484 lines
103 KiB
Plaintext
484 lines
103 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/calib2022-03-08_p0_c1.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2022-03-08_p1_c1.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2022-03-08_p2_c1.dat')\n",
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"{'selected': 0, 'averaged': 62}\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2022-03-08_p0_c4.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2022-03-08_p1_c4.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2022-03-08_p2_c4.dat')\n",
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"{'selected': 0, 'averaged': 62}\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, 'X161269', 'CX-1050-CU'),\n",
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" Sensor(4, 'X163062', 'CX-1050-CU'),\n",
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" ],\n",
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" t_points = (1.0, 1.2) + logrange(1.4, 310, n=195) + (330,), # the points to be used in the cal file\n",
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" caldate = '2022-03-08', # 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": 5,
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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 2022-03-08/X161269.340')\n",
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"('z340', 'READ ../tcl/calcurves/X161269.340')\n",
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"('z340', 'READ 2022-03-08/X163062.340')\n",
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"('z340', 'READ ../tcl/calcurves/X163062.340')\n",
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"(1542.6237023688443, 5.43805, 2.690498212554355, -0.5052457751299905)\n",
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||
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||
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"(1678.5257187766367, 5.004522, 2.5418486281952486, -0.492089628500934)\n",
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||
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"(1727.790174681757, 4.867834, 2.4939392160857956, -0.4876696255283571)\n",
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||
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||
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||
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"(1947.5965654304398, 4.35741, 2.3102093146088984, -0.46982053224073506)\n",
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||
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||
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||
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"(2443.1998891047324, 3.589555, 2.01672604205984, -0.4381682291927997)\n",
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"(4770.621927278813, 2.241735, 1.4325892830050662, -0.36094619435166675)\n",
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"(5230.870880764615, 2.120951, 1.3750131170319788, -0.3516997247781873)\n",
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"(5483.880721613951, 2.063022, 1.3467673420472936, -0.3471871157712843)\n",
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"(5753.856149250909, 2.006675, 1.3186254058187201, -0.34288043364335524)\n",
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"(6042.212569408162, 1.951866, 1.2905935005022062, -0.33878990642687246)\n",
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"(6350.559655064113, 1.898555, 1.2626732154689295, -0.3349293460189831)\n",
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"(6680.638930367525, 1.8467, 1.2348695696714116, -0.33131013717906993)\n",
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"(7413.938855851158, 1.747201, 1.1796296408295486, -0.3248460590226605)\n",
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"(7821.697214858729, 1.699479, 1.1522010846428457, -0.32202687727071316)\n",
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"(8260.265375199966, 1.653062, 1.1249082413283589, -0.31950027202345777)\n",
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"(8732.568479588233, 1.607912, 1.097756408648412, -0.31727830338450613)\n",
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"(9241.958201321704, 1.563995, 1.0707462909410215, -0.3153774206816381)\n",
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"(9792.19379711283, 1.521278, 1.043878860070456, -0.3138145295794351)\n",
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"(11032.349204190787, 1.439312, 0.9905887987754469, -0.3117622872765273)\n",
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"(11733.268256090052, 1.4, 0.9641364118714606, -0.3113311343775281)\n",
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"(16898.41610758743, 1.2, 0.8213390500515669, -0.3155507916236942)\n",
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"(26617.606475286462, 1.0, 0.6726896920393037, -0.32731030796069627)\n"
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{
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"data": {
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|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 720x432 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"# compare known sensors (skip if not applicable)\n",
|
||
|
|
"plt.figure(figsize=(10, 6))\n",
|
||
|
|
"tmin,tmax,dmax=1.4,310,0.001\n",
|
||
|
|
"testlist = (('X161269', 'z340'),('X163062', 'z340'),)\n",
|
||
|
|
"for sensno, kind in testlist:\n",
|
||
|
|
" r0, t0 = read_curve('2022-03-08/%s.340' % sensno, 'z340')\n",
|
||
|
|
" r1, t1 = read_curve('../tcl/calcurves/%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 2022-03-08/X161269.340')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2022-03-08_p0_c1.dat')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2022-03-08_p1_c1.dat')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2022-03-08_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 2022-03-08/X163062.340')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2022-03-08_p0_c4.dat')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2022-03-08_p1_c4.dat')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2022-03-08_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"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"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": 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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{
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{
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