_10.csv\n",
    "# -rw-rw-rw-  1 peer  staff  34073243 Apr  4 18:06 GOOG_2012-06-21_34200000_57600000_orderbook_real_id_0_gen_id_0_10.csv\n",
    "# -rw-rw-rw-  1 peer  staff  34073243 Apr  4 18:07 GOOG_2012-06-21_34200000_57600000_orderbook_real_id_0_gen_id_1_10.csv\n",
    "# (base) peer@Peers-MacBook-Pro lob_bench % ls -l data_test_real \n",
    "# total 78472\n",
    "# -rw-rw-rw-  1 peer  staff   6094817 Apr  4 18:04 GOOG_2012-06-21_34200000_57600000_message_real_id_0_10.csv\n",
    "# -rw-rw-rw-  1 peer  staff  34073243 Apr  4 18:04 GOOG_2012-06-21_34200000_57600000_orderbook_real_id_0_10.csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "mb_seqs=[impact.filter_touch_events(m,b) for m,b in zip(m_seqs,b_seqs)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Concat Done\n",
      "Time split & Calc done\n"
     ]
    }
   ],
   "source": [
    "res=impact.macro_impact_analyse(3*60,100,32,m_seqs,b_seqs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'P_i')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = plt.gca()\n",
    "ax.plot(res[1][:],res[0][:], 'o', c='blue', alpha=0.5, markeredgecolor='none')\n",
    "ax.set_title(\"GOOG Real Long Form\")\n",
    "ax.set_ylabel(\"M_i\")\n",
    "ax.set_xlabel(\"P_i\")\n",
    "#ax.set_ylim([-2,2])\n",
    "#ax.set_yscale('log')\n",
    "#ax.set_xscale('log')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[15.374613003095975,\n",
       " -13.787617554858935,\n",
       " 6.9309153713298794,\n",
       " 19.697811447811446,\n",
       " 5.7817589576547235,\n",
       " 32.77603305785124,\n",
       " -11.471544715447154,\n",
       " 31.342056074766354,\n",
       " -13.509041591320072,\n",
       " -7.895238095238096,\n",
       " 11.487279843444227,\n",
       " 4.079055441478439,\n",
       " -3.97741273100616,\n",
       " 6.631868131868132,\n",
       " -30.32800982800983,\n",
       " -18.125964010282775,\n",
       " -38.3753280839895,\n",
       " -11.589887640449438,\n",
       " -41.1038338658147,\n",
       " -16.49685534591195,\n",
       " -8.455516014234876,\n",
       " -40.45454545454545,\n",
       " -79.64047619047619,\n",
       " -52.37671232876713,\n",
       " -33.575675675675676,\n",
       " -32.08967391304348,\n",
       " -27.23701298701299,\n",
       " -40.151785714285715,\n",
       " -30.48739495798319,\n",
       " -28.828358208955223,\n",
       " -45.016260162601625,\n",
       " -4.800925925925926]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res[0][:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "root_path=\"/data1/sascha/data/sqrt/GOOG/\"\n",
    "\n",
    "loader = data_loading.Simple_Loader(\n",
    "            real_data_path= root_path+\"data_real\",\n",
    "            gen_data_path= root_path+\"data_gen\",\n",
    "            cond_data_path=root_path+\"data_cond\",\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([-0.08296943231441048,\n",
       "  0.29411764705882354,\n",
       "  -0.32954545454545453,\n",
       "  0.01,\n",
       "  0.03389830508474576,\n",
       "  0.2962962962962963,\n",
       "  -0.5258620689655172,\n",
       "  -0.5849056603773585,\n",
       "  -0.1,\n",
       "  -0.08035714285714286,\n",
       "  0.3384615384615385,\n",
       "  -0.40350877192982454,\n",
       "  -0.65625,\n",
       "  -0.2672413793103448,\n",
       "  -0.010869565217391304,\n",
       "  -0.6619718309859155,\n",
       "  0.5784313725490197,\n",
       "  -0.6120689655172413,\n",
       "  0.06363636363636363,\n",
       "  -0.07,\n",
       "  0.031914893617021274,\n",
       "  0.3191489361702128,\n",
       "  -1.1097560975609757,\n",
       "  0.603448275862069,\n",
       "  -0.21428571428571427,\n",
       "  -0.19642857142857142,\n",
       "  0.12962962962962962,\n",
       "  0.08771929824561403,\n",
       "  -0.38461538461538464,\n",
       "  0.16666666666666666,\n",
       "  -0.33088235294117646,\n",
       "  0.276036866359447],\n",
       " [0.003217272129271781,\n",
       "  0.04659515106296707,\n",
       "  0.07964149844981017,\n",
       "  0.10888090202378978,\n",
       "  0.1405581454662132,\n",
       "  0.1722173421513684,\n",
       "  0.20293387195592116,\n",
       "  0.23267178976524452,\n",
       "  0.2669631168099657,\n",
       "  0.29837095987249324,\n",
       "  0.3304763448509834,\n",
       "  0.35938023028741095,\n",
       "  0.389459460322405,\n",
       "  0.42369728191307593,\n",
       "  0.4525365792563309,\n",
       "  0.4884182530048692,\n",
       "  0.5158445054718253,\n",
       "  0.5480399350024152,\n",
       "  0.5768412313953936,\n",
       "  0.6081262669829821,\n",
       "  0.6404739911682995,\n",
       "  0.6722156052933137,\n",
       "  0.7043556104253192,\n",
       "  0.7355322860298463,\n",
       "  0.7684175907448952,\n",
       "  0.795275015278725,\n",
       "  0.8287456568733864,\n",
       "  0.8587353075615993,\n",
       "  0.8906251470997937,\n",
       "  0.9225849309872408,\n",
       "  0.9545837618908074,\n",
       "  0.9986872044624675],\n",
       " [-19.679061135371178,\n",
       "  -0.3137254901960784,\n",
       "  -0.3068181818181818,\n",
       "  0.26,\n",
       "  -0.03389830508474576,\n",
       "  0.06481481481481481,\n",
       "  -0.39655172413793105,\n",
       "  -0.2169811320754717,\n",
       "  0.625,\n",
       "  -0.42857142857142855,\n",
       "  -0.23846153846153847,\n",
       "  0.20175438596491227,\n",
       "  -0.46875,\n",
       "  -0.5689655172413793,\n",
       "  -0.4891304347826087,\n",
       "  -0.4859154929577465,\n",
       "  0.3333333333333333,\n",
       "  0.1810344827586207,\n",
       "  -0.5,\n",
       "  -0.16,\n",
       "  0.1276595744680851,\n",
       "  -0.22340425531914893,\n",
       "  0.10975609756097561,\n",
       "  -0.02586206896551724,\n",
       "  -0.33035714285714285,\n",
       "  0.008928571428571428,\n",
       "  -0.7685185185185185,\n",
       "  -0.2982456140350877,\n",
       "  0.009615384615384616,\n",
       "  -0.42592592592592593,\n",
       "  -0.47794117647058826,\n",
       "  -8.329963133640554],\n",
       " [0.660916494816065,\n",
       "  0.615509942301896,\n",
       "  0.5585648603021138,\n",
       "  0.6257998765062338,\n",
       "  0.6246078339095908,\n",
       "  0.5817628422059843,\n",
       "  0.6148585577998698,\n",
       "  0.5463090845442606,\n",
       "  0.6120597703741081,\n",
       "  0.6096037862776129,\n",
       "  0.5960940292847342,\n",
       "  0.5644074844339417,\n",
       "  0.6220484424399143,\n",
       "  0.5819502240060557,\n",
       "  0.6263600986633349,\n",
       "  0.5683652507463778,\n",
       "  0.5962452551312153,\n",
       "  0.5741241360024785,\n",
       "  0.5997328964815912,\n",
       "  0.5926503816555084,\n",
       "  0.6924053532363178,\n",
       "  0.5558974658380379,\n",
       "  0.5386084715310491,\n",
       "  0.6425211964077844,\n",
       "  0.6157170573086904,\n",
       "  0.6275747396717897,\n",
       "  0.6515197452647044,\n",
       "  0.6295510240440466,\n",
       "  0.5984154233530068,\n",
       "  0.5634851051986948,\n",
       "  0.6583994627233827,\n",
       "  0.6117823895135778])"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df=impact.macro_impact_compare(100000,100,32,loader)\n",
    "df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.1046739686609951"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ar=np.load('/data1/sascha/comparison_graphINTC_done2.npy',allow_pickle=False)\n",
    "np.mean(ar/21)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "21\n"
     ]
    }
   ],
   "source": [
    "ar=np.load('/data1/sascha/x_vals_GOOG_done2.npy',allow_pickle=False)\n",
    "print(len(ar))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-1.0, 1.0)"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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XKy4uTrGxsRo5cqR2797tfO3gwYPKy8tzOWZYWJgSExNrPGZJSYkcDofLA96FDzD34P6N9cdIIOAbvGZ5h1OnTqm0tNRlREqSIiMjtXfv3ir36d69u1atWqXevXurqKhITz31lAYNGqTdu3erY8eOysvLcx7j8mNWvFaV9PR0LVq0qIEVwVNycyuPsnz0UflioQkJnuqVb+L+jfVzpZHAuDjWVjPp7NnyPwLOni3/ObOWHRrCa0a06iMpKUkTJkxQQkKCbr75Zq1bt07t27fXCy+80KDjzp8/X0VFRc7H0aNHG6nHMI1TWe7F/Rvrh5FAz2EkEY3Na4JWu3btFBgYqPz8fJft+fn5ioqKqtUxmjdvrr59++rAgQOS5Nyvrse02+0KDQ11ecA78AHmXty/8f/U5XQ1I4GewR9iMMFrglZQUJD69++vzMxM57aysjJlZmYqKSmpVscoLS3VF198oejoaElSly5dFBUV5XJMh8OhHTt21PqY8C58gLkX928sV9dREkYCPYM/xGCC18zRkqS0tDRNnDhRAwYM0MCBA7V06VKdO3dOkydPliRNmDBBHTp0UHp6uiRp8eLFuvHGG9WtWzcVFhbqySef1OHDh3XnnXdKKr8icdasWXr44Yd1zTXXqEuXLlqwYIFiYmI0atQoT5UJg/gAcz9/v39jfeZb9etXPm+wqg99fxsJdCf+EIMJXhW0xowZo5MnT2rhwoXKy8tTQkKCNm/e7JzMfuTIEQX84E/ns2fPaurUqcrLy1ObNm3Uv39/ffzxx4qPj3e2mTNnjs6dO6dp06apsLBQgwcP1ubNmystbArfwAeYZ/jz/RtrM0py+c+mYiTw8oDmbyOB7sYfYjDBZlmW5elOeDuHw6GwsDAVFRUxX8sLVHXVYcUHWJ8+HusWfNSbb5afLqxOr17S6NFVv1Zx9Zs/jgR6wtmz5ad0q/tD7J57+Pn7Gnd8fnvViBbQGPz9VBbcqyGjJP48EugJjCTCBIIW/BIfYHAXTld7F/4QQ2MjaAGAQYySeB/+EENjImjBa7F6M6rT1H43GCUB/BeT4RsBk+Hdr7oJ7dxGB/xuAKgtd3x+e82CpUAFVm9GdfjdANDUELTgdVi9GdXhdwNAU0PQgtdh9WZUh98NAE0Nk+HhdVi9GdVprN+NpjaZHoD3ImjB67AuEarTGL8bVU2m/+gjJtMDqB9OHcLrVKxLFHDZby/rEqGhvxtMpgfQ2BjRgldiXSJUpyG/G/W5ATQA1ISgBa/F6s2oTn1/N5hMD6CxceoQAP4XF1oAaGwELQD4X/36VZ7fVYELLQDUB0ELAP4XF1oAaGzM0QKAH+BCCwCNiaAFAJfhQgsAjYVThwAAAIYQtAAAAAzh1CGAeuF+gABwZQQtAHXmL/cDJEwCaCiCFoA6udL9AOPifCOM+EuYBGAWc7QA1Elt7gfo7bi5NIDGQtACUCf+cD/AijD53XfS119L//lP+dfvvvOdMAnAPTh1CI9jHox38Yf7AZ49K+XlSfv2SZb1f9uPHpW6d/eNMAnAPQha8CjmwXiffv3K/42qOn3oK/cDbNascsiSyp/v2yelpnqmXwC8D6cO4THMg/FO3A+waTl7VsrMlN58s/wr/98ATQsjWvCY2kyq5jYoTZOv3w/w0qXyU4SXj2rZbOXbS0s917cfYkQYaPoIWvAYf5hU7ct8+X6AbdpIUVFSWJh04oT0/fdScLAUHS2FhDSNeWj+sswG4O04dQiP8YdJ1fBO/fqVnwoNCZG6dpXi48u/hoQ0nXlo/rDMBuALCFrwmIoPs6o0lQ8z+CdvmIfGiDDgHTh1CI+p+DC7/PRHU/owg/9q6vPQGBEGvANBCx7V1D/M4N+a8jw0f1hmA/AFBC14XFP+MAM8oTaL+DIiDHgHr5ujtXz5cnXu3FnBwcFKTExUdnZ2tW1feukl/ehHP1KbNm3Upk0bJScnV2o/adIk2Ww2l0cqqxEC8JDcXOnZZ6UPPpB27Sr/+uyz5dsvl5Ag3XOP9KMfSb16lX+95x6pTx83dxpAtbwqaL3++utKS0vTQw89pJ07d6pPnz5KSUlRQUFBle23b9+uX/3qV3rvvfeUlZWl2NhYDRs2TMePH3dpl5qaqhMnTjgfr732mjvKAQAX9VnEt2JEePTo8q+MZAFNi82yLr/JRNOVmJioG264Qc8995wkqaysTLGxsbrnnns0b968K+5fWlqqNm3a6LnnntOECRMklY9oFRYWasOGDfXul8PhUFhYmIqKihQaGlrv4wDwb5mZ5SNY1fnRjzjNDjQmd3x+e82I1oULF5STk6Pk5GTntoCAACUnJysrK6tWxzh//rwuXryotm3bumzfvn27IiIi1L17d02fPl2nT59u1L4DvohbvzQ+lmwAfI/XTIY/deqUSktLFRkZ6bI9MjJSe/furdUx5s6dq5iYGJewlpqaqp/97Gfq0qWLvvrqK/3mN7/RLbfcoqysLAUGBlZ5nJKSEpWUlDifOxyOelQEeC9u/WIGSzYAvsdrglZDPfbYY1q7dq22b9+u4OBg5/axY8c6/7tXr17q3bu3rr76am3fvl1DqxmjT09P16JFi4z32VfU5goqeA9u/WIOSzYAvsdrTh22a9dOgYGBys/Pd9men5+vqKioGvd96qmn9Nhjj2nr1q3q3bt3jW27du2qdu3a6cCBA9W2mT9/voqKipyPo0eP1r4QP1OXK6jgHbj1iznesCI9gLrxmhGtoKAg9e/fX5mZmRo1apSk8snwmZmZmjlzZrX7PfHEE3rkkUe0ZcsWDRgw4Irf59ixYzp9+rSio6OrbWO322W32+tcQ1PhrhEmRj58E/OIzGIRX8C3eE3QkqS0tDRNnDhRAwYM0MCBA7V06VKdO3dOkydPliRNmDBBHTp0UHp6uiTp8ccf18KFC7VmzRp17txZeXl5kqRWrVqpVatWKi4u1qJFizR69GhFRUXpq6++0pw5c9StWzelpKR4rE6T3Dm3pjYjH1xB5X2YR2Qei/gCvsOrgtaYMWN08uRJLVy4UHl5eUpISNDmzZudE+SPHDmigB+MuT///PO6cOGCfv7zn7sc56GHHtLvf/97BQYG6vPPP9fLL7+swsJCxcTEaNiwYVqyZIlXj1hVx90jTO4c+WAemPswjwgAas+r1tFqqrxlHS13r9Hjru9X1ShdQABXwJlU3c985EhWJQfgPdzx+e1VI1poGHfPrXHHyAfzwDyDeUQAUDsELT/i7rk17rjpLfPAPId5RABwZQQtP+KJuTWmRz48dQUcc8IAALVB0PIj7hhhqu77mhr58MQVcKyKDgCoLYKWn/G1uTXuHqVjThgAoC4IWn7Il+bWuHuUjjlhAIC6IGjB67lzlM4fVkVn/hkANB6CFnyCu0bpfH1VdOafAUDj8pqbSgNNQb9+lW/4W8HbV0W/0vyzK43mAQAqI2gBdVAxJ+zysGX6yk13qM38MwBA3XDqEKgjX7tys4I/zD8DAHcjaAH14EtXblbw9flnAOAJBC0Akjxz5wAAqIkvXAVN0AIgyXN3DgCAqvjKVdAELQBOvjr/DIB38aW7cBC0mihfGC6Fd/LF+WcAvIsv3YWDoNUE+cpwKQAA9eFLV0GzjlYTw6KRAAB/50tXQRO0mhgWjQQA+DtfugsHQauJ8aXhUgAA6sOX7sLBHK0mxpeGSwEAqC9fuQqaoNXEsGgkAADlfOEqaE4dNjG+NFwKAIC/Y0SrCfKV4VIAAPwdQauJ8oXhUtQPi9UCgO8gaAFNCIvVAoBvYY4W0ESwWC0A+B6CFtBEsFgtAPgeghbQRLBYLQD4HoIW0ESwWC0A+B4mwwNNBIvV+i+uNAV8F0ELaCIqFqu9fEI8i9X6Nl+90pTwCJQjaAFNCIvV+pcrXWkaF+ed//a+Gh6B+qhT0EpLS9OSJUvUsmVLpaWl1dj2mWeeaVDHAH/FYrX+ozZXmnrb74KvhkegvuoUtP7973/r4sWLzv+ujs1ma1ivAHg1ThvVTl2uNPWWn6kvhkegIeoUtN57770q/7smx44dU0xMjAIuv0syAJ/EaaPaq+2Vpt70M2WZEsCV8fQTHx+vQ4cONdrxli9frs6dOys4OFiJiYnKzs6usf0bb7yhHj16KDg4WL169dI777zj8rplWVq4cKGio6MVEhKi5ORk7d+/v9H6C/gTVrevm379yi92qErFlabe9jNlmRLAlfGgZVlWox3r9ddfV1pamh566CHt3LlTffr0UUpKigoKCqps//HHH+tXv/qVpkyZon//+98aNWqURo0apV27djnbPPHEE1q2bJlWrFihHTt2qGXLlkpJSdH333/faP0G/AWr29dNxZWml4etH15p6m0/09qER8Cf2KzGTEJVaN26tT777DN17dq1wcdKTEzUDTfcoOeee06SVFZWptjYWN1zzz2aN29epfZjxozRuXPntGnTJue2G2+8UQkJCVqxYoUsy1JMTIxmz56tBx54QJJUVFSkyMhIZWRkaOzYsbXql8PhUFhYmIqKihQaGtrgOgFv9eab0g/+jqmkVy9p9Gj39cdbVMy/qupKU2/8mVZ1qrMiPPbp47FuAZW44/Pba5Z3uHDhgnJycjR//nzntoCAACUnJysrK6vKfbKysipdHZmSkqINGzZIkg4ePKi8vDwlJyc7Xw8LC1NiYqKysrKqDVolJSUqKSlxPnc4HPUtC/ApnDaqn5quNPXGnynLlAD/x2tmqJ86dUqlpaWKjIx02R4ZGam8vLwq98nLy6uxfcXXuhxTktLT0xUWFuZ8xMbG1rkewBdx2qjxeevPtCI8jh5d/pWQBX9lPGj54lIP8+fPV1FRkfNx9OhRT3cJaBJqM+cIdcPPFPBuxk8dNtYUsHbt2ikwMFD5+fku2/Pz8xUVFVXlPlFRUTW2r/ian5+v6OholzYJNVwzbbfbZbfb61MG4PM4bdT4+JkC3qvOQeuOO+6oVbtVq1ZJkv7zn/8oJiamrt+mkqCgIPXv31+ZmZkaNWqUpPLJ8JmZmZo5c2aV+yQlJSkzM1OzZs1ybtu2bZuSkpIkSV26dFFUVJQyMzOdwcrhcGjHjh2aPn16g/sM+CtWt298/EwB71TnoJWRkaG4uDj17du3VqNVjTl/KS0tTRMnTtSAAQM0cOBALV26VOfOndPkyZMlSRMmTFCHDh2Unp4uSbrvvvt088036+mnn9aIESO0du1affrpp3rxxRcllZ/WnDVrlh5++GFdc8016tKlixYsWKCYmBhnmAMAAKivOget6dOn67XXXtPBgwc1efJkjR8/Xm3btjXRt0rGjBmjkydPauHChcrLy1NCQoI2b97snMx+5MgRlxXoBw0apDVr1uh3v/udfvOb3+iaa67Rhg0bdP311zvbzJkzR+fOndO0adNUWFiowYMHa/PmzQoODnZLTQAAwHfVax2tkpISrVu3TqtWrdLHH3+sESNGaMqUKRo2bJhPTn6/EtbRAgDA+7jj87vBC5YePnxYGRkZeuWVV3Tp0iXt3r1brVq1aqz+eQWCFgAA3scdn98NXt4hICBANptNlmWptLS0MfoEAADgE+oVtEpKSvTaa6/pv/7rv3Tttdfqiy++0HPPPacjR4743WgWAABAdeo8Gf7uu+/W2rVrFRsbqzvuuEOvvfaa2rVrZ6JvAAAAXq3Oc7QCAgLUqVMn9e3bt8aJ7+vWrWtw57wFc7QAAPA+TfKm0hMmTPDLKwsBAADqql4LlgIAAODKjN9UGgAAwF8RtAAAAAwhaAEAABhC0AIAADCEoAUAAGAIQQsAAMAQghYAAIAhBC0AAABDCFoAAACGELQAAAAMIWgBAAAYQtACAAAwhKAFAABgCEELAADAEIIWAACAIQQtAAAAQwhaAAAAhhC0AAAADCFoAQAAGELQAgAAMISgBQAAYAhBCwAAwBCCFgAAgCEELQAAAEMIWgAAAIYQtAAAAAwhaAEAABhC0AIAADDEa4LWmTNnNG7cOIWGhio8PFxTpkxRcXFxje3vuecede/eXSEhIerUqZPuvfdeFRUVubSz2WyVHmvXrjVdDgAA8APNPN2B2ho3bpxOnDihbdu26eLFi5o8ebKmTZumNWvWVNn+m2++0TfffKOnnnpK8fHxOnz4sO666y598803evPNN13arl69Wqmpqc7n4eHhJksBAAB+wmZZluXpTlzJnj17FB8fr08++UQDBgyQJG3evFnDhw/XsWPHFBMTU6vjvPHGGxo/frzOnTunZs3KM6bNZtP69es1atSoevfP4XAoLCxMRUVFCg0NrfdxAACA+7jj89srTh1mZWUpPDzcGbIkKTk5WQEBAdqxY0etj1Pxg6wIWRVmzJihdu3aaeDAgVq1apWulD1LSkrkcDhcHgAAAJfzilOHeXl5ioiIcNnWrFkztW3bVnl5ebU6xqlTp7RkyRJNmzbNZfvixYv105/+VC1atNDWrVt19913q7i4WPfee2+1x0pPT9eiRYvqXggAAPArHh3RmjdvXpWT0X/42Lt3b4O/j8Ph0IgRIxQfH6/f//73Lq8tWLBAN910k/r27au5c+dqzpw5evLJJ2s83vz581VUVOR8HD16tMF9BAAAvsejI1qzZ8/WpEmTamzTtWtXRUVFqaCgwGX7pUuXdObMGUVFRdW4/7fffqvU1FS1bt1a69evV/PmzWtsn5iYqCVLlqikpER2u73KNna7vdrXAAAAKng0aLVv317t27e/YrukpCQVFhYqJydH/fv3lyS9++67KisrU2JiYrX7ORwOpaSkyG63a+PGjQoODr7i98rNzVWbNm0IUgAAoMG8Yo5Wz549lZqaqqlTp2rFihW6ePGiZs6cqbFjxzqvODx+/LiGDh2qV155RQMHDpTD4dCwYcN0/vx5/eUvf3GZtN6+fXsFBgbq7bffVn5+vm688UYFBwdr27ZtevTRR/XAAw94slwAAOAjvCJoSdKrr76qmTNnaujQoQoICNDo0aO1bNky5+sXL17Uvn37dP78eUnSzp07nVckduvWzeVYBw8eVOfOndW8eXMtX75c999/vyzLUrdu3fTMM89o6tSp7isMAAD4LK9YR6upYx0tAAC8D+toAQAAeDGCFgAAgCEELQAAAEMIWgAAAIYQtAAAAAwhaAEAABhC0AIAADCEoAUAAGAIQQsAAMAQghYAAIAhBC0AAABDCFoAAACGELQAAAAMIWgBAAAYQtACAAAwhKAFAABgCEELAADAEIIWAACAIQQtAAAAQwhaAAAAhhC0AAAADCFoAQAAGELQAgAAMISgBQAAYAhBCwAAwBCCFgAAgCEELQAAAEMIWgAAAIYQtAAAAAwhaAEAABhC0AIAADCEoAUAAGAIQQsAAMAQghYAAIAhBC0AAABDvCZonTlzRuPGjVNoaKjCw8M1ZcoUFRcX17jPkCFDZLPZXB533XWXS5sjR45oxIgRatGihSIiIvTggw/q0qVLJksBAAB+opmnO1Bb48aN04kTJ7Rt2zZdvHhRkydP1rRp07RmzZoa95s6daoWL17sfN6iRQvnf5eWlmrEiBGKiorSxx9/rBMnTmjChAlq3ry5Hn30UWO1AAAA/2CzLMvydCeuZM+ePYqPj9cnn3yiAQMGSJI2b96s4cOH69ixY4qJialyvyFDhighIUFLly6t8vX/9//+n/77v/9b33zzjSIjIyVJK1as0Ny5c3Xy5EkFBQXVqn8Oh0NhYWEqKipSaGho3QsEAABu547Pb684dZiVlaXw8HBnyJKk5ORkBQQEaMeOHTXu++qrr6pdu3a6/vrrNX/+fJ0/f97luL169XKGLElKSUmRw+HQ7t27qz1mSUmJHA6HywMAAOByXnHqMC8vTxERES7bmjVrprZt2yovL6/a/X79618rLi5OMTEx+vzzzzV37lzt27dP69atcx73hyFLkvN5TcdNT0/XokWL6lsOAADwEx4NWvPmzdPjjz9eY5s9e/bU+/jTpk1z/nevXr0UHR2toUOH6quvvtLVV19d7+POnz9faWlpzucOh0OxsbH1Ph4AAPBNHg1as2fP1qRJk2ps07VrV0VFRamgoMBl+6VLl3TmzBlFRUXV+vslJiZKkg4cOKCrr75aUVFRys7OdmmTn58vSTUe1263y2631/r7AgAA/+TRoNW+fXu1b9/+iu2SkpJUWFionJwc9e/fX5L07rvvqqyszBmeaiM3N1eSFB0d7TzuI488ooKCAuepyW3btik0NFTx8fF1rAYAAMCVV0yG79mzp1JTUzV16lRlZ2fro48+0syZMzV27FjnFYfHjx9Xjx49nCNUX331lZYsWaKcnBwdOnRIGzdu1IQJE/TjH/9YvXv3liQNGzZM8fHxuv322/XZZ59py5Yt+t3vfqcZM2YwYgUAABrMK4KWVH71YI8ePTR06FANHz5cgwcP1osvvuh8/eLFi9q3b5/zqsKgoCD94x//0LBhw9SjRw/Nnj1bo0eP1ttvv+3cJzAwUJs2bVJgYKCSkpI0fvx4TZgwwWXdLQAAgPryinW0mjrW0QIAwPuwjhYAAIAXI2gBAAAYQtACAAAwhKAFAABgCEELAADAEIIWAACAIQQtAAAAQwhaAAAAhhC0AAAADCFoAQAAGELQAgAAMISgBQAAYAhBCwAAwBCCFgAAgCEELQAAAEMIWgAAAIYQtAAAAAwhaAEAABhC0AIAADCEoAUAAGAIQQsAAMAQghYAAIAhBC0AAABDCFoAAACGELQAAAAMIWgBAAAYQtACAAAwhKAFAABgCEELAADAEIIWAACAIQQtAAAAQwhaAAAAhhC0AAAADCFoAQAAGELQAgAAMMRrgtaZM2c0btw4hYaGKjw8XFOmTFFxcXG17Q8dOiSbzVbl44033nC2q+r1tWvXuqMkAADg45p5ugO1NW7cOJ04cULbtm3TxYsXNXnyZE2bNk1r1qypsn1sbKxOnDjhsu3FF1/Uk08+qVtuucVl++rVq5Wamup8Hh4e3uj9BwAA/scrgtaePXu0efNmffLJJxowYIAk6dlnn9Xw4cP11FNPKSYmptI+gYGBioqKctm2fv16/fKXv1SrVq1ctoeHh1dqCwAA0FBeceowKytL4eHhzpAlScnJyQoICNCOHTtqdYycnBzl5uZqypQplV6bMWOG2rVrp4EDB2rVqlWyLKvGY5WUlMjhcLg8AAAALucVI1p5eXmKiIhw2dasWTO1bdtWeXl5tTrGypUr1bNnTw0aNMhl++LFi/XTn/5ULVq00NatW3X33XeruLhY9957b7XHSk9P16JFi+peCAAA8CseHdGaN29etRPWKx579+5t8Pf57rvvtGbNmipHsxYsWKCbbrpJffv21dy5czVnzhw9+eSTNR5v/vz5Kioqcj6OHj3a4D4CAADf49ERrdmzZ2vSpEk1tunatauioqJUUFDgsv3SpUs6c+ZMreZWvfnmmzp//rwmTJhwxbaJiYlasmSJSkpKZLfbq2xjt9urfQ0AAKCCR4NW+/bt1b59+yu2S0pKUmFhoXJyctS/f39J0rvvvquysjIlJiZecf+VK1fq1ltvrdX3ys3NVZs2bQhSAACgwbxijlbPnj2VmpqqqVOnasWKFbp48aJmzpypsWPHOq84PH78uIYOHapXXnlFAwcOdO574MABvf/++3rnnXcqHfftt99Wfn6+brzxRgUHB2vbtm169NFH9cADD7itNgAA4Lu8ImhJ0quvvqqZM2dq6NChCggI0OjRo7Vs2TLn6xcvXtS+fft0/vx5l/1WrVqljh07atiwYZWO2bx5cy1fvlz333+/LMtSt27d9Mwzz2jq1KnG6wEAAL7PZl1pLQNckcPhUFhYmIqKihQaGurp7gAAgFpwx+e3V6yjBQAA4I0IWgAAAIYQtAAAAAwhaAEAABhC0AIAADCEoAUAAGAIQQsAAMAQghYAAIAhBC0AAABDCFoAAACGELQAAAAMIWgBAAAYQtACAAAwhKAFAABgCEELAADAEIIWAACAIQQtAAAAQwhaAAAAhhC0AAAADCFoAQAAGELQAgAAMISgBQAAYAhBCwAAwBCCFgAAgCEELQAAAEMIWgAAAIYQtAAAAAwhaAEAABhC0AIAADCEoAUAAGAIQQsAAMAQghYAAIAhBC0AAABDCFoAAACGELQAAAAM8Zqg9cgjj2jQoEFq0aKFwsPDa7WPZVlauHChoqOjFRISouTkZO3fv9+lzZkzZzRu3DiFhoYqPDxcU6ZMUXFxsYEKAACAv/GaoHXhwgX94he/0PTp02u9zxNPPKFly5ZpxYoV2rFjh1q2bKmUlBR9//33zjbjxo3T7t27tW3bNm3atEnvv/++pk2bZqIEAADgZ2yWZVme7kRdZGRkaNasWSosLKyxnWVZiomJ0ezZs/XAAw9IkoqKihQZGamMjAyNHTtWe/bsUXx8vD755BMNGDBAkrR582YNHz5cx44dU0xMTK365HA4FBYWpqKiIoWGhjaoPgAA4B7u+Pz2mhGtujp48KDy8vKUnJzs3BYWFqbExERlZWVJkrKyshQeHu4MWZKUnJysgIAA7dixw+19BgAAvqWZpztgSl5eniQpMjLSZXtkZKTztby8PEVERLi83qxZM7Vt29bZpiolJSUqKSlxPi8qKpJUnowBAIB3qPjcNnlyz6NBa968eXr88cdrbLNnzx716NHDTT2qnfT0dC1atKjS9tjYWA/0BgAANMTp06cVFhZm5NgeDVqzZ8/WpEmTamzTtWvXeh07KipKkpSfn6/o6Gjn9vz8fCUkJDjbFBQUuOx36dIlnTlzxrl/VebPn6+0tDTn87KyMp05c0ZXXXWVbDZbvfpbGw6HQ7GxsTp69KjPzwWjVt/jL3VK1OqL/KVOyb9qLSoqUqdOndS2bVtj38OjQat9+/Zq3769kWN36dJFUVFRyszMdAYrh8OhHTt2OK9cTEpKUmFhoXJyctS/f39J0rvvvquysjIlJiZWe2y73S673e6yrbZLTjSG0NBQn//lr0Ctvsdf6pSo1Rf5S52Sf9UaEGBuyrrXTIY/cuSIcnNzdeTIEZWWlio3N1e5ubkua1716NFD69evlyTZbDbNmjVLDz/8sDZu3KgvvvhCEyZMUExMjEaNGiVJ6tmzp1JTUzV16lRlZ2fro48+0syZMzV27NhaX3EIAABQHa+ZDL9w4UK9/PLLzud9+/aVJL333nsaMmSIJGnfvn3OiemSNGfOHJ07d07Tpk1TYWGhBg8erM2bNys4ONjZ5tVXX9XMmTM1dOhQBQQEaPTo0Vq2bJl7igIAAD7Na4JWRkaGMjIyamxz+VUDNptNixcv1uLFi6vdp23btlqzZk1jdNE4u92uhx56qNJpS19Erb7HX+qUqNUX+UudErU2Nq9bsBQAAMBbeM0cLQAAAG9D0AIAADCEoAUAAGAIQQsAAMAQgpaHLV++XJ07d1ZwcLASExOVnZ1dbduMjAzZbDaXxw+XqrjcXXfdJZvNpqVLlxroed2ZqHXPnj269dZbFRYWppYtW+qGG27QkSNHTJZxRY1dZ3FxsWbOnKmOHTsqJCRE8fHxWrFihekyaqUutUpSYWGhZsyYoejoaNntdl177bV65513GnRMd2jsOtPT03XDDTeodevWioiI0KhRo7Rv3z7TZdSKiX/TCo899phzjcOmwEStx48f1/jx43XVVVcpJCREvXr10qeffmqyjCtq7DpLS0u1YMECdenSRSEhIbr66qu1ZMkSo/cLrK261DpkyJBK7782m00jRoxwtrEsSwsXLlR0dLRCQkKUnJys/fv3161TFjxm7dq1VlBQkLVq1Spr9+7d1tSpU63w8HArPz+/yvarV6+2QkNDrRMnTjgfeXl5VbZdt26d1adPHysmJsb6wx/+YLCK2jFR64EDB6y2bdtaDz74oLVz507rwIED1ltvvVXtMd3BRJ1Tp061rr76auu9996zDh48aL3wwgtWYGCg9dZbb7mjpGrVtdaSkhJrwIAB1vDhw60PP/zQOnjwoLV9+3YrNze33sd0BxN1pqSkWKtXr7Z27dpl5ebmWsOHD7c6depkFRcXu6usKpmotUJ2drbVuXNnq3fv3tZ9991nuJIrM1HrmTNnrLi4OGvSpEnWjh07rK+//trasmWLdeDAAXeVVYmJOh955BHrqquusjZt2mQdPHjQeuONN6xWrVpZf/zjH91VVpXqWuvp06dd3nt37dplBQYGWqtXr3a2eeyxx6ywsDBrw4YN1meffWbdeuutVpcuXazvvvuu1v0iaHnQwIEDrRkzZjifl5aWWjExMVZ6enqV7VevXm2FhYVd8bjHjh2zOnToYO3atcuKi4trEkHLRK1jxoyxxo8f35jdbDATdV533XXW4sWLXbb169fP+u1vf9vg/jZEXWt9/vnnra5du1oXLlxotGO6g4k6L1dQUGBJsv75z382uL8NYarWb7/91rrmmmusbdu2WTfffHOTCFomap07d641ePDgRu9rQ5ioc8SIEdYdd9zhsu1nP/uZNW7cuMbpdD019P3jD3/4g9W6dWvnHzxlZWVWVFSU9eSTTzrbFBYWWna73Xrttddq3S9OHXrIhQsXlJOTo+TkZOe2gIAAJScnKysrq9r9iouLFRcXp9jYWI0cOVK7d+92eb2srEy33367HnzwQV133XXG+l8XJmotKyvT3//+d1177bVKSUlRRESEEhMTtWHDBpOl1MjUv+mgQYO0ceNGHT9+XJZl6b333tOXX36pYcOGGavlSupT68aNG5WUlKQZM2YoMjJS119/vR599FGVlpbW+5immaizKhV3tDB5Y9srMVnrjBkzNGLECJdje5KpWjdu3KgBAwboF7/4hSIiItS3b1+99NJLxuupjqk6Bw0apMzMTH355ZeSpM8++0wffvihbrnlFrMF1aAx3j9WrlypsWPHqmXLlpKkgwcPKi8vz+WYYWFhSkxMrNN7EkHLQ06dOqXS0lJFRka6bI+MjFReXl6V+3Tv3l2rVq3SW2+9pb/85S8qKyvToEGDdOzYMWebxx9/XM2aNdO9995rtP91YaLWgoICFRcX67HHHlNqaqq2bt2q2267TT/72c/0z3/+03hNVTH1b/rss88qPj5eHTt2VFBQkFJTU7V8+XL9+Mc/NlpPTepT69dff60333xTpaWleuedd7RgwQI9/fTTevjhh+t9TNNM1Hm5srIyzZo1SzfddJOuv/76Rq+htkzVunbtWu3cuVPp6elG+18Xpmr9+uuv9fzzz+uaa67Rli1bNH36dN17770ut49zJ1N1zps3T2PHjlWPHj3UvHlz9e3bV7NmzdK4ceOM1lOThr5/ZGdna9euXbrzzjud2yr2a+h7ktfcggdSUlKSkpKSnM8HDRqknj176oUXXtCSJUuUk5OjP/7xj9q5c6dsNpsHe9pwV6q1rKxMkjRy5Ejdf//9kqSEhAR9/PHHWrFihW6++WaP9LuurlSnVB60/vWvf2njxo2Ki4vT+++/rxkzZigmJqbJjBDURllZmSIiIvTiiy8qMDBQ/fv31/Hjx/Xkk0/qoYce8nT3Gk1d65wxY4Z27dqlDz/80AO9bZgr1Xr06FHdd9992rZtW40X7niD2vy7lpWVacCAAXr00Uclld+Td9euXVqxYoUmTpzoye7XWm3q/Otf/6pXX31Va9as0XXXXafc3FzNmjVLMTExXlPn5VauXKlevXpp4MCBjX5sgpaHtGvXToGBgcrPz3fZnp+fr6ioqFodo+IviQMHDkiSPvjgAxUUFKhTp07ONqWlpZo9e7aWLl2qQ4cONVr/68JEre3atVOzZs0UHx/v0q5nz54e+8AyUed3332n3/zmN1q/fr3zSpjevXsrNzdXTz31lMeCVn1qjY6OVvPmzRUYGOjc1rNnT+Xl5enChQuN8vNrbCbqDAoKcm6fOXOmNm3apPfff18dO3Y0U0Qtmag1JydHBQUF6tevn/P10tJSvf/++3ruuedUUlLisq+7mPp3jY6OrvI96W9/+1vjF1ELpup88MEHnaNaktSrVy8dPnxY6enpHgtaDXn/OHfunNauXVvpvsgV++Xn5ys6OtrlmAkJCbXuG6cOPSQoKEj9+/dXZmamc1tZWZkyMzNdRjhqUlpaqi+++ML5C3D77bfr888/V25urvMRExOjBx98UFu2bDFSR22YqDUoKEg33HBDpUviv/zyS8XFxTVe5+vARJ0XL17UxYsXFRDg+r9qYGCgc1TPE+pT60033aQDBw649PvLL79UdHS0goKCGuXn19hM1CmVXzI+c+ZMrV+/Xu+++666dOlitpBaMFHr0KFD9cUXX7i8Jw0YMEDjxo1Tbm6uR0KWZO7f9aabbvL696Ta1Hn+/HmfeE+q8MYbb6ikpETjx4932d6lSxdFRUW5HNPhcGjHjh11e0+q9bR5NLq1a9dadrvdysjIsP7zn/9Y06ZNs8LDw52X999+++3WvHnznO0XLVpkbdmyxfrqq6+snJwca+zYsVZwcLC1e/fuar9HU7nq0ESt69ats5o3b269+OKL1v79+61nn33WCgwMtD744AO311fBRJ0333yzdd1111nvvfee9fXXX1urV6+2goODrT/96U9ur++H6lrrkSNHrNatW1szZ8609u3bZ23atMmKiIiwHn744Vof0xNM1Dl9+nQrLCzM2r59u8vl5efPn3d7fT9kotbLNZWrDk3Ump2dbTVr1sx65JFHrP3791uvvvqq1aJFC+svf/mL2+urYKLOiRMnWh06dHAu77Bu3TqrXbt21pw5c9xe3w/VtdYKgwcPtsaMGVPlMR977DErPDzceuutt6zPP//cGjlyJMs7eJtnn33W6tSpkxUUFGQNHDjQ+te//uV87eabb7YmTpzofD5r1ixn28jISGv48OHWzp07azx+UwlalmWm1pUrV1rdunWzgoODrT59+lgbNmxwRyk1auw6T5w4YU2aNMmKiYmxgoODre7du1tPP/20VVZW5q6SqlWXWi3Lsj7++GMrMTHRstvtVteuXa1HHnnEunTpUq2P6SmNXaekKh8/XL/HU0z8m/5QUwlalmWm1rffftu6/vrrLbvdbvXo0cN68cUX3VFKjRq7TofDYd13331Wp06drODgYKtr167Wb3/7W6ukpMRdJVWrrrXu3bvXkmRt3bq1yuOVlZVZCxYssCIjIy273W4NHTrU2rdvX536ZLOsJrCUKwAAgA9ijhYAAIAhBC0AAABDCFoAAACGELQAAAAMIWgBAAAYQtACAAAwhKAFAABgCEELAOopIyND4eHhnu4GgCaMoAXA702aNEk2m002m01BQUHq1q2bFi9erEuXLtW435gxY/Tll1+6qZcAvFEzT3cAAJqC1NRUrV69WiUlJXrnnXc0Y8YMNW/eXPPnz692n5CQEIWEhLixlwC8DSNaACDJbrcrKipKcXFxmj59upKTk7Vx48Ya9+HUIYArIWgBQBVCQkJ04cIFT3cDgJcjaAHAD1iWpX/84x/asmWLfvrTn3q6OwC8HHO0AEDSpk2b1KpVK128eFFlZWX69a9/rd///vee7hYAL0fQAgBJP/nJT/T8888rKChIMTExataMt0cADcc7CQBIatmypbp16+bpbgDwMczRAgAAMISgBQAAYIjNsizL050AAADwRYxoAQAAGELQAoBq3HLLLWrVqlWVj0cffdTT3QPgBTh1CADVOH78uL777rsqX2vbtq3atm3r5h4B8DYELQAAAEM4dQgAAGAIQQsAAMAQghYAAIAhBC0AAABDCFoAAACGELQAAAAMIWgBAAAYQtACAAAw5P8DXJ7fyQHjp5UAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = plt.gca()\n",
