prepare_X.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from findataflow.dataprocs import feature_generator as fg\n",
    "from findataflow.dataprocs import resample as resampler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "specs = []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "lines_to_next_cell": 2
   },
   "outputs": [],
   "source": [
    "# BB\n",
    "FUNCS = {\n",
    "    'price': ['BULL_MA', 'BULL_UP', 'BULL_DOWN'],}\n",
    "PARAMETER = [\n",
    "    {\n",
    "        'timeperiod':5,\n",
    "        'nbdevup': 2, \n",
    "        'nbdevdn': 2\n",
    "    }\n",
    "]\n",
    "specs += [\n",
    "        {\n",
    "            'symbol': 'TXF',\n",
    "            'type': func_type,\n",
    "            'freq': '1D',\n",
    "            'func': func, \n",
    "            'args': param\n",
    "        } \n",
    "        for param in PARAMETER\n",
    "        for func_type, funcs in FUNCS.items()\n",
    "        for func in funcs\n",
    "    ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "lines_to_next_cell": 2
   },
   "outputs": [],
   "source": [
    "# BIAS\n",
    "FUNCS = {\n",
    "    'swig': ['BIAS'],\n",
    "}\n",
    "assert all(func_type in ['price', 'swig', 'vol'] for func_type in FUNCS.keys())\n",
    "PARAMETER = [\n",
    "    {'timeperiod': 5}, {'timeperiod': 10}, {'timeperiod': 15}, \n",
    "         {'timeperiod': 20}, {'timeperiod': 25}, {'timeperiod': 30}\n",
    "]\n",
    "specs += [\n",
    "        {\n",
    "            'symbol': 'TXF',\n",
    "            'type': func_type,\n",
    "            'freq': '1D',\n",
    "            'func': func, \n",
    "            'args': param\n",
    "        } \n",
    "        for param in PARAMETER\n",
    "        for func_type, funcs in FUNCS.items()\n",
    "        for func in funcs\n",
    "    ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "lines_to_next_cell": 2
   },
   "outputs": [],
   "source": [
    "# candlestick\n",
    "FUNCS = {\n",
    "    'price': ['candlestick'],\n",
    "}\n",
    "assert all(func_type in ['price', 'swig', 'vol'] for func_type in FUNCS.keys())\n",
    "PARAMETER = [\n",
    "    {}\n",
    "]\n",
    "\n",
    "specs += [\n",
    "        {\n",
    "            'symbol': 'TXF',\n",
    "            'type': func_type,\n",
    "            'freq': '1D',\n",
    "            'func': func, \n",
    "            'args': param\n",
    "        } \n",
    "        for param in PARAMETER\n",
    "        for func_type, funcs in FUNCS.items()\n",
    "        for func in funcs\n",
    "    ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "lines_to_next_cell": 2
   },
   "outputs": [],
   "source": [
    "# CDP\n",
    "FUNCS = {\n",
    "    'price': [\n",
    "        'CDP', 'AH', 'AL', 'NH', 'NL'\n",
    "    ],\n",
    "}\n",
    "assert all(func_type in ['price', 'swig', 'vol'] for func_type in FUNCS.keys())\n",
    "PARAMETER = [\n",
    "    {}\n",
    "]\n",
    "\n",
    "specs += [\n",
    "        {\n",
    "            'symbol': 'TXF',\n",
    "            'type': func_type,\n",
    "            'freq': '1D',\n",
    "            'func': func, \n",
    "            'args': param\n",
    "        } \n",
    "        for param in PARAMETER\n",
    "        for func_type, funcs in FUNCS.items()\n",
    "        for func in funcs\n",
    "    ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "lines_to_next_cell": 2
   },
   "outputs": [],
   "source": [
    "# DMI \n",
    "FUNCS = {\n",
    "    'swig': [\n",
    "        'plusDM', 'minusDM', 'plusDI', 'minusDI', 'DX', 'ADX'\n",
    "    ],\n",
    "}\n",
    "assert all(func_type in ['price', 'swig', 'vol'] for func_type in FUNCS.keys())\n",
    "PARAMETER = [\n",
    "    {'timeperiod': 5}, {'timeperiod': 10}, {'timeperiod': 15}, \n",
    "         {'timeperiod': 20}, {'timeperiod': 25}, {'timeperiod': 30}\n",
    "]\n",
    "specs += [\n",
    "        {\n",
    "            'symbol': 'TXF',\n",
    "            'type': func_type,\n",
    "            'freq': '1D',\n",
    "            'func': func, \n",
    "            'args': param\n",
    "        } \n",
    "        for param in PARAMETER\n",
    "        for func_type, funcs in FUNCS.items()\n",
    "        for func in funcs\n",
    "    ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "lines_to_next_cell": 2
   },
   "outputs": [],
   "source": [
    "# KD\n",
    "FUNCS = {\n",
    "    'swig': [\n",
    "        'RSV', 'K', 'D'\n",
    "    ],\n",
    "}\n",
    "assert all(func_type in ['price', 'swig', 'vol'] for func_type in FUNCS.keys())\n",
    "PARAMETER = [\n",
    "    {\n",
    "        'fastk_period': 9,\n",
    "        'slowk_period': 3,\n",
    "        'slowd_period': 3\n",
    "    },\n",
    "]\n",
    "specs += [\n",
    "        {\n",
    "            'symbol': 'TXF',\n",
