691 lines
483 KiB
Plaintext
691 lines
483 KiB
Plaintext
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Scripts for Calibration of Cernox Sensors\n",
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"---------------------------------------\n",
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"\n",
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"Make a copy of this notebook for an other run."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"import matplotlib.pyplot as plt\n",
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"import math\n",
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"from scipy.interpolate import splrep, splev\n",
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"from zcalib import read_curve, convert_res, compare_calib, make_calib, logrange, Sensor, CalibRun, nplog, npexp"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"('lsdat', 'READ /afs/psi.ch/project/SampleEnvironment/SE_internal/Thermometer_calibs/2012/73027 Cernox 5/X75610.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-06_p0_c1.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-06_p1_c1.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-06_p2_c1.dat')\n",
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"(15258.68, 1786.369, 20544.125265674887, 10.500493607801573)\n",
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"(18736.18, 25480.67, 1.88352736694433, -0.9999260801475416)\n",
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"{'selected': 4, 'averaged': 55}\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-06_p0_c2.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-06_p1_c2.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-06_p2_c2.dat')\n",
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"(15248.38, 1469.515, 14672.470993977638, 8.984567012910816)\n",
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"(18715.13, 17977.81, 2.2962777513343333, -0.9998722715530237)\n",
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"{'selected': 4, 'averaged': 55}\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-06_p0_c4.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-06_p1_c4.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-06_p2_c4.dat')\n",
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"(15238.75, 1213.462, 10503.50589053061, 7.655817726909134)\n",
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"(18742.71, 12637.2, 2.639492752373098, -0.999791133102873)\n",
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"{'selected': 4, 'averaged': 55}\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-06_p0_c5.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-06_p1_c5.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-06_p2_c5.dat')\n",
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"(15229.03, 1851.737, 18563.677039786682, 9.025007352440806)\n",
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"(18760.93, 22892.35, 2.543014843352976, -0.9998889142074382)\n",
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"{'selected': 4, 'averaged': 55}\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-06_p0_c6.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-06_p1_c6.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-06_p2_c6.dat')\n",
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"(15219.33, 1719.351, 16133.874058825291, 8.383700046602055)\n",
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"(18774.43, 19870.37, 2.703731731772659, -0.9998639314853335)\n",
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"{'selected': 4, 'averaged': 55}\n"
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]
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}
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],
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"source": [
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"run = CalibRun([\n",
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" Sensor(3, 'X75610'), # the reference sensor must be the first\n",
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" Sensor(1, 'X225622', 'CX-1050-SD-HT'),\n",
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" Sensor(2, 'X225623', 'CX-1050-SD-HT'),\n",
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" Sensor(4, 'X225624', 'CX-1050-SD-HT'),\n",
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" Sensor(5, 'X196718', 'CX-1050-CU-HT'),\n",
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" Sensor(6, 'X196719', 'CX-1050-CU-HT'),\n",
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" ],\n",
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" t_points = (1.2, 1.4) + logrange(1.6, 310, n=195) + (330,), # the points to be used in the cal file\n",
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" caldate = '2024-12-06', # the first measuring day!\n",
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" logT = False,\n",
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" logR = True,\n",
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" calib_data_file = '/home/l_samenv/sea/calib_scripts/calib_data/calib%s_p%d_c%d.dat',\n",
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" outputpath='%s/%s.340')\n",
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"# smooth depends on number of measured points (1e-7 for 60, 0.8e-7 for 48 and 0.4e-7 for 24 points)\n",
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"run.make(diflim=0.001, smoothref=1e-7, smoothtst=0.4e-7)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"('z340', 'READ 2023-11-05/X133982.340')\n"
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]
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},
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{
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"ename": "IOError",
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"evalue": "[Errno 2] No such file or directory: '2023-11-05/X133982.340'",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m\u001b[0m",
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"\u001b[0;31mIOError\u001b[0mTraceback (most recent call last)",