    "ax.plot(df[1][:],df[0][:], 'o', c='blue', alpha=0.5, markeredgecolor='none')\n",
    "ax.set_title(\"Real\")\n",
    "ax.set_ylabel(\"M_i\")\n",
    "ax.set_xlabel(\"P_i\")\n",
    "ax.set_ylim([-1,1])\n",
    "#ax.set_yscale('log')\n",
    "#ax.set_xscale('log')\n",
    "\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = plt.gca()\n",
    "ax.plot(np.abs(df[3][:]),np.abs(df[2][:]), 'o', c='blue', alpha=0.5, markeredgecolor='none')\n",
    "ax.set_title(\"Gen\")\n",
    "ax.set_ylabel(\"M_i\")\n",
    "ax.set_xlabel(\"P_i\")\n",
    "ax.set_ylim([-1,1])\n",
    "#ax.set_yscale('log')\n",
    "#ax.set_xscale('log')\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    }\n",
       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
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       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
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       "      <th>31</th>\n",
       "      <th>32</th>\n",
       "      <th>33</th>\n",
       "      <th>34</th>\n",
       "      <th>35</th>\n",
       "      <th>36</th>\n",
       "      <th>37</th>\n",
       "      <th>38</th>\n",
       "      <th>39</th>\n",
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       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>530000</td>\n",
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       "      <td>529500</td>\n",
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       "      <td>536700</td>\n",
       "      <td>100</td>\n",
       "      <td>526200</td>\n",
       "      <td>20</td>\n",
       "      <td>538000</td>\n",
       "      <td>2</td>\n",
       "      <td>526000</td>\n",
       "      <td>201</td>\n",
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       "      <td>526000</td>\n",
       "      <td>201</td>\n",
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       "      <td>538900</td>\n",
       "      <td>700</td>\n",
       "      <td>526000</td>\n",
       "      <td>201</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>530800</td>\n",
       "      <td>1</td>\n",
       "      <td>529900</td>\n",
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       "      <td>101</td>\n",
       "      <td>531200</td>\n",
       "      <td>3</td>\n",
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       "      <td>526300</td>\n",
       "      <td>300</td>\n",
       "      <td>538000</td>\n",
       "      <td>2</td>\n",
       "      <td>526200</td>\n",
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       "      <td>201</td>\n",
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       "      <th>4</th>\n",
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       "      <td>1</td>\n",
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       "      <td>7937</td>\n",
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       "      <td>3</td>\n",
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       "      <td>526300</td>\n",
       "      <td>300</td>\n",
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       "      <td>2</td>\n",
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       "      <td>20</td>\n",
       "      <td>538900</td>\n",
       "      <td>700</td>\n",
       "      <td>526000</td>\n",
       "      <td>201</td>\n",
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       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>379403</th>\n",
       "      <td>534400</td>\n",
       "      <td>20750</td>\n",
       "      <td>534300</td>\n",
       "      <td>40874</td>\n",
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       "      <td>4200</td>\n",
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       "      <td>533500</td>\n",
       "      <td>2746</td>\n",
       "      <td>535400</td>\n",
       "      <td>8000</td>\n",
       "      <td>533400</td>\n",
       "      <td>196</td>\n",
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       "      <td>534400</td>\n",
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       "      <td>41374</td>\n",
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       "      <td>4200</td>\n",
       "      <td>534200</td>\n",
       "      <td>45100</td>\n",
       "      <td>534600</td>\n",
       "      <td>14870</td>\n",
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       "      <td>533500</td>\n",
       "      <td>2746</td>\n",
       "      <td>535400</td>\n",
       "      <td>8000</td>\n",
       "      <td>533400</td>\n",
       "      <td>196</td>\n",
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       "      <th>379405</th>\n",
       "      <td>534400</td>\n",
       "      <td>20750</td>\n",
       "      <td>534300</td>\n",
       "      <td>40474</td>\n",
       "      <td>534500</td>\n",
       "      <td>4200</td>\n",
       "      <td>534200</td>\n",
       "      <td>45100</td>\n",
       "      <td>534600</td>\n",
       "      <td>14870</td>\n",
       "      <td>...</td>\n",
       "      <td>533600</td>\n",
       "      <td>23501</td>\n",
       "      <td>535200</td>\n",
       "      <td>18900</td>\n",
       "      <td>533500</td>\n",
       "      <td>2746</td>\n",
       "      <td>535400</td>\n",
       "      <td>8000</td>\n",
       "      <td>533400</td>\n",
       "      <td>196</td>\n",
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       "    <tr>\n",
       "      <th>379406</th>\n",
       "      <td>534400</td>\n",
       "      <td>20750</td>\n",
       "      <td>534300</td>\n",
       "      <td>40474</td>\n",
       "      <td>534500</td>\n",
       "      <td>4200</td>\n",
       "      <td>534200</td>\n",
       "      <td>57598</td>\n",
       "      <td>534600</td>\n",
       "      <td>14870</td>\n",
       "      <td>...</td>\n",
       "      <td>533600</td>\n",
       "      <td>23501</td>\n",
       "      <td>535200</td>\n",
       "      <td>18900</td>\n",
       "      <td>533500</td>\n",
       "      <td>2746</td>\n",
       "      <td>535400</td>\n",
       "      <td>8000</td>\n",
       "      <td>533400</td>\n",
       "      <td>196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>379407</th>\n",
       "      <td>534400</td>\n",
       "      <td>20750</td>\n",
       "      <td>534300</td>\n",
       "      <td>40474</td>\n",
       "      <td>534500</td>\n",
       "      <td>4200</td>\n",
       "      <td>534200</td>\n",
       "      <td>57598</td>\n",
       "      <td>534600</td>\n",
       "      <td>27368</td>\n",
       "      <td>...</td>\n",
       "      <td>533600</td>\n",
       "      <td>23501</td>\n",
       "      <td>535200</td>\n",
       "      <td>18900</td>\n",
       "      <td>533500</td>\n",
       "      <td>2746</td>\n",
       "      <td>535400</td>\n",
       "      <td>8000</td>\n",
       "      <td>533400</td>\n",
       "      <td>196</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>379408 rows × 40 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            0      1       2      3       4     5       6      7       8   \\\n",
       "0       530000     13  529900   7937  530800     1  529500      1  531000   \n",
       "1       530000      3  529900   7937  530800     1  529500      1  531000   \n",
       "2       530800      1  529900   7937  531000     5  529500      1  531200   \n",
       "3       530800      1  529900   7937  531000     5  529500    101  531200   \n",
       "4       530800      1  529900   7937  531000     5  529500      1  531200   \n",
       "...        ...    ...     ...    ...     ...   ...     ...    ...     ...   \n",
       "379403  534400  20750  534300  40874  534500  4200  534200  45100  534600   \n",
       "379404  534400  20750  534300  41374  534500  4200  534200  45100  534600   \n",
       "379405  534400  20750  534300  40474  534500  4200  534200  45100  534600   \n",
       "379406  534400  20750  534300  40474  534500  4200  534200  57598  534600   \n",
       "379407  534400  20750  534300  40474  534500  4200  534200  57598  534600   \n",
       "\n",
       "           9   ...      30     31      32     33      34    35      36    37  \\\n",
       "0           5  ...  526300    300  536700    100  526200    20  538000     2   \n",
       "1           5  ...  526300    300  536700    100  526200    20  538000     2   \n",
       "2           3  ...  526300    300  538000      2  526200    20  538900   700   \n",
       "3           3  ...  526300    300  538000      2  526200    20  538900   700   \n",
       "4           3  ...  526300    300  538000      2  526200    20  538900   700   \n",
       "...       ...  ...     ...    ...     ...    ...     ...   ...     ...   ...   \n",
       "379403  14870  ...  533600  23501  535200  18900  533500  2746  535400  8000   \n",
       "379404  14870  ...  533600  23501  535200  18900  533500  2746  535400  8000   \n",
       "379405  14870  ...  533600  23501  535200  18900  533500  2746  535400  8000   \n",
       "379406  14870  ...  533600  23501  535200  18900  533500  2746  535400  8000   \n",
       "379407  27368  ...  533600  23501  535200  18900  533500  2746  535400  8000   \n",
       "\n",
       "            38   39  \n",
       "0       526000  201  \n",
       "1       526000  201  \n",
       "2       526000  201  \n",
       "3       526000  201  \n",
       "4       526000  201  \n",
       "...        ...  ...  \n",
       "379403  533400  196  \n",
       "379404  533400  196  \n",
       "379405  533400  196  \n",
       "379406  533400  196  \n",
       "379407  533400  196  \n",
       "\n",
       "[379408 rows x 40 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b_seqs[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((0.0, ConfidenceInterval(low=0, high=0)),\n",
       " (0.0, ConfidenceInterval(low=0, high=0)))"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r,g=impact.apply_to_Sequences(impact.response_func,0.95,10,('MO_0',1),loader)\n",
    "r,g"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>379401</th>\n",
       "      <td>57599.941790671</td>\n",
       "      <td>4</td>\n",
       "      <td>506276242</td>\n",
       "      <td>1539</td>\n",
       "      <td>534300</td>\n",
       "      <td>1</td>\n",
       "      <td>534400</td>\n",
       "      <td>20750</td>\n",
       "      <td>534300</td>\n",
       "      <td>41161</td>\n",
       "      <td>...</td>\n",
       "      <td>533600</td>\n",
       "      <td>23501</td>\n",
       "      <td>535200</td>\n",
       "      <td>18900</td>\n",
       "      <td>533500</td>\n",
       "      <td>2746</td>\n",
       "      <td>535400</td>\n",
       "      <td>8000</td>\n",
       "      <td>533400</td>\n",
       "      <td>196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>379402</th>\n",
       "      <td>57599.944077062</td>\n",
       "      <td>4</td>\n",
       "      <td>506276242</td>\n",
       "      <td>200</td>\n",
       "      <td>534300</td>\n",
       "      <td>1</td>\n",
       "      <td>534400</td>\n",
       "      <td>20750</td>\n",
       "      <td>534300</td>\n",
       "      <td>40961</td>\n",
       "      <td>...</td>\n",
       "      <td>533600</td>\n",
       "      <td>23501</td>\n",
       "      <td>535200</td>\n",
       "      <td>18900</td>\n",
       "      <td>533500</td>\n",
       "      <td>2746</td>\n",
       "      <td>535400</td>\n",
       "      <td>8000</td>\n",
       "      <td>533400</td>\n",
       "      <td>196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>379403</th>\n",
