480 lines
388 KiB
Plaintext
480 lines
388 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/calib2024-12-17_p0_c1.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-17_p1_c1.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-17_p2_c1.dat')\n",
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"{'selected': 2, 'averaged': 58}\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-17_p0_c2.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-17_p1_c2.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-17_p2_c2.dat')\n",
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"{'selected': 3, 'averaged': 57}\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-17_p0_c4.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-17_p1_c4.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-17_p2_c4.dat')\n",
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"{'selected': 3, 'averaged': 57}\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-17_p0_c5.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-17_p1_c5.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-17_p2_c5.dat')\n",
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"{'selected': 3, 'averaged': 57}\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, 'X198039', 'CX-1050-CU-HT'),\n",
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" Sensor(2, 'X196722', 'CX-1050-CU-HT'),\n",
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" Sensor(4, 'X196720', 'CX-1050-SD-HT'),\n",
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" Sensor(5, 'X196721', 'CX-1050-CU-HT'),\n",
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" ],\n",
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" t_points = (1.58,1.59) + logrange(1.6, 310, n=195) + (330,), # the points to be used in the cal file\n",
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" caldate = '2024-12-17', # 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 2024-12-17/X198039.340')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-17_p0_c1.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-17_p1_c1.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-17_p2_c1.dat')\n"
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]
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},
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{
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"data": {
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"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 2024-12-17/X196721.340')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-17_p0_c5.dat')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-17_p1_c5.dat')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-17_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"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"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 2024-12-17/X198039.340')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-17_p0_c1.dat')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-17_p1_c1.dat')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-17_p2_c1.dat')\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
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"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 2024-12-17/X196721.340')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-17_p0_c5.dat')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-17_p1_c5.dat')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-17_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"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"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": 5,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"('z340', 'READ 2024-12-17/X198039.340')\n",
|
||
|
|
"('z340', 'READ 2024-12-17/X196722.340')\n",
|
||
|
|
"('z340', 'READ 2024-12-17/X196720.340')\n",
|
||
|
|
"('z340', 'READ 2024-12-17/X196721.340')\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"<matplotlib.legend.Legend at 0x48d5d10>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 5,
|
||
|
|
"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": []
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"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
|
||
|
|
}
|