    "            'type': func_type,\n",
    "            'freq': '1D',\n",
    "            'func': func, \n",
    "            'args': param\n",
    "        } \n",
    "        for param in PARAMETER\n",
    "        for func_type, funcs in FUNCS.items()\n",
    "        for func in funcs\n",
    "    ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "lines_to_next_cell": 2
   },
   "outputs": [],
   "source": [
    "# MACD\n",
    "FUNCS = {\n",
    "    'swig': [\n",
    "        'MACD', 'MACD_SIGNAL', 'MACD_HIST'\n",
    "            ],\n",
    "}\n",
    "assert all(func_type in ['price', 'swig', 'vol'] for func_type in FUNCS.keys())\n",
    "PARAMETER = [\n",
    "    {\n",
    "        'fastperiod': 12, \n",
    "        'slowperiod': 26, \n",
    "        'signalperiod': 9\n",
    "    }, \n",
    "]\n",
    "specs += [\n",
    "        {\n",
    "            'symbol': 'TXF',\n",
    "            'type': func_type,\n",
    "            'freq': '1D',\n",
    "            'func': func, \n",
    "            'args': param\n",
    "        } \n",
    "        for param in PARAMETER\n",
    "        for func_type, funcs in FUNCS.items()\n",
    "        for func in funcs\n",
    "    ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "lines_to_next_cell": 2
   },
   "outputs": [],
   "source": [
    "# MFI\n",
    "FUNCS = {\n",
    "    'swig': ['MFI'],\n",
    "}\n",
    "assert all(func_type in ['price', 'swig', 'vol'] for func_type in FUNCS.keys())\n",
    "PARAMETER = [\n",
    "    {'timeperiod': 5}, {'timeperiod': 10}, {'timeperiod': 15}, \n",
    "         {'timeperiod': 20}, {'timeperiod': 25}, {'timeperiod': 30}\n",
    "]\n",
    "specs += [\n",
    "        {\n",
    "            'symbol': 'TXF',\n",
    "            'type': func_type,\n",
    "            'freq': '1D',\n",
    "            'func': func, \n",
    "            'args': param\n",
    "        } \n",
    "        for param in PARAMETER\n",
    "        for func_type, funcs in FUNCS.items()\n",
    "        for func in funcs\n",
    "    ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "lines_to_next_cell": 2
   },
   "outputs": [],
   "source": [
    "# OBV\n",
    "FUNCS = {\n",
    "    'vol': ['OBV'],\n",
    "}\n",
    "assert all(func_type in ['price', 'swig', 'vol'] for func_type in FUNCS.keys())\n",
    "PARAMETER = [\n",
    "    {}\n",
    "]\n",
    "specs += [\n",
    "        {\n",
    "            'symbol': 'TXF',\n",
    "            'type': func_type,\n",
    "            'freq': '1D',\n",
    "            'func': func, \n",
    "            'args': param\n",
    "        } \n",
    "        for param in PARAMETER\n",
    "        for func_type, funcs in FUNCS.items()\n",
    "        for func in funcs\n",
    "    ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "lines_to_next_cell": 2
   },
   "outputs": [],
   "source": [
    "# RSI\n",
    "FUNCS = {\n",
    "    'swig': ['RSI'],\n",
    "}\n",
    "assert all(func_type in ['price', 'swig', 'vol'] for func_type in FUNCS.keys())\n",
    "PARAMETER = [\n",
    "    {'timeperiod': 5}, {'timeperiod': 14}, {'timeperiod': 25}\n",
    "]\n",
    "specs += [\n",
    "        {\n",
    "            'symbol': 'TXF',\n",
    "            'type': func_type,\n",
    "            'freq': '1D',\n",
    "            'func': func, \n",
    "            'args': param\n",
    "        } \n",
    "        for param in PARAMETER\n",
    "        for func_type, funcs in FUNCS.items()\n",
    "        for func in funcs\n",
    "    ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "lines_to_next_cell": 2
   },
   "outputs": [],
   "source": [
    "# SAR\n",
    "FUNCS = {\n",
    "    'swig': ['SAR'],\n",
    "}\n",
    "assert all(func_type in ['price', 'swig', 'vol'] for func_type in FUNCS.keys())\n",
    "\n",
    "PARAMETER = [\n",
    "    {\n",
    "        'acceleration': 0.02,\n",
    "        'maximum': 0.2   \n",
    "    }\n",
    "]\n",
    "specs += [\n",
    "        {\n",
    "            'symbol': 'TXF',\n",
    "            'type': func_type,\n",
    "            'freq': '1D',\n",
    "            'func': func, \n",
    "            'args': param\n",
    "        } \n",
    "        for param in PARAMETER\n",
    "        for func_type, funcs in FUNCS.items()\n",
    "        for func in funcs\n",
    "    ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# SMA\n",
    "FUNCS = {\n",
    "    'price': ['SMA'],\n",
    "}\n",
    "assert all(func_type in ['price', 'swig', 'vol'] for func_type in FUNCS.keys())\n",
    "PARAMETER = [\n",
    "    {'timeperiod': 5}, {'timeperiod': 10}, {'timeperiod': 15}, \n",
    "         {'timeperiod': 20}, {'timeperiod': 25}, {'timeperiod': 30}\n",
    "]\n",
    "specs += [\n",
    "        {\n",
    "            'symbol': 'TXF',\n",