       "      <td>57599.970434748</td>\n",
       "      <td>4</td>\n",
       "      <td>506276242</td>\n",
       "      <td>87</td>\n",
       "      <td>534300</td>\n",
       "      <td>1</td>\n",
       "      <td>534400</td>\n",
       "      <td>20750</td>\n",
       "      <td>534300</td>\n",
       "      <td>40874</td>\n",
       "      <td>...</td>\n",
       "      <td>533600</td>\n",
       "      <td>23501</td>\n",
       "      <td>535200</td>\n",
       "      <td>18900</td>\n",
       "      <td>533500</td>\n",
       "      <td>2746</td>\n",
       "      <td>535400</td>\n",
       "      <td>8000</td>\n",
       "      <td>533400</td>\n",
       "      <td>196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>379404</th>\n",
       "      <td>57599.978782977</td>\n",
       "      <td>1</td>\n",
       "      <td>506358486</td>\n",
       "      <td>500</td>\n",
       "      <td>534300</td>\n",
       "      <td>1</td>\n",
       "      <td>534400</td>\n",
       "      <td>20750</td>\n",
       "      <td>534300</td>\n",
       "      <td>41374</td>\n",
       "      <td>...</td>\n",
       "      <td>533600</td>\n",
       "      <td>23501</td>\n",
       "      <td>535200</td>\n",
       "      <td>18900</td>\n",
       "      <td>533500</td>\n",
       "      <td>2746</td>\n",
       "      <td>535400</td>\n",
       "      <td>8000</td>\n",
       "      <td>533400</td>\n",
       "      <td>196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>379405</th>\n",
       "      <td>57599.980216127</td>\n",
       "      <td>3</td>\n",
       "      <td>506315434</td>\n",
       "      <td>900</td>\n",
       "      <td>534300</td>\n",
       "      <td>1</td>\n",
       "      <td>534400</td>\n",
       "      <td>20750</td>\n",
       "      <td>534300</td>\n",
       "      <td>40474</td>\n",
       "      <td>...</td>\n",
       "      <td>533600</td>\n",
       "      <td>23501</td>\n",
       "      <td>535200</td>\n",
       "      <td>18900</td>\n",
       "      <td>533500</td>\n",
       "      <td>2746</td>\n",
       "      <td>535400</td>\n",
       "      <td>8000</td>\n",
       "      <td>533400</td>\n",
       "      <td>196</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>276522 rows × 46 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   time  event_type   order_id  size   price  direction  \\\n",
       "0       34200.071086177           1   20584110  7937  529900          1   \n",
       "1       34200.071461557           4   17065926    10  530000         -1   \n",
       "2       34200.071557986           4   17065926     3  530000         -1   \n",
       "9       34200.086371118           1   20594634     3  529900          1   \n",
       "11      34200.100864107           1   20601670     3  530800         -1   \n",
       "...                 ...         ...        ...   ...     ...        ...   \n",
       "379401  57599.941790671           4  506276242  1539  534300          1   \n",
       "379402  57599.944077062           4  506276242   200  534300          1   \n",
       "379403  57599.970434748           4  506276242    87  534300          1   \n",
       "379404  57599.978782977           1  506358486   500  534300          1   \n",
       "379405  57599.980216127           3  506315434   900  534300          1   \n",
       "\n",
       "             0      1       2      3  ...      30     31      32     33  \\\n",
       "0       530000     13  529900   7937  ...  526300    300  536700    100   \n",
       "1       530000      3  529900   7937  ...  526300    300  536700    100   \n",
       "2       530800      1  529900   7937  ...  526300    300  538000      2   \n",
       "9       530800      1  529900   7940  ...  526300    300  538000      2   \n",
       "11      530800      4  529900   7940  ...  526200     20  538000      2   \n",
       "...        ...    ...     ...    ...  ...     ...    ...     ...    ...   \n",
       "379401  534400  20750  534300  41161  ...  533600  23501  535200  18900   \n",
       "379402  534400  20750  534300  40961  ...  533600  23501  535200  18900   \n",
       "379403  534400  20750  534300  40874  ...  533600  23501  535200  18900   \n",
       "379404  534400  20750  534300  41374  ...  533600  23501  535200  18900   \n",
       "379405  534400  20750  534300  40474  ...  533600  23501  535200  18900   \n",
       "\n",
       "            34    35      36    37      38   39  \n",
       "0       526200    20  538000     2  526000  201  \n",
       "1       526200    20  538000     2  526000  201  \n",
       "2       526200    20  538900   700  526000  201  \n",
       "9       526200    20  538900   700  526000  201  \n",
       "11      526000   201  538900   700  525200   54  \n",
       "...        ...   ...     ...   ...     ...  ...  \n",
       "379401  533500  2746  535400  8000  533400  196  \n",
       "379402  533500  2746  535400  8000  533400  196  \n",
       "379403  533500  2746  535400  8000  533400  196  \n",
       "379404  533500  2746  535400  8000  533400  196  \n",
       "379405  533500  2746  535400  8000  533400  196  \n",
       "\n",
       "[276522 rows x 46 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mb_seqs=[impact.filter_touch_events(m,b) for m,b in zip(m_seqs,b_seqs)]\n",
    "mb_seqs[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Calculating for event type:  MO_0\n",
      "Calculating for event type:  MO_1\n",
      "Calculating for event type:  LO_0\n",
      "Calculating for event type:  LO_1\n",
      "31\r"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[208], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mimpact\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mimpact_compare\u001b[49m\u001b[43m(\u001b[49m\u001b[43mloader\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m/data1/sascha/lob_bench/impact.py:241\u001b[0m, in \u001b[0;36mimpact_compare\u001b[0;34m(loader)\u001b[0m\n\u001b[1;32m    239\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m event \u001b[38;5;129;01min\u001b[39;00m events:\n\u001b[1;32m    240\u001b[0m     \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCalculating for event type: \u001b[39m\u001b[38;5;124m\"\u001b[39m, event)\n\u001b[0;32m--> 241\u001b[0m     r,g\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mzip\u001b[39m(\u001b[38;5;241m*\u001b[39m[apply_to_Sequences(response_func,\u001b[38;5;241m0.975\u001b[39m,\u001b[38;5;241m100\u001b[39m,(event,i),loader) \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m x])\n\u001b[1;32m    242\u001b[0m     r_m,r_ci\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mzip\u001b[39m(\u001b[38;5;241m*\u001b[39mr)\n\u001b[1;32m    243\u001b[0m     g_m,g_ci\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mzip\u001b[39m(\u001b[38;5;241m*\u001b[39mg)\n",
      "File \u001b[0;32m/data1/sascha/lob_bench/impact.py:241\u001b[0m, in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m    239\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m event \u001b[38;5;129;01min\u001b[39;00m events:\n\u001b[1;32m    240\u001b[0m     \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCalculating for event type: \u001b[39m\u001b[38;5;124m\"\u001b[39m, event)\n\u001b[0;32m--> 241\u001b[0m     r,g\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mzip\u001b[39m(\u001b[38;5;241m*\u001b[39m[\u001b[43mapply_to_Sequences\u001b[49m\u001b[43m(\u001b[49m\u001b[43mresponse_func\u001b[49m\u001b[43m,\u001b[49m\u001b[38;5;241;43m0.975\u001b[39;49m\u001b[43m,\u001b[49m\u001b[38;5;241;43m100\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m(\u001b[49m\u001b[43mevent\u001b[49m\u001b[43m,\u001b[49m\u001b[43mi\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43mloader\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m x])\n\u001b[1;32m    242\u001b[0m     r_m,r_ci\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mzip\u001b[39m(\u001b[38;5;241m*\u001b[39mr)\n\u001b[1;32m    243\u001b[0m     g_m,g_ci\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mzip\u001b[39m(\u001b[38;5;241m*\u001b[39mg)\n",
      "File \u001b[0;32m/data1/sascha/lob_bench/impact.py:212\u001b[0m, in \u001b[0;36mapply_to_Sequences\u001b[0;34m(fun, CI, max_seq, args, loader)\u001b[0m\n\u001b[1;32m    209\u001b[0m metrics_real\u001b[38;5;241m.\u001b[39mappend(metr)\n\u001b[1;32m    211\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m j,mgen \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m(loader[i]\u001b[38;5;241m.\u001b[39mm_gen):\n\u001b[0;32m--> 212\u001b[0m     gen_df\u001b[38;5;241m=\u001b[39m\u001b[43mclassify_event_types\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    213\u001b[0m \u001b[43m                \u001b[49m\u001b[43mmerge_MOs\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    214\u001b[0m \u001b[43m                \u001b[49m\u001b[43mfilter_touch_events\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmgen\u001b[49m\u001b[43m,\u001b[49m\u001b[43mloader\u001b[49m\u001b[43m[\u001b[49m\u001b[43mi\u001b[49m\u001b[43m]\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mb_gen\u001b[49m\u001b[43m[\u001b[49m\u001b[43mj\u001b[49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    215\u001b[0m     metr\u001b[38;5;241m=\u001b[39mfun(\u001b[38;5;241m*\u001b[39margs,gen_df)\n\u001b[1;32m    216\u001b[0m     metrics_gen\u001b[38;5;241m.\u001b[39mappend(metr)\n",
      "File \u001b[0;32m/data1/sascha/lob_bench/impact.py:121\u001b[0m, in \u001b[0;36mclassify_event_types\u001b[0;34m(big_df)\u001b[0m\n\u001b[1;32m    118\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m: \n\u001b[1;32m    119\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mEvent type is none of 1, 2, 3 or 4. Ensure filtering is done properly beforehand.\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m--> 121\u001b[0m big_df[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mbouchaud_event\u001b[39m\u001b[38;5;124m'\u001b[39m]\u001b[38;5;241m=\u001b[39m\u001b[43mbig_df\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mapply\u001b[49m\u001b[43m(\u001b[49m\u001b[43mclassification_fun\u001b[49m\u001b[43m,\u001b[49m\u001b[43maxis\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    122\u001b[0m eps\u001b[38;5;241m=\u001b[39mbig_df\u001b[38;5;241m.\u001b[39mapply(epsilon_fun,axis\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mcolumns\u001b[39m\u001b[38;5;124m'\u001b[39m,result_type\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mexpand\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m    123\u001b[0m df\u001b[38;5;241m=\u001b[39mpd\u001b[38;5;241m.\u001b[39mconcat([big_df,eps],axis\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mcolumns\u001b[39m\u001b[38;5;124m'\u001b[39m)\n",
      "File \u001b[0;32m~/miniconda3/envs/alphatrade_new/lib/python3.10/site-packages/pandas/core/frame.py:10037\u001b[0m, in \u001b[0;36mDataFrame.apply\u001b[0;34m(self, func, axis, raw, result_type, args, by_row, **kwargs)\u001b[0m\n\u001b[1;32m  10025\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mpandas\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mcore\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mapply\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m frame_apply\n\u001b[1;32m  10027\u001b[0m op \u001b[38;5;241m=\u001b[39m frame_apply(\n\u001b[1;32m  10028\u001b[0m     \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m  10029\u001b[0m     func\u001b[38;5;241m=\u001b[39mfunc,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m  10035\u001b[0m     kwargs\u001b[38;5;241m=\u001b[39mkwargs,\n\u001b[1;32m  10036\u001b[0m )\n\u001b[0;32m> 10037\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mop\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mapply\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241m.\u001b[39m__finalize__(\u001b[38;5;28mself\u001b[39m, method\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mapply\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
