calib_scripts/calib_cernox_2021-04-30.ipynb

{
 "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": 1,
   "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": 2,
   "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/calib2021-04-30_p0_c1.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p1_c1.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p2_c1.dat')\n",
      "{'selected': 0, 'averaged': 62}\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p0_c2.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p1_c2.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p2_c2.dat')\n",
      "{'selected': 1, 'averaged': 61}\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p0_c4.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p1_c4.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p2_c4.dat')\n",
      "{'selected': 0, 'averaged': 62}\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p0_c5.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p1_c5.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p2_c5.dat')\n",
      "{'selected': 2, 'averaged': 60}\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p0_c6.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p1_c6.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p2_c6.dat')\n",
      "{'selected': 0, 'averaged': 62}\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=194) + (330,),  # the points to be used in the cal file\n",
    "    caldate = '2021-04-30',  # 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": 3,
   "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": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('z340', 'READ 2021-04-30/X154359.340')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p0_c1.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p1_c1.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p2_c1.dat')\n"
     ]
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('z340', 'READ 2021-04-30/X148906.340')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p0_c2.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p1_c2.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p2_c2.dat')\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('z340', 'READ 2021-04-30/X154360.340')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p0_c4.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p1_c4.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p2_c4.dat')\n"
     ]
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('z340', 'READ 2021-04-30/X148903.340')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p0_c5.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p1_c5.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p2_c5.dat')\n"
     ]
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('z340', 'READ 2021-04-30/X142474.340')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p0_c6.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p1_c6.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p2_c6.dat')\n"
     ]
    },
    {
     "data": {
      "image/png": "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
      "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.axis([240,330,-1,1])\n",
    "\n",
    "    # plt.legend(['dif1','dif2','dif3','est'])\n",
    "    plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('z340', 'READ 2021-04-30/X154359.340')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p0_c1.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p1_c1.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p2_c1.dat')\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('z340', 'READ 2021-04-30/X148906.340')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p0_c2.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p1_c2.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p2_c2.dat')\n"
     ]
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('z340', 'READ 2021-04-30/X154360.340')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p0_c4.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p1_c4.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p2_c4.dat')\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('z340', 'READ 2021-04-30/X148903.340')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p0_c5.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p1_c5.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p2_c5.dat')\n"
     ]
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('z340', 'READ 2021-04-30/X142474.340')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p0_c6.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p1_c6.dat')\n",
      "('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-04-30_p2_c6.dat')\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "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",
    "        plt.plot(t0, r0, '-')\n",
    "        plt.plot(tc, rc, '.')\n",
    "    plt.xscale('log')\n",
    "    plt.yscale('log')\n",
    "    plt.grid(True, axis='y')\n",
    "    # plt.axis([min(t0),max(t0),-1,1])\n",
    "    # plt.axis([240,330,-1,1])\n",
    "\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": []
  }
 ],
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   "language": "python",
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  "language_info": {
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