375 lines
90 KiB
Plaintext
375 lines
90 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": 5,
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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": 21,
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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/calib2024-11-08_p0_c1.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-11-08_p1_c1.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-11-08_p2_c1.dat')\n",
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"{'selected': 4, 'averaged': 57}\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-11-08_p0_c2.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-11-08_p1_c2.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-11-08_p2_c2.dat')\n",
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"{'selected': 0, 'averaged': 61}\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-11-08_p0_c4.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-11-08_p1_c4.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-11-08_p2_c4.dat')\n",
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"{'selected': 3, 'averaged': 58}\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, 'X219230', 'CX-1050-SD-HT'),\n",
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" Sensor(2, 'X219226', 'CX-1050-SD-HT'),\n",
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" Sensor(4, 'X219227', 'CX-1050-SD-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 = '2024-11-08', # 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": 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 2018-11-22/X133982.340')\n",
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"('z340', 'READ 2018-11-20/X133982.340')\n",
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"('z340', 'READ 2018-11-22/X133928.340')\n",
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"('z340', 'READ 2018-11-20/X133928.340')\n",
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"('z340', 'READ 2018-11-22/X131824.340')\n",
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"('z340', 'READ 2018-11-20/X131824.340')\n",
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"('z340', 'READ 2018-11-22/X132254.340')\n",
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"('z340', 'READ 2018-11-20/X132254.340')\n",
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"('z340', 'READ 2018-11-22/X137461.340')\n",
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"('z340', 'READ 2018-11-20/X137461.340')\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: '2018-11-20/X137461.340'",
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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-e7e8a820ce5b>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\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[1;32m 6\u001b[0m \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'2018-11-22/%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[0;32m----> 7\u001b[0;31m \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'2018-11-20/%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[0m\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\u001b[1;32m 9\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mt0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdiff\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'-'\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.py\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: '2018-11-20/X137461.340'"
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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": [
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"<Figure size 720x432 with 1 Axes>"
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]
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},
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"metadata": {
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"needs_background": "light"
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},
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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",
|
||
|
|
" r0, t0 = read_curve('2023-11-05/%s.340' % sensno, 'z340')\n",
|
||
|
|
