{
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Analysing GITT data\n",
    "\n",
    "PyProBE includes built-in analysis methods for pulsing experiments, which this example\n",
    "will demonstrate.\n",
    "\n",
    "First import the required libraries and data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%capture\n",
    "%pip install matplotlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import pyprobe\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "info_dictionary = {\n",
    "    \"Name\": \"Sample cell\",\n",
    "    \"Chemistry\": \"NMC622\",\n",
    "    \"Nominal Capacity [Ah]\": 0.04,\n",
    "    \"Cycler number\": 1,\n",
    "    \"Channel number\": 1,\n",
    "}\n",
    "data_directory = \"../../../tests/sample_data/neware\"\n",
    "\n",
    "# Create a cell object\n",
    "cell = pyprobe.Cell(info=info_dictionary)\n",
    "cell.add_procedure(\n",
    "    procedure_name=\"Sample\",\n",
    "    folder_path=data_directory,\n",
    "    filename=\"sample_data_neware.parquet\",\n",
    ")\n",
    "print(cell.procedure[\"Sample\"].experiment_names)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will plot the Break-in Cycles and Discharge Pulses:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots()\n",
    "cell.procedure[\"Sample\"].experiment(\"Break-in Cycles\").plot(\n",
    "    x=\"Time [hr]\", y=\"Voltage [V]\", ax=ax, label=\"Break-in Cycles\", color=\"blue\"\n",
    ")\n",
    "cell.procedure[\"Sample\"].experiment(\"Discharge Pulses\").plot(\n",
    "    x=\"Time [hr]\", y=\"Voltage [V]\", ax=ax, label=\"Discharge Pulses\", color=\"red\"\n",
    ")\n",
    "ax.set_ylabel(\"Voltage [V]\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "State-of-charge is a useful metric when working with battery data, however it must be carefully defined. PyProBE doesn't automatically calculate a value for cell SOC until instructed to by the user for this reason.\n",
    "\n",
    "To add an SOC column to the data, we call `set_SOC()` on the procedure. We are going to provide an argument to `reference_charge`. This will be the final charge of the break-in cycles. This argument instructs PyProBE that the final data point of this charge is our 100% SOC reference."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "reference_charge = cell.procedure[\"Sample\"].experiment(\"Break-in Cycles\").charge(-1)\n",
    "cell.procedure[\"Sample\"].set_SOC(reference_charge=reference_charge)\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "cell.procedure[\"Sample\"].experiment(\"Break-in Cycles\").plot(\n",
    "    x=\"Time [hr]\", y=\"SOC\", ax=ax, label=\"Break-in Cycles\", color=\"blue\"\n",
    ")\n",
    "cell.procedure[\"Sample\"].experiment(\"Discharge Pulses\").plot(\n",
    "    x=\"Time [hr]\", y=\"SOC\", ax=ax, label=\"Discharge Pulses\", color=\"red\"\n",
    ")\n",
    "ax.set_ylabel(\"SOC\")\n",
    "plt.legend(loc=\"lower left\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then we'll filter to only the pulsing experiment:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pulsing_experiment = cell.procedure[\"Sample\"].experiment(\"Discharge Pulses\")\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "pulsing_experiment.plot(\n",
    "    x=\"Experiment Time [hr]\",\n",
    "    y=\"Voltage [V]\",\n",
    "    ax=ax,\n",
    "    label=\"Discharge Pulses\",\n",
    "    color=\"red\",\n",
    ")\n",
    "ax.set_ylabel(\"Voltage [V]\")\n",
    "plt.legend(loc=\"lower left\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And then create our pulsing analysis object."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyprobe.analysis import pulsing\n",
    "\n",
    "pulse_object = pulsing.Pulsing(input_data=pulsing_experiment)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "With the pulsing object we can separate out individual pulses:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots()\n",
    "pulse_object.input_data.plot(\n",
    "    x=\"Experiment Time [hr]\",\n",
    "    y=\"Voltage [V]\",\n",
    "    label=\"Full Experiment\",\n",
    "    color=\"blue\",\n",
    "    ax=ax,\n",
    ")\n",
    "pulse_object.pulse(4).plot(\n",
    "    x=\"Experiment Time [hr]\", y=\"Voltage [V]\", label=\"Pulse 5\", color=\"red\", ax=ax\n",
    ")\n",
    "ax.set_ylabel(\"Voltage [V]\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also extract key parameters from the pulsing experiment, with the `get_resistances()` method."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pulse_resistances = pulsing.get_resistances(input_data=pulsing_experiment)\n",
    "print(pulse_resistances.data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `get_resistances()` method can take an argument of a list of times at which to evaluate the resistance after the pulse, for instance at 10s after the pulse:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pulse_resistances = pulsing.get_resistances(input_data=pulsing_experiment, r_times=[10])\n",
    "print(pulse_resistances.data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As a result object, the pulse summary can also be plotted:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots()\n",
    "pulse_resistances.plot(x=\"SOC\", y=\"R0 [Ohms]\", ax=ax, label=\"R0\", color=\"blue\")\n",
    "pulse_resistances.plot(x=\"SOC\", y=\"R_10s [Ohms]\", ax=ax, label=\"R_10s\", color=\"red\")\n",
    "ax.set_ylabel(\"Resistance [Ohms]\")"
   ]
  }
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