14_CFScombinefiles.ipynb

{
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  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'\\ncombine all output files from 13_CFScrossdataset.py that was split up when run to increase comp time\\n\\nShaina Lu\\nZador & Gillis Labs\\nMay 2020\\n'"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\"\n",
    "combine all output files from 13_CFScrossdataset.py that was split up when run to increase comp time\n",
    "\n",
    "Shaina Lu\n",
    "Zador & Gillis Labs\n",
    "May 2020\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# ST to ABA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "def read4files(file1, file2, file3, file4):\n",
    "    file1 = pd.read_csv(file1, sep=',', index_col=False)\n",
    "    file1.set_index(file1.columns, inplace=True)\n",
    "    \n",
    "    file2 = pd.read_csv(file2, sep=',', index_col=False)\n",
    "    file2.set_index(file2.columns, inplace=True)\n",
    "    \n",
    "    file3 = pd.read_csv(file3, sep=',', index_col=False)\n",
    "    file3.set_index(file3.columns, inplace=True)\n",
    "    \n",
    "    file4 = pd.read_csv(file4, sep=',', index_col=False)\n",
    "    file4.set_index(file4.columns, inplace=True)\n",
    "    \n",
    "    return file1, file2, file3, file4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "def combine4df(df1, df2, df3, df4):\n",
    "    df1.iloc[101:201,:] = df2.iloc[101:201,:]\n",
    "    df1.iloc[201:301,:] = df3.iloc[201:301,:]\n",
    "    df1.iloc[301:len(list(df1)),:] = df4.iloc[301:len(list(df1)),:]\n",
    "    \n",
    "    return df1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ST train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "file1 = \"/home/slu/spatial/data/cross_CFS/STtoABA_STtrain_f1_CFS_052220.csv\"\n",
    "file2 = \"/home/slu/spatial/data/cross_CFS/STtoABA_STtrain_f1_2_CFS_052420.csv\"\n",
    "file3 = \"/home/slu/spatial/data/cross_CFS/STtoABA_STtrain_f1_3_CFS_052420.csv\"\n",
    "file4 = \"/home/slu/spatial/data/cross_CFS/STtoABA_STtrain_f1_4_CFS_052420.csv\"\n",
    "outfile = \"/home/slu/spatial/data/cross_CFS/STtoABA_STtrain_f1_all_CFS_052920.csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "data1, data2, data3, data4 = read4files(file1, file2, file3, file4)\n",
    "allcombined = combine4df(data1, data2, data3, data4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(445, 445)"
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     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "allcombined.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
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   },
   "outputs": [
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       "      577  657 1114  606  472  632 1072  893  543 1088  ...  \\\n",
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       "\n",
       "                                                    785  \\\n",
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       "\n",
       "                                                    241  \\\n",
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       "\n",
       "                                                   1104  \\\n",
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       "\n",
       "                                                    702  \\\n",
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       "\n",
       "                                                    954  \\\n",
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       "\n",
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       "\n",
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       "\n",
       "[6 rows x 445 columns]"
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     "execution_count": 71,
     "metadata": {},
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   "source": [
    "allcombined.iloc[99:105]"
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  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
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   "source": [
    "allcombined.to_csv(outfile, header=True, index=False)"
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   "source": [
    "ST test"
