{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "604ace42-84fa-4391-bd92-0209e50a4dda",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from scipy.optimize import curve_fit\n",
    "import scipy.constants as const\n",
    "import h5py"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "214268c5-b46c-48bb-8abd-d82131611df3",
   "metadata": {
    "tags": []
   },
   "source": [
    "## load HDF5 file with context manager"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "27079012-b1c5-489a-8ae9-f2f1f6901a54",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "with h5py.File(\n",
    "    r\"kaust_temp_entry_1.nxs\", \"r\"\n",
    ") as f:\n",
    "    # get the data\n",
    "    data = f[list(f.keys())[0]][\"data\"]\n",
    "    SMU_mesI1 = data[\"Simple_Sweep\"][\"SMU_mesI1\"][:]\n",
    "    SMU_mesV1 = data[\"Simple_Sweep\"][\"SMU_mesV1\"][:]\n",
    "    SMU_setV1 = data[\"Simple_Sweep\"][\"SMU_setV1\"][:]\n",
    "    temperatue_PID = data[\"PID_current_value\"][:]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6aaecf64-d685-4308-9a22-9a9ae6c3ff4e",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Split data into chucks of 51 points"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ecf3df2b-0684-46c4-a7ac-fdbdbabe1f23",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "n = 51\n",
    "mesV1_split = [SMU_mesV1[i:i + n] for i in range(0, len(SMU_mesV1), n)]\n",
    "mesI1_split = [SMU_mesI1[i:i + n] for i in range(0, len(SMU_mesI1), n)]\n",
    "setV1_split = [SMU_setV1[i:i + n] for i in range(0, len(SMU_setV1), n)]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f9da0b63-268b-478d-bbfa-6d8e7ef365da",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Perform the fit for each chuck and plot it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1a5c315c-98cb-4da3-a81a-df0493ae09e0",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "a_list = []\n",
    "b_list = []\n",
    "R = []\n",
    "for mesV1, mesI1 in zip(mesV1_split, mesI1_split):\n",
    "    fit_result = curve_fit(lambda x, a, b: a * x + b, mesV1, mesI1)\n",
    "    a, b = fit_result[0]\n",
    "    a_list.append(a)\n",
    "    b_list.append(b)\n",
    "    R.append(1/a)\n",
    "\n",
    "# Plot the individual IV curves and fits\n",
    "plt.figure()\n",
    "for mesV1, mesI1, a, b in zip(mesV1_split, mesI1_split, a_list, b_list):\n",
    "    plt.plot(mesV1, mesI1, 'x')\n",
    "    plt.plot(mesV1, a * mesV1 + b)\n",
    "plt.xlabel(\"Voltage (V)\")\n",
    "plt.ylabel(\"Current (A)\")\n",
    "plt.title(\"IV curves and fits\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aed3a692-2cd8-40c0-bb1f-a845dedbbd90",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Fit  and plot the resistance vs temperature with an exponential function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3fa8b188-8a68-4cd0-98c0-fb90aff1ea5f",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def exp_fit(T, R0, Ea):\n",
    "    return R0 * np.exp(Ea*const.e/(T * const.k))\n",
    "# Add starting values for the fit\n",
    "fit_result = curve_fit(exp_fit, temperatue_PID, R, p0=[50, 0.5])\n",
    "R0, Ea = fit_result[0]\n",
    "\n",
    "## Plot the resistance against the temperature\n",
    "plt.figure()\n",
    "plt.plot(temperatue_PID, R, 'x')\n",
    "plt.xlabel(\"Temperature (K)\")\n",
    "plt.ylabel(\"Resistance (Ohm)\")\n",
    "plt.title(\"Resistance vs Temperature\")\n",
    "\n",
    "# Plot the fit\n",
    "T = np.linspace(temperatue_PID.min(), temperatue_PID.max(), 100)\n",
    "plt.plot(T, exp_fit(T, R0, Ea))\n",
    "plt.title(f\"R0 = {R0:.2f}, $E_a$ = {Ea:.2f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "68f94d29-dfc5-44f6-9d58-dae35c6345fe",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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