{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d12db561",
   "metadata": {},
   "outputs": [],
   "source": [
    "from library.analysis import loadDataset, testSets\n",
    "from library.generators.convGeN import ConvGeN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "63b800ff",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = loadDataset(\"data_input/\" + testSets[4])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2b0329e5",
   "metadata": {},
   "outputs": [],
   "source": [
    "print((len(data.data), len(data.data0), len(data.data1)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a4853614",
   "metadata": {},
   "outputs": [],
   "source": [
    "gen = ConvGeN(data.data0.shape[1], neb=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "842f6772",
   "metadata": {},
   "outputs": [],
   "source": [
    "gen.reset(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "333d62b9",
   "metadata": {},
   "outputs": [],
   "source": [
    "gen.train(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f6f58a17",
   "metadata": {},
   "outputs": [],
   "source": [
    "syntheticPoints = gen.generateData(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "82ae5f98",
   "metadata": {},
   "outputs": [],
   "source": [
    "syntheticPoints"
   ]
  }
 ],
 "metadata": {
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   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
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   "file_extension": ".py",
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   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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 "nbformat": 4,
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