      "File \u001b[0;32m~/miniconda3/envs/alphatrade_new/lib/python3.10/site-packages/pandas/core/apply.py:837\u001b[0m, in \u001b[0;36mFrameApply.apply\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    834\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mraw:\n\u001b[1;32m    835\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mapply_raw()\n\u001b[0;32m--> 837\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mapply_standard\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/miniconda3/envs/alphatrade_new/lib/python3.10/site-packages/pandas/core/apply.py:963\u001b[0m, in \u001b[0;36mFrameApply.apply_standard\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    962\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mapply_standard\u001b[39m(\u001b[38;5;28mself\u001b[39m):\n\u001b[0;32m--> 963\u001b[0m     results, res_index \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mapply_series_generator\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    965\u001b[0m     \u001b[38;5;66;03m# wrap results\u001b[39;00m\n\u001b[1;32m    966\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mwrap_results(results, res_index)\n",
      "File \u001b[0;32m~/miniconda3/envs/alphatrade_new/lib/python3.10/site-packages/pandas/core/apply.py:979\u001b[0m, in \u001b[0;36mFrameApply.apply_series_generator\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    976\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m option_context(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmode.chained_assignment\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m):\n\u001b[1;32m    977\u001b[0m     \u001b[38;5;28;01mfor\u001b[39;00m i, v \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m(series_gen):\n\u001b[1;32m    978\u001b[0m         \u001b[38;5;66;03m# ignore SettingWithCopy here in case the user mutates\u001b[39;00m\n\u001b[0;32m--> 979\u001b[0m         results[i] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mv\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    980\u001b[0m         \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(results[i], ABCSeries):\n\u001b[1;32m    981\u001b[0m             \u001b[38;5;66;03m# If we have a view on v, we need to make a copy because\u001b[39;00m\n\u001b[1;32m    982\u001b[0m             \u001b[38;5;66;03m#  series_generator will swap out the underlying data\u001b[39;00m\n\u001b[1;32m    983\u001b[0m             results[i] \u001b[38;5;241m=\u001b[39m results[i]\u001b[38;5;241m.\u001b[39mcopy(deep\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m)\n",
      "File \u001b[0;32m/data1/sascha/lob_bench/impact.py:105\u001b[0m, in \u001b[0;36mclassify_event_types.<locals>.classification_fun\u001b[0;34m(series)\u001b[0m\n\u001b[1;32m    102\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    103\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mMO_0\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m--> 105\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m ((\u001b[43mseries\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mevent_type\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[38;5;241m==\u001b[39m\u001b[38;5;241m2\u001b[39m) \u001b[38;5;241m|\u001b[39m\n\u001b[1;32m    106\u001b[0m       (series[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mevent_type\u001b[39m\u001b[38;5;124m'\u001b[39m]\u001b[38;5;241m==\u001b[39m\u001b[38;5;241m3\u001b[39m)):\n\u001b[1;32m    107\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m ((series[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124maskprice_diff\u001b[39m\u001b[38;5;124m'\u001b[39m]\u001b[38;5;241m!=\u001b[39m\u001b[38;5;241m0\u001b[39m)\u001b[38;5;241m|\u001b[39m \n\u001b[1;32m    108\u001b[0m        (series[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mbidprice_diff\u001b[39m\u001b[38;5;124m'\u001b[39m]\u001b[38;5;241m!=\u001b[39m\u001b[38;5;241m0\u001b[39m)):\n\u001b[1;32m    109\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCA_1\u001b[39m\u001b[38;5;124m\"\u001b[39m\n",
      "File \u001b[0;32m~/miniconda3/envs/alphatrade_new/lib/python3.10/site-packages/pandas/core/series.py:1040\u001b[0m, in \u001b[0;36mSeries.__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   1037\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_values[key]\n\u001b[1;32m   1039\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m key_is_scalar:\n\u001b[0;32m-> 1040\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get_value\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1042\u001b[0m \u001b[38;5;66;03m# Convert generator to list before going through hashable part\u001b[39;00m\n\u001b[1;32m   1043\u001b[0m \u001b[38;5;66;03m# (We will iterate through the generator there to check for slices)\u001b[39;00m\n\u001b[1;32m   1044\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m is_iterator(key):\n",
      "File \u001b[0;32m~/miniconda3/envs/alphatrade_new/lib/python3.10/site-packages/pandas/core/series.py:1139\u001b[0m, in \u001b[0;36mSeries._get_value\u001b[0;34m(self, label, takeable)\u001b[0m\n\u001b[1;32m   1136\u001b[0m     new_mgr \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_mgr\u001b[38;5;241m.\u001b[39mget_rows_with_mask(indexer)\n\u001b[1;32m   1137\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_constructor_from_mgr(new_mgr, axes\u001b[38;5;241m=\u001b[39mnew_mgr\u001b[38;5;241m.\u001b[39maxes)\u001b[38;5;241m.\u001b[39m__finalize__(\u001b[38;5;28mself\u001b[39m)\n\u001b[0;32m-> 1139\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_get_value\u001b[39m(\u001b[38;5;28mself\u001b[39m, label, takeable: \u001b[38;5;28mbool\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m):\n\u001b[1;32m   1140\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m   1141\u001b[0m \u001b[38;5;124;03m    Quickly retrieve single value at passed index label.\u001b[39;00m\n\u001b[1;32m   1142\u001b[0m \n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m   1150\u001b[0m \u001b[38;5;124;03m    scalar value\u001b[39;00m\n\u001b[1;32m   1151\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[1;32m   1152\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m takeable:\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "impact.impact_compare(loader)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Calculating for event type:  MO_0\n",
      "1\n",
      "1\n",
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      "79\n",
      "Calculating for event type:  MO_1\n",
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      "79\n",
      "Calculating for event type:  LO_0\n",
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      "79\n",
      "Calculating for event type:  LO_1\n",
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      "79\n",
      "Calculating for event type:  CA_0\n",
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      "63\n",
      "79\n",
      "Calculating for event type:  CA_1\n",
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      "79\n"
     ]
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 204,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sum of abs differences for  MO_0  events: 2.3904164746228127\n",
      "Sum of abs differences for  MO_1  events: 3.6448076485976912\n",
      "Sum of abs differences for  LO_0  events: 0.43380571352449526\n",
      "Sum of abs differences for  LO_1  events: 1.1270795562163416\n",
      "Sum of abs differences for  CA_0  events: 1.109748685279331\n",
      "Sum of abs differences for  CA_1  events: 2.275502047437252\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "1.8302266876129873"
      ]
     },
     "execution_count": 204,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [],
   "source": [
    "fun=partial(impact.sign_autocorr,)\n",
    "x=(10** np.arange(0,4,step=0.1)).astype(int)\n",
    "y,std_y=zip(*[impact.apply_to_seqs(impact.sign_autocorr,(i,'s'),df_seqs) for i in x])\n",
    "z,std_z=zip(*[impact.apply_to_seqs(impact.sign_autocorr,(i,'eps'),df_seqs) for i in x])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_loglog(x,[y,z],None,['s','eps','-0.3 power'],title='Time autocorrelation of signs eps and s.',loglog=0.3,ylabel=\"Autocorrelation\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [],
   "source": [
    "x=(10** np.arange(0,4,step=0.1)).astype(int)\n",
    "\n",
    "ys=[]\n",
    "stds=[]\n",
    "events=['MO_0','MO_1','LO_0','LO_1','CA_0','CA_1']\n",
    "for event2 in events:\n",
    "    mean,std=zip(*[impact.apply_to_seqs(impact.event_cross_corr,('MO_0',event2,i),df_seqs) for i in x])\n",
    "    ys.append(mean)\n",
    "    stds.append(np.array(std))\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_loglog(x,ys,None,legend=events,\n",
    "            title=\"Correlation of MO_0 event with other event types\",\n",
    "            ylabel=\"Correlation\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [],
   "source": [
    "x=(10** np.arange(0,6,step=0.1)).astype(int)\n",
    "ys=[]\n",
    "stds=[]\n",
    "for event2 in events:\n",
    "    mean,std=zip(*[impact.apply_to_seqs(impact.event_cross_corr,('MO_1',event2,i),df_seqs) for i in x])\n",
    "    ys.append(mean)\n",
    "    stds.append(np.array(std))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_223308/1476874460.py:21: UserWarning: Attempt to set non-positive ylim on a log-scaled axis will be ignored.\n",
      "  ax.set_ylim(np.array(ys_lims)*1.2)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "plot_loglog(x,ys,stds,legend=events,\n",
    "            title=\"Correlation of MO_1 event with other event types\",\n",
    "            ylabel=\"Correlation\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "can't multiply sequence by non-int of type 'tuple'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[119], line 4\u001b[0m\n\u001b[1;32m      2\u001b[0m ys\u001b[38;5;241m=\u001b[39m[]\n\u001b[1;32m      3\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m event2 \u001b[38;5;129;01min\u001b[39;00m events:\n\u001b[0;32m----> 4\u001b[0m     ys\u001b[38;5;241m.\u001b[39mappend([impact\u001b[38;5;241m.\u001b[39mapply_to_seqs(impact\u001b[38;5;241m.\u001b[39mu_event_corr,(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mMO_0\u001b[39m\u001b[38;5;124m'\u001b[39m,event2,i),df_seqs) \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m x])\n",
      "Cell \u001b[0;32mIn[119], line 4\u001b[0m, in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m      2\u001b[0m ys\u001b[38;5;241m=\u001b[39m[]\n\u001b[1;32m      3\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m event2 \u001b[38;5;129;01min\u001b[39;00m events:\n\u001b[0;32m----> 4\u001b[0m     ys\u001b[38;5;241m.\u001b[39mappend([\u001b[43mimpact\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mapply_to_seqs\u001b[49m\u001b[43m(\u001b[49m\u001b[43mimpact\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mu_event_corr\u001b[49m\u001b[43m,\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mMO_0\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43mevent2\u001b[49m\u001b[43m,\u001b[49m\u001b[43mi\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43mdf_seqs\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m x])\n",