    "            'type': func_type,\n",
    "            'freq': '1D',\n",
    "            'func': func, \n",
    "            'args': param\n",
    "        } \n",
    "        for param in PARAMETER\n",
    "        for func_type, funcs in FUNCS.items()\n",
    "        for func in funcs\n",
    "    ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_single_feature(spec):\n",
    "    df_feature = (\n",
    "        resampler.get_OHLCV_given_frequency(spec['symbol'], spec['freq']).\n",
    "        pipe(fg.generate_root_feature, spec=spec)\n",
    "    )\n",
    "    return df_feature\n",
    "\n",
    "def get_featrues(specs, nlags=5, cache=False, add_diff=False):\n",
    "    cache_file = 'X.csv'\n",
    "    if cache:\n",
    "        if os.path.exists(cache_file):\n",
    "            df_features = pd.read_csv(cache_file, index_col=0)\n",
    "            df_features.index = pd.to_datetime(df_features.index, format='%Y-%m-%d %H:%M:%S')\n",
    "            return df_features\n",
    "        \n",
    "    df_features = pd.concat([\n",
    "        get_single_feature(spec).pipe(fg.extend_by_nlags, spec='', nlags=nlags)\n",
    "        for spec in specs\n",
    "    ], axis=1)\n",
    "\n",
    "    colnames = []\n",
    "    for idx_spec in range(len(specs)):\n",
    "        colnames += list(map(lambda x: f'{idx_spec}_{x}', df_features.columns[idx_spec*nlags: (idx_spec+1)*nlags]))\n",
    "    df_features.columns = colnames\n",
    "    \n",
    "    if add_diff:\n",
    "        df_features = add_diff(df_features)\n",
    "    df_features.to_csv(cache_file, index=True)\n",
    "    return df_features\n",
    "\n",
    "from itertools import combinations\n",
    "def add_diff(df_features):\n",
    "    df = df_features.copy()\n",
    "    for i,j in combinations(df_features.columns, 2):\n",
    "        df[f'diff_{i}_{j}'] = df[i] - df[j]\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 97367270 has generated.\n",
      "feature 97367270_lag1 has generated.\n",
      "feature 97367270_lag2 has generated.\n",
      "feature 97367270_lag3 has generated.\n",
      "feature 97367270_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 68488648 has generated.\n",
      "feature 68488648_lag1 has generated.\n",
      "feature 68488648_lag2 has generated.\n",
      "feature 68488648_lag3 has generated.\n",
      "feature 68488648_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 56494646 has generated.\n",
      "feature 56494646_lag1 has generated.\n",
      "feature 56494646_lag2 has generated.\n",
      "feature 56494646_lag3 has generated.\n",
      "feature 56494646_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 62918036 has generated.\n",
      "feature 62918036_lag1 has generated.\n",
      "feature 62918036_lag2 has generated.\n",
      "feature 62918036_lag3 has generated.\n",
      "feature 62918036_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 09904850 has generated.\n",
      "feature 09904850_lag1 has generated.\n",
      "feature 09904850_lag2 has generated.\n",
      "feature 09904850_lag3 has generated.\n",
      "feature 09904850_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 41716908 has generated.\n",
      "feature 41716908_lag1 has generated.\n",
      "feature 41716908_lag2 has generated.\n",
      "feature 41716908_lag3 has generated.\n",
      "feature 41716908_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 22224505 has generated.\n",
      "feature 22224505_lag1 has generated.\n",
      "feature 22224505_lag2 has generated.\n",
      "feature 22224505_lag3 has generated.\n",
      "feature 22224505_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 65400347 has generated.\n",
      "feature 65400347_lag1 has generated.\n",
      "feature 65400347_lag2 has generated.\n",
      "feature 65400347_lag3 has generated.\n",
      "feature 65400347_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 79649739 has generated.\n",
      "feature 79649739_lag1 has generated.\n",
      "feature 79649739_lag2 has generated.\n",
      "feature 79649739_lag3 has generated.\n",
      "feature 79649739_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 96290600 has generated.\n",
      "feature 96290600_lag1 has generated.\n",
      "feature 96290600_lag2 has generated.\n",
      "feature 96290600_lag3 has generated.\n",
      "feature 96290600_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 38805934 has generated.\n",
      "feature 38805934_lag1 has generated.\n",
      "feature 38805934_lag2 has generated.\n",
      "feature 38805934_lag3 has generated.\n",
      "feature 38805934_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 70807987 has generated.\n",
      "feature 70807987_lag1 has generated.\n",
      "feature 70807987_lag2 has generated.\n",
      "feature 70807987_lag3 has generated.\n",