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   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "file1 = \"/home/slu/spatial/data/cross_CFS/STtoABA_STtest_f1_CFS_052220.csv\"\n",
    "file2 = \"/home/slu/spatial/data/cross_CFS/STtoABA_STtest_f1_2_CFS_052420.csv\"\n",
    "file3 = \"/home/slu/spatial/data/cross_CFS/STtoABA_STtest_f1_3_CFS_052420.csv\"\n",
    "file4 = \"/home/slu/spatial/data/cross_CFS/STtoABA_STtest_f1_4_CFS_052420.csv\"\n",
    "outfile = \"/home/slu/spatial/data/cross_CFS/STtoABA_STtest_f1_all_CFS_052920.csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "data1, data2, data3, data4 = read4files(file1, file2, file3, file4)\n",
    "allcombined = combine4df(data1, data2, data3, data4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(445, 445)"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "allcombined.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [],
   "source": [
    "allcombined.to_csv(outfile, header=True, index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "featsets ST train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [],
   "source": [
    "file1 = \"/home/slu/spatial/data/cross_CFS/STtoABA_featsetsSTtrain_f1_CFS_052220.csv\"\n",
    "file2 = \"/home/slu/spatial/data/cross_CFS/STtoABA_featsetsSTtrain_f1_2_CFS_052420.csv\"\n",
    "file3 = \"/home/slu/spatial/data/cross_CFS/STtoABA_featsetsSTtrain_f1_3_CFS_052420.csv\"\n",
    "file4 = \"/home/slu/spatial/data/cross_CFS/STtoABA_featsetsSTtrain_f1_4_CFS_052420.csv\"\n",
    "outfile = \"/home/slu/spatial/data/cross_CFS/STtoABA_featsetsSTtrain_f1_all_CFS_052920.csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [],
   "source": [
    "data1, data2, data3, data4 = read4files(file1, file2, file3, file4)\n",
    "allcombined = combine4df(data1, data2, data3, data4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(445, 445)"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "allcombined.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "allcombined.to_csv(outfile, header=True, index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ABA all"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [],
   "source": [
    "file1 = \"/home/slu/spatial/data/cross_CFS/STtoABA_ABAall_f1_CFS_052220.csv\"\n",
    "file2 = \"/home/slu/spatial/data/cross_CFS/STtoABA_ABAall_f1_2_CFS_052420.csv\"\n",
    "file3 = \"/home/slu/spatial/data/cross_CFS/STtoABA_ABAall_f1_3_CFS_052420.csv\"\n",
    "file4 = \"/home/slu/spatial/data/cross_CFS/STtoABA_ABAall_f1_4_CFS_052420.csv\"\n",
    "outfile = \"/home/slu/spatial/data/cross_CFS/STtoABA_ABAall_f1_all_CFS_052920.csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [],
   "source": [
    "data1, data2, data3, data4 = read4files(file1, file2, file3, file4)\n",
    "allcombined = combine4df(data1, data2, data3, data4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(445, 445)"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "allcombined.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [],
   "source": [
    "allcombined.to_csv(outfile, header=True, index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# ABA to ST"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [],
   "source": [
    "def read5files(file1, file2, file3, file4, file5):\n",
    "    file1 = pd.read_csv(file1, sep=',', index_col=False)\n",
    "    file1.set_index(file1.columns, inplace=True)\n",
    "    \n",
    "    file2 = pd.read_csv(file2, sep=',', index_col=False)\n",
    "    file2.set_index(file2.columns, inplace=True)\n",
    "    \n",
    "    file3 = pd.read_csv(file3, sep=',', index_col=False)\n",
    "    file3.set_index(file3.columns, inplace=True)\n",
    "    \n",
    "    file4 = pd.read_csv(file4, sep=',', index_col=False)\n",
    "    file4.set_index(file4.columns, inplace=True)\n",
    "    \n",
    "    file5 = pd.read_csv(file5, sep=',', index_col=False)\n",
    "    file5.set_index(file5.columns, inplace=True)\n",
    "    \n",
    "    return file1, file2, file3, file4, file5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [],
   "source": [
    "def combine5df(df1, df2, df3, df4, df5):\n",
    "    df1.iloc[91:181,:] = df2.iloc[91:181,:]\n",
    "    df1.iloc[181:271,:] = df3.iloc[181:271,:]\n",
    "    df1.iloc[271:361,:] = df4.iloc[271:361,:]\n",
    "    df1.iloc[361:len(list(df1)),:] = df5.iloc[361:len(list(df1)),:]\n",