      "File \u001b[0;32m/data1/sascha/lob_bench/impact.py:170\u001b[0m, in \u001b[0;36mapply_to_seqs\u001b[0;34m(fun, args, sequences)\u001b[0m\n\u001b[1;32m    168\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mapply_to_seqs\u001b[39m(fun,args,sequences:\u001b[38;5;28mlist\u001b[39m):\n\u001b[1;32m    169\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"Fun must return a scalar\"\"\"\u001b[39;00m\n\u001b[0;32m--> 170\u001b[0m     metrics\u001b[38;5;241m=\u001b[39mpd\u001b[38;5;241m.\u001b[39mconcat([fun(\u001b[38;5;241m*\u001b[39margs,seq) \u001b[38;5;28;01mfor\u001b[39;00m seq \u001b[38;5;129;01min\u001b[39;00m sequences],axis\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0\u001b[39m)\n\u001b[1;32m    171\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m metrics\u001b[38;5;241m.\u001b[39mmean(),metrics\u001b[38;5;241m.\u001b[39mstd()\n",
      "File \u001b[0;32m/data1/sascha/lob_bench/impact.py:170\u001b[0m, in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m    168\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mapply_to_seqs\u001b[39m(fun,args,sequences:\u001b[38;5;28mlist\u001b[39m):\n\u001b[1;32m    169\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"Fun must return a scalar\"\"\"\u001b[39;00m\n\u001b[0;32m--> 170\u001b[0m     metrics\u001b[38;5;241m=\u001b[39mpd\u001b[38;5;241m.\u001b[39mconcat([\u001b[43mfun\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43mseq\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mfor\u001b[39;00m seq \u001b[38;5;129;01min\u001b[39;00m sequences],axis\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0\u001b[39m)\n\u001b[1;32m    171\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m metrics\u001b[38;5;241m.\u001b[39mmean(),metrics\u001b[38;5;241m.\u001b[39mstd()\n",
      "File \u001b[0;32m/data1/sascha/lob_bench/impact.py:158\u001b[0m, in \u001b[0;36mu_event_corr\u001b[0;34m(event1, event2, lag, sequence)\u001b[0m\n\u001b[1;32m    155\u001b[0m series\u001b[38;5;241m=\u001b[39m(sequence[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mbouchaud_event\u001b[39m\u001b[38;5;124m'\u001b[39m]\u001b[38;5;241m.\u001b[39meq(event1)\n\u001b[1;32m    156\u001b[0m         \u001b[38;5;241m*\u001b[39m sequence[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mbouchaud_event\u001b[39m\u001b[38;5;124m'\u001b[39m]\u001b[38;5;241m.\u001b[39mshift(periods\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m-\u001b[39mlag)\u001b[38;5;241m.\u001b[39meq(event2))\n\u001b[1;32m    157\u001b[0m num\u001b[38;5;241m=\u001b[39mseries\u001b[38;5;241m.\u001b[39mmean()\n\u001b[0;32m--> 158\u001b[0m PI_pi1_pi2\u001b[38;5;241m=\u001b[39mseries \u001b[38;5;241m/\u001b[39m (\u001b[43mProb_pi\u001b[49m\u001b[43m(\u001b[49m\u001b[43mevent1\u001b[49m\u001b[43m,\u001b[49m\u001b[43msequence\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    159\u001b[0m \u001b[43m                 \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mProb_pi\u001b[49m\u001b[43m(\u001b[49m\u001b[43mevent2\u001b[49m\u001b[43m,\u001b[49m\u001b[43msequence\u001b[49m\u001b[43m)\u001b[49m) \u001b[38;5;241m-\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m    160\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m PI_pi1_pi2\n",
      "\u001b[0;31mTypeError\u001b[0m: can't multiply sequence by non-int of type 'tuple'"
     ]
    }
   ],
   "source": [
    "x=(10** np.arange(0,4,step=0.1)).astype(int)\n",
    "ys=[]\n",
    "for event2 in events:\n",
    "    ys.append([impact.apply_to_seqs(impact.u_event_corr,('MO_0',event2,i),df_seqs) for i in x])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_loglog(x,ys,legend=events,\n",
    "            title=\"Unsigned correlation of MO_0 event with other event types\",\n",
    "            ylabel=\"Correlation\")\n",
    "ys_neg=[([-i for i in y]) for y in ys]\n",
    "plot_loglog(x,ys_neg,legend=events,\n",
    "            title=\"Unsigned correlation of MO_0 event with other event types\",\n",
    "            ylabel=\"Correlation (negative)\",\n",
    "            invert=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "x=(10** np.arange(0,4,step=0.1)).astype(int)\n",
    "ys=[]\n",
    "for event2 in events:\n",
    "    ys.append([impact.apply_to_seqs(impact.u_event_corr,('MO_1',event2,i),df_seqs) for i in x])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_loglog(x,ys,legend=events,\n",
    "            title=\"Unsigned correlation of MO_1 event with other event types\",\n",
    "            ylabel=\"Correlation\")\n",
    "ys_neg=[([-i for i in y]) for y in ys]\n",
    "plot_loglog(x,ys_neg,legend=events,\n",
    "            title=\"Unsigned correlation of MO_1 event with other event types\",\n",
    "            ylabel=\"Correlation (negative)\",\n",
    "            invert=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "impact_msgs, impact_books=impact.filter_sequence_for_impact(m,b,ordersize=(1100,1300),orderside=1,sequence_length=1000,timestamp=('34200.034289918','34900.134289918'))\n",
    "print(impact_msgs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "eval.time_to_first_fill(m).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "eval.time_to_cancel(m).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "eval.l1_volume(m, b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "eval.total_volume(m, b, 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "eval.limit_order_depth(m, b)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "eval.cancellation_depth(m, b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "eval._order_levels(m, b, (1,2,3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "eval.cancel_order_levels(m, b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "eval.spread(b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ret = eval.mid_returns(m, b, '1min')\n",
    "ret"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "eval.time_to_first_fill(m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "eval.autocorr(ret)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "eval.autocorr(ret**2, 10, alpha=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "eval.l1_volume(m, b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "eval.total_volume(m, b, 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "eval.limit_order_depth(m_real, b_real)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# DEPRECATED\n",
    "# eval.compute_metrics(loader)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "s=loader"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "s = loader[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in loader:\n",
    "    print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ask_lvls, bid_lvls = eval.limit_order_levels(m_real, b_real)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ask_lvls"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "m_real"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "b_real"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "mid = eval.mid_price(m_real, b_real)\n",
    "mid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "book_real_3d = eval.compute_3d_book_changes(m_real, b_real)\n",
    "book_real_3d\n",
    "\n",
    "\n",
    "# TODO: bin this data for all dimensions separately and then compute the L1 norm of the distributions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "book_real_3d_groups, bins = eval.compute_3d_book_groups(book_real_3d, 5)\n",
    "book_real_3d_groups\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "value_counts = book_real_3d_groups.value_counts()\n",
    "value_counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "bins"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# TODO: get the values from value_counts and match them to the right bins\n",
    "#       also compute the L1 norm of the distributions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "value_counts.sort_index().values.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "values.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "# X, Y, Z = np.meshgrid([-10,0,10], [-10,0,10], [-10,0,10])\n",
    "X, Y, Z = np.meshgrid(*bins)\n",
    "values = 2*X*X - Y*Y + 1/(Z*Z+1)\n",
    "# values = value_counts.sort_index().values\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111, projection='3d')\n",
    "scatter = ax.scatter(X, Y, Z, c=values, cmap='viridis', marker='s', alpha=0.5, s=200)\n",
    "fig.colorbar(scatter, ax=ax)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# compute 3d book tuples for all real data samples\n",
    "book_real_3d = pd.concat(partitioning.score_real(loader, eval.compute_3d_book_changes))\n",
    "book_real_3d.dropna().hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "# from mpl_toolkits.mplot3d import Axes3D\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111, projection='3d')\n",
    "\n",
    "ax.scatter(book_real_3d['mid_change'], book_real_3d['price'], book_real_3d['size'])\n",
    "\n",
    "ax.set_xlabel('Mid Change')\n",
    "ax.set_ylabel('Price')\n",
    "ax.set_zlabel('Size')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "eval.mid_returns(m_real, b_real)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "m_real.iloc[1163]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "b_real.iloc[1163]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "eval.autocorr(eval.mid_returns(m_real, b_real, '1min'), 4)\n",
    "# eval.mid_returns(m_real, b_real, '5min')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "eval._order_levels(m_real, b_real, (2,3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "cnl_lvl_ask, cnl_lvl_bid = eval.cancel_order_levels(m_real, b_real)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "eval.mean_per_interval(cnl_lvl_ask, \"5min\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Library Use Cases"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from data_loading import Simple_Loader, Lobster_Sequence, Lazy_Tuple"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# loader = data_loading.Simple_Loader('data_test_real', 'data_test_gen', 'data_test_cond')\n",
    "loader = data_loading.Simple_Loader('data_saved/GOOG/data_real', 'data_saved/GOOG/data_gen', 'data_saved/GOOG/data_cond')\n",
    "s = loader[0]\n",
    "# s.materialize()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "s.m_real"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "partitioning.score_real(loader, lambda x, y: 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "scores = partitioning.score_real(\n",
    "    tuple(partitioning.get_subseqs(s, time_interval='10min') for s in loader),\n",
    "    lambda m, b: m.time.diff().mean()\n",
    ")\n",
    "scores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "scores = partitioning.score_cond(\n",
    "    loader, \n",
    "    lambda m, b: m.time.diff().mean()\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "scores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "subseq = partitioning.get_subseqs(s, subseq_len=1000)\n",
    "len(subseq.m_real)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "s.m_gen[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "subseq = partitioning.get_subseqs(loader[0], time_interval='5min')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Example of how grouping works\n",
    "\n",
    "partitioning.group_by_score(\n",
    "    scores_real=[9, 10, 9.5, 9, 8, 11, 5.5],\n",
    "    scores_gen=[8, 10, 9.5, 9, 8, 11, 5.5, 1, 1, 1, 2, 3, 6],\n",
    "    n_bins=4\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# ..using subsequences\n",
    "\n",
    "partitioning.group_by_score(\n",
    "    scores_real=[[9, 10], [9.5, 9], [8, 11, 5.5]],\n",
    "    scores_gen=[[[8, 10, 9.5], [9, 8, 11]], [[5.5, 1, 1], [1, 2, 3, 6]]],\n",
    "    quantiles=[0.2, 0.5, 0.8]\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "loader"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import metrics\n",
    "import plotting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# unconditional comparison of distributions (of 10 min intervals)\n",
