QI_Infarctus.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from importlib import reload  \n",
    "import pandas as pd\n",
    "\n",
    "import clintraj_qi\n",
    "\n",
    "from clintraj_qi import quantify_nans\n",
    "from clintraj_qi import detect_variable_type\n",
    "from clintraj_qi import quantify_dataframe_univariate\n",
    "from clintraj_qi import SVDcomplete_imputation_method\n",
    "from clintraj_qi import load_quantification_info\n",
    "from clintraj_qi import invert_quant_info\n",
    "from clintraj_qi import dequantify_table\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
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       "<p>1574 rows × 124 columns</p>\n",
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      ],
      "text/plain": [
       "        ID   AGE  SEX  INF_ANAM  STENOK_AN  FK_STENOK  IBS_POST   GB  \\\n",
       "0        1  77.0    1       2.0        1.0        1.0       2.0  3.0   \n",
       "1        2  55.0    1       1.0        0.0        0.0       0.0  0.0   \n",
       "2        3  52.0    1       0.0        0.0        0.0       2.0  2.0   \n",
       "3        4  68.0    0       0.0        0.0        0.0       2.0  2.0   \n",
       "4        5  60.0    1       0.0        0.0        0.0       2.0  3.0   \n",
       "...    ...   ...  ...       ...        ...        ...       ...  ...   \n",
       "1569  1695  77.0    0       0.0        0.0        0.0       0.0  2.0   \n",
       "1570  1696  77.0    0       0.0        4.0        2.0       1.0  2.0   \n",
       "1571  1697  70.0    0       0.0        6.0        2.0       1.0  2.0   \n",
       "1572  1699  79.0    0       2.0        2.0        2.0       1.0  2.0   \n",
       "1573  1700  63.0    1       2.0        NaN        NaN       NaN  2.0   \n",
       "\n",
       "      SIM_GIPERT  DLIT_AG  ...  REC_IM  P_IM_STEN  LET_IS_0  LET_IS_1  \\\n",
       "0            0.0      7.0  ...       0        0.0         1         0   \n",
       "1            0.0      0.0  ...       0        0.0         1         0   \n",
       "2            0.0      2.0  ...       0        0.0         1         0   \n",
       "3            0.0      3.0  ...       0        0.0         1         0   \n",
       "4            0.0      7.0  ...       0        0.0         1         0   \n",
       "...          ...      ...  ...     ...        ...       ...       ...   \n",
       "1569         0.0      7.0  ...       0        0.0         0         0   \n",
       "1570         0.0      7.0  ...       0        0.0         0         0   \n",
       "1571         0.0      7.0  ...       0        0.0         0         1   \n",
       "1572         0.0      7.0  ...       0        0.0         0         1   \n",
       "1573         0.0      NaN  ...       0        0.0         0         1   \n",
       "\n",
       "      LET_IS_2  LET_IS_3  LET_IS_4  LET_IS_5  LET_IS_6  LET_IS_7  \n",
       "0            0         0         0         0         0         0  \n",
       "1            0         0         0         0         0         0  \n",
       "2            0         0         0         0         0         0  \n",
       "3            0         0         0         0         0         0  \n",
       "4            0         0         0         0         0         0  \n",
       "...        ...       ...       ...       ...       ...       ...  \n",
       "1569         0         1         0         0         0         0  \n",
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       "1572         0         0         0         0         0         0  \n",
       "1573         0         0         0         0         0         0  \n",
       "\n",
       "[1574 rows x 124 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# loading the table\n",
    "\n",
    "file = 'data/infarction/all_dummies.txt'\n",
    "df = pd.read_csv(file,delimiter='\\t')\n",
    "display(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Missing values 4780 (2.468982758442578%)\n",
      "Number of complete rows: 533 (33.86277001270648%)\n"
     ]
    }
   ],
   "source": [