" r1, t1 = read_curve('2023-11-05/%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": 22,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"('z340', 'READ 2024-11-08/X219230.340')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-11-08_p0_c1.dat')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-11-08_p1_c1.dat')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-11-08_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 2024-11-08/X219226.340')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-11-08_p0_c2.dat')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-11-08_p1_c2.dat')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-11-08_p2_c2.dat')\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAYgAAAECCAYAAADkaECYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi40LCBodHRwOi8vbWF0cGxvdGxpYi5vcmcv7US4rQAAIABJREFUeJzt3Xd8FMX/x/HX5NI7CQkJCRCQGulVRCEgKkgVFUEFRSz4FVHxx9feC5avDUURFRGUJoIiRZASeu8koYQSUgghvZe7m98fFzHgBgJeTAKf5+ORh97czOzk2Oz7dnd2V2mtEUIIIc7nUNUDEEIIUT1JQAghhDAkASGEEMKQBIQQQghDEhBCCCEMSUAIIYQwJAEhhBDCkASEEEIIQ45VPYA/KaU8gC+AYiBSa/1jFQ9JCCGuapW6B6GUmqaUSlFKHTivvI9S6pBSKlYp9Vxp8RBgvtb6YWBgZY5LCCHExVX2IabpQJ+yBUopEzAZ6AuEA8OVUuFAKBBfWs1SyeMSQghxEZUaEFrrdUD6ecWdgVit9TGtdTEwBxgEJGALiUoflxBCiIurinMQIfy1pwC2YOgCTAI+V0r1A34rr7FS6hFgAuDr7OxcOywsrBKHKoQQV57Dhw+naq0DLlav2pyk1lrnAaMqUG8qMBWgY8eOeseOHZU9NCGEuKIopeIqUq8qDuUkAvXKvA4tLRNCCFGNVEVAbAeaKKUaKqWcgWHAoioYhxBCiAuo7Gmus4HNQDOlVIJSarTW2gyMBZYDMcA8rXVUZY5DCCHEpavUcxBa6+HllC8FllbmsoUQQvwzMp1UCCGEIQkIIYQQhiQghBBCGJKAEEIIYUgCQgghhCEJCCGEEIYkIIQQQhiSgBBCCGFIAkIIIYQhCQghhBCGJCCEEEIYkoAQQghhSAJCCCGEIQkIIYQQhiQghBBCGJKAEEIIYahaBYRSqpFS6lul1PyqHosQQlzt7BYQSqlpSqkUpdSB88r7KKUOKaVilVLPXagPrfUxrfVoe41JCCHE5bPnI0enA58DM/4sUEqZgMnAzUACsF0ptQgwARPPa/+g1jrFjuMRQgjxD9gtILTW65RSYecVdwZitdbHAJRSc4BBWuuJQH97LVsIIYT92XMPwkgIEF/mdQLQpbzKSil/4G2gnVLq+dIgOb/OI8AEwNfX15fIyEj7jlgIIQRQ+QFxSbTWacCYi9SZCkwF6Nixo46IiPgXRiaEEFefyp7FlAjUK/M6tLRMCCFENVfZAbEdaKKUaqiUcgaGAYsqeZlCCCHswJ7TXGcDm4FmSqkEpdRorbUZGAssB2KAeVrrKHstUwghROWx5yym4eWULwWW2ms5Qggh/h3V6kpqIYQQ1YcEhBBCCEMSEEIIIQxJQAghhDAkASGEEMKQBIQQQghDEhBCCCEMSUAIIYQwJAEhhBDCkASEEEIIQxIQQgghDElACCGEMCQBIYQQwpAEhBBCCEMSEEIIIQxJQAghhDAkASGEEMKQ3Z4oZw9KqcFAP8Ab+FZrvaKKhySEEFctez6TeppSKkUpdeC88j5KqUNKqVil1HMX6kNr/YvW+mFgDHC3vcYmhBDi0tlzD2I68Dkw488CpZQJmAzcDCQA25VSiwATMPG89g9qrVNK//+l0nZCCCGqiN0CQmu9TikVdl5xZyBWa30MQCk1BxiktZ4I9D+/D6WUAt4FlmmtdxktRyn1CDAB8PX19SUyMtJev4IQQogyKvscRAgQX+Z1AtDlAvWfAHoDPkqpxlrrKedX0FpPBaYCdOzYUUdERNhvtEIIIc6qVieptdaTgElVPQ4hhBCVP801EahX5nVoaZkQQohqrrIDYjvQRCnVUCnlDAwDFlXyMoUQQtiBPae5zgY2A82UUglKqdFaazMwFlgOxADztNZR9lqmEEKIymPPWUzDyylfCiy113KEEEL8O+RWG0IIIQxJQAghhDAkASGEEMKQBIQQQghDEhBCCCEMSUAIIYQwJAEhhBDCkASEEEIIQxIQQgghDElACCGEMCQBIYQQwpAEhBBCCEMSEEIIIQxJQAghhDAkASGEEMKQBIQQQghD1SoglFItlFJTlFLzlVKPVfV4hBDiambPR45OU0qlKKUOnFfeRyl1SCkVq5R67kJ9aK1jtNZjgKFAN3uNTQghxKWz5x7EdKBP2QKllAmYDPQFwoHhSqlwpVQrpdTi834CS9sMBJYgjykVQogqZc9nUq9TSoWdV9wZiNVaHwNQSs0BBmmtJwL9y+lnEbBIKbUEmPVPxpQxdx7Zixf/ky6EEKLG8+7fn1p3D73kdnYLiHKEAPFlXicAXcqrrJSKAIYALpSzB6GUegSYAPj6+voSGRlZ7sJr/fADjgkJmENDL3ngQghxJXBMSCAzM5O9dQIvvW0ljOeyaa0jgciL1JkKTAXo2LGjjoiIKLdu3LfTwNeXBjNn2G+QQghRg8SNGAlAmwtsK8tT2bOYEoF6ZV6HlpYJIYSo5io7ILYDTZRSDZVSzsAwYFElL1MIIYQd2HOa62xgM9BMKZWglBqttTYDY4HlQAwwT2sdZa9lCiGEqDz2nMU0vJzypciUVSGEqHGq1ZXUQgghqg8JCCGEEIYkIIQQQhiSgBBCCGFIAkIIIYQhCQghhBCGanZAFGVX9QiEEOKKVbMDIv0YHFlZ1aMQQoga4/cTv1e4bs0OCEc3mHsfxG2u6pEIIUSN8MWeLypct2YHhP814BMCs+6GU/uqejRCCFGtxefEczzreIXr1+yAcHCEEb+AixfMvB1SY6t6REIIUW1tSNxwSfVrdkAA+NaDkb/a/n/GIMhKqNrxCCFENbU+YT31vepXuH7NDwiA2o1hxALbrKYZgyH3TFWPSAghqpVCcyHbkrfRPbR7hdtcGQEBENwG7pln24P4YQgUZlX1iIQQotrYnrydIksRN4bcWOE2V05AADToCnfPhJRomDUMtLWqR1QtaK1Jyy1Ca13VQxFCVJH1ietxc3SjQ1CHCre5sgICoMnNMGQqnNwMKTEgG0U+Wx1Lh7dWcu2ry5m8Rk7k/0lrTUxaDIfSD/39zVN74avu8OvjcHLrvz+4q4W5GPLT5e+0kmls5x+6BHXBxeRS4XZ2e2BQtdLyDijKgVVvQOohKM4HZ/cLNknKTeKxlY8RnxNP01pNmXbrNNydLtymKsWkxVBiLaF1QOsL1otPz+fzNbF0beSPo0nx4YpD9GgaQMsQn39ppNXT8azj/Gflf0jITcDN0Y1FgxcR5BFEXpEZU0oULrMGoZQJ0o7B3jnwwFKo36Wqh/3vKs6Hwkxw8wMnV/v2nXYUljwDx9bYXjfsDgMmgV9D+y5HAFBoKSQhN4FRLUddUrsrbw/iTx0eAL8wyEuFzztB1MILfkv5dv+3xOfEc2fTO4lOi2bS7kn/2lAvVdTxVdy/eBgPLh1BTGr0Beu+vSQGk1J8dHcbJg9uyEuuPxH0bXv0D3fC3rl2/+aWW5zLs+ueZdqBaWQVVc/zQBarhZc2vkR2cTbPd34eq7by1B9vMGjyRtq8uoTkr+/iTKGJVTfMQj+1H3zqwU/3Q27KZS/vox0f8cDvD/Dk6idJyb+8fv5VVgtMuwU+agHvNYBjkfbr++ga+PJ6SNwJN4yHHs9B4m6YciOcOWy/5dQ0Rbmw7Fn4tC0k77/sbrTWTNk7hWcin+H347+j0WQVZQJwQ8gNl9TXlRsQAN6hENQK3GrBTw/A9P6QfOBv1VLyU1gYu5DBjQfzQpcXGN58OD/G/MjO0zsrb2xaQ0EGZJy4pI108uGl/GfNOPxKivE1F/PUH4+SWZhpWDc6KZvfo5J5LOIagt0V3rP6Mkr/woGSEPJPHYaFj8D8UVBon3taaa15ZdMrLDu+jI93fszABf1ILUi1S9/2NCN6BvvO7OOFLi/QyW8AHgW3EJW1ngxLFF+2iiXM4TSfuY5h9KJUXlqegL57JhRk2r7xXiKtNRO3TeS7qO8osZawIXEDn+76tEJt80ryyCrKwmK1XPJy/7FdM2wbqevHgUegbW/cHl8mkg/A3BHgdw08vg16vwo9n4fHNoL
