402 lines
81 KiB
Plaintext
402 lines
81 KiB
Plaintext
|
{
|
||
|
|
"cells": [
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"Scripts for Calibration of Cernox Sensors\n",
|
||
|
|
"---------------------------------------\n",
|
||
|
|
"\n",
|
||
|
|
"Make a copy of this notebook for an other run.\n",
|
||
|
|
"\n",
|
||
|
|
"See also http://samenv.psi.ch:8080/sample_environment/83"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 1,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"import numpy as np\n",
|
||
|
|
"import matplotlib.pyplot as plt\n",
|
||
|
|
"import math\n",
|
||
|
|
"from scipy.interpolate import splrep, splev\n",
|
||
|
|
"from zcalib import read_curve, convert_res, compare_calib, make_calib, logrange, Sensor, CalibRun, nplog, npexp"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 2,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"('lsdat', 'READ /afs/psi.ch/project/SampleEnvironment/SE_internal/Thermometer_calibs/2012/73027 Cernox 5/X75610.dat')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-05-04_p0_c1.dat')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-05-04_p1_c1.dat')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-05-04_p2_c1.dat')\n",
|
||
|
|
"{'selected': 0, 'averaged': 62}\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-05-04_p0_c2.dat')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-05-04_p1_c2.dat')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-05-04_p2_c2.dat')\n",
|
||
|
|
"{'selected': 0, 'averaged': 62}\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-05-04_p0_c4.dat')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-05-04_p1_c4.dat')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-05-04_p2_c4.dat')\n",
|
||
|
|
"{'selected': 0, 'averaged': 62}\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-05-04_p0_c5.dat')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-05-04_p1_c5.dat')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-05-04_p2_c5.dat')\n",
|
||
|
|
"{'selected': 0, 'averaged': 62}\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-05-04_p0_c6.dat')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-05-04_p1_c6.dat')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-05-04_p2_c6.dat')\n",
|
||
|
|
"{'selected': 20, 'averaged': 42}\n",
|
||
|
|