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"\u001b[0;32m<ipython-input-3-fb75a641ebf6>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0mtestlist\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'X133982'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'z340'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'X133928'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'z340'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'X131824'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'z340'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'X132254'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'z340'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'X137461'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'z340'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0msensno\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkind\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mtestlist\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 6\u001b[0;31m \u001b[0mr0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mt0\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mread_curve\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'2023-11-05/%s.340'\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0msensno\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'z340'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 7\u001b[0m \u001b[0mr1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mt1\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mread_curve\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'2023-11-05/%s.340'\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0msensno\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkind\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[0mdiff\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcompare_calib\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mr1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mt1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mr0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mt0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;32m/home/l_samenv/sea/calib_scripts/zcalib.pyc\u001b[0m in \u001b[0;36mread_curve\u001b[0;34m(filename, kind, instance, **filterargs)\u001b[0m\n\u001b[1;32m 118\u001b[0m \u001b[0;32mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkind\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"READ %s\"\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0mfilename\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 119\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 120\u001b[0;31m \u001b[0;32mwith\u001b[0m \u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilename\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 121\u001b[0m \u001b[0mcurves\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mc\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mfilter\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moutput\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 122\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mline\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;31mIOError\u001b[0m: [Errno 2] No such file or directory: '2023-11-05/X133982.340'"
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]
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},
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{
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"data": {
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"text/plain": [
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"<Figure size 720x432 with 0 Axes>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"# compare known sensors (skip if not applicable)\n",
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"plt.figure(figsize=(10, 6))\n",
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"tmin,tmax,dmax=1.4,310,0.001\n",
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"testlist = (('X133982', 'z340'),('X133928', 'z340'),('X131824', 'z340'),('X132254', 'z340'),('X137461', 'z340'))\n",
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"for sensno, kind in testlist:\n",
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" r0, t0 = read_curve('2023-11-05/%s.340' % sensno, 'z340')\n",
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" r1, t1 = read_curve('2023-11-05/%s.340' % sensno, kind)\n",
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" diff = compare_calib(r1, t1, r0, t0)\n",
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" plt.plot(t0, diff, '-')\n",
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"plt.plot([tmin,tmax,tmax,tmin,tmin], [-dmax,-dmax,dmax,dmax,-dmax], '-')\n",
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"plt.legend([sensno + \".\" + kind[-3:] for sensno, kind in testlist] + [\"window\"])\n",
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"plt.xscale('log')\n",
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"plt.yscale('symlog',linthreshy=dmax)\n",
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"plt.grid(True, axis='y')\n",
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"plt.axis([1.0,350,-1,1])\n",
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"plt.show()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"('z340', 'READ 2024-12-06/X225622.340')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-06_p0_c1.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-06_p1_c1.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-06_p2_c1.dat')\n",
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"(1.684022493682333e-14, 1.2, 5.239156889296299e+18, 4.365964074413583e+18)\n",
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"(1.9349768431510698e-08, 1.4, 2522887954413.2397, 1802062824579.8857)\n",
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"(0.0011041781650934638, 1.6, 27784579.402813975, 17365361.126758732)\n",
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"(0.009000264846393347, 1.6438017078531195, 3118461.970852214, 1897102.498526637)\n",
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"(0.07069809045478842, 1.6888025342130204, 363766.01822266355, 215397.78751554457)\n",