      "feature 70807987_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 05846388 has generated.\n",
      "feature 05846388_lag1 has generated.\n",
      "feature 05846388_lag2 has generated.\n",
      "feature 05846388_lag3 has generated.\n",
      "feature 05846388_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 60827192 has generated.\n",
      "feature 60827192_lag1 has generated.\n",
      "feature 60827192_lag2 has generated.\n",
      "feature 60827192_lag3 has generated.\n",
      "feature 60827192_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 32678710 has generated.\n",
      "feature 32678710_lag1 has generated.\n",
      "feature 32678710_lag2 has generated.\n",
      "feature 32678710_lag3 has generated.\n",
      "feature 32678710_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 09074581 has generated.\n",
      "feature 09074581_lag1 has generated.\n",
      "feature 09074581_lag2 has generated.\n",
      "feature 09074581_lag3 has generated.\n",
      "feature 09074581_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 95740378 has generated.\n",
      "feature 95740378_lag1 has generated.\n",
      "feature 95740378_lag2 has generated.\n",
      "feature 95740378_lag3 has generated.\n",
      "feature 95740378_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 79761808 has generated.\n",
      "feature 79761808_lag1 has generated.\n",
      "feature 79761808_lag2 has generated.\n",
      "feature 79761808_lag3 has generated.\n",
      "feature 79761808_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 40585393 has generated.\n",
      "feature 40585393_lag1 has generated.\n",
      "feature 40585393_lag2 has generated.\n",
      "feature 40585393_lag3 has generated.\n",
      "feature 40585393_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 23530526 has generated.\n",
      "feature 23530526_lag1 has generated.\n",
      "feature 23530526_lag2 has generated.\n",
      "feature 23530526_lag3 has generated.\n",
      "feature 23530526_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 64738114 has generated.\n",
      "feature 64738114_lag1 has generated.\n",
      "feature 64738114_lag2 has generated.\n",
      "feature 64738114_lag3 has generated.\n",
      "feature 64738114_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 35321937 has generated.\n",
      "feature 35321937_lag1 has generated.\n",
      "feature 35321937_lag2 has generated.\n",
      "feature 35321937_lag3 has generated.\n",
      "feature 35321937_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 16853914 has generated.\n",
      "feature 16853914_lag1 has generated.\n",
      "feature 16853914_lag2 has generated.\n",
      "feature 16853914_lag3 has generated.\n",
      "feature 16853914_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 73272611 has generated.\n",
      "feature 73272611_lag1 has generated.\n",
      "feature 73272611_lag2 has generated.\n",
      "feature 73272611_lag3 has generated.\n",
      "feature 73272611_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 98447210 has generated.\n",
      "feature 98447210_lag1 has generated.\n",
      "feature 98447210_lag2 has generated.\n",
      "feature 98447210_lag3 has generated.\n",
      "feature 98447210_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 18654221 has generated.\n",
      "feature 18654221_lag1 has generated.\n",
      "feature 18654221_lag2 has generated.\n",
      "feature 18654221_lag3 has generated.\n",
      "feature 18654221_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 86775622 has generated.\n",
      "feature 86775622_lag1 has generated.\n",
      "feature 86775622_lag2 has generated.\n",
      "feature 86775622_lag3 has generated.\n",
      "feature 86775622_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 29303935 has generated.\n",
      "feature 29303935_lag1 has generated.\n",
      "feature 29303935_lag2 has generated.\n",
      "feature 29303935_lag3 has generated.\n",
      "feature 29303935_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 95895325 has generated.\n",
      "feature 95895325_lag1 has generated.\n",
      "feature 95895325_lag2 has generated.\n",
      "feature 95895325_lag3 has generated.\n",
      "feature 95895325_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 79527895 has generated.\n",
      "feature 79527895_lag1 has generated.\n",
      "feature 79527895_lag2 has generated.\n",
      "feature 79527895_lag3 has generated.\n",
      "feature 79527895_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 20968309 has generated.\n",
      "feature 20968309_lag1 has generated.\n",
      "feature 20968309_lag2 has generated.\n",
      "feature 20968309_lag3 has generated.\n",
      "feature 20968309_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 43266536 has generated.\n",