"ERROR: data for X163062 is not monotonic\n"
|
||
|
|
]
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"run = CalibRun([\n",
|
||
|
|
" Sensor(3, 'X75610'), # the reference sensor must be the first\n",
|
||
|
|
" Sensor(1, 'X161269', 'CX-1050-CU-HT-1.4M'),\n",
|
||
|
|
" Sensor(2, 'X163059', 'CX-1050-CU-HT'),\n",
|
||
|
|
" Sensor(4, 'X163060', 'CX-1050-CU-HT'),\n",
|
||
|
|
" Sensor(5, 'X163061', 'CX-1050-CU-HT'),\n",
|
||
|
|
" Sensor(6, 'X163062', 'CX-1050-CU-HT'),\n",
|
||
|
|
" ],\n",
|
||
|
|
" #t_points = (1.0, 1.2) + logrange(1.4, 310, n=194) + (330,), # the points to be used in the cal file\n",
|
||
|
|
" t_points = (1.38, 1.42, 1.51) + logrange(1.55, 288, n=57) + (302,310), # the points to be used in the cal file\n",
|
||
|
|
" caldate = '2021-05-04', # the first measuring day!\n",
|
||
|
|
" logT = False,\n",
|
||
|
|
" logR = True,\n",
|
||
|
|
" calib_data_file = '/home/l_samenv/sea/calib_scripts/calib_data/calib%s_p%d_c%d.dat',\n",
|
||
|
|
" outputpath='%s/%s.340')\n",
|
||
|
|
"# smooth depends on number of measured points (1e-7 for 60, 0.8e-7 for 48 and 0.4e-7 for 24 points)\n",
|
||
|
|
"run.make(diflim=0.001, smoothref=1e-7, smoothtst=0.4e-7)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 3,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"('z340', 'READ 2021-05-04/X161269.340')\n",
|
||
|
|
"('z340', 'READ lakeshore/X161269.340')\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 720x432 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"# compare known sensors\n",
|
||
|
|
"if True: # set to True when known sensors are measured\n",
|
||
|
|
" plt.figure(figsize=(10, 6))\n",
|
||
|
|
" tmin,tmax,dmax=1.4,310,0.001\n",
|
||
|
|
" testlist = [('X161269', 'z340')]\n",
|
||
|
|
" for sensno, kind in testlist:\n",
|
||
|
|
" r0, t0 = read_curve('%s/%s.340' % (run.outputoptions['caldate'], sensno), 'z340')\n",
|
||
|
|
" r1, t1 = read_curve('lakeshore/%s.340' % sensno, kind)\n",
|
||
|
|
" diff = compare_calib(r1, t1, r0, t0)\n",
|
||
|
|
" plt.plot(t0, diff, '-')\n",
|
||
|
|
" plt.plot([tmin,tmax,tmax,tmin,tmin], [-dmax,-dmax,dmax,dmax,-dmax], '-')\n",
|
||
|
|
" plt.legend([sensno + \".\" + kind[-3:] for sensno, kind in testlist] + [\"window\"])\n",
|
||
|
|
" plt.xscale('log')\n",
|
||
|
|
" plt.yscale('symlog',linthreshy=dmax)\n",
|
||
|
|
" plt.grid(True, axis='y')\n",