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"(0.5357209973359398, 1.7350353062287744, 44054.244487024516, 25389.97869009918)\n",
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"(3.9200406912003594, 1.7825337497276996, 5533.198555798439, 3103.1199397451473)\n",
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"(27.727089648395893, 1.8313325138176362, 719.9926044442835, 392.1523079571012)\n",
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"(189.75849555752626, 1.8814671961627354, 103.81835737423089, 54.17946716582097)\n",
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"(1257.73428224644, 1.932974368951203, 14.592320351907075, 6.549153566803167)\n",
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"(6177.070831745967, 1.9858916055739333, 3.7817188567622106, 0.9042926845291104)\n",
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"(14867.7489823991, 2.0402575080335033, 2.2719839481732893, 0.11357705545861951)\n",
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"(21266.516812125887, 2.153495031258826, 1.9119858855229528, -0.11214752865935293)\n"
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]
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},
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{
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"data": {
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|
|
"(34.26192971306782, 1.8313325138176362, 875.6236712873967, 477.13472686183695)\n",
|
||
|
|
"(201.41097945571718, 1.8814671961627354, 127.64014521606214, 66.84074974912402)\n",
|
||
|
|
"(1149.5944079881458, 1.932974368951203, 16.294805202794894, 7.429912710966861)\n",
|
||
|
|
"(5107.839116510911, 1.9858916055739333, 3.8749138493926036, 0.9512212240167724)\n",
|
||
|
|
"(11735.009083053337, 2.0402575080335033, 2.2924373956411404, 0.1236019897560382)\n",
|
||
|
|
"(16659.006995260028, 2.153495031258826, 1.9152777395363252, -0.11061891867159357)\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",
|
||
|
|
" tmin,tmax,dmax=1.4,310,0.001\n",
|
||
|
|
" plt.plot([tmin,tmax,tmax,tmin,tmin], [-dmax,-dmax,dmax,dmax,-dmax], '-')\n",
|
||
|
|
" plt.legend(['dif1','dif2','dif3','est'])\n",
|
||
|
|
" plt.show()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 4,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"('z340', 'READ 2024-12-06/X225622.340')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-06_p0_c1.dat')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-06_p1_c1.dat')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-06_p2_c1.dat')\n",
|
||
|
|
"(1.684022493682333e-14, 1.2, 5.239156889296299e+18, 4.365964074413583e+18)\n",
|
||
|
|
"(1.9349768431510698e-08, 1.4, 2522887954413.2397, 1802062824579.8857)\n",
|
||
|
|
"(0.0011041781650934638, 1.6, 27784579.402813975, 17365361.126758732)\n",
|
||
|
|
"(0.009000264846393347, 1.6438017078531195, 3118461.970852214, 1897102.498526637)\n",
|
||
|
|
"(0.07069809045478842, 1.6888025342130204, 363766.01822266355, 215397.78751554457)\n",
|
||
|
|
"(0.5357209973359398, 1.7350353062287744, 44054.244487024516, 25389.97869009918)\n",
|
||
|
|
"(3.9200406912003594, 1.7825337497276996, 5533.198555798439, 3103.1199397451473)\n",
|
||
|
|
"(27.727089648395893, 1.8313325138176362, 719.9926044442835, 392.1523079571012)\n",
|
||
|
|
"(189.75849555752626, 1.8814671961627354, 103.81835737423089, 54.17946716582097)\n",
|
||
|
|
"(1257.73428224644, 1.932974368951203, 14.592320351907075, 6.549153566803167)\n",
|
||
|
|
"(6177.070831745967, 1.9858916055739333, 3.7817188567622106, 0.9042926845291104)\n",
|
||
|
|
"(14867.7489823991, 2.0402575080335033, 2.2719839481732893, 0.11357705545861951)\n",
|
||
|
|
"(21266.516812125887, 2.153495031258826, 1.9119858855229528, -0.11214752865935293)\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
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|
|
"(34.26192971306782, 1.8313325138176362, 875.6236712873967, 477.13472686183695)\n",
|
||
|
|
"(201.41097945571718, 1.8814671961627354, 127.64014521606214, 66.84074974912402)\n",
|
||
|
|
"(1149.5944079881458, 1.932974368951203, 16.294805202794894, 7.429912710966861)\n",
|
||
|
|
"(5107.839116510911, 1.9858916055739333, 3.8749138493926036, 0.9512212240167724)\n",
|
||
|
|
"(11735.009083053337, 2.0402575080335033, 2.2924373956411404, 0.1236019897560382)\n",
|
||
|
|
"(16659.006995260028, 2.153495031258826, 1.9152777395363252, -0.11061891867159357)\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": [
|
||
|
|
"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",
|
||
|
|
" tmin,tmax,dmax=1.4,310,0.001\n",
|
||
|
|
" plt.plot([tmin,tmax,tmax,tmin,tmin], [-dmax,-dmax,dmax,dmax,-dmax], '-')\n",
|
||
|
|
" plt.legend(['dif1','dif2','dif3','est'])\n",
|
||
|
|
" plt.show()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 10,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"('z340', 'READ 2024-12-06/X225622.340')\n",
|
||
|
|
"('z340', 'READ 2024-12-06/X225623.340')\n",
|
||
|
|
"('z340', 'READ 2024-12-06/X225624.340')\n",
|
||
|
|
"('z340', 'READ 2024-12-06/X196718.340')\n",
|
||
|
|
"('z340', 'READ 2024-12-06/X196719.340')\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"<matplotlib.legend.Legend at 0x4e0a690>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 10,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 1500x900 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"plt.figure(figsize=(10,6),dpi=150)\n",
|
||
|
|
"for sensor in run.sensors:\n",
|
||
|
|
" r0, t0 = read_curve(sensor.outputpath, sensor.outputkind)\n",
|
||
|
|
" plt.loglog(t0,r0,'o',alpha=0.5, label=\"CH{}:{} {}\".format(sensor.channel, sensor.serialno, sensor.model))\n",
|
||
|
|
"\n",
|
||
|
|
"plt.title(sensor.outputpath.split('/')[0])\n",
|
||
|
|
"plt.grid(which='both',alpha=0.2)\n",
|
||
|
|
"plt.xlabel('T (K)')\n",
|
||
|
|
"plt.ylabel('R (Ohm)')\n",
|
||
|
|
"plt.legend()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"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"
|
||
|
|
},
|
||
|
|
"widgets": {
|
||
|
|
"application/vnd.jupyter.widget-state+json": {
|
||
|
|
"state": {},
|
||
|
|
"version_major": 2,
|
||
|
|
"version_minor": 0
|
||
|
|
}
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"nbformat": 4,
|
||
|
|
"nbformat_minor": 4
|
||
|
|
}
|