    "quantify_nans(df,file_to_write=file[:-4]+'_complete.txt')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "variable_types, binary, continuous, ordinal = detect_variable_type(df,10,verbose=False)\n",
    "#correct_column_types_in_dataframe(df,variable_types)\n",
    "#variable_types, binary, continuous, ordinal = detect_variable_type(df,10,verbose=True)\n",
    "    \n",
    "df[binary].to_csv(file[:-4]+'_binary.txt', index=False,sep='\\t')\n",
    "df[continuous].to_csv(file[:-4]+'_continuous.txt', index=False,sep='\\t')\n",
    "df[ordinal].to_csv(file[:-4]+'_ordinal.txt', index=False,sep='\\t')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "STENOK_AN\tFK_STENOK\t0.8571367770625654\n",
      "FK_STENOK\tSTENOK_AN\t0.8571367770625654\n",
      "S_AD_ORIT\tD_AD_ORIT\t0.8390942067580507\n",
      "D_AD_ORIT\tS_AD_ORIT\t0.8390942067580507\n",
      "MP_TP_POST\tritm_ecg_p_02\t0.8441447275002549\n",
      "ritm_ecg_p_02\tMP_TP_POST\t0.8441447275002549\n",
      "RAZRIV\tLET_IS_3\t1.0\n",
      "LET_IS_3\tRAZRIV\t1.0\n"
     ]
    }
   ],
   "source": [
    "# analyzing correlations between all columns, in order to detect tightly correlated variables\n",
    "# the hope is it can be used to fill in part of the missing values using a naive approach\n",
    "\n",
    "corr_table = df.corr(method='spearman')\n",
    "# display(corr_table)\n",
    "\n",
    "# print strong variable correlations\n",
    "correlation_threshold = 0.8\n",
    "\n",
    "for v in corr_table.items():\n",
    "    for val in v[1].items():\n",
    "        corr = val[1]\n",
    "        name = val[0]\n",
    "        if not name==v[0]:\n",
    "            if corr>=correlation_threshold:\n",
    "                print(v[0]+'\\t'+name+'\\t'+str(corr))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "# naive imputation of values based on variable similarity (not yet implemented)\n",
    "# redundant_pair = ('MP_TP_POST','ritm_ecg_p_02') \n",
    "# binary = True\n",
    "# if binary:\n",
    "#    df_imputed = binary_naive_imputation(df,redundant_pair)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# univariate table quantification\n",
    "dfq,replacement_info = quantify_dataframe_univariate(df,variable_types)\n",
    "#display(dfq)\n",
    "#print(replacement_info)\n",
    "with open(file[:-4]+'_norm_info.txt','w') as fid:\n",
    "    fid.write(replacement_info)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/zinovyev/anaconda3/lib/python3.7/site-packages/numpy/lib/histograms.py:839: RuntimeWarning: invalid value encountered in greater_equal\n",
      "  keep = (tmp_a >= first_edge)\n",
      "/home/zinovyev/anaconda3/lib/python3.7/site-packages/numpy/lib/histograms.py:840: RuntimeWarning: invalid value encountered in less_equal\n",
      "  keep &= (tmp_a <= last_edge)\n"
     ]
    },
    {
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\n",
      "text/plain": [
       "<Figure size 1152x792 with 22 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# univariate table quantification, check histograms for different variable types\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "dframe = dfq\n",
    "\n",
    "nbins = int(dframe.shape[0]/50)\n",
    "#var_type = 'CONTINUOUS'\n",
    "var_type = 'ORDINAL'\n",
    "#var_type = 'BINARY'\n",
    "\n",
    "ncont = variable_types.count(var_type)\n",
    "plt.figure(figsize=(16,ncont/4*2))\n",
    "plt.subplots_adjust(hspace=0.5,top=3)\n",
    "\n",
    "k = 1\n",
    "for i,v in enumerate(variable_types):\n",
    "    if v==var_type:\n",
    "        plt.subplot(ncont,4,k)\n",
    "        col = dframe.columns[i+1]\n",
    "        vals = dframe[col].to_numpy()\n",
    "        plt.hist(vals,bins=nbins)\n",
    "        plt.title(col)\n",
    "        k = k+1\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Matrix shape: (533, 123)\n",
      "Effective linear dimension 24\n",
      "Full matrix shape (1574, 123)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>AGE</th>\n",
       "      <th>SEX</th>\n",
       "      <th>INF_ANAM</th>\n",
       "      <th>STENOK_AN</th>\n",
       "      <th>FK_STENOK</th>\n",
       "      <th>IBS_POST</th>\n",
       "      <th>GB</th>\n",
       "      <th>SIM_GIPERT</th>\n",
       "      <th>DLIT_AG</th>\n",