      "feature 43266536_lag1 has generated.\n",
      "feature 43266536_lag2 has generated.\n",
      "feature 43266536_lag3 has generated.\n",
      "feature 43266536_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 38155758 has generated.\n",
      "feature 38155758_lag1 has generated.\n",
      "feature 38155758_lag2 has generated.\n",
      "feature 38155758_lag3 has generated.\n",
      "feature 38155758_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 98334683 has generated.\n",
      "feature 98334683_lag1 has generated.\n",
      "feature 98334683_lag2 has generated.\n",
      "feature 98334683_lag3 has generated.\n",
      "feature 98334683_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 08737879 has generated.\n",
      "feature 08737879_lag1 has generated.\n",
      "feature 08737879_lag2 has generated.\n",
      "feature 08737879_lag3 has generated.\n",
      "feature 08737879_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 31387256 has generated.\n",
      "feature 31387256_lag1 has generated.\n",
      "feature 31387256_lag2 has generated.\n",
      "feature 31387256_lag3 has generated.\n",
      "feature 31387256_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 85906314 has generated.\n",
      "feature 85906314_lag1 has generated.\n",
      "feature 85906314_lag2 has generated.\n",
      "feature 85906314_lag3 has generated.\n",
      "feature 85906314_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 42576887 has generated.\n",
      "feature 42576887_lag1 has generated.\n",
      "feature 42576887_lag2 has generated.\n",
      "feature 42576887_lag3 has generated.\n",
      "feature 42576887_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 29362743 has generated.\n",
      "feature 29362743_lag1 has generated.\n",
      "feature 29362743_lag2 has generated.\n",
      "feature 29362743_lag3 has generated.\n",
      "feature 29362743_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 96105422 has generated.\n",
      "feature 96105422_lag1 has generated.\n",
      "feature 96105422_lag2 has generated.\n",
      "feature 96105422_lag3 has generated.\n",
      "feature 96105422_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 77356892 has generated.\n",
      "feature 77356892_lag1 has generated.\n",
      "feature 77356892_lag2 has generated.\n",
      "feature 77356892_lag3 has generated.\n",
      "feature 77356892_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 01615041 has generated.\n",
      "feature 01615041_lag1 has generated.\n",
      "feature 01615041_lag2 has generated.\n",
      "feature 01615041_lag3 has generated.\n",
      "feature 01615041_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 72391189 has generated.\n",
      "feature 72391189_lag1 has generated.\n",
      "feature 72391189_lag2 has generated.\n",
      "feature 72391189_lag3 has generated.\n",
      "feature 72391189_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 05236104 has generated.\n",
      "feature 05236104_lag1 has generated.\n",
      "feature 05236104_lag2 has generated.\n",
      "feature 05236104_lag3 has generated.\n",
      "feature 05236104_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 64835975 has generated.\n",
      "feature 64835975_lag1 has generated.\n",
      "feature 64835975_lag2 has generated.\n",
      "feature 64835975_lag3 has generated.\n",
      "feature 64835975_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 01082365 has generated.\n",
      "feature 01082365_lag1 has generated.\n",
      "feature 01082365_lag2 has generated.\n",
      "feature 01082365_lag3 has generated.\n",
      "feature 01082365_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 94111142 has generated.\n",
      "feature 94111142_lag1 has generated.\n",
      "feature 94111142_lag2 has generated.\n",
      "feature 94111142_lag3 has generated.\n",
      "feature 94111142_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 84940937 has generated.\n",
      "feature 84940937_lag1 has generated.\n",
      "feature 84940937_lag2 has generated.\n",
      "feature 84940937_lag3 has generated.\n",
      "feature 84940937_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 72243738 has generated.\n",
      "feature 72243738_lag1 has generated.\n",
      "feature 72243738_lag2 has generated.\n",
      "feature 72243738_lag3 has generated.\n",
      "feature 72243738_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 63872636 has generated.\n",
      "feature 63872636_lag1 has generated.\n",
      "feature 63872636_lag2 has generated.\n",
      "feature 63872636_lag3 has generated.\n",
      "feature 63872636_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 12082156 has generated.\n",
      "feature 12082156_lag1 has generated.\n",
      "feature 12082156_lag2 has generated.\n",
