{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Scripts for Calibration of Cernox Sensors\n",
    "---------------------------------------\n",
    "\n",
    "Make a copy of this notebook for an other run.\n",
    "\n",
    "See also http://samenv.psi.ch:8080/sample_environment/83"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import math\n",
    "from scipy.interpolate import splrep, splev\n",
    "from zcalib import read_curve, convert_res, compare_calib, make_calib, logrange, Sensor, CalibRun, nplog, npexp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('lsdat', 'READ /afs/psi.ch/project/SampleEnvironment/SE_internal/Thermometer_calibs/2012/73027 Cernox 5/X75610.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-26_p0_c1.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-26_p1_c1.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-26_p2_c1.dat')\n",
      "{'selected': 0, 'averaged': 59}\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-26_p0_c2.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-26_p1_c2.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-26_p2_c2.dat')\n",
      "{'selected': 0, 'averaged': 58}\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-26_p0_c4.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-26_p1_c4.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-26_p2_c4.dat')\n",
      "{'selected': 0, 'averaged': 57}\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-26_p0_c5.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-26_p1_c5.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-26_p2_c5.dat')\n",
      "{'selected': 0, 'averaged': 56}\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-26_p0_c6.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-26_p1_c6.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-26_p2_c6.dat')\n",
      "{'selected': 0, 'averaged': 55}\n"
     ]
    }
   ],
   "source": [
    "run = CalibRun([\n",
    "        Sensor(3, 'X75610'), # the reference sensor must be the first\n",
    "        Sensor(1, 'X154359', 'CX-1050-CU-HT'),\n",
    "        Sensor(2, 'X148906', 'CX-1050-CU-HT'),\n",
    "        Sensor(4, 'X154360', 'CX-1050-CU-HT'),\n",
    "        Sensor(5, 'X148903', 'CX-1050-CU-HT'),\n",
    "        Sensor(6, 'X142474', 'CX-1050-CU-HT'),\n",
    "    ],\n",
    "    t_points = (1.0, 1.2) + logrange(1.4, 310, n=195) + (330,),  # the points to be used in the cal file\n",
    "    caldate = '2021-04-26',  # the first measuring day!\n",
    "    logT = False,\n",
    "    logR = True,\n",
    "    calib_data_file = '/home/l_samenv/sea/calib_scripts/calib_data/calib%s_p%d_c%d.dat',\n",
    "    outputpath='%s/%s.340')\n",
    "# smooth depends on number of measured points (1e-7 for 60, 0.8e-7 for 48 and 0.4e-7 for 24 points)\n",
    "run.make(diflim=0.001, smoothref=1e-7, smoothtst=0.4e-7)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# compare known sensors\n",
    "if False:  # set to True when known sensors are measured\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    tmin,tmax,dmax=1.4,310,0.001\n",
    "    testlist = [('X133982', 'z340'),('X133928', 'z340'),('X131824', 'z340'),('X132254', 'z340'),('X137461', 'z340')]\n",
    "    for sensno, kind in testlist:\n",
    "        r0, t0 = read_curve('2018-11-22/%s.340' % sensno, 'z340')\n",
    "        r1, t1 = read_curve('2018-11-20/%s.340' % sensno, kind)\n",
    "        diff = compare_calib(r1, t1, r0, t0)\n",
    "        plt.plot(t0, diff, '-')\n",
    "    plt.plot([tmin,tmax,tmax,tmin,tmin], [-dmax,-dmax,dmax,dmax,-dmax], '-')\n",
    "    plt.legend([sensno + \".\" + kind[-3:] for sensno, kind in testlist] + [\"window\"])\n",
    "    plt.xscale('log')\n",
    "    plt.yscale('symlog',linthreshy=dmax)\n",
    "    plt.grid(True, axis='y')\n",
    "    plt.axis([1.0,350,-1,1])\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('z340', 'READ 2021-04-26/X154359.340')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-26_p0_c1.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-26_p1_c1.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-26_p2_c1.dat')\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('z340', 'READ 2021-04-26/X148906.340')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-26_p0_c2.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-26_p1_c2.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-26_p2_c2.dat')\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('z340', 'READ 2021-04-26/X154360.340')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-26_p0_c4.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-26_p1_c4.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-26_p2_c4.dat')\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('z340', 'READ 2021-04-26/X148903.340')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-26_p0_c5.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-26_p1_c5.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-26_p2_c5.dat')\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('z340', 'READ 2021-04-26/X142474.340')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-26_p0_c6.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-26_p1_c6.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-26_p2_c6.dat')\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# compare calibration files from points 0,1,2\n",
    "# with the optimized (average or selection of best)\n",
    "\n",
    "for sensor in run.sensors:\n",
    "    r0, t0 = read_curve(sensor.outputpath, sensor.outputkind)\n",
    "    plt.figure()\n",
    "    dif = [0,0,0]\n",
    "    for j in range(3):\n",
    "        rr, rt = read_curve(sensor.caldat_file[j], 'zdat')\n",
    "        rc, tc = make_calib(run.rref, run.tref, rr, rt, run.t_points)\n",
    "        dif[j] = compare_calib(r0, t0, rc, tc)\n",
    "        plt.plot(t0, dif[j], '-')\n",
    "    plt.xscale('log')\n",
    "    plt.yscale('symlog', linthreshy=0.001)\n",
    "    plt.grid(True, axis='y')\n",
    "    plt.axis([min(t0),max(t0),-1,1])\n",
    "    # plt.legend(['dif1','dif2','dif3','est'])\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2.7",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}