       "      <th>...</th>\n",
       "      <th>REC_IM</th>\n",
       "      <th>P_IM_STEN</th>\n",
       "      <th>LET_IS_0</th>\n",
       "      <th>LET_IS_1</th>\n",
       "      <th>LET_IS_2</th>\n",
       "      <th>LET_IS_3</th>\n",
       "      <th>LET_IS_4</th>\n",
       "      <th>LET_IS_5</th>\n",
       "      <th>LET_IS_6</th>\n",
       "      <th>LET_IS_7</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1.352878</td>\n",
       "      <td>0.210873</td>\n",
       "      <td>1.303131</td>\n",
       "      <td>-0.021130</td>\n",
       "      <td>-0.200314</td>\n",
       "      <td>0.485205</td>\n",
       "      <td>1.232888</td>\n",
       "      <td>-0.059345</td>\n",
       "      <td>1.038212</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.12977</td>\n",
       "      <td>-0.122575</td>\n",
       "      <td>0.066089</td>\n",
       "      <td>-0.101252</td>\n",
       "      <td>-0.024958</td>\n",
       "      <td>-0.063020</td>\n",
       "      <td>-0.02979</td>\n",
       "      <td>-0.018572</td>\n",
       "      <td>-0.032129</td>\n",
       "      <td>-0.035553</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>-0.585009</td>\n",
       "      <td>0.210873</td>\n",
       "      <td>0.630318</td>\n",
       "      <td>-0.743723</td>\n",
       "      <td>-0.834564</td>\n",
       "      <td>-0.870894</td>\n",
       "      <td>-0.887781</td>\n",
       "      <td>-0.059345</td>\n",
       "      <td>-0.884730</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.12977</td>\n",
       "      <td>-0.122575</td>\n",
       "      <td>0.066089</td>\n",
       "      <td>-0.101252</td>\n",
       "      <td>-0.024958</td>\n",
       "      <td>-0.063020</td>\n",
       "      <td>-0.02979</td>\n",
       "      <td>-0.018572</td>\n",
       "      <td>-0.032129</td>\n",
       "      <td>-0.035553</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>-0.849266</td>\n",
       "      <td>0.210873</td>\n",
       "      <td>-0.534430</td>\n",
       "      <td>-0.743723</td>\n",
       "      <td>-0.834564</td>\n",
       "      <td>0.485205</td>\n",
       "      <td>0.350100</td>\n",
       "      <td>-0.059345</td>\n",
       "      <td>-0.095930</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.12977</td>\n",
       "      <td>-0.122575</td>\n",
       "      <td>0.066089</td>\n",
       "      <td>-0.101252</td>\n",
       "      <td>-0.024958</td>\n",
       "      <td>-0.063020</td>\n",
       "      <td>-0.02979</td>\n",
       "      <td>-0.018572</td>\n",
       "      <td>-0.032129</td>\n",
       "      <td>-0.035553</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>0.560106</td>\n",
       "      <td>-0.355533</td>\n",
       "      <td>-0.534430</td>\n",
       "      <td>-0.743723</td>\n",
       "      <td>-0.834564</td>\n",
       "      <td>0.485205</td>\n",
       "      <td>0.350100</td>\n",
       "      <td>-0.059345</td>\n",
       "      <td>0.004838</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.12977</td>\n",
       "      <td>-0.122575</td>\n",
       "      <td>0.066089</td>\n",
       "      <td>-0.101252</td>\n",
       "      <td>-0.024958</td>\n",
       "      <td>-0.063020</td>\n",
       "      <td>-0.02979</td>\n",
       "      <td>-0.018572</td>\n",
       "      <td>-0.032129</td>\n",
       "      <td>-0.035553</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>-0.144580</td>\n",
       "      <td>0.210873</td>\n",
       "      <td>-0.534430</td>\n",
       "      <td>-0.743723</td>\n",
       "      <td>-0.834564</td>\n",
       "      <td>0.485205</td>\n",
       "      <td>1.232888</td>\n",
       "      <td>-0.059345</td>\n",
       "      <td>1.038212</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.12977</td>\n",
       "      <td>-0.122575</td>\n",
       "      <td>0.066089</td>\n",
       "      <td>-0.101252</td>\n",
       "      <td>-0.024958</td>\n",
       "      <td>-0.063020</td>\n",
       "      <td>-0.02979</td>\n",
       "      <td>-0.018572</td>\n",
       "      <td>-0.032129</td>\n",
       "      <td>-0.035553</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <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",