    "    \n",
    "    return df1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ABA train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "file1 = \"/home/slu/spatial/data/cross_CFS/ABAtoST_ABAtrain_f1_1_CFS_052420.csv\"\n",
    "file2 = \"/home/slu/spatial/data/cross_CFS/ABAtoST_ABAtrain_f1_2_CFS_052420.csv\"\n",
    "file3 = \"/home/slu/spatial/data/cross_CFS/ABAtoST_ABAtrain_f1_3_CFS_052420.csv\"\n",
    "file4 = \"/home/slu/spatial/data/cross_CFS/ABAtoST_ABAtrain_f1_4_CFS_052420.csv\"\n",
    "file5 = \"/home/slu/spatial/data/cross_CFS/ABAtoST_ABAtrain_f1_5_CFS_052420.csv\"\n",
    "outfile = \"/home/slu/spatial/data/cross_CFS/ABAtoST_ABAtrain_f1_all_CFS_052920.csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [],
   "source": [
    "data1, data2, data3, data4, data5 = read5files(file1, file2, file3, file4, file5)\n",
    "allcombined = combine5df(data1, data2, data3, data4, data5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [],
   "source": [
    "allcombined.to_csv(outfile, header=True, index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ABA test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [],
   "source": [
    "file1 = \"/home/slu/spatial/data/cross_CFS/ABAtoST_ABAtest_f1_1_CFS_052420.csv\"\n",
    "file2 = \"/home/slu/spatial/data/cross_CFS/ABAtoST_ABAtest_f1_2_CFS_052420.csv\"\n",
    "file3 = \"/home/slu/spatial/data/cross_CFS/ABAtoST_ABAtest_f1_3_CFS_052420.csv\"\n",
    "file4 = \"/home/slu/spatial/data/cross_CFS/ABAtoST_ABAtest_f1_4_CFS_052420.csv\"\n",
    "file5 = \"/home/slu/spatial/data/cross_CFS/ABAtoST_ABAtest_f1_5_CFS_052420.csv\"\n",
    "outfile = \"/home/slu/spatial/data/cross_CFS/ABAtoST_ABAtest_f1_all_CFS_052920.csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [],
   "source": [
    "data1, data2, data3, data4, data5 = read5files(file1, file2, file3, file4, file5)\n",
    "allcombined = combine5df(data1, data2, data3, data4, data5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [],
   "source": [
    "allcombined.to_csv(outfile, header=True, index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "featsets ABA train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [],
   "source": [
    "file1 = \"/home/slu/spatial/data/cross_CFS/ABAtoST_featsetsABAtrain_f1_1_CFS_052420.csv\"\n",
    "file2 = \"/home/slu/spatial/data/cross_CFS/ABAtoST_featsetsABAtrain_f1_2_CFS_052420.csv\"\n",
    "file3 = \"/home/slu/spatial/data/cross_CFS/ABAtoST_featsetsABAtrain_f1_3_CFS_052420.csv\"\n",
    "file4 = \"/home/slu/spatial/data/cross_CFS/ABAtoST_featsetsABAtrain_f1_4_CFS_052420.csv\"\n",
    "file5 = \"/home/slu/spatial/data/cross_CFS/ABAtoST_featsetsABAtrain_f1_5_CFS_052420.csv\"\n",
    "outfile = \"/home/slu/spatial/data/cross_CFS/ABAtoST_featstsABAtrain_f1_all_CFS_052920.csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [],
   "source": [
    "data1, data2, data3, data4, data5 = read5files(file1, file2, file3, file4, file5)\n",
    "allcombined = combine5df(data1, data2, data3, data4, data5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [],
   "source": [
    "allcombined.to_csv(outfile, header=True, index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ST all"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [],
   "source": [
    "file1 = \"/home/slu/spatial/data/cross_CFS/ABAtoST_STall_f1_1_CFS_052420.csv\"\n",
    "file2 = \"/home/slu/spatial/data/cross_CFS/ABAtoST_STall_f1_2_CFS_052420.csv\"\n",
    "file3 = \"/home/slu/spatial/data/cross_CFS/ABAtoST_STall_f1_3_CFS_052420.csv\"\n",
    "file4 = \"/home/slu/spatial/data/cross_CFS/ABAtoST_STall_f1_4_CFS_052420.csv\"\n",
    "file5 = \"/home/slu/spatial/data/cross_CFS/ABAtoST_STall_f1_5_CFS_052420.csv\"\n",
    "outfile = \"/home/slu/spatial/data/cross_CFS/ABAtoST_STall_f1_all_CFS_052920.csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [],
   "source": [
    "data1, data2, data3, data4, data5 = read5files(file1, file2, file3, file4, file5)\n",
    "allcombined = combine5df(data1, data2, data3, data4, data5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [],
   "source": [
    "allcombined.to_csv(outfile, header=True, index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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