|
||
|
|
" plt.axis([1.0,350,-1,1])\n",
|
||
|
|
" plt.show()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 4,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"('z340', 'READ 2021-05-04/X161269.340')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-05-04_p0_c1.dat')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-05-04_p1_c1.dat')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-05-04_p2_c1.dat')\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAYgAAAECCAYAAADkaECYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi40LCBodHRwOi8vbWF0cGxvdGxpYi5vcmcv7US4rQAAIABJREFUeJzt3Xl4VdW9//H390yZSUgCYUgEhAAiOEZwqqUVFW4tiletWK1tUWqrtnawtbWDbbW0t/3dtliqFyeqrSBqtagoODSligOIogwCAQXCkJCBzMmZ1u+PRBvjThg8MQE/r+c5D+y1917rm2Qnn7P3Xuccc84hIiLSka+nCxARkd5JASEiIp4UECIi4kkBISIinhQQIiLiSQEhIiKeFBAiIuJJASEiIp4CPV3Ae8wsDfgzEAaKnXN/6+GSREQ+0br1DMLM7jGzcjNb06F9spltMLMSM7uxrfkC4GHn3FXA1O6sS0RE9q27LzHNAya3bzAzPzAHmAKMAaab2RggH9jetlmsm+sSEZF96NaAcM4tA6o6NI8HSpxzW5xzYWABcB5QSmtIdHtdIiKybz1xD2Iw/zlTgNZgmADMBv5kZp8DHu9sZzObCdwAZIVCodyhQ4d2Y6kiIoefjRs3Vjjn+u1ru15zk9o51wB8ZT+2mwvMBSgqKnIrV67s7tJERA4rZrZ1f7briUs5O4CCdsv5bW0iItKL9ERArAAKzWyYmYWAS4BFPVCHiIh0obunuc4HXgJGmVmpmc1wzkWBa4ElwHpgoXNubXfWISIiB65b70E456Z30r4YWNydY4uIyEej6aQiIuJJASEiIp4UECIi4kkBISIinhQQIiLiSQEhIiKeFBAiIuJJASEiIp4UECIi4kkBISIinhQQIiLiSQEhIiKeFBAiIuJJASEiIp4UECIi4kkBISIinnpVQJjZkWZ2t5k93NO1iIh80iUsIMzsHjMrN7M1Hdonm9kGMysxsxu76sM5t8U5NyNRNYmIyMFL5EeOzgP+BNz3XoOZ+YE5wFlAKbDCzBYBfmBWh/2/6pwrT2A9IiLyESQsIJxzy8xsaIfm8UCJc24LgJktAM5zzs0Czk3U2CIikniJPIPwMhjY3m65FJjQ2cZmlgPcChxvZj9sC5KO28wEbgCysrKyKC4uTmzFIiICdH9AHBDnXCVw9T62mQvMBSgqKnITJ078GCoTEfnk6e5ZTDuAgnbL+W1tIiLSy3V3QKwACs1smJmFgEuARd08poiIJEAip7nOB14CRplZqZnNcM5FgWuBJcB6YKFzbm2ixhQRke6TyFlM0ztpXwwsTtQ4IiLy8ehVr6QWEZHeQwEhIiKeFBAiIuJJASEiIp4UECIi4kkBISIinhQQIiLiSQEhIiKeFBAiIuJJASEiIp4UECIi4kkBISIinhQQIiLiSQEhIiKeFBAiIuJJASEiIp4UECIi4ilhnyiXCGZ2PvA5oA9wt3NuaQ+XJCLyiZXIz6S+x8zKzWxNh/bJZrbBzErM7Mau+nDOPeacuwq4GvhComoTEZEDl8gziHnAn4D73mswMz8wBzgLKAVWmNkiwA/M6rD/V51z5W3//3HbfiIi0kMSFhDOuWVmNrRD83igxDm3BcDMFgDnOedmAed27MPMDPg18JRzbpXXOGY2E7gByMrKyqK4uDhRX4KIiLTT3fcgBgPb2y2XAhO62P46YBKQaWYjnHN3dNzAOTcXmAtQVFTkJk6cmLhqRUTkfb3qJrVzbjYwu6frEBGR7p/mugMoaLec39YmIiK9XHcHxAqg0MyGmVkIuARY1M1jiohIAiRymut84CVglJmVmtkM51wUuBZYAqwHFjrn1iZqTBER6T6JnMU0vZP2xcDiRI0jIiIfD73VhoiIeFJAiIiIJwWEiIh4UkCIiIgnBYSIiHhSQIiIiCcFhIiIeFJAiIiIJwWEiIh4UkCIiIgnBYSIiHhSQIiIiCcFhIiIeFJAiIiIJwWEiIh4UkCIiIinXhUQZnaUmd1hZg+b2dd7uh4RkU+yRH7k6D1mVm5mazq0TzazDWZWYmY3dtWHc269c+5q4GLgtETVJiIiBy6RZxDzgMntG8zMD8wBpgBjgOlmNsbMxpnZEx0e/dv2mQo8iT6mVESkRyXyM6mXmdnQDs3jgRLn3BYAM1sAnOecmwWc20k/i4BFZvYk8ECi6hMRkQOTsIDoxGBge7vlUmBCZxub2UTgAiCJTs4gzGwmcAOQlZWVRXFxcaJqFRGRdro7IA6Ic64YKN7HNnOBuQBFRUVu4sSJ3V6XiMgnUXfPYtoBFLRbzm9rExGRXq67A2IFUGhmw8wsBFwCLOrmMUVEJAESOc11PvASMMrMSs1shnMuClwLLAHWAwudc2sTNaaIiHSfRM5imt5J+2I0ZVVE5JDTq15JLSIivYcCQkREPCkgRETEkwJCREQ8KSBERMSTAkJERDwpIERExJMCQkREPCkgRETEkwJCREQ8KSBERMSTAkJERDwpIERExJMCQg4LzZEY9S3Rni5D5LCigJDDwjfnv84Ff36ReNz1dCkihw0FRC/nandR89QtEA33dCm91o69TTyzvoyNZfX8a9Oeni5H5LChgOjl/rnwem7Zcg/rlv6xp0vptRau2A5AVmqQeS++27PFiBxGFBC9WHxvKQsjq3g6PY3HSu7ChRt7uqReJxZ3PLRyO6cUJnPh+DT+tXEPW/bU93RZIocFBUQv9uwTP+bF1GRS4kk83CfIskW39HRJvc6yjXvYWVtHRfIs/lF+HUkZG7jvpa09XVaPi7s4sXisp8uQQ5wCordqqOCRuuWkxnzcN/VBzBl/L3uESGPNAXcViUVYW7mWSCzSDYX2rPmvbiNv4FJ2RcroF24kZfC9PP/2X6hr7t6v9c0dZXzv8YfY29h77g3FXZw3yt9g1iuzOHPhZ7nk8YsIxw6uvvqWKGt31lBafXiftZaU11PTeHj8XtS01LC+cj0v73qZJe8uYeGGhdz11l3MfXMuFU0VB9VnIME1ShecczRGG6kP15OdnE3QH+x022VLb2Z5ahITU6cwOmc452SfxeO+Z3js7zdy0WW37/eYuxt2893nruPN6rfpE8zgrKFn87kjP8eJeSfis97x/CAcCxONR0kNph7QfuW1zTz/zirShvyb8+sb+cGoy/nW5gW8mvcUf3iolJ9ceh/49+8Qj7s4xduLaYo2cfbQswn6vH82zjlmPz6Hh8vvZm8wyvp5z3HvZX+gf5/k/a67ORJj7c4a3theQ0V9C185bSj9M/Z//471rKtcx1ObH2fJO4vZ3VJNyMHxzc28klLJ3Nf+yLXjb+iyj7W71zPr+Zvxx0+krv5Etlc69tS1AOD3GZefPITrJxWSlRo68AKr3oFoM/QbDWYHvHssGmHWY99gZ9Nufjr1dgZk5ne5fV19DctWPsrk0y/DH+j6Z//o66V8d+FqkgJ+LirK5yunDWNYbtoB1be2Yi0PbXyI0dmjuXDkhQR8H++f1NrmCJvL61m4YSFP7ZxLDO8nBPeuuZdrjruGS0ZfckA1mnO9Z1qgmU0G/gj4gbucc7/uavuiUflu5cqVkDHg4AeNthCt2kYg+wgIJB18P7T+spY3lrO+agMrd67hrT3rKa3fSnOsgZZYPWHXhKP1+52XNJCHzn+Qvsl9P9xRcy0z553Em6EkHvnvZQzOzKIh3MA5fz2V/EgLd138b9L79vMuom43bH8Vdq3m5R3L+X50Oy3m+EZ1DW8nhXguNZUmn5FnyUzJPppzhn+eowqn4g90Hlb7KxqPUt5Yzq6GXexu2E3cxQn6gwRbGgmWv02obA3Rio2UEmGrxXnX4rzrh51+I25GJj4GBjIYkJrHwKyhDM4dw5Thn6d/an/P8WY/v577S66ij7+SR4dcTJ9JPydc9Q4zF17MaynNXBFN4jtT7sQ36PhOa47Foix5ax53rr+fknAVAEMC6Vxz5DTOOXYGvtScti8uTNnK+fz+tT/yZHqE/EiUYVHHv1OC5FVfwJ2Xfb/TPy7RWJx7ixeyc9vrBKv2kF2/h9GxPRRaOVnUs9I3jn4