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"('z340', 'READ 2024-11-08/X219227.340')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-11-08_p0_c4.dat')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-11-08_p1_c4.dat')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-11-08_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"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"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": 13,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"X219219.340 X219225.340 X219231.340\n"
|
||
|
|
]
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"run.rref"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"run.tref"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"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": [],
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||
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|
"source": []
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||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
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||
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|
"source": []
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||
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|
},
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||
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|
{
|
||
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|
"cell_type": "code",
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||
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|
"execution_count": null,
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|
"metadata": {},
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||
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|
"outputs": [],
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"source": []
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},
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|
{
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|
"cell_type": "code",
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||
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|
"execution_count": null,
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||
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|
"metadata": {},
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|
"outputs": [],
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"source": []
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||
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|
},
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|
{
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||
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|
"cell_type": "code",
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||
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|
"execution_count": null,
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||
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|
"metadata": {},
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||
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|
"outputs": [],
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|
"source": []
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||
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|
},
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||
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|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
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||
|
|
"outputs": [],
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||
|
|
"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"
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},
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"widgets": {
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"application/vnd.jupyter.widget-state+json": {
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"state": {},
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"version_major": 2,
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"version_minor": 0
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}
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"nbformat": 4,
|
||
|
|
"nbformat_minor": 4
|
||
|
|
}
|