      "feature 12082156_lag3 has generated.\n",
      "feature 12082156_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 68213521 has generated.\n",
      "feature 68213521_lag1 has generated.\n",
      "feature 68213521_lag2 has generated.\n",
      "feature 68213521_lag3 has generated.\n",
      "feature 68213521_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 27257567 has generated.\n",
      "feature 27257567_lag1 has generated.\n",
      "feature 27257567_lag2 has generated.\n",
      "feature 27257567_lag3 has generated.\n",
      "feature 27257567_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 65532996 has generated.\n",
      "feature 65532996_lag1 has generated.\n",
      "feature 65532996_lag2 has generated.\n",
      "feature 65532996_lag3 has generated.\n",
      "feature 65532996_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 66701434 has generated.\n",
      "feature 66701434_lag1 has generated.\n",
      "feature 66701434_lag2 has generated.\n",
      "feature 66701434_lag3 has generated.\n",
      "feature 66701434_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 92195671 has generated.\n",
      "feature 92195671_lag1 has generated.\n",
      "feature 92195671_lag2 has generated.\n",
      "feature 92195671_lag3 has generated.\n",
      "feature 92195671_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 38690895 has generated.\n",
      "feature 38690895_lag1 has generated.\n",
      "feature 38690895_lag2 has generated.\n",
      "feature 38690895_lag3 has generated.\n",
      "feature 38690895_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 56076046 has generated.\n",
      "feature 56076046_lag1 has generated.\n",
      "feature 56076046_lag2 has generated.\n",
      "feature 56076046_lag3 has generated.\n",
      "feature 56076046_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 92248921 has generated.\n",
      "feature 92248921_lag1 has generated.\n",
      "feature 92248921_lag2 has generated.\n",
      "feature 92248921_lag3 has generated.\n",
      "feature 92248921_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 84331432 has generated.\n",
      "feature 84331432_lag1 has generated.\n",
      "feature 84331432_lag2 has generated.\n",
      "feature 84331432_lag3 has generated.\n",
      "feature 84331432_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 74430244 has generated.\n",
      "feature 74430244_lag1 has generated.\n",
      "feature 74430244_lag2 has generated.\n",
      "feature 74430244_lag3 has generated.\n",
      "feature 74430244_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 44070915 has generated.\n",
      "feature 44070915_lag1 has generated.\n",
      "feature 44070915_lag2 has generated.\n",
      "feature 44070915_lag3 has generated.\n",
      "feature 44070915_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 62755712 has generated.\n",
      "feature 62755712_lag1 has generated.\n",
      "feature 62755712_lag2 has generated.\n",
      "feature 62755712_lag3 has generated.\n",
      "feature 62755712_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 76453313 has generated.\n",
      "feature 76453313_lag1 has generated.\n",
      "feature 76453313_lag2 has generated.\n",
      "feature 76453313_lag3 has generated.\n",
      "feature 76453313_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 55471756 has generated.\n",
      "feature 55471756_lag1 has generated.\n",
      "feature 55471756_lag2 has generated.\n",
      "feature 55471756_lag3 has generated.\n",
      "feature 55471756_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 88127301 has generated.\n",
      "feature 88127301_lag1 has generated.\n",
      "feature 88127301_lag2 has generated.\n",
      "feature 88127301_lag3 has generated.\n",
      "feature 88127301_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 00957305 has generated.\n",
      "feature 00957305_lag1 has generated.\n",
      "feature 00957305_lag2 has generated.\n",
      "feature 00957305_lag3 has generated.\n",
      "feature 00957305_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 46067661 has generated.\n",
      "feature 46067661_lag1 has generated.\n",
      "feature 46067661_lag2 has generated.\n",
      "feature 46067661_lag3 has generated.\n",
      "feature 46067661_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 37865502 has generated.\n",
      "feature 37865502_lag1 has generated.\n",
      "feature 37865502_lag2 has generated.\n",
      "feature 37865502_lag3 has generated.\n",
      "feature 37865502_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 48032436 has generated.\n",
      "feature 48032436_lag1 has generated.\n",
      "feature 48032436_lag2 has generated.\n",
      "feature 48032436_lag3 has generated.\n",