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"('z340', 'READ 2021-05-04/X163059.340')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-05-04_p0_c2.dat')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-05-04_p1_c2.dat')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-05-04_p2_c2.dat')\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAYgAAAECCAYAAADkaECYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi40LCBodHRwOi8vbWF0cGxvdGxpYi5vcmcv7US4rQAAIABJREFUeJzt3Xl8lOW99/HPb2Yy2UkgJIBJEGQVN9AIWnsqdam4VHusVbC1WlFEq92e41FbrZ6ex2M9bY+tR60HK1JPK2ipVkR8tFijVVHBjUW2sAgJS0LIRpZZr+ePRBrinZDgjEn0+3695gX3dV/3df2S3Jnv3EtmzDmHiIhIR77eLkBERPomBYSIiHhSQIiIiCcFhIiIeFJAiIiIJwWEiIh4UkCIiIgnBYSIiHgK9HYBHzGzTOABIAyUOuf+2MsliYh8riX1CMLM5ppZpZmt7tA+zczWm1mZmd3c1nwhsNA5dzVwfjLrEhGRg0v2KaZ5wLT2DWbmB+4HzgYmADPMbAJQBGxv6xZLcl0iInIQSQ0I59wrwN4OzZOBMufcZudcGFgAXACU0xoSSa9LREQOrjeuQRTyjyMFaA2GKcC9wH1mdi7wTGcbm9ks4EYgNxgMDh4xYkQSSxUR+ezZsGHDHudc/sH69ZmL1M65RuA73eg3B5gDUFJS4lasWJHs0kREPlPM7MPu9OuNUzkVQHG75aK2NhER6UN6IyCWA2PMbKSZBYHpwKJeqENERLqQ7Ntc5wPLgHFmVm5mM51zUeB64HlgLfCEc25NMusQEZGeS+o1COfcjE7alwBLkjm3iIh8MrqdVEREPCkgRETEkwJCREQ8KSBERMSTAkJERDwpIERExJMCQkREPCkgRETEkwJCREQ8KSBERMSTAkJERDwpIERExJMCQkREPCkgRETEkwJCREQ8KSBERMRTnwoIMzvCzB42s4W9XYuIyOddwgLCzOaaWaWZre7QPs3M1ptZmZnd3NUYzrnNzrmZiapJREQOXSI/cnQecB/w6EcNZuYH7gfOBMqB5Wa2CPADd3XY/krnXGUC6xERkU8gYQHhnHvFzEZ0aJ4MlDnnNgOY2QLgAufcXcB5iZpbREQSL5FHEF4Kge3tlsuBKZ11NrM84E5gkpnd0hYkHfvMAm4EcnNzcyktLU1sxSIiAiQ/IHrEOVcNzD5InznAHICSkhI3derUT6EyEZHPn2TfxVQBFLdbLmprExGRPi7ZAbEcGGNmI80sCEwHFiV5ThERSYBE3uY6H1gGjDOzcjOb6ZyLAtcDzwNrgSecc2sSNaeIiCRPIu9imtFJ+xJgSaLmERGRT0ef+ktqERHpOxQQIiLiSQEhIiKeFBAiIuJJASEiIp4UECIi4kkBISIinhQQIiLiSQEhIiKeFBAiIuJJASEiIp4UECIi4kkBISIinhQQIiLiSQEhIiKeFBAiIuJJASEiIp4S9olyiWBmXwPOBQYADzvnXujlkkREPrcS+ZnUc82s0sxWd2ifZmbrzazMzG7uagzn3F+cc1cDs4FLElWbiIj0XCKPIOYB9wGPftRgZn7gfuBMoBxYbmaLAD9wV4ftr3TOVbb9/9a27UREpJckLCCcc6+Y2YgOzZOBMufcZgAzWwBc4Jy7Cziv4xhmZsDPgeecc+94zWNms4Abgdzc3FxKS0sT9SWIiEg7yb4GUQhsb7dcDkzpov8NwBlAjpmNds492LGDc24OMAegpKTETZ06NXHViojIfn3qIrVz7l7g3t6uQ0REkn+bawVQ3G65qK1NRET6uGQHxHJgjJmNNLMgMB1YlOQ5RUQkARJ5m+t8YBkwzszKzWymcy4KXA88D6wFnnDOrUnUnCIikjyJvItpRiftS4AliZpHREQ+HXqrDRER8aSAEBERTwoIERHxpIAQERFPCggREfGkgBAREU8KCBER8aSAEBERTwoIERHxpIAQERFPCggREfGkgBAREU8KCBER8aSAEBERTwoIERHxpIAQERFPfSogzOxIM3vQzBaa2bW9XY+IyOdZIj9ydK6ZVZrZ6g7t08xsvZmVmdnNXY3hnFvrnJsNXAyckqjaRESk5xJ5BDEPmNa+wcz8wP3A2cAEYIaZTTCzY8xscYdHQds25wPPoo8pFRHpVYn8TOpXzGxEh+bJQJlzbjOAmS0ALnDO3QWc18k4i4BFZvYs8Fii6hMRkZ5JWEB0ohDY3m65HJjSWWczmwpcCKTSyRGEmc0CbgRyc3NzKS0tTVStIiLSTrIDokecc6VA6UH6zAHmAJSUlLipU6cmvS4Rkc+jZN/FVAEUt1suamsTEZE+LtkBsRwYY2YjzSwITAcWJXlOERFJgETe5jofWAaMM7NyM5vpnIsC1wPPA2uBJ5xzaxI1p4iIJE8i72Ka0Un7EnTLqohIv9On/pJaRET6DgWEiIh4UkCIiIgnBYSIiHhSQIiIiCcFhIiIeFJAiIiIJwWEiIh4UkCIiIgnBYSIiHhSQIiIiCcFhIiIeFJAiIiIJwWEiIh4UkCIiIgnBYSIiHhSQIiIiCcFRALs3RfinIf/iwVvr+rtUkR6Lh6H3R+Ac71difQxCohPKB53zF5wE9sDj/C7FbOpqG1M6Pgry2v51/8tpbKhJaHj9nUVezdw6e+/yKJl/92t/uuqN/Ba+RtJruqzqfLZn1E15xRqXnmwt0uRPkYB8Qndvvh3rAssZUQ4wu60em574qe4g70SCzdCc81Bx67eF+J/n7iMFeFr+eXcm2kOxxJUdd+2vXodl/3lG6yijv9c+z/UNVZ12X9feB/fXnQ5s1+8mplP3UpTOPwpVdr/hXev56myRzhteBHPrfgP6soUsp91r27c0+2+n5uAcM6xtW4r6/euJxqPJmTMp997gxf23MvYcJQFU3/DsWHH+sDzPPZq579krn4Xdz58Ev8y72RCu1Z32i8Wd9w772ZeHLSFPX4/r2X/lbvn/Zx4vGenAbbVb+PGl2/kC/O/wB2v38GWui092v7TtrlqDZc9fTFhInytppgGH9y1aFaX2/zr8z+jxRr4cmMTb9U/zYy5X2bRay8fPKgPVTQEe7fArtWtp2f6muZaKHsRKtd13c85Xnv8Kn47MJsgqdydl8PSp75NU+3uT6fOPqCssoFt1U09/r36SEVtM0+/V0F5TVOCK+u+pkgTv1/ze85aeBZnLTyL2Utn84vlv+DPG/7Mu5XvUh+uB6CmMcy/Lnyfbz38ZrfHtqT9Eh0CM5sG/AbwA79zzv28q/4lJSVuxYoVH2uPxuK8tXUva3Zv472qtyive4PdsXU0+lpP/wRdgNGphZQMOZqSopM4tvAU8jLze1Tr5upKrn7qLCK+EL8/7iZGnnA569c+xfQ3b+P4hkz+/VsvcdjAjAO2cY3V3DPvdB7Jaj0S+FJzlP+68GlSC8Z+bPyH/vQIj9X/ghQLcs9XHuC6F64h4GJckPkjvjf9qoPWt3NfJXe/dg8v7VqC38GY5gw2pDcRszin5E9m1gnfZdKQ43v0Ne8Xj0Pddhp3vsv721+lrmkvRekDGZY2mLy0gVgwA1IyYMhRkD8ezLo17Ppd73PVksswosxImc7MGbfywwdP5rWsRv745d9y1OH/9LFtVuxYxcwXLuWfGxr56T/dybx35vLfvp0Mi0a5cm8xR33pRxw5ZVq3azhAcw1sewO2LWNf9UYq6rezs6mS3bFGdgT8NPp8nGo5fOHYy/BP+hZkD+35HIco7uKEYiHCjdU0791IXcVb7N3xLtVV62lqqaTW52NUJM5pFz2GHXGq5xhbXvofvld2D9WBATx58SKueeYqypu3clNNLv98w0ukpKR0WUM0FmfLrj1s3rqFHeUf0lBfR9qIEzluVDHHFeeSluJPwBcaaw08nx/Sc7vs6pyjoraZnXUtjB+aTXaad/0tkRjPrtzJo8u28n55HQBZqQHGDc1m/NBsjhgSIDd7H0cXjGFgRhoD0lL2fy0tkRhvbK7mlQ17eHlDJZuqGrGUarJSA/zya6dy1rhB0LCr9RGqh7zRMHBEa/1e9lVB+XLY8S4MOAyOmAqDRu7/esprmtmyp5E
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"('z340', 'READ 2021-05-04/X163060.340')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-05-04_p0_c4.dat')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-05-04_p1_c4.dat')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-05-04_p2_c4.dat')\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"('z340', 'READ 2021-05-04/X163061.340')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-05-04_p0_c5.dat')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-05-04_p1_c5.dat')\n",