       "      <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",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1569</th>\n",
       "      <td>1695</td>\n",
       "      <td>1.352878</td>\n",
       "      <td>-0.355533</td>\n",
       "      <td>-0.534430</td>\n",
       "      <td>-0.743723</td>\n",
       "      <td>-0.834564</td>\n",
       "      <td>-0.870894</td>\n",
       "      <td>0.350100</td>\n",
       "      <td>-0.059345</td>\n",
       "      <td>1.038212</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.12977</td>\n",
       "      <td>-0.122575</td>\n",
       "      <td>-0.345075</td>\n",
       "      <td>-0.101252</td>\n",
       "      <td>-0.024958</td>\n",
       "      <td>1.808563</td>\n",
       "      <td>-0.02979</td>\n",
       "      <td>-0.018572</td>\n",
       "      <td>-0.032129</td>\n",
       "      <td>-0.035553</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1570</th>\n",
       "      <td>1696</td>\n",
       "      <td>1.352878</td>\n",
       "      <td>-0.355533</td>\n",
       "      <td>-0.534430</td>\n",
       "      <td>0.568705</td>\n",
       "      <td>0.510410</td>\n",
       "      <td>0.067104</td>\n",
       "      <td>0.350100</td>\n",
       "      <td>-0.059345</td>\n",
       "      <td>1.038212</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.12977</td>\n",
       "      <td>-0.122575</td>\n",
       "      <td>-0.345075</td>\n",
       "      <td>-0.101252</td>\n",
       "      <td>-0.024958</td>\n",
       "      <td>1.808563</td>\n",
       "      <td>-0.02979</td>\n",
       "      <td>-0.018572</td>\n",
       "      <td>-0.032129</td>\n",
       "      <td>-0.035553</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1571</th>\n",
       "      <td>1697</td>\n",
       "      <td>0.736278</td>\n",
       "      <td>-0.355533</td>\n",
       "      <td>-0.534430</td>\n",
       "      <td>0.887614</td>\n",
       "      <td>0.510410</td>\n",
       "      <td>0.067104</td>\n",
       "      <td>0.350100</td>\n",
       "      <td>-0.059345</td>\n",
       "      <td>1.038212</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.12977</td>\n",
       "      <td>-0.122575</td>\n",
       "      <td>-0.345075</td>\n",
       "      <td>1.508559</td>\n",
       "      <td>-0.024958</td>\n",
       "      <td>-0.063020</td>\n",
       "      <td>-0.02979</td>\n",
       "      <td>-0.018572</td>\n",
       "      <td>-0.032129</td>\n",
       "      <td>-0.035553</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1572</th>\n",
       "      <td>1699</td>\n",
       "      <td>1.529049</td>\n",
       "      <td>-0.355533</td>\n",
       "      <td>1.303131</td>\n",
       "      <td>0.201624</td>\n",
       "      <td>0.510410</td>\n",
       "      <td>0.067104</td>\n",
       "      <td>0.350100</td>\n",
       "      <td>-0.059345</td>\n",
       "      <td>1.038212</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.12977</td>\n",
       "      <td>-0.122575</td>\n",
       "      <td>-0.345075</td>\n",
       "      <td>1.508559</td>\n",
       "      <td>-0.024958</td>\n",
       "      <td>-0.063020</td>\n",
       "      <td>-0.02979</td>\n",
       "      <td>-0.018572</td>\n",
       "      <td>-0.032129</td>\n",
       "      <td>-0.035553</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1573</th>\n",
       "      <td>1700</td>\n",
       "      <td>0.119677</td>\n",
       "      <td>0.210873</td>\n",
       "      <td>1.303131</td>\n",
       "      <td>-0.021130</td>\n",
       "      <td>-0.200314</td>\n",
       "      <td>0.067104</td>\n",
       "      <td>0.350100</td>\n",
       "      <td>-0.059345</td>\n",
       "      <td>0.076070</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.12977</td>\n",
       "      <td>-0.122575</td>\n",
       "      <td>-0.345075</td>\n",
       "      <td>1.508559</td>\n",
       "      <td>-0.024958</td>\n",
       "      <td>-0.063020</td>\n",
       "      <td>-0.02979</td>\n",
       "      <td>-0.018572</td>\n",
       "      <td>-0.032129</td>\n",