      "feature 48032436_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 27939058 has generated.\n",
      "feature 27939058_lag1 has generated.\n",
      "feature 27939058_lag2 has generated.\n",
      "feature 27939058_lag3 has generated.\n",
      "feature 27939058_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 23569330 has generated.\n",
      "feature 23569330_lag1 has generated.\n",
      "feature 23569330_lag2 has generated.\n",
      "feature 23569330_lag3 has generated.\n",
      "feature 23569330_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 22166205 has generated.\n",
      "feature 22166205_lag1 has generated.\n",
      "feature 22166205_lag2 has generated.\n",
      "feature 22166205_lag3 has generated.\n",
      "feature 22166205_lag4 has generated.\n",
      "transformed OHLCV at frequency 1D\n",
      "reading cache of TXF in 1D OHLCV\n",
      "feature: 49320730 has generated.\n",
      "feature 49320730_lag1 has generated.\n",
      "feature 49320730_lag2 has generated.\n",
      "feature 49320730_lag3 has generated.\n",
      "feature 49320730_lag4 has generated.\n",
      "> \u001b[0;32m<ipython-input-32-ba57931453f0>\u001b[0m(7)\u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32m      4 \u001b[0;31m    \u001b[0;32massert\u001b[0m \u001b[0mdf_features\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mspecs\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mnlags\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0m\u001b[0;32m      5 \u001b[0;31m    \u001b[0;32mimport\u001b[0m \u001b[0mpdb\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0m\u001b[0;32m      6 \u001b[0;31m    \u001b[0mpdb\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_trace\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0m\u001b[0;32m----> 7 \u001b[0;31m    \u001b[0mdf_features\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mto_csv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'X'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0m\u001b[0;32m      8 \u001b[0;31m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0m\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "ipdb>  df_features.head()\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                     0_97367270  0_97367270_lag1  0_97367270_lag2  \\\n",
      "2011-01-03 13:45:00         NaN              NaN              NaN   \n",
      "2011-01-04 13:45:00         NaN              NaN              NaN   \n",
      "2011-01-05 13:45:00         NaN              NaN              NaN   \n",
      "2011-01-06 13:45:00         NaN              NaN              NaN   \n",
      "2011-01-07 13:45:00      8891.6              NaN              NaN   \n",
      "\n",
      "                     0_97367270_lag3  0_97367270_lag4   1_68488648  \\\n",
      "2011-01-03 13:45:00              NaN              NaN          NaN   \n",
      "2011-01-04 13:45:00              NaN              NaN          NaN   \n",
      "2011-01-05 13:45:00              NaN              NaN          NaN   \n",
      "2011-01-06 13:45:00              NaN              NaN          NaN   \n",
      "2011-01-07 13:45:00              NaN              NaN  9084.566733   \n",
      "\n",
      "                     1_68488648_lag1  1_68488648_lag2  1_68488648_lag3  \\\n",
      "2011-01-03 13:45:00              NaN              NaN              NaN   \n",
      "2011-01-04 13:45:00              NaN              NaN              NaN   \n",
      "2011-01-05 13:45:00              NaN              NaN              NaN   \n",
      "2011-01-06 13:45:00              NaN              NaN              NaN   \n",
      "2011-01-07 13:45:00              NaN              NaN              NaN   \n",
      "\n",
      "                     1_68488648_lag4  ...  72_22166205  72_22166205_lag1  \\\n",
      "2011-01-03 13:45:00              NaN  ...          NaN               NaN   \n",
      "2011-01-04 13:45:00              NaN  ...          NaN               NaN   \n",
      "2011-01-05 13:45:00              NaN  ...          NaN               NaN   \n",
      "2011-01-06 13:45:00              NaN  ...          NaN               NaN   \n",
      "2011-01-07 13:45:00              NaN  ...          NaN               NaN   \n",
      "\n",
      "                     72_22166205_lag2  72_22166205_lag3  72_22166205_lag4  \\\n",
      "2011-01-03 13:45:00               NaN               NaN               NaN   \n",
      "2011-01-04 13:45:00               NaN               NaN               NaN   \n",
      "2011-01-05 13:45:00               NaN               NaN               NaN   \n",
      "2011-01-06 13:45:00               NaN               NaN               NaN   \n",
      "2011-01-07 13:45:00               NaN               NaN               NaN   \n",
      "\n",
      "                     73_49320730  73_49320730_lag1  73_49320730_lag2  \\\n",