    "\n",
    "subseqs = tuple(partitioning.get_subseqs(s, time_interval='10min') for s in loader)\n",
    "scoring_fn = lambda m, b: eval.spread(m, b).mean()\n",
    "\n",
    "scores_real, scores_gen = partitioning.score_real_gen(subseqs, scoring_fn)\n",
    "\n",
    "# compare distributions of scores\n",
    "metrics.wasserstein(scores_real, scores_gen)\n",
    "\n",
    "# print(scores_real)\n",
    "# print(scores_gen)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plotting.hist(scores_real, scores_gen)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "groups[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# comparison conditional on time of day (which subsequence part)\n",
    "\n",
    "subseqs = tuple(partitioning.get_subseqs(s, time_interval='10min') for s in loader)\n",
    "scoring_fn = lambda m, b: eval.spread(m, b).mean()\n",
    "\n",
    "scores_real, scores_gen = partitioning.score_real_gen(subseqs, scoring_fn)\n",
    "\n",
    "# enumerate groups for each subseq for each real and gen. sequence\n",
    "groups_real, groups_gen = partitioning.group_by_subseq(subseqs)\n",
    "score_df = partitioning.get_score_table(scores_real, scores_gen, groups_real, groups_gen)\n",
    "\n",
    "score_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# print entire score table\n",
    "with pd.option_context('display.max_rows', None, 'display.max_columns', None):\n",
    "    print(score_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "group_counts = score_df.groupby(['type', 'group']).count()\n",
    "group_counts = pd.merge(group_counts.loc['real'], group_counts.loc['generated'], on='group')\n",
    "(group_counts.score_x - group_counts.score_y).abs().mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def l1_by_group(score_df: pd.DataFrame) -> float:\n",
    "    \"\"\"\n",
    "    Takes a \"score dataframe\" with columns score (real numbers), group (+int), type (\"real\" or \"generated\")\n",
    "    Returns the mean L1 distance between the number of scores in each group for the real and generated data.\n",
    "    \"\"\"\n",
    "    group_counts = score_df.groupby(['type', 'group']).count()\n",
    "    group_counts = pd.merge(group_counts.loc['real'], group_counts.loc['generated'], on='group')\n",
    "    return (group_counts.score_x - group_counts.score_y).abs().mean()\n",
    "l1_by_group(score_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "l1_by_group(score_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "score_df.type.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plotting.line(score_df, '', 'time interval', 'spread')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "b_real=loader[0].b_real\n",
    "m_real=loader[0].m_real\n",
    "columns = [item for i in range(1,11) for item in (f\"askPrice{i}\", f\"askQuant{i}\", f\"bidPrice{i}\", f\"bidQuant{i}\")]\n",
    "b_real.columns=columns\n",
    "b_real['mid_price']=(b_real['askPrice1']*b_real['askQuant1']+b_real['bidPrice1']*b_real['bidQuant1'])/(b_real['askQuant1']+b_real['bidQuant1'])\n",
    "b_real['delta_mid_price']=b_real['mid_price'].diff().fillna(0)\n",
    "b_real"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "np.set_printoptions(suppress=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "idx = 2\n",
    "delta_mid_price = b_real.iloc[idx,-1]\n",
    "lb_array=b_real.iloc[idx-1,:40].values.reshape(20,2)\n",
    "b_array=b_real.iloc[idx,:40].values.reshape(20,2)\n",
    "lb_unique = np.array([x for x in lb_array if not any(np.array_equal(x, y) for y in b_array)])\n",
    "b_unique = np.array([x for x in b_array if not any(np.array_equal(x, y) for y in lb_array)])\n",
    "first_lb_unique=lb_unique[0];first_b_unique=b_unique[0]\n",
    "index = np.where(b_array[:, 0] == first_b_unique[0])[0][0]\n",
    "quant = np.where(first_b_unique[0] == first_lb_unique[0], first_b_unique[1] - first_lb_unique[1], first_b_unique[1])\n",
    "result = np.array([delta_mid_price,index,quant])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "b_real['delta_mid_price'].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def ob3Drepr(orderbook, row_index):\n",
    "    price_level = 10\n",
    "    delta_mid_price = b_real.iloc[row_index,-1]\n",
    "    lb_array=b_real.iloc[row_index-1,:4*price_level].values.reshape(2*price_level,2)\n",
    "    b_array=b_real.iloc[row_index,:4*price_level].values.reshape(2*price_level,2)\n",
    "    lb_unique = np.array([x for x in lb_array if not any(np.array_equal(x, y) for y in b_array)])\n",
    "    b_unique = np.array([x for x in b_array if not any(np.array_equal(x, y) for y in lb_array)])\n",
    "    first_lb_unique=lb_unique[0];first_b_unique=b_unique[0]\n",
    "    index = np.where(b_array[:, 0] == first_b_unique[0])[0][0]\n",
    "    quant = np.where(first_b_unique[0] == first_lb_unique[0], first_b_unique[1] - first_lb_unique[1], first_b_unique[1])\n",
    "    result = np.array([delta_mid_price,index,quant])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# calculate scores of entire real and generated data (here by the spread),\n",
    "# and group each subsequence into a bin based on the score\n",
    "# for each of these bins, calculate the distribution of a statistic of interest (e.g. autocorrelation of mid returns)\n",
    "\n",
    "scoring_fn = lambda m, b: eval.spread(m, b).mean()\n",
    "scores_real, scores_gen = partitioning.score_real_gen(subseqs, scoring_fn)\n",
    "groups_real, groups_gen = partitioning.group_by_score(\n",
    "    scores_real, scores_gen,\n",
    "    # n_bins=5,\n",
    "    quantiles=[0.25, 0.5, 0.75],\n",
    ")\n",
    "score_df = partitioning.get_score_table(scores_real, scores_gen, groups_real, groups_gen)\n",
    "\n",
    "eval_fn = lambda m, b: eval.autocorr(eval.mid_returns(m, b, interval='1min'), 1)[1]\n",
    "eval_real, eval_gen = partitioning.score_real_gen(subseqs, eval_fn)\n",
    "eval_df = partitioning.get_score_table(eval_real, eval_gen, groups_real, groups_gen)\n",
    "\n",
    "eval_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 1-minute return autocorrelation by spread quartile\n",
    "eval_df.groupby(['type', 'group']).score.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# split data into subsequences (10min each),\n",
    "# calculate scores of real and generated data (here by the spread),\n",
    "# and group each subsequence into a bin based on the score\n",
    "\n",
    "subseqs = tuple(partitioning.get_subseqs(s, time_interval='10min') for s in loader)\n",
    "scoring_fn = lambda m, b: eval.spread(m, b).mean()\n",
    "\n",
    "scores_real, scores_gen = partitioning.score_real_gen(subseqs, scoring_fn)\n",
    "\n",
    "partitioning.group_by_score(\n",
    "    scores_real, scores_gen,\n",
    "    n_bins=5\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "partitioning.group_by_score(\n",
    "    scores_real=[9, 10, 9.5, 9, 8, 11, 5.5],\n",
    "    scores_gen=[(8, 10, 9.5, 9, 8, 11, 5.5, 1, 1, 1, 2, 3, 6)],\n",
    "    n_bins=5\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# example use of scoring for real data\n",
    "print(\n",
    "    partitioning.score_real(loader, lambda m, b: eval.spread(m, b).mean())\n",
    ")\n",
    "# example use of scoring for generated data\n",
    "print(\n",
    "    partitioning.score_gen(loader, lambda m, b: eval.spread(m, b).mean())\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# TOOD: use partitioning.group_by_score to get groups and then compare relevant metrics for each group\n",
    "#      solve this for conditioning on cond. data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# condition only on input data\n",
    "scores = partitioning.score_cond(\n",
    "    loader,\n",
    "    lambda m, b: eval.spread(m, b).mean()\n",
    ")\n",
    "print(scores)\n",
    "\n",
    "# --> only single groups (combined scores using input sequences) relevant here\n",
    "groups, _ = partitioning.group_by_score(\n",
    "    scores,\n",
    "    n_bins=5\n",
    ")\n",
    "groups"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "loader[0].m_real"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "scores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# TODO: compare relevant metrics for each group (can we compute all metrics in one go? and then do different groupings and comparisons?)\n",
    "#       think about more principled dim. reduction functions for this\n",
    "\n",
    "#       implement some distance metrics to compare distributions of metrics for different groups (wasserstein, KL, etc.)\n",
    "\n",
    "#       TRAIN LARGE MODEL AND RUN INFERENCE\n",
    "\n",
    "#       implement some market impact metrics (e.g. price impact of trades, etc.) --> how should we structure the data for this?\n",
    "#           --> e.g. market impact flag if cond. input has artificial orders?\n",
    "#           - define function to generate input sequences with artificial orders\n",
    "#           - function to find sequences with naturally occuring taking orders etc? "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## KL Divergence"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import scipy.stats\n",
    "from sklearn.neighbors import KernelDensity\n",
    "# Example usage\n",
    "N = 1011\n",
    "M = 1234\n",
    "# M = 211\n",
    "K = 1\n",
    "a = np.random.rand(N, K)\n",
    "b = np.random.rand(M, K)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "import numpy as np\n",
    "import scipy, time\n",
    "import matplotlib.pyplot as plt\n",
    "from scipy.interpolate import interp1d\n",
    "from scipy import stats, integrate\n",
    "\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "\n",
    "def KLD_PerezCruz(P, Q, eps=1e-11):\n",
    "    '''takes two datasets to estimate the relative entropy between their PDFs\n",
    "    we use eps=10^-11, but it could be defined as < the minimal interval between data points'''\n",
    "    def cumcount_reduced(arr):\n",
    "        '''Returns the step function value at each increment of the CDF'''\n",
    "        sorted_arr = np.array(sorted(arr))\n",
    "        counts = np.zeros(len(arr))\n",
    "        \n",
    "        rolling_count = 0\n",
    "        for idx, elem in enumerate(sorted_arr):\n",
    "            rolling_count += 1\n",
    "            counts[idx] = rolling_count\n",
    "\n",
    "        counts /= len(counts)\n",
    "        counts -= (1 / (2 * len(counts)))\n",
    "\n",
    "        return (sorted_arr, counts)\n",
    "    P = sorted(P)\n",
    "    Q = sorted(Q)\n",
    "    \n",
    "    P_positions, P_counts = cumcount_reduced(P)\n",
    "    Q_positions, Q_counts = cumcount_reduced(Q)\n",
    "    \n",
    "    #definition of x_0 and x_{n+1}\n",
    "    x_0 = np.min([P_positions[0], Q_positions[0]]) - 1\n",
    "    P_positions = np.insert(P_positions, 0, [x_0])\n",
    "    P_counts = np.insert(P_counts, 0, [0])\n",
    "    Q_positions = np.insert(Q_positions, 0, [x_0])\n",
    "    Q_counts = np.insert(Q_counts, 0, [0])\n",
    "    \n",
    "    x_np1 = np.max([P_positions[-1], Q_positions[-1]]) + 1\n",
    "    P_positions = np.append(P_positions, [x_np1])\n",
    "    P_counts = np.append(P_counts, [1])\n",
    "    Q_positions = np.append(Q_positions, [x_np1])\n",
    "    Q_counts = np.append(Q_counts, [1])\n",
    "    \n",
    "    f_P = interp1d(P_positions, P_counts)\n",
    "    f_Q = interp1d(Q_positions, Q_counts) \n",
    "    \n",
    "    X = P_positions[1:-2]\n",
    "    values = (f_P(X) - f_P(X - eps)) / (f_Q(X) - f_Q(X - eps))\n",
    "    filt = ((values != 0.) & ~(np.isinf(values)) & ~(np.isnan(values)))\n",
    "    values_filter = values[filt]\n",
    "    out = (np.sum(np.log(values_filter)) / len(values_filter)) - 1.\n",