|
||
|
|
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2021-05-04_p2_c5.dat')\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 432x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"('z340', 'READ 2021-05-04/X163062.340')\n",
|
||
|
|
"('ERROR:', IOError(2, 'No such file or directory'))\n"
|
||
|
|
]
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"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",
|
||
|
|
" try:\n",
|
||
|
|
" r0, t0 = read_curve(sensor.outputpath, sensor.outputkind)\n",
|
||
|
|
" plt.figure()\n",
|
||
|
|
" dif = [0,0,0]\n",
|
||
|
|
" for j in range(3):\n",
|
||
|
|
" rr, rt = read_curve(sensor.caldat_file[j], 'zdat')\n",
|
||
|
|
" rc, tc = make_calib(run.rref, run.tref, rr, rt, run.t_points)\n",
|
||
|
|
" dif[j] = compare_calib(r0, t0, rc, tc)\n",
|
||
|
|
" plt.plot(t0, dif[j], '-')\n",
|
||
|
|
" plt.xscale('log')\n",
|
||
|
|
" plt.yscale('symlog', linthreshy=0.001)\n",
|
||
|
|
" plt.grid(True, axis='y')\n",
|
||
|
|
" plt.axis([min(t0),max(t0),-1,1])\n",
|
||
|
|
" # plt.axis([240,330,-1,1])\n",
|
||
|
|
"\n",
|
||
|
|
" # plt.legend(['dif1','dif2','dif3','est'])\n",
|
||
|
|
" plt.show()\n",
|
||
|
|
" except Exception as e:\n",
|
||
|
|
" print('ERROR:', e)\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 5,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"if False:\n",
|
||
|
|
" for sensor in run.sensors[4:]:\n",
|
||
|
|
" r0, t0 = read_curve(sensor.outputpath, sensor.outputkind)\n",
|
||
|
|
" plt.figure()\n",
|
||
|
|
" dif = [0,0,0]\n",
|
||
|
|
" plt.plot(t0, r0, '.')\n",
|
||
|
|
" for j in range(3):\n",
|
||
|
|
" rr, rt = read_curve(sensor.caldat_file[j], 'zdat')\n",
|
||
|
|
" rc, tc = make_calib(run.rref, run.tref, rr, rt, run.t_points)\n",
|
||
|
|
" plt.plot(tc, rc, '-')\n",
|
||
|
|
" plt.xscale('log')\n",
|
||
|
|
" plt.yscale('log')\n",
|
||
|
|
" plt.grid(True, axis='y')\n",
|
||
|
|
" plt.axis([20,330,80,300])\n",
|
||
|
|
"\n",
|
||
|
|
" # plt.legend(['dif1','dif2','dif3','est'])\n",
|
||
|
|
" plt.show()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"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"
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"nbformat": 4,
|
||
|
|
"nbformat_minor": 4
|
||
|
|
}
|