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 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Sharing Data\n",
    "\n",
    "PyProBE makes sharing data simple and straightforward. This is a simple example to demonstrate the process.\n",
    "\n",
    "First we will import some sample data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pyprobe\n",
    "import os\n",
    "import shutil\n",
    "\n",
    "# Describe the cell. Required fields are 'Name'.\n",
    "info_dictionary = {'Name': 'Sample cell',\n",
    "                   'Chemistry': 'NMC622',\n",
    "                   'Nominal Capacity [Ah]': 0.04,\n",
    "                   'Cycler number': 1,\n",
    "                   'Channel number': 1,}\n",
    "\n",
    "# Create a cell object\n",
    "cell = pyprobe.Cell(info=info_dictionary)\n",
    "\n",
    "data_directory = '../../../tests/sample_data/neware'\n",
    "\n",
    "cell.add_procedure(procedure_name='Sample',\n",
    "                   folder_path = data_directory,\n",
    "                   filename = 'sample_data_neware.parquet')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can then use the `archive()` method of the cell object. This stores all attributes of the `cell` object into a single folder. The data is stored as `.parquet` files and the metadata is stored in `.json` files."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "cell.archive(path = 'sample_archive')\n",
    "os.listdir('.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can choose to compress the folder by adding `.zip` to the path:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "cell.archive(path = 'sample_archive.zip')\n",
    "os.listdir('.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can then retrieve the archived object with the `pyprobe.load_archive()` method:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "saved_cell = pyprobe.load_archive('sample_archive.zip')\n",
    "print(saved_cell.info)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig = pyprobe.Plot()\n",
    "fig.add_line(saved_cell.procedure['Sample'], 'Time [hr]', 'Voltage [V]')\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Clean up after example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "shutil.rmtree('sample_archive')"
   ]
  }
 ],
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