calib_scripts/calib_cernox_2018-10-25.ipynb

Scripts for Calibration of Cernox Sensors¶

Make a copy of this notebook for an other run

In [1]:

import numpy as np
import matplotlib.pyplot as plt
import math

from zcalib import read_curve, convert_res, compare_calib, make_calib, logrange, Sensor, CalibRun, nplog, npexp

In [2]:

run = CalibRun([
        Sensor(3, 'X75610'), # the reference sensor must be the first
        Sensor(1, 'X133979', 'CX-1050-SD'),
        Sensor(2, 'X133978', 'CX-1050-SD'),
        Sensor(4, 'X133928', 'CX-1050-SD'),
        Sensor(6, 'X133981', 'CX-1050-SD'),
    ],
    t_points = (1.0, 1.2) + logrange(1.4, 310, n=195) + (330,),
    caldate = '2018-10-25',
    logT = False,
    logR = True,
    calib_data_file = 'calib_data/calib%s_p%d_c%d.dat',
    outputpath='%s/%s.340')
# use slightly lower smoothtst as we measured less points (1e-7 for 60, 0.8e-7 for 48 and 0.4e-7 for 24 points)
run.make(diflim=0.001, smoothref=1e-7, smoothtst=0.8e-7)
print('calibration file has %d points' % len(run.t_points))

('lsdat', 'READ /afs/psi.ch/project/SampleEnvironment/SE_internal/Thermometer_calibs/2012/73027 Cernox 5/X75610.dat')
('zdat', 'READ calib_data/calib2018-10-25_p0_c1.dat')
('zdat', 'READ calib_data/calib2018-10-25_p1_c1.dat')
('zdat', 'READ calib_data/calib2018-10-25_p2_c1.dat')
{'selected': 2, 'averaged': 46}
('zdat', 'READ calib_data/calib2018-10-25_p0_c2.dat')
('zdat', 'READ calib_data/calib2018-10-25_p1_c2.dat')
('zdat', 'READ calib_data/calib2018-10-25_p2_c2.dat')
{'selected': 2, 'averaged': 46}
('zdat', 'READ calib_data/calib2018-10-25_p0_c4.dat')
('zdat', 'READ calib_data/calib2018-10-25_p1_c4.dat')
('zdat', 'READ calib_data/calib2018-10-25_p2_c4.dat')
{'selected': 2, 'averaged': 46}
('zdat', 'READ calib_data/calib2018-10-25_p0_c6.dat')
('zdat', 'READ calib_data/calib2018-10-25_p1_c6.dat')
('zdat', 'READ calib_data/calib2018-10-25_p2_c6.dat')
{'selected': 2, 'averaged': 46}
calibration file has 199 points

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In [3]:

# compare calibration files from points 1,2 and 3
# with the optimized from above. To estimate the precision
# at each point the curve with the biggest difference does
# not have to be taken in to account

for sensor in run.sensors:
    r0, t0 = read_curve(sensor.outputpath, sensor.outputkind)
    plt.figure()
    dif = [0,0,0]
    for j in range(3):
        rref, rtst = read_curve(sensor.caldat_file[j], 'zdat')
        rc, tc = make_calib(run.rref, run.tref, rref, rtst, run.t_points)
        dif[j] = compare_calib(r0, t0, rc, tc)
        plt.plot(t0, dif[j], '-')
    #n = len(dif[0])
    #dd = np.zeros(n)
    #for i in range(n):
    #    # determine second biggest absolute value
    #    dd[i] = sorted([abs(dif[j][i]) for j in range(3)])[1]
    #plt.plot(t0, dd, '.')
    plt.xscale('log')
    # plt.yscale('symlog', linthreshy=0.001)
    plt.grid(True, axis='y')
    plt.axis([min(t0),max(t0),-0.005,0.005])
    plt.legend(['dif1','dif2','dif3','est'])
    plt.show()

('z340', 'READ 2018-10-25/X133979.340')
('zdat', 'READ calib_data/calib2018-10-25_p0_c1.dat')
('zdat', 'READ calib_data/calib2018-10-25_p1_c1.dat')
('zdat', 'READ calib_data/calib2018-10-25_p2_c1.dat')

('z340', 'READ 2018-10-25/X133978.340')
('zdat', 'READ calib_data/calib2018-10-25_p0_c2.dat')
('zdat', 'READ calib_data/calib2018-10-25_p1_c2.dat')
('zdat', 'READ calib_data/calib2018-10-25_p2_c2.dat')

('z340', 'READ 2018-10-25/X133928.340')
('zdat', 'READ calib_data/calib2018-10-25_p0_c4.dat')
('zdat', 'READ calib_data/calib2018-10-25_p1_c4.dat')
('zdat', 'READ calib_data/calib2018-10-25_p2_c4.dat')

('z340', 'READ 2018-10-25/X133981.340')
('zdat', 'READ calib_data/calib2018-10-25_p0_c6.dat')
('zdat', 'READ calib_data/calib2018-10-25_p1_c6.dat')
('zdat', 'READ calib_data/calib2018-10-25_p2_c6.dat')

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