plaintext_to_numpy_convertor.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "b671eeca",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "frgc_cluster_63.npy\n",
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      "frgc_cluster_38.npy\n",
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      "frgc_cluster_47.npy\n",
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      "frgc_cluster_59.npy\n",
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      "frgc_cluster_6.npy\n",
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      "frgc_cluster_32.npy\n",
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      "frgc_cluster_45.npy\n",
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      "frgc_cluster_40.npy\n",
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      "frgc_cluster_11.npy\n",
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      "frgc_cluster_26.npy\n",
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      "frgc_cluster_19.npy\n",
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      "  0.02250294 -0.01538094]\n",
      "frgc_cluster_16.npy\n",
      "[-7.70346627e-03 -5.96364588e-03 -2.79975975e-03 -1.31152232e-02\n",
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      "frgc_cluster_41.npy\n",
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      "frgc_cluster_60.npy\n",
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      "frgc_cluster_7.npy\n",
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      " -4.57601930e-02  2.97075046e-02  2.31018223e-02  5.34337221e-02]\n",
      "frgc_cluster_33.npy\n",
      "[-0.02323654 -0.00262174 -0.01578097  0.04002808 -0.01094626 -0.04356252\n",
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      "  0.0065506   0.00800468]\n",
      "frgc_cluster_4.npy\n",
      "[ 0.02170013  0.01861897  0.01414196  0.01570776  0.01472041  0.0026833\n",
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      "frgc_cluster_8.npy\n",
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      "  2.51023352e-03 -2.18116366e-02 -4.85094067e-02 -3.45126273e-02]\n",
      "frgc_cluster_36.npy\n",
      "[ 0.01757106  0.03717683  0.00824684 -0.01070689 -0.0019277   0.00137815\n",
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      "frgc_cluster_21.npy\n",
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      "frgc_cluster_52.npy\n",
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      "frgc_cluster_46.npy\n",
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      "frgc_cluster_44.npy\n",
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      "frgc_cluster_55.npy\n",
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      "frgc_cluster_53.npy\n",
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      " -0.01910655  0.03506919]\n",
      "frgc_cluster_39.npy\n",
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      "frgc_cluster_56.npy\n",
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      "frgc_cluster_31.npy\n",
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      "  1.93936990e-03 -7.58038061e-03 -2.94881961e-03  1.17385496e-02]\n",
      "frgc_cluster_50.npy\n",
      "[ 0.00090348  0.0245035   0.01881581  0.04591613 -0.00435673 -0.00015368\n",
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      "frgc_cluster_51.npy\n",
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      " -0.02506733 -0.02431097]\n",
      "frgc_cluster_35.npy\n",
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      "frgc_cluster_10.npy\n",
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      "frgc_cluster_29.npy\n",
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      "frgc_cluster_28.npy\n",
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      "frgc_cluster_25.npy\n",
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      "frgc_cluster_49.npy\n",
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      "frgc_cluster_61.npy\n",
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      "frgc_cluster_34.npy\n",
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      "frgc_cluster_20.npy\n",
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      "frgc_cluster_54.npy\n",
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      "frgc_cluster_27.npy\n",
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      "frgc_cluster_17.npy\n",
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     ]
    }
   ],
   "source": [
    "import os\n",
    "from numpy import genfromtxt\n",
    "import numpy\n",
    "\n",
    "input = '/home/ubuntu/trainingfiles/frgc_cluster_centers/'\n",
    "output = '/home/ubuntu/trainingfiles/frgc_centers_converted/'\n",
    "if not os.path.exists(output):\n",
    "    os.makedirs(output)\n",
    "\n",
    "for filename in os.listdir(input):\n",
    "    if not filename.startswith('.'):\n",
    "        print(filename)\n",
    "        cluster_center = genfromtxt(os.path.join(input, filename), delimiter=',')\n",
    "        print(cluster_center)\n",
    "        numpy.save(os.path.join(output, filename), numpy.array(cluster_center))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8de60838",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e971525a",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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