      "2011-01-03 13:45:00          NaN               NaN               NaN   \n",
      "2011-01-04 13:45:00          NaN               NaN               NaN   \n",
      "2011-01-05 13:45:00          NaN               NaN               NaN   \n",
      "2011-01-06 13:45:00          NaN               NaN               NaN   \n",
      "2011-01-07 13:45:00          NaN               NaN               NaN   \n",
      "\n",
      "                     73_49320730_lag3  73_49320730_lag4  \n",
      "2011-01-03 13:45:00               NaN               NaN  \n",
      "2011-01-04 13:45:00               NaN               NaN  \n",
      "2011-01-05 13:45:00               NaN               NaN  \n",
      "2011-01-06 13:45:00               NaN               NaN  \n",
      "2011-01-07 13:45:00               NaN               NaN  \n",
      "\n",
      "[5 rows x 370 columns]\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "ipdb>  q\n"
     ]
    },
    {
     "ename": "BdbQuit",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mBdbQuit\u001b[0m                                   Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-32-ba57931453f0>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      5\u001b[0m     \u001b[0;32mimport\u001b[0m \u001b[0mpdb\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m     \u001b[0mpdb\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_trace\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 7\u001b[0;31m     \u001b[0mdf_features\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mto_csv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'X'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      8\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m<ipython-input-32-ba57931453f0>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      5\u001b[0m     \u001b[0;32mimport\u001b[0m \u001b[0mpdb\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m     \u001b[0mpdb\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_trace\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 7\u001b[0;31m     \u001b[0mdf_features\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mto_csv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'X'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      8\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/stock_path_tracker/lib/python3.8/bdb.py\u001b[0m in \u001b[0;36mtrace_dispatch\u001b[0;34m(self, frame, event, arg)\u001b[0m\n\u001b[1;32m     86\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0;31m# None\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     87\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mevent\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'line'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 88\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdispatch_line\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mframe\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     89\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mevent\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'call'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     90\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdispatch_call\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mframe\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0marg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/stock_path_tracker/lib/python3.8/bdb.py\u001b[0m in \u001b[0;36mdispatch_line\u001b[0;34m(self, frame)\u001b[0m\n\u001b[1;32m    111\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstop_here\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mframe\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbreak_here\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mframe\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    112\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0muser_line\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mframe\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 113\u001b[0;31m             \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mquitting\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;32mraise\u001b[0m \u001b[0mBdbQuit\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    114\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtrace_dispatch\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    115\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mBdbQuit\u001b[0m: "
     ]
    }
   ],
   "source": [
    "if __name__ == '__main__':\n",
    "    nlags=5\n",
    "    df_features = get_featrues(specs, nlags, add_diff=False)\n",
    "#     assert df_features.shape[1] == len(specs) * nlags\n",
    "    \n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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