       "      <td>-0.035553</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1574 rows × 124 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        ID       AGE       SEX  INF_ANAM  STENOK_AN  FK_STENOK  IBS_POST  \\\n",
       "0        1  1.352878  0.210873  1.303131  -0.021130  -0.200314  0.485205   \n",
       "1        2 -0.585009  0.210873  0.630318  -0.743723  -0.834564 -0.870894   \n",
       "2        3 -0.849266  0.210873 -0.534430  -0.743723  -0.834564  0.485205   \n",
       "3        4  0.560106 -0.355533 -0.534430  -0.743723  -0.834564  0.485205   \n",
       "4        5 -0.144580  0.210873 -0.534430  -0.743723  -0.834564  0.485205   \n",
       "...    ...       ...       ...       ...        ...        ...       ...   \n",
       "1569  1695  1.352878 -0.355533 -0.534430  -0.743723  -0.834564 -0.870894   \n",
       "1570  1696  1.352878 -0.355533 -0.534430   0.568705   0.510410  0.067104   \n",
       "1571  1697  0.736278 -0.355533 -0.534430   0.887614   0.510410  0.067104   \n",
       "1572  1699  1.529049 -0.355533  1.303131   0.201624   0.510410  0.067104   \n",
       "1573  1700  0.119677  0.210873  1.303131  -0.021130  -0.200314  0.067104   \n",
       "\n",
       "            GB  SIM_GIPERT   DLIT_AG  ...   REC_IM  P_IM_STEN  LET_IS_0  \\\n",
       "0     1.232888   -0.059345  1.038212  ... -0.12977  -0.122575  0.066089   \n",
       "1    -0.887781   -0.059345 -0.884730  ... -0.12977  -0.122575  0.066089   \n",
       "2     0.350100   -0.059345 -0.095930  ... -0.12977  -0.122575  0.066089   \n",
       "3     0.350100   -0.059345  0.004838  ... -0.12977  -0.122575  0.066089   \n",
       "4     1.232888   -0.059345  1.038212  ... -0.12977  -0.122575  0.066089   \n",
       "...        ...         ...       ...  ...      ...        ...       ...   \n",
       "1569  0.350100   -0.059345  1.038212  ... -0.12977  -0.122575 -0.345075   \n",
       "1570  0.350100   -0.059345  1.038212  ... -0.12977  -0.122575 -0.345075   \n",
       "1571  0.350100   -0.059345  1.038212  ... -0.12977  -0.122575 -0.345075   \n",
       "1572  0.350100   -0.059345  1.038212  ... -0.12977  -0.122575 -0.345075   \n",
       "1573  0.350100   -0.059345  0.076070  ... -0.12977  -0.122575 -0.345075   \n",
       "\n",
       "      LET_IS_1  LET_IS_2  LET_IS_3  LET_IS_4  LET_IS_5  LET_IS_6  LET_IS_7  \n",
       "0    -0.101252 -0.024958 -0.063020  -0.02979 -0.018572 -0.032129 -0.035553  \n",
       "1    -0.101252 -0.024958 -0.063020  -0.02979 -0.018572 -0.032129 -0.035553  \n",
       "2    -0.101252 -0.024958 -0.063020  -0.02979 -0.018572 -0.032129 -0.035553  \n",
       "3    -0.101252 -0.024958 -0.063020  -0.02979 -0.018572 -0.032129 -0.035553  \n",
       "4    -0.101252 -0.024958 -0.063020  -0.02979 -0.018572 -0.032129 -0.035553  \n",
       "...        ...       ...       ...       ...       ...       ...       ...  \n",
       "1569 -0.101252 -0.024958  1.808563  -0.02979 -0.018572 -0.032129 -0.035553  \n",
       "1570 -0.101252 -0.024958  1.808563  -0.02979 -0.018572 -0.032129 -0.035553  \n",
       "1571  1.508559 -0.024958 -0.063020  -0.02979 -0.018572 -0.032129 -0.035553  \n",
       "1572  1.508559 -0.024958 -0.063020  -0.02979 -0.018572 -0.032129 -0.035553  \n",
       "1573  1.508559 -0.024958 -0.063020  -0.02979 -0.018572 -0.032129 -0.035553  \n",
       "\n",
       "[1574 rows x 124 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x1080 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dfq_imputed = SVDcomplete_imputation_method(dfq, variable_types, verbose=True,num_components=-1)\n",
    "display(dfq_imputed)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# saving the quantified and imputed file\n",
    "#display(dfq_imputed)\n",
    "dfq_imputed.round(3).to_csv(file[:-4]+'_q_imp_SVDcomplete.txt',index=False,sep='\\t')\n",
    "\n",
    "# saving the de-quantified imputed file\n",
    "dequant_info = invert_quant_info(load_quantification_info(file[:-4]+'_norm_info.txt'))\n",
    "#print(dequant_info)\n",
    "\n",
    "df_imputed = dequantify_table(dfq_imputed,dequant_info)\n",
    "#display(df_imputed)\n",
    "\n",
    "df_imputed.to_csv(file[:-4]+'_imp_SVDcomplete.txt',index=False,sep='\\t')"
   ]
  }
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