    "\n",
    "    return out\n",
    "KLD_PerezCruz(a, b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from scipy.spatial import KDTree\n",
    "\n",
    "def kl(X, Y):\n",
    "    \"\"\"\n",
    "    Estimate the Kullback-Leibler divergence between two multivariate samples.\n",
    "    Adapted for Python from R code at https://gist.github.com/atabakd/ed0f7581f8510c8587bc2f41a094b518\n",
    "    as described in Fernando Pérez-cruz, Kullback-Leibler Divergence Estimation of Continuous Distributions,\n",
    "    Proceedings of IEEE International Symposium on Information Theory, 2008, 1666--1670\n",
    "\n",
    "    Parameters\n",
    "    ----------\n",
    "    X : 2D array (n,d)\n",
    "        Samples from distribution P, which typically represents the true distribution.\n",
    "    Y : 2D array (m,d)\n",
    "        Samples from distribution Q, which typically represents the approximate distribution.\n",
    "\n",
    "    Returns\n",
    "    -------\n",
    "    out : float\n",
    "        The estimated Kullback-Leibler divergence D(P||Q).\n",
    "    \"\"\"\n",
    "import numpy as np\n",
    "from scipy.spatial import KDTree\n",
    "\n",
    "def kl(X, Y):\n",
    "    \"\"\"\n",
    "    Estimate the Kullback-Leibler divergence between two multivariate samples.\n",
    "    Adapted for Python from R code at https://gist.github.com/atabakd/ed0f7581f8510c8587bc2f41a094b518\n",
    "    as described in Fernando Pérez-cruz, Kullback-Leibler Divergence Estimation of Continuous Distributions,\n",
    "    Proceedings of IEEE International Symposium on Information Theory, 2008, 1666--1670\n",
    "\n",
    "    Parameters\n",
    "    ----------\n",
    "    X : 2D array (n,d)\n",
    "        Samples from distribution P, which typically represents the true distribution.\n",
    "    Y : 2D array (m,d)\n",
    "        Samples from distribution Q, which typically represents the approximate distribution.\n",
    "\n",
    "    Returns\n",
    "    -------\n",
    "    out : float\n",
    "        The estimated Kullback-Leibler divergence D(P||Q).\n",
    "    \"\"\"\n",
    "    # get important dimensions\n",
    "    d = X.shape[1]  # number of dimensions, must be the same in X and Y\n",
    "    n = X.shape[0]  # number of samples in X\n",
    "    m = Y.shape[0]  # number of samples in Y\n",
    "    \n",
    "    # get distances to nearest neighbors using KDTree\n",
    "    tree_X = KDTree(X)\n",
    "    tree_Y = KDTree(Y)\n",
    "    \n",
    "    r = tree_X.query(X, k=2, eps=0.01)[0][:, 1]  # get 2 closest neighbors, then take the second (the closest is the point itself) to get n x 1 array\n",
    "    s = tree_Y.query(X, k=1, eps=0.01)[0]  # also n x 1 array\n",
    "    \n",
    "    # Add a small value to avoid log of zero\n",
    "    epsilon = 1e-10\n",
    "    r = r + epsilon\n",
    "    s = s + epsilon\n",
    "    \n",
    "    # Correct implementation of KL divergence formula\n",
    "    term1 = np.sum(np.log(s / r)) * d / n\n",
    "    term2 = np.log(m / (n - 1.))\n",
    "    \n",
    "    # Ensure the term1 calculation aligns with the KL divergence definition\n",
    "    kl_divergence = (term1 + term2) * n / m  # Adjust based on the definition in the referenced paper\n",
    "    \n",
    "    return kl_divergence\n",
    "kl(a, b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "def kl_divergence(a, b):\n",
    "    \"\"\"\n",
    "    Calculate the Kullback-Leibler (KL) divergence between the KDEs of two datasets.\n",
    "\n",
    "    Args:\n",
    "        a (np.ndarray): First dataset of shape (N, K), where N is the number of samples and K is the number of features.\n",
    "        b (np.ndarray): Second dataset of shape (M, K), where M is the number of samples and K is the number of features.\n",
    "\n",
    "    Returns:\n",
    "        float: The KL divergence between the two datasets.\n",
    "    \"\"\"\n",
    "    N = a.shape[0]\n",
    "    M = b.shape[0]\n",
    "    K = a.shape[1]\n",
    "    assert a.shape[1] == b.shape[1]    \n",
    "\n",
    "    # Fit KDE models\n",
    "    kde_a = KernelDensity(kernel='gaussian', bandwidth=0.1).fit(a)\n",
    "    kde_b = KernelDensity(kernel='gaussian', bandwidth=0.1).fit(b)\n",
    "\n",
    "    # Generate evaluation points based on the average number of samples\n",
    "    num_points = int(np.mean([N, M]) * 10)\n",
    "    # x = np.linspace(0, 1, 1000)\n",
    "    x = np.linspace(0, 1, num_points)\n",
    "\n",
    "    # Generate a grid of K-dimensional points for PDF evaluation\n",
    "    grid = np.array(np.meshgrid(*([x] * K))).T.reshape(-1, K)\n",
    "    \n",
    "\n",
    "    log_pdf_a = kde_a.score_samples(grid)\n",
    "    log_pdf_b = kde_b.score_samples(grid)\n",
    "\n",
    "    pdf_a = np.exp(log_pdf_a)\n",
    "    pdf_b = np.exp(log_pdf_b)\n",
    "\n",
    "    # Add a small value to PDFs to avoid log(0)\n",
    "    epsilon = 1e-10\n",
    "    pdf_a += epsilon\n",
    "    pdf_b += epsilon\n",
    "\n",
    "    # Normalize PDFs\n",
    "    pdf_a /= np.sum(pdf_a)\n",
    "    pdf_b /= np.sum(pdf_b)\n",
    "\n",
    "    # Calculate KL divergence\n",
    "    kl_div = scipy.stats.entropy(pdf_a, pdf_b)\n",
    "\n",
    "    # print(\"KL Divergence:\", kl_div)\n",
    "    return kl_div\n",
    "kl_divergence(a, b)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import math\n",
    "import scipy.stats\n",
    "from sklearn.neighbors import NearestNeighbors\n",
    "\n",
    "def k_nearest_neighbors_density_estimation(X, k):\n",
    "    \"\"\"\n",
    "    Estimate density using k-nearest neighbors.\n",
    "    \n",
    "    Args:\n",
    "        X (np.ndarray): Data points of shape (N, K).\n",
    "        k (int): Number of nearest neighbors to use.\n",
    "    \n",
    "    Returns:\n",
    "        densities (np.ndarray): Density estimates of shape (N,).\n",
    "    \"\"\"\n",
    "    N, K = X.shape\n",
    "    nbrs = NearestNeighbors(n_neighbors=k + 1).fit(X)\n",
    "    distances, _ = nbrs.kneighbors(X)\n",
    "    radius = distances[:, -1]  # Distance to the k-th nearest neighbor\n",
    "    volume = np.pi**(K / 2) / math.gamma(K / 2 + 1) * radius**K\n",
    "    densities = k / (N * volume)\n",
    "    return densities\n",
    "\n",
    "def kl_divergence_knn(a, b, k=50):\n",
    "    \"\"\"\n",
    "    Estimate the Kullback-Leibler (KL) divergence between two datasets using k-nearest neighbors.\n",
    "    \n",
    "    Args:\n",
    "        a (np.ndarray): First dataset of shape (N, K).\n",
    "        b (np.ndarray): Second dataset of shape (M, K).\n",
    "        k (int): Number of nearest neighbors to use. Default is 50.\n",
    "    \n",
    "    Returns:\n",
    "        float: The average KL divergence between the two datasets.\n",
    "    \"\"\"\n",
    "    N = a.shape[0]\n",
    "    M = b.shape[0]\n",
    "    K = a.shape[1]\n",
    "    assert a.shape[1] == b.shape[1]\n",
    "\n",
    "    # Determine number of samples and iterations based on dataset sizes and dimensionality\n",
    "    num_samples = 100 * np.mean([N, M])\n",
    "    num_iterations = 100 * K\n",
    "    \n",
    "    kl_divergences = []\n",
    "    \n",
    "    for _ in range(num_iterations):\n",
    "        # Select min(N, M, num_samples) samples from both datasets\n",
    "        sample_size = min(N, M, num_samples)\n",
    "        indices_a = np.random.choice(N, sample_size, replace=False)\n",
    "        indices_b = np.random.choice(M, sample_size, replace=False)\n",
    "        \n",
    "        a_sample = a[indices_a]\n",
    "        b_sample = b[indices_b]\n",
    "\n",
    "        # Estimate densities\n",
    "        p_hat_a = k_nearest_neighbors_density_estimation(a_sample, k)\n",
    "        q_hat_b = k_nearest_neighbors_density_estimation(b_sample, k)\n",
    "        \n",
    "        # Compute KL divergence\n",
    "        kl_div = (K / sample_size) * np.sum(np.log(p_hat_a / q_hat_b)) + np.log(M / (N - 1))\n",
    "        kl_divergences.append(kl_div)\n",
    "    \n",
    "    # Average KL divergence over all iterations\n",
    "    avg_kl_div = np.mean(kl_divergences)\n",
    "    \n",
    "    return avg_kl_div\n",
    "\n",
    "kl_div = kl_divergence_knn(a, b, k=100)\n",
    "print(\"Average KL Divergence:\", kl_div)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import math\n",
    "import scipy.stats\n",
    "from sklearn.neighbors import NearestNeighbors, KernelDensity\n",
    "import pandas as pd\n",
    "\n",
    "def k_nearest_neighbors_density_estimation(X, k):\n",
    "    N, K = X.shape\n",
    "    nbrs = NearestNeighbors(n_neighbors=k + 1).fit(X)\n",
    "    distances, _ = nbrs.kneighbors(X)\n",
    "    radius = distances[:, -1]  # Distance to the k-th nearest neighbor\n",
    "    volume = np.pi**(K / 2) / math.gamma(K / 2 + 1) * radius**K\n",
    "    densities = k / (N * volume)\n",
    "    return densities\n",
    "\n",
    "def kl_divergence_knn(a, b, k=50):\n",
    "    N = a.shape[0]\n",
    "    M = b.shape[0]\n",
    "    K = a.shape[1]\n",
    "    assert a.shape[1] == b.shape[1]\n",
    "\n",
    "    num_samples = int(np.mean([N, M]) * 10)\n",
    "    num_iterations = 100 * K\n",
    "    \n",
    "    kl_divergences = []\n",
    "    \n",
    "    for _ in range(num_iterations):\n",
    "        sample_size = min(N, M, num_samples)\n",
    "        indices_a = np.random.choice(N, sample_size, replace=False)\n",
    "        indices_b = np.random.choice(M, sample_size, replace=False)\n",
    "        \n",
    "        a_sample = a[indices_a]\n",
    "        b_sample = b[indices_b]\n",
    "\n",
    "        p_hat_a = k_nearest_neighbors_density_estimation(a_sample, k)\n",
    "        q_hat_b = k_nearest_neighbors_density_estimation(b_sample, k)\n",
    "        \n",
    "        kl_div = (K / sample_size) * np.sum(np.log(p_hat_a / q_hat_b)) + np.log(M / (N - 1))\n",
    "        kl_divergences.append(kl_div)\n",
    "    \n",
    "    avg_kl_div = np.mean(kl_divergences)\n",
    "    \n",
    "    return avg_kl_div\n",
    "\n",
    "def kl_divergence_kde(a, b, bandwidth=0.1):\n",
    "    N = a.shape[0]\n",
    "    M = b.shape[0]\n",
    "    K = a.shape[1]\n",
    "    assert a.shape[1] == b.shape[1]    \n",
    "\n",
    "    kde_a = KernelDensity(kernel='gaussian', bandwidth=bandwidth).fit(a)\n",
    "    kde_b = KernelDensity(kernel='gaussian', bandwidth=bandwidth).fit(b)\n",
    "\n",
    "    num_points = int(np.mean([N, M]) * 10)\n",
    "    x = np.linspace(0, 1, num_points)\n",
    "\n",
    "    grid = np.array(np.meshgrid(*([x] * K))).T.reshape(-1, K)\n",
    "    \n",
    "    log_pdf_a = kde_a.score_samples(grid)\n",
    "    log_pdf_b = kde_b.score_samples(grid)\n",
    "\n",
    "    pdf_a = np.exp(log_pdf_a)\n",
    "    pdf_b = np.exp(log_pdf_b)\n",
    "\n",
    "    epsilon = 1e-10\n",
    "    pdf_a += epsilon\n",
    "    pdf_b += epsilon\n",
    "\n",
    "    pdf_a /= np.sum(pdf_a)\n",
    "    pdf_b /= np.sum(pdf_b)\n",
    "\n",
    "    kl_div = scipy.stats.entropy(pdf_a, pdf_b)\n",
    "\n",
    "    return kl_div\n",
    "\n",
    "# Example usage\n",
    "N = 101\n",
    "M = 211\n",
    "K = 1\n",
    "a = np.random.rand(N, K)\n",
    "b = np.random.rand(M, K)\n",
    "\n",
    "kl_div_knn = kl_divergence_knn(a, b, k=100)\n",
    "kl_div_kde = kl_divergence_kde(a, b, bandwidth=0.1)\n",
    "\n",
    "results = {\n",
    "    \"KL Divergence using k-NN\": kl_div_knn,\n",
    "    \"KL Divergence using KDE\": kl_div_kde\n",
    "}\n",
    "\n",
    "results_df = pd.DataFrame.from_dict(results, orient='index', columns=[\"KL Divergence\"])\n",
    "results_df\n"
   ]
  }
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